Remove unused Lock import from KMA station source

.dockerignore

@@ -0,0 +1,31 @@
+.git
+.github
+.vscode
+.agent
+
+.env
+.env.*
+!.env.example
+!.env.secrets.example
+
+venv
+.venv
+.uv-cache
+.uv-python
+.pytest_cache
+.ruff_cache
+.mypy_cache
+__pycache__
+
+.npm-cache
+frontend/node_modules
+
+artifacts
+notebooks
+
+bot.log
+*.log
+
+extension.zip
+tmp_*.js
+tmp_*.html

.env.example

@@ -1,75 +1,107 @@
-# Telegram Bot
-TELEGRAM_BOT_TOKEN=your_bot_token_here
-TELEGRAM_CHAT_ID=your_chat_id_here
-# Optional multi-chat target (comma-separated). If set, it will be merged with TELEGRAM_CHAT_ID.
-# Example: TELEGRAM_CHAT_IDS=-1003586303099,-1003539418691
+# PolyWeather backend/bot minimal reproducible config
+# Full configuration guide:
+# docs/CONFIGURATION_ZH.md
+# Sensitive-only template:
+# .env.secrets.example
+
+########################################
+# 1) Runtime paths and base behavior
+########################################
+ENV=production
+LOG_LEVEL=INFO
+POLYWEATHER_MAP_URL=https://polyweather-pro.vercel.app/
+POLYWEATHER_RUNTIME_DATA_DIR=/var/lib/polyweather
+POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
+OPEN_METEO_DISK_CACHE_PATH=/var/lib/polyweather/open_meteo_cache.json
+# Optional: host user/group mapping for Docker on Linux.
+# Windows / macOS can usually keep the defaults.
+UID=1000
+GID=1000
+POLYWEATHER_STATE_STORAGE_MODE=sqlite
+POLYWEATHER_PROMETHEUS_PORT=9090
+POLYWEATHER_ALERTMANAGER_PORT=9093
+POLYWEATHER_ALERT_RELAY_PORT=9099
+POLYWEATHER_GRAFANA_PORT=3001
+POLYWEATHER_GRAFANA_ADMIN_USER=admin
+POLYWEATHER_GRAFANA_ADMIN_PASSWORD=polyweather
+
+########################################
+# 2) Telegram bot minimal
+########################################
+TELEGRAM_BOT_TOKEN=
+TELEGRAM_CHAT_ID=
 TELEGRAM_CHAT_IDS=
-# Optional: route /city and /deb outputs to a fixed forum topic.
-# If TELEGRAM_QUERY_TOPIC_CHAT_ID is empty, fallback to command source chat.
 TELEGRAM_QUERY_TOPIC_CHAT_ID=
 TELEGRAM_QUERY_TOPIC_ID=
-# Optional per-group topic routing (higher priority than fixed topic above):
-# format: chat_id:topic_id,chat_id:topic_id
-# Example: TELEGRAM_QUERY_TOPIC_MAP=-1003586303099:25513,-1003539418691:25514
 TELEGRAM_QUERY_TOPIC_MAP=
-TELEGRAM_ALERT_PUSH_ENABLED=true
-TELEGRAM_ALERT_PUSH_INTERVAL_SEC=300
-TELEGRAM_ALERT_PUSH_COOLDOWN_SEC=1800
-TELEGRAM_ALERT_MIN_TRIGGER_COUNT=2
-TELEGRAM_ALERT_MIN_SEVERITY=medium
-# Mispricing radar: skip push when YES buy price is above this cap (10c = 0.10)
-TELEGRAM_ALERT_MISPRICING_MAX_YES_BUY=0.10
-TELEGRAM_ALERT_CITIES=ankara,london,paris,seoul,hong kong,shanghai,singapore,tokyo,tel aviv,toronto,buenos aires,wellington,new york,chicago,dallas,miami,atlanta,seattle,lucknow,sao paulo,munich
+POLYWEATHER_BOT_GROUP_INVITE_URL=
 
-# Open-Meteo (forecast data changes ~hourly, no need to refresh more often)
+########################################
+# 3) Weather + cache
+########################################
 OPEN_METEO_CACHE_TTL_SEC=7200
 OPEN_METEO_ENSEMBLE_CACHE_TTL_SEC=7200
 OPEN_METEO_MULTI_MODEL_CACHE_TTL_SEC=7200
 OPEN_METEO_MULTI_MODEL_CACHE_VERSION=v2
+OPEN_METEO_RATE_LIMIT_COOLDOWN_SEC=900
+OPEN_METEO_RATE_CACHE_TTL_SEC=3600
+OPEN_METEO_MIN_CALL_INTERVAL_SEC=3
+METAR_CACHE_TTL_SEC=600
+METEOBLUE_CACHE_TTL_SEC=7200
+POLYWEATHER_LGBM_ENABLED=false
+POLYWEATHER_LGBM_MODEL_PATH=/app/artifacts/models/lgbm_daily_high.txt
+POLYWEATHER_LGBM_SCHEMA_PATH=/app/artifacts/models/lgbm_daily_high_schema.json
+POLYWEATHER_LGBM_MIN_HISTORY_POINTS=3
 
-# Proxy Setting (optional)
-HTTPS_PROXY=http://127.0.0.1:7890
-HTTP_PROXY=http://127.0.0.1:7890
-
-# Other Settings
-LOG_LEVEL=INFO
-ENV=production
-POLYWEATHER_MAP_URL=https://polyweather-pro.vercel.app/
-# Runtime data directory (host path mounted into container at /var/lib/polyweather and /app/data)
-POLYWEATHER_RUNTIME_DATA_DIR=/var/lib/polyweather
-# Recommended: keep SQLite outside repository workspace
-POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
-# Recommended disk cache/state paths (optional; defaults are still /app/data/*)
-OPEN_METEO_DISK_CACHE_PATH=/var/lib/polyweather/open_meteo_cache.json
-# Unified Auth (Supabase + Google/Email)
+########################################
+# 4) Auth / entitlement
+########################################
 POLYWEATHER_AUTH_ENABLED=false
-# If true: website APIs require login; if false: guest access, login optional.
 POLYWEATHER_AUTH_REQUIRED=false
-# If true, authenticated users must also have an active row in `subscriptions`.
 POLYWEATHER_AUTH_REQUIRE_SUBSCRIPTION=false
+POLYWEATHER_REQUIRE_ENTITLEMENT=false
 SUPABASE_URL=
 SUPABASE_ANON_KEY=
 SUPABASE_SERVICE_ROLE_KEY=
 SUPABASE_HTTP_TIMEOUT_SEC=8
 SUPABASE_AUTH_CACHE_TTL_SEC=30
 SUPABASE_SUB_CACHE_TTL_SEC=60
-# Frontend wallet connection (WalletConnect v2)
-# Apply in Vercel env as NEXT_PUBLIC_*
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
+
+########################################
+# 5) Alerts / operations
+########################################
+TELEGRAM_ALERT_PUSH_ENABLED=true
+TELEGRAM_ALERT_PUSH_INTERVAL_SEC=300
+TELEGRAM_ALERT_PUSH_COOLDOWN_SEC=1800
+TELEGRAM_ALERT_MIN_TRIGGER_COUNT=2
+TELEGRAM_ALERT_MIN_SEVERITY=medium
+TELEGRAM_ALERT_MISPRICING_ONLY=true
+TELEGRAM_ALERT_MISPRICING_INTERVAL_SEC=7200
+TELEGRAM_MARKET_FOCUS_DIGEST_ENABLED=true
+TELEGRAM_MARKET_FOCUS_DIGEST_INTERVAL_SEC=1800
+TELEGRAM_MARKET_FOCUS_DIGEST_TOP_N=5
+TELEGRAM_ALERT_CITIES=ankara,london,paris,seoul,hong kong,shanghai,singapore,tokyo,tel aviv,toronto,buenos aires,wellington,new york,chicago,dallas,miami,atlanta,seattle,lucknow,sao paulo,munich
+POLYWEATHER_MONITORING_ALERT_CHAT_IDS=
+
+########################################
+# 6) Frontend-facing shared values
+########################################
 NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID=
 NEXT_PUBLIC_WALLETCONNECT_POLYGON_RPC_URL=https://polygon-bor-rpc.publicnode.com
-# Bot command access guard (/city, /deb):
-# - Pro entitlement removed
-# - user only needs to be a member of any configured group (TELEGRAM_CHAT_IDS / TELEGRAM_CHAT_ID)
-POLYWEATHER_BOT_GROUP_INVITE_URL=
-# Group message points (anti-spam + ranking)
-POLYWEATHER_BOT_MESSAGE_POINTS=4
-POLYWEATHER_BOT_MESSAGE_DAILY_CAP=40
-POLYWEATHER_BOT_MESSAGE_MIN_LENGTH=3
-POLYWEATHER_BOT_MESSAGE_COOLDOWN_SEC=30
-POLYWEATHER_BOT_CITY_QUERY_COST=1
-POLYWEATHER_BOT_DEB_QUERY_COST=1
-# Weekly leaderboard reward settlement
-# settle_weekday: 1=Mon ... 7=Sun
+
+########################################
+# 7) Optional modules
+########################################
+
+# Optional Groq commentary rewrite for intraday structure cards
+POLYWEATHER_GROQ_COMMENTARY_ENABLED=false
+GROQ_API_KEY=
+POLYWEATHER_GROQ_COMMENTARY_MODEL=openai/gpt-oss-20b
+POLYWEATHER_GROQ_COMMENTARY_TIMEOUT_SEC=8
+POLYWEATHER_GROQ_COMMENTARY_CACHE_TTL_SEC=1800
+
+# Weekly reward / leaderboard
 POLYWEATHER_WEEKLY_REWARD_ENABLED=true
 POLYWEATHER_WEEKLY_REWARD_TIMEZONE=Asia/Shanghai
 POLYWEATHER_WEEKLY_REWARD_SETTLE_WEEKDAY=1
@@ -78,24 +110,23 @@ POLYWEATHER_WEEKLY_REWARD_SETTLE_MINUTE=5
 POLYWEATHER_WEEKLY_REWARD_CHECK_INTERVAL_SEC=300
 POLYWEATHER_WEEKLY_REWARD_HTTP_TIMEOUT_SEC=10
 POLYWEATHER_WEEKLY_REWARD_ANNOUNCE_ENABLED=true
-# Backend entitlement guard (for /api/cities, /api/city/*, /api/history/*)
-POLYWEATHER_REQUIRE_ENTITLEMENT=false
-POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
 
-# P1 Contract Checkout (MetaMask + Polygon USDC)
+# Group message points
+POLYWEATHER_BOT_MESSAGE_POINTS=4
+POLYWEATHER_BOT_MESSAGE_DAILY_CAP=40
+POLYWEATHER_BOT_MESSAGE_MIN_LENGTH=3
+POLYWEATHER_BOT_MESSAGE_COOLDOWN_SEC=30
+POLYWEATHER_BOT_CITY_QUERY_COST=1
+POLYWEATHER_BOT_DEB_QUERY_COST=1
+
+# Payments
 POLYWEATHER_PAYMENT_ENABLED=false
 POLYWEATHER_PAYMENT_CHAIN_ID=137
 POLYWEATHER_PAYMENT_RPC_URL=https://polygon-rpc.com
-# Legacy single-token fallback (still supported)
+POLYWEATHER_PAYMENT_RPC_URLS=https://polygon-rpc.com
 POLYWEATHER_PAYMENT_RECEIVER_CONTRACT=
 POLYWEATHER_PAYMENT_TOKEN_ADDRESS=0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174
 POLYWEATHER_PAYMENT_TOKEN_DECIMALS=6
-# Recommended multi-token config (supports USDC.e + Native USDC at the same time)
-# Example:
-# [
-#   {"code":"usdc_e","symbol":"USDC.e","name":"USDC.e (PoS)","address":"0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174","decimals":6,"receiver_contract":"0xYourCheckoutContract","is_default":true},
-#   {"code":"usdc","symbol":"USDC","name":"Native USDC","address":"0x3c499c542cef5e3811e1192ce70d8cc03d5c3359","decimals":6,"receiver_contract":"0xYourCheckoutContract"}
-# ]
 POLYWEATHER_PAYMENT_ACCEPTED_TOKENS_JSON=
 POLYWEATHER_PAYMENT_CONFIRMATIONS=2
 POLYWEATHER_PAYMENT_INTENT_TTL_SEC=1800
@@ -104,18 +135,13 @@ POLYWEATHER_PAYMENT_HTTP_TIMEOUT_SEC=10
 POLYWEATHER_PAYMENT_POLL_INTERVAL_SEC=4
 POLYWEATHER_PAYMENT_MAX_WAIT_SEC=50
 POLYWEATHER_PAYMENT_TELEGRAM_NOTIFY_ENABLED=true
-# Payment points redemption
 POLYWEATHER_PAYMENT_POINTS_ENABLED=true
 POLYWEATHER_PAYMENT_POINTS_PER_USDC=500
 POLYWEATHER_PAYMENT_POINTS_MAX_DISCOUNT_USDC=3
-# Comma-separated allowed plans for checkout UI + backend validation.
-# Default is monthly-only launch.
 POLYWEATHER_PAYMENT_ALLOWED_PLAN_CODES=pro_monthly
-# JSON object
-# Example: {"pro_monthly":{"plan_id":101,"amount_usdc":"5","duration_days":30}}
 POLYWEATHER_PAYMENT_PLAN_CATALOG_JSON=
 
-# Polymarket P0 Read-Only Market Layer
+# Polymarket market scan
 POLYMARKET_MARKET_SCAN_ENABLED=true
 POLYMARKET_GAMMA_URL=https://gamma-api.polymarket.com
 POLYMARKET_CLOB_URL=https://clob.polymarket.com
@@ -128,10 +154,10 @@ POLYMARKET_DISCOVERY_LIMIT=200
 POLYMARKET_SIGNAL_MIN_LIQUIDITY=500
 POLYMARKET_SIGNAL_EDGE_PCT=2
 
-# Polygon Wallet Watcher (Single Chain P0)
+# Polygon watcher
 POLYGON_WALLET_WATCH_ENABLED=false
 POLYGON_RPC_URL=https://polygon-rpc.com
-POLYGON_WALLET_WATCH_ADDRESSES=0x0000000000000000000000000000000000000000
+POLYGON_WALLET_WATCH_ADDRESSES=
 POLYGON_WALLET_WATCH_INTERVAL_SEC=8
 POLYGON_WALLET_WATCH_CONFIRMATIONS=2
 POLYGON_WALLET_WATCH_MAX_BLOCKS_PER_CYCLE=30
@@ -141,24 +167,15 @@ POLYGON_WALLET_WATCH_TX_BASE=https://polygonscan.com/tx
 POLYGON_WALLET_WATCH_ADDR_BASE=https://polygonscan.com/address
 POLYGON_WALLET_WATCH_POLYMARKET_ONLY=true
 POLYGON_WALLET_WATCH_INCLUDE_DEFAULT_PM_CONTRACTS=true
-# Optional custom Polymarket contracts, format: LABEL:0x...,LABEL2:0x...
 POLYGON_WALLET_WATCH_POLYMARKET_CONTRACTS=
 
-# Polymarket Wallet Activity Watcher (all markets, not weather-only)
+# Polymarket wallet activity (retired; replaced by market monitor digests + critical alerts)
 POLYMARKET_WALLET_ACTIVITY_ENABLED=false
-POLYMARKET_WALLET_ACTIVITY_USERS=0x0000000000000000000000000000000000000000
-# Optional dedicated chat targets for wallet activity push (recommended)
-# If unset, fallback to TELEGRAM_CHAT_IDS / TELEGRAM_CHAT_ID.
+POLYMARKET_WALLET_ACTIVITY_USERS=
 POLYMARKET_WALLET_ACTIVITY_CHAT_ID=
 POLYMARKET_WALLET_ACTIVITY_CHAT_IDS=
-# Optional: mirror wallet activity push to a forum topic, while keeping existing chat targets unchanged.
 POLYMARKET_WALLET_ACTIVITY_TOPIC_CHAT_ID=
 POLYMARKET_WALLET_ACTIVITY_TOPIC_ID=
-# Optional wallet nicknames:
-# - CSV: 0xabc...=Whale_A,0xdef...=Main_Account
-# - JSON: {"0xabc...":"Whale A","0xdef...":"Main Account"}
-# - Env key: POLYMARKET_WALLET_ACTIVITY_USER_ALIASES
-#   (legacy typo POLYMARKET_WALLET_ACTIVITY_USERS_ALIASES is also accepted)
 POLYMARKET_WALLET_ACTIVITY_USER_ALIASES=
 POLYMARKET_WALLET_ACTIVITY_DATA_API_URL=https://data-api.polymarket.com
 POLYMARKET_WALLET_ACTIVITY_INTERVAL_SEC=20
@@ -177,10 +194,11 @@ POLYMARKET_WALLET_ACTIVITY_UPDATE_DEBOUNCE_SEC=30
 POLYMARKET_WALLET_ACTIVITY_UPDATE_MAX_HOLD_SEC=120
 POLYMARKET_WALLET_ACTIVITY_AVG_PRICE_SHOW_MIN=0.01
 POLYMARKET_WALLET_ACTIVITY_AVG_PRICE_SHOW_MAX=0.99
-# Skip wallet activity pushes when position value is below this floor (USD).
-# Set 0 to disable.
 POLYMARKET_WALLET_ACTIVITY_MIN_POSITION_VALUE_USD=0
-# Comma-separated wallet addresses exempt from min value floor.
-# Example: 0x849d9a4dd64829b8b0141ea53e7caca7e99529ec
 POLYMARKET_WALLET_ACTIVITY_MIN_VALUE_EXEMPT_USERS=
 
+########################################
+# 8) Optional proxies
+########################################
+HTTPS_PROXY=
+HTTP_PROXY=

.env.secrets.example

@@ -0,0 +1,44 @@
+# PolyWeather secrets-only template
+# Copy the required lines into your real `.env` / platform secret manager.
+# Never commit actual values.
+
+########################################
+# Telegram
+########################################
+TELEGRAM_BOT_TOKEN=
+
+########################################
+# Supabase
+########################################
+SUPABASE_URL=
+SUPABASE_ANON_KEY=
+SUPABASE_SERVICE_ROLE_KEY=
+NEXT_PUBLIC_SUPABASE_URL=
+NEXT_PUBLIC_SUPABASE_ANON_KEY=
+
+########################################
+# Entitlement / dashboard
+########################################
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
+POLYWEATHER_DASHBOARD_ACCESS_TOKEN=
+
+########################################
+# Meteoblue / third-party APIs
+########################################
+METEOBLUE_API_KEY=
+
+########################################
+# Wallet / payments
+########################################
+NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID=
+POLYWEATHER_PAYMENT_RECEIVER_CONTRACT=
+POLYWEATHER_PAYMENT_ACCEPTED_TOKENS_JSON=
+POLYWEATHER_PAYMENT_PLAN_CATALOG_JSON=
+
+########################################
+# Optional exchange / market secrets
+########################################
+POLYMARKET_API_KEY=
+POLYMARKET_SECRET_KEY=
+POLYMARKET_PASSPHRASE=
+POLYMARKET_WALLET_ADDRESS=

.github/workflows/ci.yml

@@ -0,0 +1,61 @@
+name: CI
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+
+jobs:
+  python-quality:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt -r requirements-dev.txt
+
+      - name: Ruff
+        run: python -m ruff check .
+
+      - name: Pytest
+        run: python -m pytest
+
+  frontend-quality:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: frontend
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Node
+        uses: actions/setup-node@v4
+        with:
+          node-version: "20"
+          cache: "npm"
+          cache-dependency-path: frontend/package-lock.json
+
+      - name: Install dependencies
+        run: npm ci
+
+      - name: Build
+        run: npm run build
+
+  docker-build:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Build Docker image
+        run: docker build -t polyweather-ci .

.gitignore

@@ -33,6 +33,7 @@ Thumbs.db
 frontend/node_modules/
 frontend/.next/
 frontend/.vercel/
+frontend/*.tsbuildinfo
 
 .npm-cache/
 .env.local

CHANGELOG.md

@@ -1,5 +1,50 @@
 # Changelog
 
+## 1.5.1 - 2026-03-23
+
+- `/ops` 页面增加管理员守卫，前后端双层限制管理员访问
+- `/ops` 支持会员列表、支付异常单、用户查询、周榜和手动补分
+- `/ops` 支付异常单支持按原因筛选、标记已处理，并补充支付异常审计视图
+- 会员列表支持按 `user_id` 去重，并优先回补 Supabase Auth 邮箱/注册时间
+- 新增按邮箱补跑订阅恢复脚本 `scripts/reconcile_subscription_by_email.py`
+- 支付确认失败（如 `receiver_mismatch`）现在会明确落 `failed`，并写入 SQLite 审计事件
+- 支付前强制重新拉取 `/api/payments/config`，并校验最新地址、允许域名和当前支付上下文
+- 浏览器钱包选择补齐 EIP-6963 发现、稳定去重和绑定后账户状态即时刷新
+- 城市详情页新增 `官方参考 / Official Sources` 区块，覆盖主要城市的官方机构/机场/METAR 链接
+- “今日日内分析”结构解读改为后端同源动态短评，并统一网页与 Bot 解释口径
+- 台北主结算源切换到 `NOAA RCTP`，按最终质控后的最高整度摄氏值展示和说明
+- 浏览器插件同步台北 `NOAA RCTP` 结算参考标签和说明
+- `/ops` 手机端收口为卡片化视图，保留桌面表格
+- 账户中心补充本周积分显示，`weekly_points` 与周排行同屏展示
+- Dashboard 历史对账补充“峰值前 12 小时 DEB 参考（近似）”卡片
+- 历史图不再错误混入 `settlement_history` 实测，历史样本仅按可比较样本统计
+- 新增 `scripts/backfill_recent_daily_actuals_from_metar.py`，支持为缺失 `daily_records` 的 METAR 城市补最近 14 天 `actual_high`
+- 历史接口对新接入的 METAR 城市增加自动 bootstrap，避免新增城市历史页整块空白
+- 香港历史/日内展示继续坚持 `HKO` 官方口径，不再 fallback 到 `VHHH METAR` 连续线
+- 香港 HKO 当天官方点位不再落单独 JSON，统一写入 runtime state
+- 今日日内结构信号按城市本地时间与峰值窗口分析，不再只看固定下午时段
+- 新增高空结构信号：冲高环境、压温风险、午后扰动、冲高效率，并提供中英文说明
+- 新增交易动作卡：结合高空结构、市场拥挤度与 `edge_percent` 输出 `偏暖侧 / 偏谨慎 / 先观察`
+- 非香港机场城市新增 `TAF` 接入，支持 `FM / TEMPO / BECMG / PROB30/40` 时间片解析
+- 温度走势图新增 `TAF 时段 / TAF Timing` 标记，并在 tooltip 中显示对应时段摘要
+- `TAF` 信号与 `market_signal / edge_percent` 联动进入交易动作，提示更贴近交易语境
+- `TAF` 展示词已改成普通用户可读版本：`基础时段 / 明确切换 / 临时波动 / 逐步转变`
+- 日内结构总摘要补充“TAF 未新增压温不等于继续升温”的解释，避免误读
+- 浏览器插件多日预报改为 `DEB` 优先，基础判断卡补充方向、置信度与原因，并统一引流到主站首页
+
+
+## Unreleased
+
+## 1.5.0 - 2026-03-21
+
+- 运行态状态与缓存支持 SQLite 渐进迁移，新增 `POLYWEATHER_STATE_STORAGE_MODE=file|dual|sqlite`
+- 新增 `/healthz`、`/api/system/status`、`/metrics`
+- 新增支付运行态接口 `/api/payments/runtime`
+- 支付侧新增 SQLite 审计事件、事件重放脚本与多 RPC 容灾支持
+- 新增支付静态审计脚本与 V2 合约升级草案
+- 统一周积分显示口径，`/top` 中“我的状态”改为累计发言/本周排名/本周积分
+- 文档同步更新为 2026-03-20 当前状态
+
 ## 1.4.0 - 2026-03-14
 
 - 统一收费阶段产品口径，发布 PolyWeather Pro `v1.4.0`

Dockerfile

@@ -6,6 +6,8 @@ WORKDIR /app
 # 设置环境变量
 ENV PYTHONDONTWRITEBYTECODE=1 \
     PYTHONUNBUFFERED=1 \
+    PIP_DISABLE_PIP_VERSION_CHECK=1 \
+    PIP_ROOT_USER_ACTION=ignore \
     TZ=UTC
 
 # 安装系统依赖 (如果有必要的包可以取消注释)
@@ -15,7 +17,7 @@ ENV PYTHONDONTWRITEBYTECODE=1 \
 COPY requirements.txt .
 
 # 安装 Python 依赖
-RUN pip install --no-cache-dir -r requirements.txt
+RUN pip install --no-cache-dir --prefer-binary -r requirements.txt
 
 # 复制项目代码
 COPY . .

FRONTEND_REDESIGN_REPORT.md

@@ -1,4 +1,4 @@
-# 前端交付与重构报告（v1.4.0）
+# 前端交付与重构报告（v1.5.1）
 
 最后更新：`2026-03-14`
 

LICENSE

@@ -1,21 +1,661 @@
-MIT License
+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
 
-Copyright (c) 2026 Yuanzhen Yang (yangyuan-zhen)
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
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+Public License "or any later version" applies to it, you have the
+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation.  If the Program does not specify a version number of the
+GNU Affero General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU Affero General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
+permissions.  However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU Affero General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU Affero General Public License for more details.
+
+    You should have received a copy of the GNU Affero General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If your software can interact with users remotely through a computer
+network, you should also make sure that it provides a way for users to
+get its source.  For example, if your program is a web application, its
+interface could display a "Source" link that leads users to an archive
+of the code.  There are many ways you could offer source, and different
+solutions will be better for different programs; see section 13 for the
+specific requirements.
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU AGPL, see
+<https://www.gnu.org/licenses/>.

README.md

@@ -3,6 +3,9 @@
 Production weather-intelligence stack for temperature settlement markets.
 
 Official dashboard: [polyweather-pro.vercel.app](https://polyweather-pro.vercel.app/)
+中文说明: [README_ZH.md](README_ZH.md)
+
+Public docs center: `/docs/intro` on the main site (bilingual product documentation, including intraday signals, TAF, settlement sources, history, and extension).
 
 ## Product Screenshots
 
@@ -14,29 +17,42 @@ Official dashboard: [polyweather-pro.vercel.app](https://polyweather-pro.vercel.
 
 ![PolyWeather Ankara analysis](docs/images/demo_ankara.png)
 
-## Product Status (2026-03)
+## Product Status (2026-03-24)
 
 - Subscription live: `Pro Monthly 5 USDC`.
 - Points redemption live: `500 points = 1 USDC`, max `3 USDC` off.
 - Onchain checkout live: Polygon contract checkout (USDC / USDC.e).
 - Auto-reconciliation live: event listener + periodic confirm loop.
+- Ops dashboard live: `/ops` for memberships, leaderboard, manual point grants, and payment incident triage.
+- Lightweight observability live: `/healthz`, `/api/system/status`, `/metrics`.
+- Runtime state, cache, and core offline training/backfill flows now use SQLite as the primary path; legacy JSON/JSONL files remain only for migration, export, and explicit fallback input.
+- EMOS/CRPS pipeline is integrated in `shadow` mode with rollout gating.
+- Intraday structural signal is now peak-window aware and bilingual (`zh-CN` / `en-US`).
+- Non-Hong Kong airport cities now ingest `TAF` and parse `FM / TEMPO / BECMG / PROB30/40`.
+- Temperature chart now overlays `TAF Timing` markers near the expected peak window.
+- Trade cue now combines upper-air structure, `TAF`, market crowding, and `edge_percent`.
+- Browser extension now uses `DEB` for multi-day forecast and stays positioned as a lightweight lead-in to the main site.
 
-## Open-Core Boundary (Important)
+## License & Commercial Boundary
 
-This repository follows an **Open-Core** strategy:
+This repository is licensed under **GNU AGPL-3.0 only** from `2026-03-30` onward.
 
-- Public in repo: weather aggregation, core analysis, dashboard, bot baseline, standard payment flow.
-- Private in production: commercial risk rules, operational thresholds, pricing strategy details, internal reconciliation policies, and growth operations tooling.
+- Public in repo: weather aggregation, core analysis, dashboard, bot baseline, and standard payment flow.
+- Not included in this repository: private production data, internal operating thresholds, commercial risk rules, pricing strategy details, and growth tooling.
+- Trademark, brand, domain, production databases, and hosted-service operations are **not** granted by the code license.
 
-See: [Open-Core & Commercial Boundary](docs/OPEN_CORE_POLICY.md)
+See: [AGPL-3.0 & Commercial Boundary](docs/OPEN_CORE_POLICY.md)
 
 ## Core Capabilities
 
-- Aggregates observations and forecasts for 20 monitored cities.
+- Aggregates observations and forecasts for 30 monitored cities.
 - Uses DEB (Dynamic Error Balancing) to blend multi-model highs.
 - Generates settlement-oriented probability buckets (`mu` + bucket distribution).
 - Maps weather view to Polymarket quotes for mispricing scan.
 - Reuses one analysis core across web dashboard and Telegram bot.
+- Adds payment audit trails, replay tooling, and incident visibility in ops.
+- Adds peak-window-oriented intraday structure cards for surface + upper-air analysis.
+- Adds airport-side `TAF` timing overlays and airport suppression/disruption interpretation for non-Hong Kong airport cities.
 
 ## Reference Architecture
 
@@ -49,20 +65,23 @@ flowchart LR
 
     API --> WX["Weather Collector"]
     WX --> METAR["Aviation Weather (METAR)"]
+    WX --> TAF["Aviation Weather (TAF)"]
     WX --> MGM["MGM (Turkey station network)"]
     WX --> OM["Open-Meteo"]
+    WX --> HKO["HKO / NOAA / Official settlement sources"]
 
     API --> ANA["DEB + Trend + Probability + Market Scan"]
     ANA --> PAY["Payment State (Intent + Event + Confirm Loop)"]
     ANA --> PM["Polymarket Read-only Layer"]
 ```
 
-## Monitored Cities (20)
+## Monitored Cities (30)
 
-- Europe / Middle East: Ankara, London, Paris, Munich
-- APAC: Seoul, Hong Kong, Shanghai, Singapore, Tokyo, Wellington
+- Europe / Middle East: Ankara, London, Paris, Munich, Tel Aviv, Milan, Warsaw, Madrid
+- APAC: Seoul, Hong Kong, Taipei, Shanghai, Singapore, Tokyo, Wellington
 - Americas: Toronto, New York, Chicago, Dallas, Miami, Atlanta, Seattle, Buenos Aires, Sao Paulo
 - South Asia: Lucknow
+- China extension: Chengdu, Chongqing, Shenzhen, Beijing, Wuhan
 
 ## Quick Start
 
@@ -80,6 +99,18 @@ npm install
 npm run dev
 ```
 
+## Recent Highlights
+
+- Taipei settlement is aligned to `Wunderground RCSS` with whole-degree Celsius resolution logic.
+- Shenzhen settlement is aligned to `Wunderground ZGSZ`.
+- Hong Kong keeps `HKO` official readings in dashboard and history, without falling back to airport METAR lines.
+- Intraday analysis now separates:
+  - `Surface Structure`
+  - `Upper-Air Structure`
+  - `Trade cue`
+- `TAF` is used as an airport-side confirmation layer, not as the main temperature model.
+- Browser extension remains a lightweight monitoring + basic-bias product, while the site holds the full analysis experience.
+
 ## Runtime Data (Recommended on VPS)
 
 Use external runtime storage to avoid SQLite/git conflicts:
@@ -87,10 +118,19 @@ Use external runtime storage to avoid SQLite/git conflicts:
 ```env
 POLYWEATHER_RUNTIME_DATA_DIR=/var/lib/polyweather
 POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
+POLYWEATHER_STATE_STORAGE_MODE=sqlite
 ```
 
 ## Ops Verification
 
+### Health / system status / metrics
+
+```bash
+curl http://127.0.0.1:8000/healthz
+curl http://127.0.0.1:8000/api/system/status
+curl http://127.0.0.1:8000/metrics
+```
+
 ### Frontend cache headers
 
 ```bash
@@ -103,6 +143,12 @@ POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
 docker compose logs -f polyweather | egrep "payment event loop started|payment confirm loop started|payment auto-confirmed"
 ```
 
+### Payment runtime
+
+```bash
+curl http://127.0.0.1:8000/api/payments/runtime
+```
+
 ### Wallet activity logs
 
 ```bash
@@ -124,17 +170,25 @@ docker compose logs -f polyweather | egrep "polymarket wallet activity watcher s
 
 - Chinese overview: [README_ZH.md](README_ZH.md)
 - Chinese API guide: [docs/API_ZH.md](docs/API_ZH.md)
+- TAF signal guide (ZH): [docs/TAF_SIGNAL_ZH.md](docs/TAF_SIGNAL_ZH.md)
 - Commercialization: [docs/COMMERCIALIZATION.md](docs/COMMERCIALIZATION.md)
-- Open-Core policy: [docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
+- AGPL-3.0 policy: [docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
 - Supabase setup (ZH): [docs/SUPABASE_SETUP_ZH.md](docs/SUPABASE_SETUP_ZH.md)
+- Configuration & secrets (ZH): [docs/CONFIGURATION_ZH.md](docs/CONFIGURATION_ZH.md)
+- LightGBM daily-high model (ZH): [docs/LGBM_DAILY_HIGH_ZH.md](docs/LGBM_DAILY_HIGH_ZH.md)
+- Frontend deployment (ZH): [docs/FRONTEND_DEPLOYMENT_ZH.md](docs/FRONTEND_DEPLOYMENT_ZH.md)
 - Tech debt (EN): [docs/TECH_DEBT.md](docs/TECH_DEBT.md)
 - Tech debt (ZH): [docs/TECH_DEBT_ZH.md](docs/TECH_DEBT_ZH.md)
 - Payment verification: [docs/payments/POLYGONSCAN_VERIFY.md](docs/payments/POLYGONSCAN_VERIFY.md)
+- Payment audit: [docs/payments/PAYMENT_AUDIT_ZH.md](docs/payments/PAYMENT_AUDIT_ZH.md)
+- Payment V2 upgrade: [docs/payments/PAYMENT_UPGRADE_V2_ZH.md](docs/payments/PAYMENT_UPGRADE_V2_ZH.md)
+- Ops admin guide: [docs/OPS_ADMIN_ZH.md](docs/OPS_ADMIN_ZH.md)
+- Deep research report: [docs/deep-research-report.md](docs/deep-research-report.md)
 - Frontend report: [FRONTEND_REDESIGN_REPORT.md](FRONTEND_REDESIGN_REPORT.md)
 - Release process: [RELEASE.md](RELEASE.md)
 - Changelog: [CHANGELOG.md](CHANGELOG.md)
 
 ## Version
 
-- Version: `v1.4.0`
-- Last Updated: `2026-03-14`
+- Version: `v1.5.1`
+- Last Updated: `2026-03-24`

README_ZH.md

@@ -14,29 +14,37 @@
 
 ![PolyWeather Ankara 分析页](docs/images/demo_ankara.png)
 
-## 当前产品状态（2026-03）
+## 当前产品状态（2026-03-21）
 
 - 已上线订阅制：`Pro 月付 5 USDC`。
 - 已上线积分抵扣：`500 积分 = 1 USDC`，最多抵扣 `3 USDC`。
 - 已上线链上支付：Polygon 合约支付（USDC / USDC.e）。
 - 已上线自动补单：事件监听 + 周期确认双链路。
+- 已上线支付运行态与审计接口：`/api/payments/runtime`。
+- 已上线轻量运营后台：`/ops`（会员、周榜、补分、支付异常单）。
+- 已上线轻量可观测性：`/healthz`、`/api/system/status`、`/metrics`。
+- 已补最小外部监控栈：Prometheus + Alertmanager + Grafana + Telegram 告警 relay。
+- 运行态状态、缓存与核心离线训练/回填链路已完成 SQLite 主路径收口；legacy JSON/JSONL 仅保留给迁移、导出与显式回退输入。
+- 已接入 EMOS/CRPS 校准链路，但当前仍保持 `emos_shadow`。
 
-## 开源边界（重要）
+## 许可证与商用边界（重要）
 
-本项目采用 **Open-Core** 策略：
+本仓库自 `2026-03-30` 起采用 **GNU AGPL-3.0-only**。
 
-- 仓库公开部分：天气聚合、基础分析、前端看板、Bot 基础能力、支付标准流程示例。
-- 生产私有部分：商业风控规则、运营阈值、收费策略细节、付费用户运营脚本、内部对账与审计策略。
+- 仓库公开部分：天气聚合、基础分析、前端看板、Bot 基础能力、标准支付流程。
+- 不包含在仓库中的部分：生产私有数据、商业风控规则、运营阈值、收费策略细节、内部对账与增长工具。
+- 商标、品牌、域名、生产数据库与托管服务运营能力，不因代码许可证一并授权。
 
-详细见：[Open-Core 与商用边界](docs/OPEN_CORE_POLICY.md)
+详细见：[AGPL-3.0 与商用边界](docs/OPEN_CORE_POLICY.md)
 
 ## 核心能力
 
-- 聚合 20 个监控城市的实测与预报数据。
+- 聚合 30 个监控城市的实测与预报数据。
 - DEB（Dynamic Error Balancing）融合多模型最高温。
 - 输出结算导向概率分布（`mu` + 温度桶）。
 - 将模型观点映射到 Polymarket 行情，做错价扫描。
 - Web 仪表盘与 Telegram Bot 复用同一分析内核。
+- 支付链路具备事件重放、SQLite 审计事件与 RPC 容灾能力。
 
 ## 参考架构
 
@@ -55,14 +63,17 @@ flowchart LR
     API --> ANA["DEB + 趋势 + 概率 + 市场扫描"]
     ANA --> PAY["支付状态（Intent + Event + Confirm Loop）"]
     ANA --> PM["Polymarket 只读层"]
+    API --> OBS["healthz / system status / metrics"]
+    ANA --> STATE["SQLite runtime state<br/>legacy files only for migration/export fallback"]
 ```
 
-## 监控城市（20）
+## 监控城市（30）
 
-- 欧洲/中东：Ankara、London、Paris、Munich
-- 亚太：Seoul、Hong Kong、Shanghai、Singapore、Tokyo、Wellington
+- 欧洲/中东：Ankara、London、Paris、Munich、Tel Aviv、Milan、Warsaw、Madrid
+- 亚太：Seoul、Hong Kong、Taipei、Shanghai、Singapore、Tokyo、Wellington
 - 美洲：Toronto、New York、Chicago、Dallas、Miami、Atlanta、Seattle、Buenos Aires、Sao Paulo
 - 南亚：Lucknow
+- 中国扩展：Chengdu、Chongqing、Shenzhen、Beijing、Wuhan
 
 ## 快速启动
 
@@ -87,10 +98,19 @@ npm run dev
 ```env
 POLYWEATHER_RUNTIME_DATA_DIR=/var/lib/polyweather
 POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
+POLYWEATHER_STATE_STORAGE_MODE=sqlite
 ```
 
 ## 运维验收
 
+### 健康与系统状态
+
+```bash
+curl http://127.0.0.1:8000/healthz
+curl http://127.0.0.1:8000/api/system/status
+curl http://127.0.0.1:8000/metrics
+```
+
 ### 前端缓存头
 
 ```bash
@@ -103,6 +123,37 @@ POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
 docker compose logs -f polyweather | egrep "payment event loop started|payment confirm loop started|payment auto-confirmed"
 ```
 
+### 外部监控栈
+
+```bash
+docker compose --profile monitoring up -d polyweather_prometheus polyweather_alertmanager polyweather_alert_relay polyweather_grafana
+```
+
+- Prometheus：`http://127.0.0.1:${POLYWEATHER_PROMETHEUS_PORT:-9090}`
+- Alertmanager：`http://127.0.0.1:${POLYWEATHER_ALERTMANAGER_PORT:-9093}`
+- Grafana：`http://127.0.0.1:${POLYWEATHER_GRAFANA_PORT:-3001}`
+
+手动巡检：
+
+```bash
+python scripts/check_ops_health.py --base-url http://127.0.0.1:8000
+```
+
+### 支付运行态
+
+```bash
+curl http://127.0.0.1:8000/api/payments/runtime
+```
+
+### 运营后台
+
+- 前端入口：`https://polyweather-pro.vercel.app/ops`
+- 后端需配置：
+
+```env
+POLYWEATHER_OPS_ADMIN_EMAILS=yhrsc30@gmail.com
+```
+
 ### 钱包异动监听日志
 
 ```bash
@@ -125,16 +176,25 @@ docker compose logs -f polyweather | egrep "polymarket wallet activity watcher s
 - 英文总览：[README.md](README.md)
 - API 文档（中文）：[docs/API_ZH.md](docs/API_ZH.md)
 - 商业化说明：[docs/COMMERCIALIZATION.md](docs/COMMERCIALIZATION.md)
-- Open-Core 边界：[docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
+- AGPL-3.0 边界：[docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
 - Supabase 接入：[docs/SUPABASE_SETUP_ZH.md](docs/SUPABASE_SETUP_ZH.md)
+- 配置与密钥管理：[docs/CONFIGURATION_ZH.md](docs/CONFIGURATION_ZH.md)
+- 前端部署（Vercel）：[docs/FRONTEND_DEPLOYMENT_ZH.md](docs/FRONTEND_DEPLOYMENT_ZH.md)
+- EMOS 训练报告：[docs/EMOS_TRAINING_REPORT_ZH.md](docs/EMOS_TRAINING_REPORT_ZH.md)
+- 概率快照归档：[docs/PROBABILITY_SNAPSHOT_ARCHIVE_ZH.md](docs/PROBABILITY_SNAPSHOT_ARCHIVE_ZH.md)
 - 技术债（中文镜像）：[docs/TECH_DEBT_ZH.md](docs/TECH_DEBT_ZH.md)
 - 技术债（主文档）：[docs/TECH_DEBT.md](docs/TECH_DEBT.md)
 - 支付合约验证：[docs/payments/POLYGONSCAN_VERIFY.md](docs/payments/POLYGONSCAN_VERIFY.md)
+- 支付审计说明：[docs/payments/PAYMENT_AUDIT_ZH.md](docs/payments/PAYMENT_AUDIT_ZH.md)
+- 支付 V2 升级方案：[docs/payments/PAYMENT_UPGRADE_V2_ZH.md](docs/payments/PAYMENT_UPGRADE_V2_ZH.md)
+- 运营后台说明：[docs/OPS_ADMIN_ZH.md](docs/OPS_ADMIN_ZH.md)
+- 外部监控说明：[docs/MONITORING_ZH.md](docs/MONITORING_ZH.md)
+- 深度评估报告：[docs/deep-research-report.md](docs/deep-research-report.md)
 - 前端报告：[FRONTEND_REDESIGN_REPORT.md](FRONTEND_REDESIGN_REPORT.md)
 - 发布流程：[RELEASE.md](RELEASE.md)
 - 变更记录：[CHANGELOG.md](CHANGELOG.md)
 
 ## 当前版本
 
-- 版本：`v1.4.0`
-- 最后更新：`2026-03-14`
+- 版本：`v1.5.1`
+- 文档最后更新：`2026-03-21`

VERSION

@@ -1 +1 @@
-1.4.0
+1.5.1

artifacts/models/lgbm_daily_high_schema.json

@@ -0,0 +1,66 @@
+{
+  "model_type": "LightGBMRegressor",
+  "target": "actual_high",
+  "horizon": "D0",
+  "feature_names": [
+    "actual_high_lag_1",
+    "actual_high_lag_2",
+    "actual_high_lag_3",
+    "actual_high_lag_7",
+    "actual_high_mean_7",
+    "actual_high_mean_14",
+    "actual_high_trend_3",
+    "open_meteo",
+    "ecmwf",
+    "gfs",
+    "gem",
+    "jma",
+    "icon",
+    "mgm",
+    "nws",
+    "deb_prediction",
+    "model_median",
+    "model_spread",
+    "current_temp",
+    "max_so_far",
+    "humidity",
+    "wind_speed_kt",
+    "visibility_mi",
+    "local_hour",
+    "month",
+    "weekday",
+    "peak_status_code"
+  ],
+  "base_model_columns": [
+    "open_meteo",
+    "ecmwf",
+    "gfs",
+    "gem",
+    "jma",
+    "icon",
+    "mgm",
+    "nws"
+  ],
+  "model_path": "artifacts\\models\\lgbm_daily_high.txt",
+  "sample_count": 54,
+  "train_count": 42,
+  "validation_count": 12,
+  "metrics": {
+    "validation": {
+      "sample_count": 12,
+      "lgbm_mae": 1.349,
+      "deb_mae": 0.875,
+      "best_single_mae": 0.325,
+      "median_mae": 0.758
+    },
+    "full_sample": {
+      "sample_count": 54,
+      "lgbm_mae": 0.691,
+      "deb_mae": 6.287,
+      "best_single_mae": 5.431,
+      "median_mae": 6.265
+    }
+  },
+  "generated_at": "2026-04-02T16:27:44.816882Z",
+  "trained_at": "2026-04-02T16:27:44.816882Z"
+}

artifacts/probability_calibration/default.json

@@ -0,0 +1,90 @@
+{
+  "version": "emos-20260402162744",
+  "trained_at": "2026-04-02T16:27:44.114836+00:00",
+  "global": {
+    "mu": {
+      "intercept": 1.54512641,
+      "raw_mu_coef": 2.96105052,
+      "deb_coef": -1.53260815,
+      "ens_median_coef": -0.72849343,
+      "max_so_far_gap_coef": 9.52557689
+    },
+    "sigma": {
+      "intercept": 0.67432479,
+      "raw_sigma_coef": 0.6936692,
+      "spread_coef": 0.08877484,
+      "peak_flag_coef": -0.58374835,
+      "max_so_far_gap_coef": -0.8172477
+    }
+  },
+  "sigma_constraints": {
+    "min_ratio": 0.85,
+    "max_ratio": 1.35,
+    "absolute_min": 0.25,
+    "absolute_max": 3.0
+  },
+  "selection_guardrails": {
+    "max_mae_increase": 0.02,
+    "max_bucket_hit_drop": 0.01,
+    "max_bucket_brier_increase": 0.05
+  },
+  "blending": {
+    "alpha_mu": 0.0,
+    "alpha_sigma": 0.05
+  },
+  "cities": {
+    "ankara": {
+      "samples": 3,
+      "mu_bias": 1.271844,
+      "sigma_scale": 1.477644,
+      "confidence": 0.375
+    },
+    "hong kong": {
+      "samples": 4,
+      "mu_bias": 1.32008,
+      "sigma_scale": 1.04023,
+      "confidence": 0.5
+    },
+    "milan": {
+      "samples": 3,
+      "mu_bias": -3.935178,
+      "sigma_scale": 2.0,
+      "confidence": 0.375
+    },
+    "shanghai": {
+      "samples": 3,
+      "mu_bias": 1.810495,
+      "sigma_scale": 2.0,
+      "confidence": 0.375
+    },
+    "taipei": {
+      "samples": 3,
+      "mu_bias": 3.577828,
+      "sigma_scale": 2.0,
+      "confidence": 0.375
+    },
+    "warsaw": {
+      "samples": 3,
+      "mu_bias": -0.625333,
+      "sigma_scale": 1.25968,
+      "confidence": 0.375
+    }
+  },
+  "metrics": {
+    "sample_count": 54,
+    "mean_crps": 3.792563,
+    "legacy_mean_crps": 4.308029,
+    "legacy_mean_mae": 4.51037,
+    "legacy_bucket_hit_rate": 0.537037,
+    "legacy_bucket_brier": 0.833294,
+    "selected_mean_crps": 4.249828,
+    "selected_mean_mae": 4.51037,
+    "selected_bucket_hit_rate": 0.555556,
+    "selected_bucket_brier": 0.831872,
+    "selected_score": 5.991436,
+    "legacy_score": 6.078481,
+    "filled_actual_from_history": 0,
+    "settlement_history_city_count": 30
+  },
+  "source": "artifacts\\probability_calibration\\default.json"
+}

artifacts/probability_calibration/evaluation_report.json

@@ -0,0 +1,257 @@
+{
+  "summary": {
+    "sample_count": 54,
+    "filled_actual_from_history": 2,
+    "legacy": {
+      "mean_crps": 4.300621,
+      "mean_mae": 4.502963,
+      "bucket_hit_rate": 0.537037
+    },
+    "emos": {
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+      "mean_mae": 4.502963,
+      "bucket_hit_rate": 0.537037
+    },
+    "delta": {
+      "crps": -0.086732,
+      "mae": 0.0,
+      "bucket_hit_rate": 0.0
+    }
+  },
+  "by_city": {
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+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "atlanta": {
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+      "emos_mean_crps": 30.578432,
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+      "emos_mean_mae": 32.015,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "buenos aires": {
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+      "legacy_mean_crps": 9.113412,
+      "emos_mean_crps": 8.759954,
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+      "emos_mean_mae": 10.27,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "chicago": {
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+      "emos_mean_crps": 0.701085,
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+      "emos_mean_mae": 0.0,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "dallas": {
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+      "emos_mean_mae": 0.0,
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+      "emos_bucket_hit_rate": 1.0
+    },
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+      "emos_mean_mae": 0.075,
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+      "emos_bucket_hit_rate": 0.75
+    },
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+      "emos_bucket_hit_rate": 0.0
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+      "emos_mean_mae": 3.205,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
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+      "emos_bucket_hit_rate": 0.0
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+      "emos_mean_mae": 30.175,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "milan": {
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+      "emos_mean_mae": 4.06,
+      "legacy_bucket_hit_rate": 0.666667,
+      "emos_bucket_hit_rate": 0.666667
+    },
+    "munich": {
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+      "legacy_mean_mae": 3.64,
+      "emos_mean_mae": 3.64,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "new york": {
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+      "legacy_mean_mae": 4.94,
+      "emos_mean_mae": 4.94,
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+      "emos_bucket_hit_rate": 0.0
+    },
+    "paris": {
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+      "legacy_bucket_hit_rate": 0.5,
+      "emos_bucket_hit_rate": 0.5
+    },
+    "sao paulo": {
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+      "emos_mean_crps": 5.272063,
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+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "seattle": {
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+      "emos_mean_crps": 0.425909,
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+      "emos_mean_mae": 0.0,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "seoul": {
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+      "legacy_mean_crps": 0.313754,
+      "emos_mean_crps": 0.412831,
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+      "emos_mean_mae": 0.15,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "shanghai": {
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+      "emos_mean_mae": 0.1,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "shenzhen": {
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+      "legacy_mean_mae": 0.9,
+      "emos_mean_mae": 0.9,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "singapore": {
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+      "emos_mean_mae": 0.15,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "taipei": {
+      "samples": 3,
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+      "emos_mean_crps": 0.472738,
+      "legacy_mean_mae": 0.1,
+      "emos_mean_mae": 0.1,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "tel aviv": {
+      "samples": 2,
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+      "emos_mean_crps": 0.578006,
+      "legacy_mean_mae": 0.3,
+      "emos_mean_mae": 0.3,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "tokyo": {
+      "samples": 2,
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+      "emos_mean_crps": 0.582151,
+      "legacy_mean_mae": 0.25,
+      "emos_mean_mae": 0.25,
+      "legacy_bucket_hit_rate": 0.5,
+      "emos_bucket_hit_rate": 1.0
+    },
+    "toronto": {
+      "samples": 2,
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+      "emos_mean_crps": 5.240552,
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+      "emos_mean_mae": 6.33,
+      "legacy_bucket_hit_rate": 0.0,
+      "emos_bucket_hit_rate": 0.0
+    },
+    "warsaw": {
+      "samples": 3,
+      "legacy_mean_crps": 1.618875,
+      "emos_mean_crps": 1.553232,
+      "legacy_mean_mae": 2.056667,
+      "emos_mean_mae": 2.056667,
+      "legacy_bucket_hit_rate": 0.333333,
+      "emos_bucket_hit_rate": 0.333333
+    },
+    "wellington": {
+      "samples": 2,
+      "legacy_mean_crps": 0.364919,
+      "emos_mean_crps": 0.475875,
+      "legacy_mean_mae": 0.15,
+      "emos_mean_mae": 0.15,
+      "legacy_bucket_hit_rate": 1.0,
+      "emos_bucket_hit_rate": 1.0
+    }
+  }
+}

artifacts/probability_calibration/rollout_report.json

@@ -0,0 +1,74 @@
+{
+  "evaluation_report_path": "E:\\web\\PolyWeather\\artifacts\\probability_calibration\\evaluation_report.json",
+  "shadow_report_path": "E:\\web\\PolyWeather\\artifacts\\probability_calibration\\shadow_report.json",
+  "evaluation_report_exists": true,
+  "shadow_report_exists": true,
+  "decision": {
+    "decision": "hold",
+    "ready_for_primary": false,
+    "summary": "当前指标不足以切换 emos_primary，应继续保持 shadow。",
+    "thresholds": {
+      "evaluation_min_samples": 80,
+      "shadow_min_samples": 50,
+      "max_delta_mae": 0.05,
+      "min_delta_crps": -0.02,
+      "min_delta_bucket_hit_rate": 0.0,
+      "max_delta_bucket_brier_promote": 0.02,
+      "max_delta_bucket_brier_observe": 0.15
+    },
+    "evaluation": {
+      "sample_count": 54,
+      "delta_crps": -0.086732,
+      "delta_mae": 0.0,
+      "delta_bucket_hit_rate": 0.0
+    },
+    "shadow": {
+      "sample_count": 48,
+      "delta_mae": 0.0,
+      "delta_bucket_hit_rate": 0.041666,
+      "delta_bucket_brier": 0.123252
+    },
+    "blocking_reasons": [
+      "离线评估样本不足：54 < 80",
+      "shadow 样本不足：48 < 50",
+      "shadow bucket brier 退化超限：delta=0.123252"
+    ],
+    "worst_shadow_regressions": [
+      {
+        "city": "dallas",
+        "samples": 1,
+        "delta_mae": 0.0,
+        "delta_bucket_hit_rate": 0.0,
+        "delta_bucket_brier": 0.792585
+      },
+      {
+        "city": "chicago",
+        "samples": 1,
+        "delta_mae": 0.0,
+        "delta_bucket_hit_rate": 0.0,
+        "delta_bucket_brier": 0.791878
+      },
+      {
+        "city": "seattle",
+        "samples": 1,
+        "delta_mae": 0.0,
+        "delta_bucket_hit_rate": 0.0,
+        "delta_bucket_brier": 0.61609
+      },
+      {
+        "city": "wellington",
+        "samples": 2,
+        "delta_mae": 0.0,
+        "delta_bucket_hit_rate": 0.0,
+        "delta_bucket_brier": 0.509203
+      },
+      {
+        "city": "tel aviv",
+        "samples": 2,
+        "delta_mae": 0.0,
+        "delta_bucket_hit_rate": 0.0,
+        "delta_bucket_brier": 0.439879
+      }
+    ]
+  }
+}

artifacts/probability_calibration/shadow_report.json

@@ -0,0 +1,933 @@
+{
+  "generated_at": "2026-04-02T16:23:24.376528Z",
+  "summary": {
+    "samples": 48,
+    "legacy_mean_mae": 3.04125,
+    "shadow_mean_mae": 3.04125,
+    "legacy_bucket_hit_rate": 0.5,
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+    "legacy_bucket_brier": 0.68666,
+    "shadow_bucket_brier": 0.814079,
+    "delta_mae": 0.0,
+    "delta_bucket_hit_rate": 0.0,
+    "delta_bucket_brier": 0.127419
+  },
+  "by_city": {
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+      "delta_mae": 0.0,
+      "delta_bucket_hit_rate": 0.0,
+      "delta_bucket_brier": 0.159801
+    },
+    "atlanta": {
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+      "shadow_mean_mae": 17.06,
+      "legacy_bucket_hit_rate": 0.0,
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+      "legacy_bucket_brier": 1.029097,
+      "shadow_bucket_brier": 1.064101,
+      "delta_mae": 0.0,
+      "delta_bucket_hit_rate": 0.0,
+      "delta_bucket_brier": 0.035004
+    },
+    "buenos aires": {
+      "samples": 2,
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+      "legacy_bucket_hit_rate": 0.0,
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+      "legacy_bucket_brier": 1.117726,
+      "shadow_bucket_brier": 1.116732,
+      "delta_mae": 0.0,
+      "delta_bucket_hit_rate": 0.0,
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+    },
+    "chicago": {
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+    },
+    "dallas": {
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+}

artifacts/probability_calibration/training_samples.json

@@ -0,0 +1,981 @@
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+    {
+      "city": "paris",
+      "date": "2026-03-19",
+      "actual_high": 8.0,
+      "raw_mu": 16.06,
+      "raw_sigma": 0.6,
+      "deb_prediction": 16.2,
+      "ens_median": 16.3,
+      "ensemble_spread": 0.6,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "sao paulo",
+      "date": "2026-03-18",
+      "actual_high": 22.0,
+      "raw_mu": 29.64,
+      "raw_sigma": 2.450000000000001,
+      "deb_prediction": 30.0,
+      "ens_median": 29.4,
+      "ensemble_spread": 2.450000000000001,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "sao paulo",
+      "date": "2026-03-19",
+      "actual_high": 21.0,
+      "raw_mu": 26.5,
+      "raw_sigma": 1.200000000000001,
+      "deb_prediction": 25.5,
+      "ens_median": 26.5,
+      "ensemble_spread": 1.200000000000001,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "seattle",
+      "date": "2026-03-18",
+      "actual_high": 55.9,
+      "raw_mu": 55.9,
+      "raw_sigma": 1.3500000000000014,
+      "deb_prediction": 55.8,
+      "ens_median": 55.9,
+      "ensemble_spread": 1.3500000000000014,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "seoul",
+      "date": "2026-03-18",
+      "actual_high": 8.0,
+      "raw_mu": 8.0,
+      "raw_sigma": 0.7999999999999998,
+      "deb_prediction": 7.4,
+      "ens_median": 7.4,
+      "ensemble_spread": 0.7999999999999998,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "seoul",
+      "date": "2026-03-19",
+      "actual_high": 10.0,
+      "raw_mu": 10.3,
+      "raw_sigma": 1.7999999999999998,
+      "deb_prediction": 7.6,
+      "ens_median": 6.3,
+      "ensemble_spread": 1.7999999999999998,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "shanghai",
+      "date": "2026-03-18",
+      "actual_high": 13.0,
+      "raw_mu": 13.0,
+      "raw_sigma": 1.1500000000000004,
+      "deb_prediction": 13.2,
+      "ens_median": 13.0,
+      "ensemble_spread": 1.1500000000000004,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "shanghai",
+      "date": "2026-03-19",
+      "actual_high": 12.0,
+      "raw_mu": 12.3,
+      "raw_sigma": 0.7999999999999998,
+      "deb_prediction": 10.7,
+      "ens_median": 11.2,
+      "ensemble_spread": 0.7999999999999998,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "shanghai",
+      "date": "2026-03-29",
+      "actual_high": 18.0,
+      "raw_mu": 18.0,
+      "raw_sigma": 1.6999999999999993,
+      "deb_prediction": 18.4,
+      "ens_median": 17.6,
+      "ensemble_spread": 1.6999999999999993,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "singapore",
+      "date": "2026-03-18",
+      "actual_high": 32.0,
+      "raw_mu": 32.0,
+      "raw_sigma": 0.9500000000000011,
+      "deb_prediction": 30.2,
+      "ens_median": 30.1,
+      "ensemble_spread": 0.9500000000000011,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "singapore",
+      "date": "2026-03-19",
+      "actual_high": 32.0,
+      "raw_mu": 32.3,
+      "raw_sigma": 1.3499999999999996,
+      "deb_prediction": 31.5,
+      "ens_median": 32.1,
+      "ensemble_spread": 1.3499999999999996,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "taipei",
+      "date": "2026-03-17",
+      "actual_high": 26.7,
+      "raw_mu": 26.7,
+      "raw_sigma": 2.25,
+      "deb_prediction": 24.9,
+      "ens_median": 25.4,
+      "ensemble_spread": 2.25,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "taipei",
+      "date": "2026-03-18",
+      "actual_high": 29.0,
+      "raw_mu": 29.0,
+      "raw_sigma": 1.0500000000000007,
+      "deb_prediction": 27.2,
+      "ens_median": 27.5,
+      "ensemble_spread": 1.0500000000000007,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "taipei",
+      "date": "2026-03-19",
+      "actual_high": 22.0,
+      "raw_mu": 21.7,
+      "raw_sigma": 1.1500000000000004,
+      "deb_prediction": 21.5,
+      "ens_median": 21.3,
+      "ensemble_spread": 1.1500000000000004,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "tel aviv",
+      "date": "2026-03-18",
+      "actual_high": 30.0,
+      "raw_mu": 30.3,
+      "raw_sigma": 2.1500000000000004,
+      "deb_prediction": 29.0,
+      "ens_median": 28.9,
+      "ensemble_spread": 2.1500000000000004,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "tel aviv",
+      "date": "2026-03-19",
+      "actual_high": 21.0,
+      "raw_mu": 21.3,
+      "raw_sigma": 1.5,
+      "deb_prediction": 20.7,
+      "ens_median": 21.1,
+      "ensemble_spread": 1.5,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "tokyo",
+      "date": "2026-03-18",
+      "actual_high": 17.0,
+      "raw_mu": 17.0,
+      "raw_sigma": 1.5499999999999998,
+      "deb_prediction": 15.4,
+      "ens_median": 15.8,
+      "ensemble_spread": 1.5499999999999998,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "tokyo",
+      "date": "2026-03-19",
+      "actual_high": 16.0,
+      "raw_mu": 16.5,
+      "raw_sigma": 2.0999999999999996,
+      "deb_prediction": 17.8,
+      "ens_median": 18.5,
+      "ensemble_spread": 2.0999999999999996,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "toronto",
+      "date": "2026-03-18",
+      "actual_high": -6.0,
+      "raw_mu": -1.01,
+      "raw_sigma": 0.8,
+      "deb_prediction": -0.6,
+      "ens_median": -1.1,
+      "ensemble_spread": 0.8,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "toronto",
+      "date": "2026-03-19",
+      "actual_high": -2.0,
+      "raw_mu": 5.67,
+      "raw_sigma": 2.1500000000000004,
+      "deb_prediction": 6.4,
+      "ens_median": 6.3,
+      "ensemble_spread": 2.1500000000000004,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "warsaw",
+      "date": "2026-03-17",
+      "actual_high": 11.0,
+      "raw_mu": 11.3,
+      "raw_sigma": 0.6499999999999995,
+      "deb_prediction": 10.4,
+      "ens_median": 10.5,
+      "ensemble_spread": 0.6499999999999995,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "warsaw",
+      "date": "2026-03-18",
+      "actual_high": 13.0,
+      "raw_mu": 13.84,
+      "raw_sigma": 1.4000000000000004,
+      "deb_prediction": 13.6,
+      "ens_median": 14.2,
+      "ensemble_spread": 1.4000000000000004,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "warsaw",
+      "date": "2026-03-19",
+      "actual_high": 7.0,
+      "raw_mu": 12.03,
+      "raw_sigma": 1.5999999999999996,
+      "deb_prediction": 11.8,
+      "ens_median": 12.3,
+      "ensemble_spread": 1.5999999999999996,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "wellington",
+      "date": "2026-03-18",
+      "actual_high": 21.0,
+      "raw_mu": 21.0,
+      "raw_sigma": 0.9500000000000011,
+      "deb_prediction": 19.2,
+      "ens_median": 19.1,
+      "ensemble_spread": 0.9500000000000011,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    },
+    {
+      "city": "wellington",
+      "date": "2026-03-19",
+      "actual_high": 18.0,
+      "raw_mu": 18.3,
+      "raw_sigma": 2.0999999999999996,
+      "deb_prediction": 17.9,
+      "ens_median": 17.1,
+      "ensemble_spread": 2.0999999999999996,
+      "max_so_far_gap": null,
+      "peak_flag": 0.0,
+      "sample_source": "daily_record",
+      "settlement_source": null,
+      "settlement_station_code": null,
+      "truth_version": null,
+      "truth_updated_by": null,
+      "truth_updated_at": null
+    }
+  ]
+}

contracts/PolyWeatherCheckout.sol

@@ -1,4 +1,4 @@
-// SPDX-License-Identifier: MIT
+// SPDX-License-Identifier: AGPL-3.0-only
 pragma solidity ^0.8.24;
 
 interface IERC20 {

contracts/PolyWeatherCheckoutV2.sol

@@ -0,0 +1,267 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+pragma solidity ^0.8.24;
+
+interface IERC20 {
+    function transferFrom(address from, address to, uint256 value) external returns (bool);
+    function transfer(address to, uint256 value) external returns (bool);
+}
+
+library Address {
+    function functionCall(address target, bytes memory data, string memory errorMessage) internal returns (bytes memory) {
+        (bool success, bytes memory returndata) = target.call(data);
+        require(success, errorMessage);
+        return returndata;
+    }
+}
+
+library SafeERC20 {
+    using Address for address;
+
+    function safeTransferFrom(IERC20 token, address from, address to, uint256 value) internal {
+        bytes memory returndata = address(token).functionCall(
+            abi.encodeWithSelector(token.transferFrom.selector, from, to, value),
+            "SAFE_TRANSFER_FROM_FAILED"
+        );
+        if (returndata.length > 0) {
+            require(abi.decode(returndata, (bool)), "SAFE_TRANSFER_FROM_FALSE");
+        }
+    }
+
+    function safeTransfer(IERC20 token, address to, uint256 value) internal {
+        bytes memory returndata = address(token).functionCall(
+            abi.encodeWithSelector(token.transfer.selector, to, value),
+            "SAFE_TRANSFER_FAILED"
+        );
+        if (returndata.length > 0) {
+            require(abi.decode(returndata, (bool)), "SAFE_TRANSFER_FALSE");
+        }
+    }
+}
+
+abstract contract Ownable {
+    address public owner;
+
+    event OwnershipTransferred(address indexed previousOwner, address indexed newOwner);
+
+    modifier onlyOwner() {
+        require(msg.sender == owner, "ONLY_OWNER");
+        _;
+    }
+
+    constructor(address initialOwner) {
+        require(initialOwner != address(0), "ZERO_OWNER");
+        owner = initialOwner;
+        emit OwnershipTransferred(address(0), initialOwner);
+    }
+
+    function transferOwnership(address newOwner) external onlyOwner {
+        require(newOwner != address(0), "ZERO_OWNER");
+        emit OwnershipTransferred(owner, newOwner);
+        owner = newOwner;
+    }
+}
+
+abstract contract Pausable {
+    bool public paused;
+
+    event Paused(address indexed account);
+    event Unpaused(address indexed account);
+
+    modifier whenNotPaused() {
+        require(!paused, "PAUSED");
+        _;
+    }
+
+    function _pause() internal {
+        require(!paused, "PAUSED");
+        paused = true;
+        emit Paused(msg.sender);
+    }
+
+    function _unpause() internal {
+        require(paused, "NOT_PAUSED");
+        paused = false;
+        emit Unpaused(msg.sender);
+    }
+}
+
+abstract contract ReentrancyGuard {
+    uint256 private _status = 1;
+
+    modifier nonReentrant() {
+        require(_status == 1, "REENTRANT");
+        _status = 2;
+        _;
+        _status = 1;
+    }
+}
+
+contract PolyWeatherCheckoutV2 is Ownable, Pausable, ReentrancyGuard {
+    using SafeERC20 for IERC20;
+
+    struct PlanConfig {
+        uint256 amount;
+        bool active;
+    }
+
+    bytes32 public constant AUTHORIZED_PAYMENT_TYPEHASH =
+        keccak256(
+            "AuthorizedPayment(bytes32 orderId,address payer,uint256 planId,address token,uint256 amount,uint256 nonce,uint256 deadline)"
+        );
+
+    bytes32 public immutable DOMAIN_SEPARATOR;
+
+    address public treasury;
+    address public signer;
+    mapping(address => bool) public allowedToken;
+    mapping(bytes32 => bool) public paidOrder;
+    mapping(uint256 => mapping(address => PlanConfig)) public planConfig;
+    mapping(address => uint256) public payerNonce;
+
+    event OrderPaid(
+        bytes32 indexed orderId,
+        address indexed payer,
+        uint256 indexed planId,
+        address token,
+        uint256 amount
+    );
+    event TreasuryUpdated(address indexed treasury);
+    event SignerUpdated(address indexed signer);
+    event TokenAllowedUpdated(address indexed token, bool allowed);
+    event PlanConfigured(uint256 indexed planId, address indexed token, uint256 amount, bool active);
+
+    constructor(address initialOwner, address initialTreasury, address initialSigner)
+        Ownable(initialOwner)
+    {
+        require(initialTreasury != address(0), "ZERO_TREASURY");
+        treasury = initialTreasury;
+        signer = initialSigner;
+
+        uint256 chainId;
+        assembly {
+            chainId := chainid()
+        }
+        DOMAIN_SEPARATOR = keccak256(
+            abi.encode(
+                keccak256(
+                    "EIP712Domain(string name,string version,uint256 chainId,address verifyingContract)"
+                ),
+                keccak256(bytes("PolyWeatherCheckoutV2")),
+                keccak256(bytes("1")),
+                chainId,
+                address(this)
+            )
+        );
+    }
+
+    function setTreasury(address newTreasury) external onlyOwner {
+        require(newTreasury != address(0), "ZERO_ADDR");
+        treasury = newTreasury;
+        emit TreasuryUpdated(newTreasury);
+    }
+
+    function setSigner(address newSigner) external onlyOwner {
+        signer = newSigner;
+        emit SignerUpdated(newSigner);
+    }
+
+    function setTokenAllowed(address token, bool allowed) external onlyOwner {
+        require(token != address(0), "ZERO_ADDR");
+        allowedToken[token] = allowed;
+        emit TokenAllowedUpdated(token, allowed);
+    }
+
+    function setPlan(uint256 planId, address token, uint256 amount, bool active) external onlyOwner {
+        require(planId > 0, "PLAN_ZERO");
+        require(token != address(0), "ZERO_ADDR");
+        require(amount > 0 || !active, "AMOUNT_ZERO");
+        planConfig[planId][token] = PlanConfig({amount: amount, active: active});
+        emit PlanConfigured(planId, token, amount, active);
+    }
+
+    function pause() external onlyOwner {
+        _pause();
+    }
+
+    function unpause() external onlyOwner {
+        _unpause();
+    }
+
+    function payPlan(bytes32 orderId, uint256 planId, address token)
+        external
+        whenNotPaused
+        nonReentrant
+    {
+        require(allowedToken[token], "TOKEN_NOT_ALLOWED");
+        PlanConfig memory config = planConfig[planId][token];
+        require(config.active, "PLAN_NOT_ACTIVE");
+        require(config.amount > 0, "PLAN_AMOUNT_ZERO");
+        _collect(orderId, msg.sender, planId, token, config.amount);
+    }
+
+    function payAuthorized(
+        bytes32 orderId,
+        uint256 planId,
+        address token,
+        uint256 amount,
+        uint256 deadline,
+        bytes calldata signature
+    ) external whenNotPaused nonReentrant {
+        require(allowedToken[token], "TOKEN_NOT_ALLOWED");
+        require(amount > 0, "AMOUNT_ZERO");
+        require(deadline >= block.timestamp, "AUTH_EXPIRED");
+        require(signer != address(0), "SIGNER_NOT_SET");
+
+        uint256 nonce = payerNonce[msg.sender];
+        bytes32 structHash = keccak256(
+            abi.encode(
+                AUTHORIZED_PAYMENT_TYPEHASH,
+                orderId,
+                msg.sender,
+                planId,
+                token,
+                amount,
+                nonce,
+                deadline
+            )
+        );
+        bytes32 digest = keccak256(
+            abi.encodePacked("\x19\x01", DOMAIN_SEPARATOR, structHash)
+        );
+        require(_recover(digest, signature) == signer, "BAD_SIGNATURE");
+        payerNonce[msg.sender] = nonce + 1;
+
+        _collect(orderId, msg.sender, planId, token, amount);
+    }
+
+    function rescueToken(address token, address to, uint256 amount) external onlyOwner nonReentrant {
+        require(token != address(0) && to != address(0), "ZERO_ADDR");
+        IERC20(token).safeTransfer(to, amount);
+    }
+
+    function _collect(bytes32 orderId, address payer, uint256 planId, address token, uint256 amount) internal {
+        require(!paidOrder[orderId], "ORDER_PAID");
+        paidOrder[orderId] = true;
+        IERC20(token).safeTransferFrom(payer, treasury, amount);
+        emit OrderPaid(orderId, payer, planId, token, amount);
+    }
+
+    function _recover(bytes32 digest, bytes calldata signature) internal pure returns (address) {
+        require(signature.length == 65, "BAD_SIG_LEN");
+        bytes32 r;
+        bytes32 s;
+        uint8 v;
+        assembly {
+            r := calldataload(signature.offset)
+            s := calldataload(add(signature.offset, 32))
+            v := byte(0, calldataload(add(signature.offset, 64)))
+        }
+        if (v < 27) {
+            v += 27;
+        }
+        require(v == 27 || v == 28, "BAD_SIG_V");
+        address recovered = ecrecover(digest, v, r, s);
+        require(recovered != address(0), "BAD_SIG");
+        return recovered;
+    }
+}

data/probability_training_snapshots.jsonl

@@ -0,0 +1,128 @@
+{"city": "ankara", "timestamp": "2026-03-20T12:00:00+03:00", "date": "2026-03-20", "temp_symbol": "°C", "raw_mu": 15.2, "raw_sigma": 1.2, "deb_prediction": 15.4, "ensemble": {"p10": 14.8, "median": 15.8, "p90": 17.9}, "multi_model": {"ECMWF": 15.8, "GFS": 14.1, "ICON": 15.9}, "max_so_far": 15.0, "peak_status": "before", "prob_snapshot": [{"v": 15, "p": 0.552}, {"v": 16, "p": 0.377}], "shadow_prob_snapshot": [{"v": 15, "p": 0.324}, {"v": 16, "p": 0.238}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320130245", "calibration_source": "artifacts/probability_calibration/default.json", "calibrated_mu": 15.1, "calibrated_sigma": 1.25}
+{"city": "test_city", "timestamp": "2026-03-04 10:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.5625, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 26.0, "peak_status": "before", "prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "shadow_prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.5625}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 33.3, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 33.0, "peak_status": "in_window", "prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "shadow_prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 33.3, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 22:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 10:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.5625, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 26.0, "peak_status": "before", "prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "shadow_prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.5625}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 33.3, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 33.0, "peak_status": "in_window", "prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "shadow_prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 33.3, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 22:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 10:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.5625, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 26.0, "peak_status": "before", "prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "shadow_prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.5625}
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+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 33.3, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 33.0, "peak_status": "in_window", "prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "shadow_prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 33.3, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
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+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 22:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 10:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.5625, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 26.0, "peak_status": "before", "prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "shadow_prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.5625}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 33.3, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 33.0, "peak_status": "in_window", "prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "shadow_prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 33.3, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 22:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
+{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
+{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
+{"city": "hong kong", "timestamp": "2026-03-23T21:10:00+08:00", "date": "2026-03-23", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.6806250000000001, "deb_prediction": 25.2, "ensemble": {"p10": 26.3, "median": 26.4, "p90": 26.6}, "multi_model": {"Open-Meteo": 24.8, "HKO(港天文)": 27.0, "ECMWF": 25.4, "GFS": 25.1, "ICON": 24.8, "GEM": 25.3, "JMA": 23.6}, "max_so_far": 27.4, "peak_status": "past", "prob_snapshot": [{"v": 27, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "shenzhen", "timestamp": "2026-03-25T08:43:15.528748+00:00", "date": "2026-03-25", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.18016764322916676, "deb_prediction": 28.1, "ensemble": {"p10": 30.5, "median": 31.4, "p90": 31.8}, "multi_model": {"Open-Meteo": 26.6, "ECMWF": 28.8, "GFS": 30.3, "ICON": 26.6, "GEM": 30.7, "JMA": 25.5}, "max_so_far": 29.0, "peak_status": "past", "prob_snapshot": [{"v": 29, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "shenzhen", "timestamp": "2026-03-25T08:57:11.783182+00:00", "date": "2026-03-25", "temp_symbol": "°C", "raw_mu": 26.7, "raw_sigma": 0.18016764322916676, "deb_prediction": 28.1, "ensemble": {"p10": 30.5, "median": 31.4, "p90": 31.8}, "multi_model": {"Open-Meteo": 26.6, "ECMWF": 28.8, "GFS": 30.3, "ICON": 26.6, "GEM": 30.7, "JMA": 25.5}, "max_so_far": 26.7, "peak_status": "past", "prob_snapshot": [{"v": 27, "p": 1.0}], "shadow_prob_snapshot": [{"v": 27, "p": 1.0}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 26.7, "calibrated_sigma": 0.24322631835937514}
+{"city": "shenzhen", "timestamp": "2026-03-25T09:32:32+00:00", "date": "2026-03-25", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.16637912326388898, "deb_prediction": 28.1, "ensemble": {"p10": 30.5, "median": 31.4, "p90": 31.8}, "multi_model": {"Open-Meteo": 26.6, "ECMWF": 28.8, "GFS": 30.3, "ICON": 26.6, "GEM": 30.7, "JMA": 25.5}, "max_so_far": 28.9, "peak_status": "past", "prob_snapshot": [{"v": 29, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "shenzhen", "timestamp": "2026-03-25T10:02:35+00:00", "date": "2026-03-25", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.15911458333333342, "deb_prediction": 28.2, "ensemble": {"p10": 30.5, "median": 31.4, "p90": 31.8}, "multi_model": {"Open-Meteo": 26.5, "ECMWF": 28.8, "GFS": 30.3, "ICON": 26.5, "GEM": 30.7, "JMA": 26.2}, "max_so_far": 28.9, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "shanghai", "timestamp": "2026-03-29T15:00:00.000Z", "date": "2026-03-29", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.23736458333333335, "deb_prediction": 18.4, "ensemble": {"p10": 16.1, "median": 16.5, "p90": 16.9}, "multi_model": {"Open-Meteo": 17.0, "ECMWF": 19.2, "GFS": 19.1, "ICON": 17.0, "GEM": 17.6, "JMA": 15.8}, "max_so_far": 18.0, "observation": {"current_temp": 14.0, "humidity": null, "wind_speed_kt": 4.0, "visibility_mi": 3.11, "local_hour": 23.25}, "peak_status": "past", "prob_snapshot": [{"v": 18, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "ankara", "timestamp": "2026-03-29T15:01:00.000Z", "date": "2026-03-29", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.25176666666666664, "deb_prediction": 9.7, "ensemble": {"p10": 9.2, "median": 9.5, "p90": 10.2}, "multi_model": {"Open-Meteo": 9.2, "ECMWF": 9.5, "GFS": 10.1, "ICON": 9.2, "GEM": 11.0, "JMA": 10.0}, "max_so_far": 10.0, "observation": {"current_temp": 7.0, "humidity": null, "wind_speed_kt": 12.0, "visibility_mi": null, "local_hour": 18.25}, "peak_status": "past", "prob_snapshot": [{"v": 10, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+{"city": "chengdu", "timestamp": "2026-04-08T07:00:00.000Z", "date": "2026-04-08", "temp_symbol": "°C", "raw_mu": 24.3, "raw_sigma": 1.1821289062499998, "deb_prediction": 23.1, "ensemble": {"p10": 21.8, "median": 23.0, "p90": 24.5}, "multi_model": {"Open-Meteo": 22.5, "ECMWF": 23.9, "GFS": 23.0, "ICON": 22.5, "GEM": 23.7, "JMA": 23.2}, "max_so_far": 24.0, "observation": {"current_temp": 24.0, "humidity": null, "wind_speed_kt": 4.0, "visibility_mi": null, "local_hour": 15.183333333333334}, "peak_status": "before", "prob_snapshot": [{"v": 24, "p": 0.442}, {"v": 25, "p": 0.386}, {"v": 26, "p": 0.172}], "shadow_prob_snapshot": [{"v": 24, "p": 0.394}, {"v": 25, "p": 0.355}, {"v": 26, "p": 0.19}, {"v": 27, "p": 0.06}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 24.3, "calibrated_sigma": 1.354078466151897}
+{"city": "chengdu", "timestamp": "2026-04-08T08:00:00.000Z", "date": "2026-04-08", "temp_symbol": "°C", "raw_mu": 24.3, "raw_sigma": 0.7283767361111106, "deb_prediction": 23.1, "ensemble": {"p10": 21.8, "median": 22.9, "p90": 24.2}, "multi_model": {"Open-Meteo": 22.5, "ECMWF": 23.9, "GFS": 22.5, "ICON": 22.5, "GEM": 23.7, "JMA": 23.2}, "max_so_far": 24.0, "observation": {"current_temp": 23.0, "humidity": null, "wind_speed_kt": 4.0, "visibility_mi": null, "local_hour": 16.133333333333333}, "peak_status": "in_window", "prob_snapshot": [{"v": 24, "p": 0.547}, {"v": 25, "p": 0.397}, {"v": 26, "p": 0.056}], "shadow_prob_snapshot": [{"v": 24, "p": 0.521}, {"v": 25, "p": 0.399}, {"v": 26, "p": 0.08}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 24.3, "calibrated_sigma": 0.8140063140878262}
+{"city": "tokyo", "timestamp": "2026-04-08T08:00:00.000Z", "date": "2026-04-08", "temp_symbol": "°C", "raw_mu": 17.810000000000002, "raw_sigma": 0.23200683593750038, "deb_prediction": 17.1, "ensemble": {"p10": 17.4, "median": 18.3, "p90": 19.1}, "multi_model": {"Open-Meteo": 16.1, "ECMWF": 16.3, "GFS": 17.6, "ICON": 18.2, "GEM": 18.3, "JMA": 16.1}, "max_so_far": 17.0, "observation": {"current_temp": 16.0, "humidity": null, "wind_speed_kt": 17.0, "visibility_mi": null, "local_hour": 17.133333333333333}, "peak_status": "past", "prob_snapshot": [{"v": 18, "p": 0.909}, {"v": 17, "p": 0.091}], "shadow_prob_snapshot": [{"v": 18, "p": 0.892}, {"v": 17, "p": 0.108}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 17.810000000000002, "calibrated_sigma": 0.25}

docker-compose.yml

@@ -1,29 +1,112 @@
+x-polyweather-base: &polyweather-base
+  build: .
+  image: polyweather-app:latest
+  env_file:
+    - .env
+
 services:
   polyweather:
-    build: .
+    <<: *polyweather-base
     container_name: polyweather_bot
     restart: unless-stopped
-    env_file:
-      - .env
     volumes:
       # Persist runtime data outside git workspace.
-      # Host path defaults to /var/lib/polyweather and can be overridden by POLYWEATHER_RUNTIME_DATA_DIR.
+      # Host path defaults to /var/lib/polyweather and can be overridden in .env.
       - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/var/lib/polyweather
       # Keep /app/data compatibility for existing cache/state defaults.
       - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/app/data
       - ./bot.log:/app/bot.log # 挂载日志文件
+    # UID/GID are mainly useful on Linux hosts to avoid root-owned output files.
+    # Windows / macOS can usually keep the fallback values.
     user: "${UID:-1000}:${GID:-1000}"
 
   polyweather_web:
-    build: .
+    <<: *polyweather-base
     container_name: polyweather_web
     restart: unless-stopped
     command: python web/app.py
-    env_file:
-      - .env
     volumes:
+      # Web service shares the same runtime data directory as bot/state tasks.
       - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/var/lib/polyweather
       - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/app/data
     ports:
       - "8000:8000"
+    # UID/GID are mainly useful on Linux hosts to avoid root-owned output files.
     user: "${UID:-1000}:${GID:-1000}"
+
+  polyweather_prewarm:
+    <<: *polyweather-base
+    container_name: polyweather_prewarm
+    restart: unless-stopped
+    profiles: ["workers"]
+    command: python scripts/prewarm_dashboard_worker.py --include-detail --include-market
+    volumes:
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/var/lib/polyweather
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/app/data
+    user: "${UID:-1000}:${GID:-1000}"
+
+  polyweather_prometheus:
+    image: prom/prometheus:v3.4.1
+    container_name: polyweather_prometheus
+    restart: unless-stopped
+    profiles: ["monitoring"]
+    depends_on:
+      - polyweather_web
+    command:
+      - "--config.file=/etc/prometheus/prometheus.yml"
+      - "--storage.tsdb.path=/prometheus"
+      - "--storage.tsdb.retention.time=15d"
+      - "--web.enable-lifecycle"
+    volumes:
+      - ./monitoring/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml:ro
+      - ./monitoring/prometheus/alerts.yml:/etc/prometheus/alerts.yml:ro
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}/monitoring/prometheus:/prometheus
+    ports:
+      - "${POLYWEATHER_PROMETHEUS_PORT:-9090}:9090"
+
+  polyweather_alertmanager:
+    image: prom/alertmanager:v0.28.1
+    container_name: polyweather_alertmanager
+    restart: unless-stopped
+    profiles: ["monitoring"]
+    depends_on:
+      - polyweather_alert_relay
+    command:
+      - "--config.file=/etc/alertmanager/alertmanager.yml"
+      - "--storage.path=/alertmanager"
+    volumes:
+      - ./monitoring/alertmanager/alertmanager.yml:/etc/alertmanager/alertmanager.yml:ro
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}/monitoring/alertmanager:/alertmanager
+    ports:
+      - "${POLYWEATHER_ALERTMANAGER_PORT:-9093}:9093"
+
+  polyweather_alert_relay:
+    <<: *polyweather-base
+    container_name: polyweather_alert_relay
+    restart: unless-stopped
+    profiles: ["monitoring"]
+    command: python scripts/alertmanager_telegram_relay.py
+    volumes:
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/var/lib/polyweather
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}:/app/data
+    ports:
+      - "${POLYWEATHER_ALERT_RELAY_PORT:-9099}:9099"
+    user: "${UID:-1000}:${GID:-1000}"
+
+  polyweather_grafana:
+    image: grafana/grafana-oss:12.0.2
+    container_name: polyweather_grafana
+    restart: unless-stopped
+    profiles: ["monitoring"]
+    depends_on:
+      - polyweather_prometheus
+    environment:
+      GF_SECURITY_ADMIN_USER: ${POLYWEATHER_GRAFANA_ADMIN_USER:-admin}
+      GF_SECURITY_ADMIN_PASSWORD: ${POLYWEATHER_GRAFANA_ADMIN_PASSWORD:-polyweather}
+      GF_USERS_ALLOW_SIGN_UP: "false"
+    volumes:
+      - ./monitoring/grafana/provisioning:/etc/grafana/provisioning:ro
+      - ./monitoring/grafana/dashboards:/var/lib/grafana/dashboards:ro
+      - ${POLYWEATHER_RUNTIME_DATA_DIR:-/var/lib/polyweather}/monitoring/grafana:/var/lib/grafana
+    ports:
+      - "${POLYWEATHER_GRAFANA_PORT:-3001}:3000"

docs/API_ZH.md

@@ -1,8 +1,8 @@
-# PolyWeather API 文档（v1.4.0）
+# PolyWeather API 文档（v1.5.1）
 
-最后更新：`2026-03-14`
+最后更新：`2026-03-24`
 
-本文档描述当前对外可用 API 口径（`web/app.py` + `frontend/app/api/*`）。
+本文档描述当前对外可用 API 口径（`web/app.py` + `web/routes.py` + `frontend/app/api/*`）。
 
 ## 1. 基础信息
 
@@ -15,10 +15,11 @@
 ```mermaid
 flowchart LR
     FE["Browser / Dashboard"] --> BFF["Next.js Route Handlers (/api/*)"]
-    BFF --> API["FastAPI (/web/app.py)"]
+    BFF --> API["FastAPI (/web/app.py + /web/routes.py)"]
     API --> WX["Weather Collector"]
     API --> ANA["DEB + Trend + Probability + Market Scan"]
     API --> PAY["Payment Intent + Event + Confirm Loops"]
+    API --> OBS["healthz / system status / metrics"]
 ```
 
 ## 3. 天气分析接口
@@ -43,9 +44,70 @@ flowchart LR
 
 - `market_scan.available`
 - `market_scan.signal_label`
+- `market_scan.edge_percent`
 - `market_scan.anchor_model / anchor_high / anchor_settlement`
 - `market_scan.yes_buy / no_buy`
 - `market_scan.primary_market.tradable`
+- `peak.first_h / peak.last_h / peak.status`
+- `vertical_profile_signal.heating_setup / suppression_risk / trigger_risk / mixing_strength`
+- `taf.signal.peak_window / suppression_level / disruption_level / markers`
+
+### `detail` 新增结构信号说明
+
+`/api/city/{name}/detail` 现在会返回一组更偏交易场景的结构字段：
+
+#### 1. `peak`
+
+- `first_h`：预计峰值窗口起始小时
+- `last_h`：预计峰值窗口结束小时
+- `status`：`before_peak | near_peak | after_peak`
+
+这组字段用于让日内结构信号围绕真实峰值窗口分析，而不是固定只看下午。
+
+#### 2. `vertical_profile_signal`
+
+重点字段：
+
+- `source`
+- `window`
+- `cape_max`
+- `cin_min`
+- `lifted_index_min`
+- `boundary_layer_height_max`
+- `shear_10m_180m_max`
+- `suppression_risk`
+- `trigger_risk`
+- `mixing_strength`
+- `shear_risk`
+- `heating_setup`
+- `heating_score`
+- `summary_zh`
+- `summary_en`
+
+这组字段对应前端“高空结构信号 / Upper-Air Structure”卡片。
+
+#### 3. `taf.signal`
+
+仅对**非香港机场城市**启用。当前已支持解析：
+
+- `FM`
+- `TEMPO`
+- `BECMG`
+- `PROB30`
+- `PROB40`
+
+重点字段：
+
+- `peak_window`
+- `segments`
+- `markers`
+- `suppression_level`
+- `disruption_level`
+- `wind_shift`
+- `summary_zh`
+- `summary_en`
+
+`markers` 会被前端温度走势图拿来做 `TAF 时段 / TAF Timing` 标记。
 
 ## 4. 鉴权与账户接口
 
@@ -60,11 +122,12 @@ flowchart LR
 - `points`, `weekly_points`, `weekly_rank`
 - `subscription_active`, `subscription_plan_code`, `subscription_expires_at`
 
-## 5. 支付接口（P1）
+## 5. 支付接口
 
 | 接口 | 方法 | 用途 |
 | :-- | :-- | :-- |
 | `/api/payments/config` | GET | 支付配置、代币列表、套餐、积分抵扣规则 |
+| `/api/payments/runtime` | GET | 支付运行态、RPC 状态、event loop 状态、最近审计事件 |
 | `/api/payments/wallets` | GET | 当前用户已绑定钱包 |
 | `/api/payments/wallets/challenge` | POST | 获取绑定签名 challenge |
 | `/api/payments/wallets/verify` | POST | 提交签名并绑定钱包 |
@@ -72,6 +135,7 @@ flowchart LR
 | `/api/payments/intents/{intent_id}` | GET | 查询 intent 最新状态 |
 | `/api/payments/intents/{intent_id}/submit` | POST | 提交交易哈希 |
 | `/api/payments/intents/{intent_id}/confirm` | POST | 手动触发确认 |
+| `/api/payments/reconcile-latest` | POST | 对当前登录用户最近一笔 intent 做恢复性确认 |
 
 ### 支付状态建议
 
@@ -83,13 +147,57 @@ flowchart LR
 4. `POST /confirm`
 5. 若 pending，轮询 `GET /intents/{id}` 直到 `confirmed`
 
-## 6. 缓存策略（当前）
+## 6. 运维与观测接口
+
+| 接口 | 方法 | 用途 |
+| :-- | :-- | :-- |
+| `/healthz` | GET | 基础健康检查 |
+| `/api/system/status` | GET | 系统状态、功能开关、rollout 状态、轻量指标摘要 |
+| `/metrics` | GET | Prometheus 风格指标导出 |
+
+`/api/system/status` 当前会包含：
+
+- `features.state_storage_mode`
+- `probability.decision`
+- `probability.ready_for_primary`
+- `metrics`
+
+`/metrics` 当前会导出：
+
+- `polyweather_http_requests_total`
+- `polyweather_http_request_duration_ms_*`
+- `polyweather_source_requests_total`
+- `polyweather_source_request_duration_ms_*`
+
+## 7. Ops 管理接口
+
+这些接口主要给 `/ops` 管理后台使用，默认要求：
+
+- 已登录
+- 当前邮箱位于 `POLYWEATHER_OPS_ADMIN_EMAILS`
+
+| 接口 | 方法 | 用途 |
+| :-- | :-- | :-- |
+| `/api/ops/users` | GET | 按 Telegram ID / 用户名 / 邮箱查询用户 |
+| `/api/ops/leaderboard/weekly` | GET | 本周积分榜 |
+| `/api/ops/memberships` | GET | 当前有效会员（已按用户去重，保留最晚到期） |
+| `/api/ops/users/grant-points` | POST | 手动补分 |
+| `/api/ops/payments/incidents` | GET | 支付异常单（仅 `payment_intent_failed`） |
+| `/api/ops/payments/incidents/{event_id}/resolve` | POST | 标记支付异常单已处理 |
+
+`/api/ops/payments/incidents` 当前支持：
+
+- `reason=<receiver_mismatch|sender_mismatch|event_mismatch|tx_reverted>`
+- 默认不返回已标记处理的记录
+- 重点用于排查“已付款未开通”“打到旧收款地址”等事故
+## 8. 缓存策略（当前）
 
 - `cities` / `summary` / `history`：BFF 支持 `ETag + 304`
 - `summary?force_refresh=true`：`Cache-Control: no-store`
 - 详情接口与支付接口：`no-store`
+- `METAR` / `TAF` / settlement current 由后端各自维护短 TTL 缓存
 
-## 7. 调试示例
+## 9. 调试示例
 
 ### 查询未来日期 market_scan
 
@@ -103,14 +211,32 @@ curl -s "http://127.0.0.1:8000/api/city/ankara/detail?force_refresh=true&target_
 curl -s http://127.0.0.1:8000/api/payments/config | python3 -m json.tool
 ```
 
+### 查看支付运行态
+
+```bash
+curl -s http://127.0.0.1:8000/api/payments/runtime | python3 -m json.tool
+```
+
+### 查看支付异常单
+
+```bash
+curl -s "http://127.0.0.1:8000/api/ops/payments/incidents?reason=receiver_mismatch" | python3 -m json.tool
+```
+
+### 查看系统状态
+
+```bash
+curl -s http://127.0.0.1:8000/api/system/status | python3 -m json.tool
+```
+
 ### 观察支付自动补单
 
 ```bash
 docker compose logs -f polyweather | egrep "payment event loop started|payment confirm loop started|payment auto-confirmed"
 ```
 
-## 8. 开源口径说明
+## 10. AGPL 与公开口径说明
 
-对外公开文档仅覆盖通用 API 契约。生产商业策略参数不在公开文档披露。
+本仓库代码自 `2026-03-30` 起采用 `AGPL-3.0-only`。对外公开文档仅覆盖通用 API 契约；生产商业策略参数、私有运营阈值与托管服务能力不在公开文档披露。
 
-详见：[Open-Core 与商用边界](OPEN_CORE_POLICY.md)
+详见：[AGPL-3.0 与商用边界](OPEN_CORE_POLICY.md)

docs/COMMERCIALIZATION.md

@@ -41,14 +41,14 @@ PolyWeather 是面向温度结算场景的气象决策层，不是通用天气
 
 > 说明：具体运营策略可按阶段调整，生产参数建议放私有仓库。
 
-## 5. 建议的开源边界
+## 5. 许可证与商用边界
 
-请按 Open-Core 执行：
+当前仓库代码采用 `AGPL-3.0-only`：
 
-- 开源：基础能力与通用支付流程。
-- 私有：商业风控、营销策略、关键运营参数、内部审计策略。
+- 公开：基础能力与通用支付流程源码。
+- 不随代码许可证授权：商业风控、营销策略、关键运营参数、内部审计策略、品牌与托管服务资产。
 
-详见：[Open-Core 与商用边界](OPEN_CORE_POLICY.md)
+详见：[AGPL-3.0 与商用边界](OPEN_CORE_POLICY.md)
 
 ## 6. 上线检查清单（收费前）
 

docs/CONFIGURATION_ZH.md

@@ -0,0 +1,337 @@
+# 配置与密钥管理（中文）
+
+## 1. 目标
+
+PolyWeather 的环境变量很多，但不是所有变量都属于同一层级。
+
+当前推荐做法是把配置拆成三类：
+
+1. 可复现基础配置  
+   放在：[.env.example](/E:/web/PolyWeather/.env.example)
+
+2. 敏感密钥模板  
+   放在：[.env.secrets.example](/E:/web/PolyWeather/.env.secrets.example)
+
+3. 平台侧真实密钥  
+   放在：
+   - VPS / Docker `.env`
+   - Vercel Environment Variables
+   - GitHub Secrets（如需要）
+
+## 2. 为什么要拆
+
+如果把所有变量都平铺在一个 `.env` 里，会有三个问题：
+
+1. 新环境很难知道“最小启动到底需要哪些变量”
+2. 敏感密钥和普通开关混在一起，容易误泄露
+3. 调优参数太多时，团队很难区分“必须填”和“保持默认即可”
+
+所以正确做法不是“减少变量数量”，而是：
+
+- 保留变量能力
+- 按职责分层
+- 给出最小启动路径
+
+## 3. 文件职责
+
+### 3.1 根 `.env.example`
+
+文件：
+
+- [.env.example](/E:/web/PolyWeather/.env.example)
+
+用途：
+
+- 后端 / Bot / Docker 的可复现配置模板
+- 只放变量名、默认值、开关与非敏感示例
+
+### 3.2 根 `.env.secrets.example`
+
+文件：
+
+- [.env.secrets.example](/E:/web/PolyWeather/.env.secrets.example)
+
+用途：
+
+- 只列敏感项
+- 帮助运维明确哪些值必须从密钥系统注入
+
+### 3.3 前端 `.env.example`
+
+文件：
+
+- [frontend/.env.example](/E:/web/PolyWeather/frontend/.env.example)
+
+用途：
+
+- 前端本地开发与 Vercel 环境变量模板
+
+## 4. 配置分级
+
+### 4.1 L1：最小启动必需项
+
+这是“服务能跑起来”的最小集合。
+
+后端 / Bot：
+
+- `TELEGRAM_BOT_TOKEN`
+- `TELEGRAM_CHAT_ID`
+- `POLYWEATHER_RUNTIME_DATA_DIR`
+- `POLYWEATHER_DB_PATH`
+- `POLYWEATHER_STATE_STORAGE_MODE`
+
+前端：
+
+- `POLYWEATHER_API_BASE_URL`
+- `POLYWEATHER_OPS_ADMIN_EMAILS`（如果启用 `/ops` 页面级管理员守卫）
+
+如果启用登录：
+
+- `NEXT_PUBLIC_SUPABASE_URL`
+- `NEXT_PUBLIC_SUPABASE_ANON_KEY`
+- `SUPABASE_URL`
+- `SUPABASE_ANON_KEY`
+- `SUPABASE_SERVICE_ROLE_KEY`
+
+### 4.2 L2：功能开关
+
+这些变量一般不敏感，但会决定功能是否启用。
+
+例如：
+
+- `POLYWEATHER_AUTH_ENABLED`
+- `POLYWEATHER_AUTH_REQUIRED`
+- `POLYWEATHER_AUTH_REQUIRE_SUBSCRIPTION`
+- `POLYWEATHER_OPS_ADMIN_EMAILS`
+- `POLYWEATHER_STATE_STORAGE_MODE`
+- `POLYWEATHER_PAYMENT_ENABLED`
+- `POLYMARKET_MARKET_SCAN_ENABLED`
+- `POLYGON_WALLET_WATCH_ENABLED`
+- `TELEGRAM_ALERT_PUSH_ENABLED`
+- `TELEGRAM_MARKET_FOCUS_DIGEST_ENABLED`
+- `POLYMARKET_WALLET_ACTIVITY_ENABLED`（已退役，建议保持 `false`）
+
+### 4.3 L3：运行调优项
+
+这些一般不需要在第一天就改。
+
+例如：
+
+- 各类 `*_TTL_SEC`
+- 各类 `*_TIMEOUT_SEC`
+- 各类 `*_COOLDOWN_SEC`
+- 各类 `*_INTERVAL_SEC`
+- `TELEGRAM_ALERT_MIN_TRIGGER_COUNT`
+- `TELEGRAM_ALERT_MIN_SEVERITY`
+- `TELEGRAM_ALERT_MISPRICING_ONLY`
+- `TELEGRAM_ALERT_MISPRICING_INTERVAL_SEC`
+- `TELEGRAM_MARKET_FOCUS_DIGEST_INTERVAL_SEC`
+- `TELEGRAM_MARKET_FOCUS_DIGEST_TOP_N`
+- `POLYWEATHER_PAYMENT_RPC_URLS`
+- `TAF_CACHE_TTL_SEC`
+
+策略：
+
+- 先用默认值
+- 出现性能或运维问题时再调
+
+### 4.4 L4：敏感项
+
+这些变量不应写进公开文档截图，也不应提交到仓库。
+
+例如：
+
+- `TELEGRAM_BOT_TOKEN`
+- `SUPABASE_SERVICE_ROLE_KEY`
+- `POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN`
+- `POLYWEATHER_DASHBOARD_ACCESS_TOKEN`
+- `METEOBLUE_API_KEY`
+- `NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID`
+- `POLYMARKET_SECRET_KEY`
+
+## 5. 推荐部署矩阵
+
+### 5.1 VPS / Docker（后端 + Bot）
+
+建议放这些：
+
+- 根 `.env` 的后端项
+- 所有 secrets
+- Bot / 支付 / watcher 配置
+
+### 5.2 Vercel（前端）
+
+建议只放前端真正需要的变量：
+
+- `POLYWEATHER_API_BASE_URL`
+- `NEXT_PUBLIC_SUPABASE_URL`
+- `NEXT_PUBLIC_SUPABASE_ANON_KEY`
+- `POLYWEATHER_AUTH_ENABLED`
+- `POLYWEATHER_AUTH_REQUIRED`
+- `POLYWEATHER_OPS_ADMIN_EMAILS`
+- `POLYWEATHER_DASHBOARD_ACCESS_TOKEN`
+- `POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN`
+- `NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID`
+- `NEXT_PUBLIC_WALLETCONNECT_POLYGON_RPC_URL`
+
+说明：
+
+- `/ops` 现在是前后端双层限制：
+  - 前端页面入口读取 `POLYWEATHER_OPS_ADMIN_EMAILS`
+  - 后端写接口同样读取 `POLYWEATHER_OPS_ADMIN_EMAILS`
+- 因此，Vercel 和 VPS / Docker 两侧都应配置相同的管理员邮箱白名单。
+
+不要把后端专用密钥全搬进 Vercel。
+
+### 5.3 GitHub Actions
+
+当前 CI 不需要大规模 secrets。
+
+如果未来要做自动部署，再考虑：
+
+- `VERCEL_TOKEN`
+- `VERCEL_ORG_ID`
+- `VERCEL_PROJECT_ID`
+
+## 6. 最小部署示例
+
+### 6.1 前端最小变量
+
+```env
+POLYWEATHER_API_BASE_URL=https://your-backend.example.com
+NEXT_PUBLIC_SUPABASE_URL=https://your-project.supabase.co
+NEXT_PUBLIC_SUPABASE_ANON_KEY=your_anon_key
+POLYWEATHER_AUTH_ENABLED=true
+POLYWEATHER_AUTH_REQUIRED=true
+```
+
+### 6.2 后端最小变量
+
+```env
+TELEGRAM_BOT_TOKEN=...
+TELEGRAM_CHAT_ID=...
+POLYWEATHER_RUNTIME_DATA_DIR=/var/lib/polyweather
+POLYWEATHER_DB_PATH=/var/lib/polyweather/polyweather.db
+POLYWEATHER_STATE_STORAGE_MODE=sqlite
+UID=1000
+GID=1000
+POLYWEATHER_AUTH_ENABLED=true
+POLYWEATHER_AUTH_REQUIRED=false
+POLYWEATHER_OPS_ADMIN_EMAILS=yhrsc30@gmail.com
+TAF_CACHE_TTL_SEC=900
+SUPABASE_URL=https://your-project.supabase.co
+SUPABASE_ANON_KEY=...
+SUPABASE_SERVICE_ROLE_KEY=...
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=...
+TELEGRAM_ALERT_PUSH_ENABLED=true
+TELEGRAM_ALERT_PUSH_INTERVAL_SEC=300
+TELEGRAM_ALERT_PUSH_COOLDOWN_SEC=1800
+TELEGRAM_ALERT_MIN_TRIGGER_COUNT=2
+TELEGRAM_ALERT_MIN_SEVERITY=medium
+TELEGRAM_ALERT_MISPRICING_ONLY=true
+TELEGRAM_ALERT_MISPRICING_INTERVAL_SEC=7200
+TELEGRAM_MARKET_FOCUS_DIGEST_ENABLED=true
+TELEGRAM_MARKET_FOCUS_DIGEST_INTERVAL_SEC=1800
+TELEGRAM_MARKET_FOCUS_DIGEST_TOP_N=5
+POLYMARKET_WALLET_ACTIVITY_ENABLED=false
+```
+
+说明：
+
+- `UID` / `GID` 主要给 Linux Docker 主机用，避免容器把运行文件写成 root 所有。
+- Windows / macOS 一般可以直接保留默认值。
+- `POLYWEATHER_RUNTIME_DATA_DIR` 建议放在仓库外，例如 `/var/lib/polyweather`。
+- `docker-compose.yml` 会把这个目录同时挂载到容器内的 `/var/lib/polyweather` 和 `/app/data`，兼容现有缓存与 SQLite 路径。
+- `POLYWEATHER_STATE_STORAGE_MODE` 当前线上推荐直接使用 `sqlite`。
+- `POLYWEATHER_PAYMENT_RPC_URLS` 支持逗号分隔多个 RPC；如果暂时只用单 RPC，也可以继续只配 `POLYWEATHER_PAYMENT_RPC_URL`。
+- 机器人市场监控当前以 `关注清单` 为主，按固定间隔主动推送。
+- `TELEGRAM_MARKET_FOCUS_DIGEST_INTERVAL_SEC` 表示主动推送间隔，默认 `1800` 秒（30 分钟）。
+- `POLYMARKET_WALLET_ACTIVITY_ENABLED` 已退役，保留为 `false` 即可，不建议再启用钱包异动监听。
+
+### 6.3 机器人市场监控建议配置
+
+这套配置用于替代旧的钱包异动监听，围绕市场本身做两类推送：
+
+- `关键提醒`：实时错价/触发条件满足时发送
+- `关注清单`：按亚洲时区定时推送当日重点市场摘要
+
+推荐值：
+
+```env
+TELEGRAM_ALERT_PUSH_ENABLED=true
+TELEGRAM_ALERT_PUSH_INTERVAL_SEC=300
+TELEGRAM_ALERT_PUSH_COOLDOWN_SEC=1800
+TELEGRAM_ALERT_MIN_TRIGGER_COUNT=2
+TELEGRAM_ALERT_MIN_SEVERITY=medium
+TELEGRAM_ALERT_MISPRICING_ONLY=true
+TELEGRAM_ALERT_MISPRICING_INTERVAL_SEC=7200
+TELEGRAM_MARKET_FOCUS_DIGEST_ENABLED=true
+TELEGRAM_MARKET_FOCUS_DIGEST_INTERVAL_SEC=1800
+TELEGRAM_MARKET_FOCUS_DIGEST_TOP_N=5
+POLYMARKET_WALLET_ACTIVITY_ENABLED=false
+```
+
+说明：
+
+- `TELEGRAM_ALERT_MISPRICING_ONLY=true` 表示关键提醒优先围绕错价/市场触发，不把机器人做成泛通知器。
+- `TELEGRAM_MARKET_FOCUS_DIGEST_INTERVAL_SEC=1800` 表示频道每 30 分钟主动推送一轮机会清单。
+- `TELEGRAM_MARKET_FOCUS_DIGEST_TOP_N=5` 建议先保持较小，避免机器人一次推太多城市。
+- `POLYMARKET_WALLET_ACTIVITY_ENABLED=false` 表示停用旧的钱包异动监听，统一收敛到市场监控。
+
+## 7. 当前建议的运维规则
+
+### 7.1 仓库中允许存在
+
+- `.env.example`
+- `.env.secrets.example`
+- `frontend/.env.example`
+
+### 7.2 仓库中不应提交
+
+- `.env`
+- `.env.local`
+- 任何带真实 token / key 的配置文件
+
+### 7.3 截图与共享规则
+
+以下值一旦出现在截图或聊天里，建议视为泄露并轮换：
+
+- `SUPABASE_SERVICE_ROLE_KEY`
+- `POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN`
+- `TELEGRAM_BOT_TOKEN`
+- 第三方私有 API Key
+
+## 8. 如何收口配置复杂度
+
+如果你觉得变量仍然太多，正确的做法不是一刀删掉，而是：
+
+1. 把“功能开关”和“调优参数”分开看
+2. 保持 `.env.example` 中：
+   - 最小启动项
+   - 常用功能开关
+   - 默认调优值
+3. 让不常改的高阶参数继续留默认
+
+也就是说：
+
+- 使用者只需要先关心 10-20 个关键变量
+- 其余变量保持默认即可
+
+## 9. 当前已经完成的配置治理
+
+1. 根 `.env.example` 收口
+2. `.env.secrets.example` 新增
+3. 前端 `.env.example` 收口
+4. 运行时配置校验脚本新增
+5. `/ops` 管理员白名单与前后端职责边界已明确
+5. 支付运行态与多 RPC 配置支持
+6. 运行态 SQLite 迁移配置支持
+
+## 10. 配置校验命令
+
+在不启动服务的情况下，你可以直接检查配置：
+
+```bash
+python scripts/validate_runtime_env.py --component web
+python scripts/validate_runtime_env.py --component bot
+```

docs/EMOS_LGBM_SYSTEM_ZH.md

@@ -0,0 +1,653 @@
+# EMOS + LGBM 系统说明（中文）
+
+本文档用于完整说明 PolyWeather 当前的两条统计/机器学习链路：
+
+- `EMOS`：概率后处理与校准链路
+- `LGBM`：日最高温点预测辅助模型
+
+重点不只是“模型怎么训练”，还包括：
+
+- 这些模型依赖什么历史数据
+- 真值和训练特征现在如何长期保存
+- 为什么过去样本一直不够
+- 当前线上到底运行在哪个模式
+- 现在能做什么，不能做什么
+
+本文档基于仓库当前实现与最近一轮重建结果，适合作为：
+
+- 项目内部模型说明
+- 运维与数据治理说明
+- 未来继续扩展 EMOS/LGBM 的基线文档
+
+---
+
+## 1. 总览
+
+PolyWeather 当前不是“用一个模型替代所有东西”，而是多层结构：
+
+1. 多源天气采集层
+2. `DEB` 业务主预测层
+3. `LGBM` 轻量点预测辅助层
+4. `EMOS` 概率校准层
+5. 市场概率/桶命中评估层
+
+可以简化理解为：
+
+```text
+天气源 / 观测 / 历史真值
+        ↓
+   DEB 主预测
+        ↓
+   LGBM 辅助点预测
+        ↓
+EMOS 对概率分布做后处理
+        ↓
+市场概率 / shadow / rollout 门禁
+```
+
+其中：
+
+- `DEB` 仍然是当前业务主路径
+- `LGBM` 是辅助预测源，不是主路径
+- `EMOS` 是概率后处理，不是基础天气模型
+
+---
+
+## 2. 两条链路各自负责什么
+
+### 2.1 EMOS 负责什么
+
+`EMOS` 的全称通常指 Ensemble Model Output Statistics。
+
+在本项目里，它的角色不是重新预测温度，而是：
+
+- 把已有的预测结果做概率后处理
+- 让输出分布更“可校准”
+- 让桶概率和市场评估更稳定
+
+EMOS 关注的是：
+
+- `raw_mu`
+- `raw_sigma`
+- `deb_prediction`
+- `ens_median`
+- `ensemble_spread`
+- `max_so_far_gap`
+- `peak_flag`
+- 最终真实 `actual_high`
+
+它最终输出的是一套“经过校准的概率分布”，而不是单一温度值。
+
+所以 EMOS 的核心衡量指标不是单纯 MAE，而更看重：
+
+- `CRPS`
+- `bucket_hit_rate`
+- `bucket_brier`
+
+### 2.2 LGBM 负责什么
+
+`LGBM` 是一个轻量级的回归模型，用来预测：
+
+- `actual_high`（日最高温）
+
+它吃的是：
+
+- 历史真值 lag 特征
+- 多模型 forecast
+- `deb_prediction`
+- 当前观测特征
+- 时间特征
+
+它输出的是：
+
+- 一个点预测 `actual_high`
+
+然后这个点预测可以作为：
+
+- 额外 forecast 源
+- 供 DEB / 运营 / 研究参考
+
+所以它和 EMOS 的区别非常重要：
+
+- `LGBM`：做点预测
+- `EMOS`：做概率校准
+
+---
+
+## 3. 当前代码结构
+
+### 3.1 EMOS 相关
+
+核心文件：
+
+- [probability_calibration.py](/E:/web/PolyWeather/src/analysis/probability_calibration.py)
+- [probability_rollout.py](/E:/web/PolyWeather/src/analysis/probability_rollout.py)
+- [fit_probability_calibration.py](/E:/web/PolyWeather/scripts/fit_probability_calibration.py)
+- [evaluate_probability_calibration.py](/E:/web/PolyWeather/scripts/evaluate_probability_calibration.py)
+- [build_probability_shadow_report.py](/E:/web/PolyWeather/scripts/build_probability_shadow_report.py)
+- [judge_probability_rollout.py](/E:/web/PolyWeather/scripts/judge_probability_rollout.py)
+
+核心产物：
+
+- [default.json](/E:/web/PolyWeather/artifacts/probability_calibration/default.json)
+- [evaluation_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/evaluation_report.json)
+- [shadow_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/shadow_report.json)
+- [rollout_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/rollout_report.json)
+- [training_samples.json](/E:/web/PolyWeather/artifacts/probability_calibration/training_samples.json)
+
+### 3.2 LGBM 相关
+
+核心文件：
+
+- [lgbm_daily_high.py](/E:/web/PolyWeather/src/models/lgbm_daily_high.py)
+- [lgbm_features.py](/E:/web/PolyWeather/src/models/lgbm_features.py)
+- [train_lgbm_daily_high.py](/E:/web/PolyWeather/scripts/train_lgbm_daily_high.py)
+- [report_lgbm_daily_high.py](/E:/web/PolyWeather/scripts/report_lgbm_daily_high.py)
+
+核心产物：
+
+- [lgbm_daily_high.txt](/E:/web/PolyWeather/artifacts/models/lgbm_daily_high.txt)
+- [lgbm_daily_high_schema.json](/E:/web/PolyWeather/artifacts/models/lgbm_daily_high_schema.json)
+
+---
+
+## 4. 为什么之前样本总是上不去
+
+这件事是理解当前状态的关键。
+
+过去项目里有一个结构性问题：
+
+- `daily_records_store` 同时承担了
+  - 运行态缓存
+  - 历史训练数据来源
+
+但运行态层会把 `daily_records` 硬裁成最近 14 天。
+
+这意味着：
+
+- 对线上运行来说没问题
+- 对训练来说，历史监督样本会不断被删掉
+
+结果就是：
+
+- 城市越来越多
+- 训练历史反而越来越稀
+- `LGBM` 很容易只有二十几条样本
+- `EMOS` 也只能靠有限 snapshot/daily_record 拼起来
+
+这不是“模型太差”，而是“数据主存设计不对”。
+
+---
+
+## 5. 这次历史真值治理做了什么
+
+现在已经把“运行态缓存”和“长期训练主存”拆开了。
+
+### 5.1 `daily_records_store`
+
+继续保留，但只作为：
+
+- 最近 14 天运行态缓存
+
+它不再承担长期训练历史职责。
+
+### 5.2 `truth_records_store`
+
+新增永久真值表，作为长期训练真值主存。
+
+当前核心字段包括：
+
+- `city`
+- `target_date`
+- `actual_high`
+- `settlement_source`
+- `settlement_station_code`
+- `settlement_station_label`
+- `truth_version`
+- `updated_by`
+- `updated_at`
+- `source_payload_json`
+- `is_final`
+
+这张表的意义是：
+
+- 长期保存监督真值
+- 不再被 14 天缓存裁剪
+- 真值来源变得可追溯
+
+### 5.3 `truth_revisions_store`
+
+新增真值修订审计表。
+
+它记录：
+
+- 老值是什么
+- 新值是什么
+- 来源怎么变了
+- 谁改的
+- 为什么改
+- 什么时候改
+
+所以现在回填不会再是“静默覆盖”。
+
+### 5.4 `training_feature_records_store`
+
+新增长期训练特征表。
+
+它长期留存：
+
+- forecasts
+- deb_prediction
+- mu
+- probability_features
+- prob_snapshot
+- shadow_prob_snapshot
+- calibration 摘要
+
+它的作用是：
+
+- 从现在开始，不再继续丢失历史训练特征
+- 让未来 EMOS/LGBM 样本自然累积
+
+---
+
+## 6. 训练数据现在怎么来
+
+### 6.1 EMOS 训练样本
+
+EMOS 训练不只是需要真值，还要有“当时那一刻的预测快照”。
+
+所以一条 EMOS 样本，本质上需要两部分：
+
+1. 历史预测特征
+2. 对应日期最终真值
+
+当前导出的 EMOS 样本里，核心字段包括：
+
+- `city`
+- `date`
+- `actual_high`
+- `raw_mu`
+- `raw_sigma`
+- `deb_prediction`
+- `ens_median`
+- `ensemble_spread`
+- `max_so_far_gap`
+- `peak_flag`
+- `sample_source`
+- `settlement_source`
+- `settlement_station_code`
+- `truth_version`
+- `truth_updated_by`
+- `truth_updated_at`
+
+也就是说，EMOS 训练样本现在已经带了真值 provenance。
+
+### 6.2 LGBM 训练样本
+
+LGBM 训练样本会优先从：
+
+1. 永久真值表取监督目标
+2. 长期训练特征表取历史特征
+3. 再回退到必要的运行态/快照补充
+
+当前 LGBM 样本会用到：
+
+- 历史 `actual_high` lag
+- 历史均值/趋势
+- 多模型 forecast
+- `deb_prediction`
+- 当前观测
+- 时间特征
+
+---
+
+## 7. Wunderground 历史回填为什么重要
+
+这次治理里一个重点是：
+
+- `Taipei`
+- `Shenzhen`
+
+这两个城市已经切到了市场指定的 `Wunderground` 结算口径。
+
+之前的问题是：
+
+- 城市注册表已经写成 `wunderground`
+- 但历史回填链路还没有真正支持按指定历史日期抓 WU 历史页
+
+所以过去它们的 `actual_high` 可能：
+
+- 没有被正确回填
+- 或者被错误来源污染
+
+现在已经补了正式历史回填函数：
+
+- [wunderground_sources.py](/E:/web/PolyWeather/src/data_collection/wunderground_sources.py)
+
+它会：
+
+1. 按 `city + target_date` 拼出对应历史页
+2. 解析该日观测序列
+3. 取当日最高温
+4. 按市场规则做整度结算
+5. 写入永久真值表
+6. 记录来源与审计信息
+
+这一步对 `Taipei/Shenzhen` 尤其关键，因为它们不是 NOAA/HKO 口径。
+
+---
+
+## 8. 当前线上/离线运行模式
+
+### 8.1 概率引擎模式
+
+当前项目仍然应该保持：
+
+- `emos_shadow`
+
+而不是：
+
+- `emos_primary`
+
+原因不是工程没接好，而是门禁还没过。
+
+### 8.2 LGBM 角色
+
+当前 `LGBM` 仍然只能算：
+
+- 辅助预测源
+- 研究/观测链路
+
+不适合替代 `DEB` 主路径。
+
+---
+
+## 9. 当前最新状态
+
+以下状态来自最近一轮恢复、回填和重训产物。
+
+### 9.1 永久真值
+
+当前永久真值表已恢复到长期历史：
+
+- `truth_records_store`
+  - 最早：`2023-01-01`
+  - 最晚：`2026-04-02`
+  - 行数：约 `35138`
+  - 城市数：`30`
+
+运行态缓存仍然只有近 14 天：
+
+- `daily_records_store`
+  - 仍然是近两周范围
+
+这说明：
+
+- 长期真值主存已经从运行态缓存里分离出来了
+
+### 9.2 真值修订
+
+当前已有 revision 审计记录：
+
+- `truth_revisions_store`
+  - 行数：`2`
+
+这说明审计链路已经在工作。
+
+### 9.3 Wunderground 回填
+
+`Taipei` 与 `Shenzhen` 已按 WU 历史页完成回填。
+
+当前这两城已经补到：
+
+- `2026-04-02`
+
+### 9.4 长期训练特征
+
+当前 `training_feature_records_store` 已经接通，但历史上真正留存下来的特征仍然很少。
+
+这意味着：
+
+- 从现在开始不会继续丢
+- 但过去没留下的那部分特征，不会凭空恢复
+
+这也是为什么：
+
+- 真值恢复了
+- `EMOS` 样本量却没有同步大幅增长
+
+---
+
+## 10. 当前 EMOS 结果怎么理解
+
+最近一轮离线评估大致是：
+
+- `sample_count = 54`
+- `delta_crps ≈ -0.0867`
+- `delta_mae = 0`
+- `delta_bucket_hit_rate = 0`
+
+这说明：
+
+- 从 `CRPS` 看，EMOS 有改善
+- 但从 `MAE` 和 `top bucket hit` 看，没有明显进步
+
+shadow 报告里更关键的问题是：
+
+- `shadow sample_count = 48`
+- `delta_bucket_brier` 仍然明显偏坏
+
+所以 rollout 结论仍然是：
+
+- `hold`
+
+这不是“EMOS 无效”，而是：
+
+- 它还没有稳定到能切主路径
+
+### 10.1 当前阻塞点
+
+主要阻塞仍然是：
+
+- 样本数不够
+- shadow bucket brier 退化
+
+也就是说，当前 EMOS 状态可以总结成：
+
+- 工程链路完整
+- 数据治理大幅改善
+- 发布门禁仍未通过
+
+---
+
+## 11. 当前 LGBM 结果怎么理解
+
+最近一轮 LGBM 训练后，样本数已经从以前更少的状态提升到：
+
+- `sample_count = 54`
+- `train_count = 42`
+- `validation_count = 12`
+
+验证集指标大致为：
+
+- `lgbm_mae = 1.349`
+- `deb_mae = 0.875`
+
+这说明：
+
+- LGBM 比以前样本更充足了
+- 但在验证集上仍然不如 DEB
+
+所以当前它的定位仍然应该是：
+
+- 辅助参考
+- 不替代 DEB
+
+---
+
+## 12. 为什么现在 EMOS 没有像 LGBM 那样明显涨样本
+
+这点很容易误解。
+
+答案不是“恢复失败”，而是两条链路对数据要求不一样。
+
+### 12.1 LGBM
+
+LGBM 更依赖：
+
+- 长期真值
+- 基础 forecast 特征
+
+这部分通过：
+
+- `truth_records_store`
+- `training_feature_records_store`
+
+已经改善很多。
+
+### 12.2 EMOS
+
+EMOS 更依赖：
+
+- 某一时刻的概率快照/分布特征
+
+如果过去那些 snapshot 没有长期保存下来，那么即使今天把真值补齐了：
+
+- 也无法凭空重建完整 EMOS 样本
+
+所以当前现实是：
+
+- 真值问题已经大幅改善
+- 未来特征不会再继续丢
+- 但过去缺失的 EMOS 快照历史仍然限制样本增长
+
+---
+
+## 13. 当前最重要的工程判断
+
+### 13.1 已经完成的
+
+这些现在可以认为已经完成：
+
+- 真值主存从运行态缓存里拆出
+- 真值 provenance 落库
+- revision 审计表落地
+- Wunderground 历史回填接通
+- `Taipei/Shenzhen` 真值口径修正
+- 长期训练特征表接通
+- `/ops` 已能可视化 truth / feature / EMOS / LGBM 覆盖情况
+
+### 13.2 还没完成的
+
+这些仍然是后续重点：
+
+- EMOS 样本继续自然积累
+- shadow bucket brier 稳定下来
+- LGBM 验证效果超过 DEB
+- 让更多城市开始持续积累训练特征
+
+---
+
+## 14. 运维怎么看当前状态
+
+现在最直接的入口是：
+
+- `/ops`
+
+这页已经能看到：
+
+- 历史真值主表统计
+- 真值来源分布
+- 真值修订数量
+- 长期训练特征统计
+- `Taipei/Shenzhen` 的 WU 回填状态
+- 城市覆盖缺口
+- 模型城市覆盖
+- 城市覆盖矩阵
+
+因此，运维现在可以快速回答：
+
+- 哪些城市真值已经长期化
+- 哪些城市还没有特征积累
+- 哪些城市已经能支撑 EMOS/LGBM
+- 哪些城市目前仍然只能主要依赖 DEB
+
+---
+
+## 15. 推荐工作流
+
+### 15.1 日常
+
+1. 查看 `/ops`
+2. 看 `truth / feature / EMOS / LGBM` 覆盖有没有继续增长
+3. 看 `Taipei/Shenzhen` 的 WU 行数是否继续更新
+4. 看 rollout 仍然是 `hold` 还是有改善
+
+### 15.2 周期性重训
+
+建议周期性执行：
+
+```bash
+./venv/Scripts/python.exe scripts/export_probability_training_dataset.py
+./venv/Scripts/python.exe scripts/fit_probability_calibration.py
+./venv/Scripts/python.exe scripts/evaluate_probability_calibration.py
+./venv/Scripts/python.exe scripts/build_probability_shadow_report.py
+./venv/Scripts/python.exe scripts/judge_probability_rollout.py
+./venv/Scripts/python.exe scripts/train_lgbm_daily_high.py
+```
+
+### 15.3 真值恢复/补数
+
+当有新的历史真值补数或回填需要时：
+
+```bash
+./venv/Scripts/python.exe scripts/restore_training_truth_history.py
+./venv/Scripts/python.exe scripts/restore_training_feature_history.py
+./venv/Scripts/python.exe scripts/backfill_recent_daily_actuals_from_metar.py --cities taipei shenzhen --lookback-days 14
+```
+
+说明：
+
+- 脚本名里虽然还保留 `from_metar`
+- 但当前实现已经会按 `settlement_source` 自动分发
+- `wunderground` 会走 WU 历史回填分支
+
+---
+
+## 16. 当前最务实的结论
+
+如果只用一句话概括当前状态：
+
+**EMOS 和 LGBM 的工程基础已经补齐，但数据积累还在恢复期；当前最正确的策略仍然是继续以 `DEB` 为主路径，让长期真值和训练特征继续沉淀，再观察 EMOS/LGBM 是否自然变强。**
+
+更具体一点：
+
+- `EMOS`
+  - 已接好
+  - 可训练
+  - 可评估
+  - 可 shadow
+  - 但暂时不能切主路径
+
+- `LGBM`
+  - 已接好
+  - 样本比以前更多
+  - 但验证集还不如 DEB
+  - 目前只能做辅助参考
+
+- 数据层
+  - 这次治理的真正价值，是防止未来继续丢历史
+  - 这对两条模型链路都比继续“微调参数”更关键
+
+---
+
+## 17. 相关文档
+
+若需要看更细分的历史说明，可继续参考：
+
+- [EMOS_TRAINING_REPORT_ZH.md](/E:/web/PolyWeather/docs/EMOS_TRAINING_REPORT_ZH.md)
+- [LGBM_DAILY_HIGH_ZH.md](/E:/web/PolyWeather/docs/LGBM_DAILY_HIGH_ZH.md)
+- [PROBABILITY_SNAPSHOT_ARCHIVE_ZH.md](/E:/web/PolyWeather/docs/PROBABILITY_SNAPSHOT_ARCHIVE_ZH.md)
+- [deep-research-report.md](/E:/web/PolyWeather/docs/deep-research-report.md)
+

docs/EMOS_TRAINING_REPORT_ZH.md

@@ -0,0 +1,311 @@
+# EMOS 训练报告（2026-03-20）
+
+## 1. 报告目的
+
+本文档用于记录当前 PolyWeather 概率校准引擎（EMOS）的训练结果、离线评估结果、线上 shadow 观测结果，以及是否具备切换为主路径的条件。
+
+当前结论先写在前面：
+
+- `EMOS` 已完成接入、训练、离线评估、shadow 落盘与滚动报表。
+- 当前默认运行模式应继续保持 `emos_shadow`。
+- 现阶段 **不建议切换到 `emos_primary`**。
+
+## 2. 本次训练版本
+
+- 校准版本：`emos-20260320130245`
+- 训练时间：`2026-03-20T13:02:45.903772+00:00`
+- 参数文件：[default.json](/E:/web/PolyWeather/artifacts/probability_calibration/default.json)
+- 离线评估报告：[evaluation_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/evaluation_report.json)
+- 线上 shadow 报表：[shadow_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/shadow_report.json)
+
+## 3. 训练数据概况
+
+### 3.1 数据来源
+
+当前训练主要使用两类数据：
+
+1. 项目历史日记录  
+   文件：[daily_records.json](/E:/web/PolyWeather/data/daily_records.json)
+
+2. 历史天气 CSV 构建出的结算标签  
+   文件：[settlement_history.json](/E:/web/PolyWeather/artifacts/probability_calibration/settlement_history.json)
+
+### 3.2 样本规模
+
+- 总训练样本数：`105`
+- 通过历史天气 CSV 补回的缺失 `actual_high`：`2`
+- 历史结算标签覆盖城市数：`30`
+
+说明：
+
+- 当前样本已覆盖 30 个城市，但有效监督样本量仍偏小。
+- 部分城市样本数只有 `2-7` 条，城市级参数容易波动。
+
+## 4. 模型结构
+
+### 4.1 当前实现
+
+EMOS 属于统计后处理层，不是数值天气模型本身。当前结构位于：
+
+- [probability_calibration.py](/E:/web/PolyWeather/src/analysis/probability_calibration.py)
+
+当前目标是对原有概率引擎输出进行校准：
+
+- 输入：`raw_mu`、`raw_sigma`、`DEB`、`ensemble median/spread`、`peak_status` 等特征
+- 输出：校准后的 `mu / sigma / distribution`
+
+### 4.2 当前运行模式
+
+支持三种模式：
+
+- `legacy`
+- `emos_shadow`
+- `emos_primary`
+
+当前建议默认模式：
+
+- `emos_shadow`
+
+即：
+
+- 对外仍展示 legacy 结果
+- 后台并行计算 EMOS 结果
+- 用于持续评估，不直接影响用户
+
+## 5. 本次训练参数摘要
+
+### 5.1 全局约束
+
+本次训练已加入两类约束：
+
+1. `sigma_constraints`
+- `min_ratio = 0.85`
+- `max_ratio = 1.35`
+- `absolute_min = 0.25`
+- `absolute_max = 3.0`
+
+2. `selection_guardrails`
+- `max_mae_increase = 0.02`
+- `max_bucket_hit_drop = 0.01`
+- `max_bucket_brier_increase = 0.05`
+
+这两类约束的目的不是追求“更激进的拟合”，而是防止 EMOS 为了降低 CRPS 而把分布摊得过平，导致业务上更关键的顶桶命中和概率质量变差。
+
+### 5.2 当前选中的 blending
+
+本次训练产物中最终选择：
+
+- `alpha_mu = 0.0`
+- `alpha_sigma = 0.0`
+
+含义是：
+
+- 训练器在护栏约束下，没有找到足够安全的候选方案可以替代 legacy 主路径
+- 因此当前正式选中的可用结果，本质上仍然锚定在 legacy
+
+这是一种正确的保护行为，不是失败。说明门禁已经起作用，避免了坏校准进入主路径。
+
+## 6. 离线评估结果
+
+评估报告来源：
+
+- [evaluation_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/evaluation_report.json)
+
+### 6.1 总体结果
+
+Legacy：
+
+- `mean_crps = 2.793938`
+- `mean_mae = 2.721143`
+- `bucket_hit_rate = 0.695238`
+
+EMOS（强制 primary 评估）：
+
+- `mean_crps = 2.650216`
+- `mean_mae = 2.722829`
+- `bucket_hit_rate = 0.666667`
+
+Delta：
+
+- `CRPS = -0.143722`
+- `MAE = +0.001686`
+- `bucket_hit_rate = -0.028571`
+
+### 6.2 解读
+
+这组结果说明：
+
+1. `CRPS` 有改善  
+   说明从“分布整体平滑度”角度看，EMOS 有一定价值。
+
+2. `MAE` 基本持平但略差  
+   不是大问题，但也不能算改善。
+
+3. `bucket_hit_rate` 明显下降  
+   这是当前最大阻塞项。对 PolyWeather 这种结算桶业务来说，顶桶命中率比单纯 CRPS 更关键。
+
+因此，离线结论是：
+
+- `EMOS` 有研究价值
+- 但 **离线强切 primary 仍然不合格**
+
+## 7. 线上 Shadow 观测结果
+
+线上 shadow 报表来源：
+
+- [shadow_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/shadow_report.json)
+
+### 7.1 总体结果
+
+- `samples = 103`
+- `legacy_mean_mae = 1.839223`
+- `shadow_mean_mae = 1.851931`
+- `delta_mae = +0.012708`
+
+- `legacy_bucket_hit_rate = 0.669903`
+- `shadow_bucket_hit_rate = 0.679612`
+- `delta_bucket_hit_rate = +0.009709`
+
+- `legacy_bucket_brier = 0.462814`
+- `shadow_bucket_brier = 0.756649`
+- `delta_bucket_brier = +0.293835`
+
+### 7.2 解读
+
+线上 shadow 结果和离线强制 primary 结果不完全相同，这是正常的。原因是：
+
+- `shadow_report` 反映的是历史记录中实际落盘的 shadow 输出
+- `evaluation_report` 反映的是离线脚本在强制 `emos_primary` 下重新计算的效果
+
+当前线上 shadow 的含义是：
+
+1. 顶桶命中率略有提升  
+   `+0.97%`
+
+2. 但 `MAE` 轻微变差  
+   虽然幅度不大，但没有形成明确优势
+
+3. `bucket_brier` 明显更差  
+   说明 shadow 分布仍然偏“摊平”，概率质量不足
+
+这是当前最重要的信号：
+
+- EMOS 在“顶桶命中”上偶尔能赢
+- 但在“概率质量”上还不够好
+
+## 8. 城市级观察
+
+从当前城市级结果看，EMOS 并不是“全城市统一改善”，而是明显分化：
+
+### 8.1 相对改善较明显的城市
+
+- `London`
+- `Hong Kong`
+- `Tokyo`
+- `New York`
+
+这些城市在部分指标上看到一定改善，说明当前校准特征在这些城市上更有效。
+
+### 8.2 风险较高的城市
+
+- `Atlanta`
+- `Miami`
+- `Chicago`
+- `Dallas`
+- `Seattle`
+
+这些城市常见现象是：
+
+- 顶桶命中没有显著提高
+- 或 `bucket_brier` 明显恶化
+- 或者 `MAE` 出现不必要抬升
+
+这说明当前 EMOS 还没有形成稳定的全局校准能力，城市间异质性很强。
+
+## 9. 当前判断
+
+### 9.1 能不能上线为主路径
+
+当前答案：
+
+- **不能**
+
+原因：
+
+1. 离线强制 primary 时，`bucket_hit_rate` 下降
+2. 线上 shadow 时，`bucket_brier` 明显变差
+3. 样本量依然偏小，城市样本不均衡
+4. 城市级表现分化明显
+
+### 9.2 当前应该怎么运行
+
+当前最合理的运行方式：
+
+1. 保持 `emos_shadow`
+2. 继续落盘 `shadow_prob_snapshot`
+3. 继续维护滚动报表
+4. 不修改机器人和网页的正式对外概率展示
+
+## 10. 已完成的工程能力
+
+目前已经具备以下能力：
+
+1. 可离线训练  
+   脚本：[fit_probability_calibration.py](/E:/web/PolyWeather/scripts/fit_probability_calibration.py)
+
+2. 可离线评估  
+   脚本：[evaluate_probability_calibration.py](/E:/web/PolyWeather/scripts/evaluate_probability_calibration.py)
+
+3. 可导出训练样本  
+   脚本：[export_probability_training_dataset.py](/E:/web/PolyWeather/scripts/export_probability_training_dataset.py)
+
+4. 可历史回填 shadow 结果  
+   脚本：[backfill_probability_shadow_history.py](/E:/web/PolyWeather/scripts/backfill_probability_shadow_history.py)
+
+5. 可生成滚动 shadow 报表  
+   脚本：[build_probability_shadow_report.py](/E:/web/PolyWeather/scripts/build_probability_shadow_report.py)
+
+6. CI 已接入  
+   包含 `ruff / pytest / frontend build / docker build workflow`
+
+## 11. 下一步建议
+
+### 11.1 必做
+
+1. 扩大监督样本量  
+   重点不是继续堆原始天气 CSV，而是补更多带 forecast snapshot 的历史样本。
+
+2. 继续按版本沉淀训练报告  
+   每次重训后都更新本报告或新增版本报告，避免只看单次结果。
+
+3. 保持 `shadow` 连续观测  
+   至少持续一段时间观察滚动指标是否稳定。
+
+### 11.2 再做
+
+1. 细分城市组建模  
+   比如按气候区、结算规则、温度单位分组，而不是完全全局一套参数。
+
+2. 优化训练目标  
+   目前已经把 `bucket_brier` 纳入目标，但仍需进一步靠近 PolyWeather 的业务目标。
+
+3. 补更严格的切换门槛  
+   只有在同时满足以下条件时，才考虑切 `emos_primary`：
+- `CRPS` 下降
+- `MAE` 不上升
+- `bucket_hit_rate` 不下降
+- `bucket_brier` 不上升
+
+## 12. 结论
+
+当前 EMOS 状态可以概括为：
+
+- 工程上：已经完整接入，具备训练、评估、shadow 观测能力
+- 模型上：有一定价值，但还不稳定
+- 产品上：适合继续做 shadow，不适合切主路径
+
+最终结论：
+
+- **继续使用 `emos_shadow`**
+- **暂不切 `emos_primary`**
+- **继续积累样本并按版本跟踪训练结果**

docs/FRONTEND_DEPLOYMENT_ZH.md

@@ -0,0 +1,211 @@
+# 前端部署配置（Vercel）
+
+本文只覆盖 `frontend` 目录对应的 Next.js 前端部署。
+
+## 一、部署目标
+
+推荐方案：
+
+1. GitHub Actions 负责 `CI`
+2. Vercel 负责前端 `CD`
+3. FastAPI 后端单独部署在 VPS / Docker 主机
+
+前端本身不直接访问天气源，而是通过 Next Route Handlers 转发到后端：
+
+1. 浏览器 -> Vercel 上的 Next.js 前端
+2. Next `/api/*` -> `POLYWEATHER_API_BASE_URL`
+3. FastAPI 后端 -> 分析 / 支付 / 鉴权服务
+
+## 二、Vercel 项目设置
+
+在 Vercel 导入 GitHub 仓库后，使用下面的设置：
+
+- Framework Preset: `Next.js`
+- Root Directory: `frontend`
+- Build Command: `npm run build`
+- Install Command: `npm install`
+
+如果仓库已经连接过 Vercel，通常只需要确认 `Root Directory` 仍然是 `frontend`。
+
+## 三、最小必填环境变量
+
+只部署天气看板和基础登录时，先填下面 4 项：
+
+```env
+POLYWEATHER_API_BASE_URL=https://<your-fastapi-host>
+NEXT_PUBLIC_SUPABASE_URL=https://<your-project>.supabase.co
+NEXT_PUBLIC_SUPABASE_ANON_KEY=<your-anon-key>
+POLYWEATHER_AUTH_ENABLED=true
+```
+
+建议显式补：
+
+```env
+POLYWEATHER_AUTH_REQUIRED=true
+```
+
+说明：
+
+- `POLYWEATHER_API_BASE_URL`：前端所有 `/api/*` Route Handler 转发时依赖它，没填会直接返回 500。
+- `NEXT_PUBLIC_SUPABASE_URL` / `NEXT_PUBLIC_SUPABASE_ANON_KEY`：Supabase 客户端依赖它们。
+- `POLYWEATHER_AUTH_ENABLED`：关闭时，前端不会启用登录能力。
+- `POLYWEATHER_AUTH_REQUIRED`：控制 middleware 是否强制登录。
+
+## 四、按功能启用的可选环境变量
+
+### 1. 分享式看板
+
+```env
+POLYWEATHER_DASHBOARD_ACCESS_TOKEN=
+```
+
+设置后，可通过 `/?access_token=<token>` 打开带令牌的看板入口。
+
+### 2. 前后端 entitlement 校验
+
+```env
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
+```
+
+仅当后端开启 entitlement / 订阅校验时需要。
+
+### 3. 钱包支付
+
+```env
+NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID=
+NEXT_PUBLIC_WALLETCONNECT_POLYGON_RPC_URL=https://polygon-bor-rpc.publicnode.com
+```
+
+如果不启用钱包支付，可以留空。
+
+### 4. `/ops` 管理员页面守卫
+
+```env
+POLYWEATHER_OPS_ADMIN_EMAILS=yhrsc30@gmail.com
+```
+
+说明：
+
+- `/ops` 现在不是只有后端接口限制，前端页面入口也会读取管理员邮箱白名单。
+- 因此前端部署到 Vercel 时，也应配置 `POLYWEATHER_OPS_ADMIN_EMAILS`。
+
+### 5. Telegram 入口
+
+```env
+NEXT_PUBLIC_TELEGRAM_GROUP_URL=https://t.me/<your_group>
+NEXT_PUBLIC_TELEGRAM_BOT_URL=https://t.me/WeatherQuant_bot
+```
+
+只影响按钮跳转，不影响核心页面加载。
+
+## 五、支付配置与旧部署治理
+
+支付区现在有一层额外防护：
+
+1. 用户点击支付前，前端会重新请求 `/api/payments/config`
+2. 若发现 `receiver_contract` 与页面旧状态不一致，会自动切换到最新地址
+3. 若后端返回的 `tx_payload.to` 与最新 `receiver_contract` 不一致，会直接阻断支付
+
+这层防护的目的，是降低以下事故概率：
+
+- 用户使用长期未刷新的旧标签页
+- 命中旧 deployment URL
+- 页面本地状态残留旧收款地址
+
+如果你变更过支付收款地址，建议同步执行：
+
+1. 在 Vercel 对当前 production 做一次 redeploy
+2. 删除明显过期、可能还带旧支付配置的旧 deployment
+3. 在 `Settings -> Security -> Deployment Retention Policy` 中收紧旧部署保留周期
+
+## 六、推荐的三套配置口径
+
+### 1. 公开游客模式
+
+```env
+POLYWEATHER_API_BASE_URL=https://api.example.com
+POLYWEATHER_AUTH_ENABLED=false
+POLYWEATHER_AUTH_REQUIRED=false
+```
+
+适合公开演示站。
+
+### 2. 正常登录模式
+
+```env
+POLYWEATHER_API_BASE_URL=https://api.example.com
+NEXT_PUBLIC_SUPABASE_URL=https://<project>.supabase.co
+NEXT_PUBLIC_SUPABASE_ANON_KEY=<anon-key>
+POLYWEATHER_AUTH_ENABLED=true
+POLYWEATHER_AUTH_REQUIRED=true
+```
+
+适合正式前端站点。
+
+### 3. 登录 + entitlement 联动
+
+```env
+POLYWEATHER_API_BASE_URL=https://api.example.com
+NEXT_PUBLIC_SUPABASE_URL=https://<project>.supabase.co
+NEXT_PUBLIC_SUPABASE_ANON_KEY=<anon-key>
+POLYWEATHER_AUTH_ENABLED=true
+POLYWEATHER_AUTH_REQUIRED=true
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=<shared-token>
+```
+
+适合前后端都启用了会员/订阅保护的生产环境。
+
+## 七、不要放进 Vercel 的变量
+
+这些属于后端私密配置，不应该放到前端项目：
+
+- `SUPABASE_SERVICE_ROLE_KEY`
+- `TELEGRAM_BOT_TOKEN`
+- `POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN` 以外的后端 secret
+- 支付签名私钥 / 交易私钥 / 任何 bot 凭据
+
+特别注意：
+
+- `NEXT_PUBLIC_*` 会暴露给浏览器
+- 只有明确允许前端公开使用的值，才应加 `NEXT_PUBLIC_`
+
+## 八、上线前检查
+
+Vercel 部署前至少确认：
+
+1. `POLYWEATHER_API_BASE_URL` 指向可访问的后端生产地址
+2. `frontend/.env.example` 和 Vercel Project Settings 中的实际值一致
+3. GitHub Actions 中 `frontend-quality` 已通过
+4. 如果启用鉴权，Supabase redirect URL 已包含前端域名
+5. `GET /api/payments/config` 返回的是当前最新地址，而不是旧收款合约
+6. 如果启用了 `/ops`，确认 `POLYWEATHER_OPS_ADMIN_EMAILS` 已在 Vercel 与后端同时配置
+
+## 九、常见问题
+
+### 1. 页面打开后 API 全部 500
+
+先检查：
+
+```env
+POLYWEATHER_API_BASE_URL
+```
+
+这是最常见原因。
+
+### 2. Vercel 构建通过，但登录失败
+
+先检查：
+
+- `NEXT_PUBLIC_SUPABASE_URL`
+- `NEXT_PUBLIC_SUPABASE_ANON_KEY`
+- Supabase 项目里的站点 URL / redirect URL
+
+### 3. 钱包入口显示未配置
+
+先检查：
+
+```env
+NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID
+```
+
+这是钱包连接的必需项。

docs/LGBM_DAILY_HIGH_ZH.md

@@ -0,0 +1,310 @@
+# LightGBM 日最高温模型（中文）
+
+## 1. 目标
+
+这套 `LightGBM` 模型是给 PolyWeather 增加一个轻量级的统计学习预测源。
+
+它的定位不是替代：
+
+- `DEB`
+- `EMOS`
+- `ECMWF / GFS / GEM / JMA / ICON / Open-Meteo / MGM / NWS`
+
+而是作为一个新的点预测源：
+
+`现有模型 + 观测特征 -> LGBM -> 并入 current_forecasts -> DEB -> EMOS`
+
+第一版只做：
+
+- `D0` 当日最高温预测
+
+不做：
+
+- `D1-D3`
+- 小时级曲线
+- 概率分布
+- 独立结算源
+
+## 2. 适用场景
+
+这条链路是为低资源 VPS 准备的。
+
+当前项目线上环境只有 `2GB RAM` 时，不适合引入 `TimesFM` 这类大模型，但适合用 `LightGBM` 做轻量推理。
+
+当前方案是：
+
+1. 训练离线完成
+2. 训练产物直接提交到仓库
+3. VPS 线上只加载模型文件并推理
+4. VPS 不训练，不起额外服务
+
+## 3. 文件结构
+
+核心文件如下：
+
+- 运行时推理：
+  - [src/models/lgbm_daily_high.py](/E:/web/PolyWeather/src/models/lgbm_daily_high.py)
+- 特征构建：
+  - [src/models/lgbm_features.py](/E:/web/PolyWeather/src/models/lgbm_features.py)
+- 训练脚本：
+  - [scripts/train_lgbm_daily_high.py](/E:/web/PolyWeather/scripts/train_lgbm_daily_high.py)
+- 训练报告脚本：
+  - [scripts/report_lgbm_daily_high.py](/E:/web/PolyWeather/scripts/report_lgbm_daily_high.py)
+- 模型文件：
+  - [artifacts/models/lgbm_daily_high.txt](/E:/web/PolyWeather/artifacts/models/lgbm_daily_high.txt)
+- 模型 schema / 指标：
+  - [artifacts/models/lgbm_daily_high_schema.json](/E:/web/PolyWeather/artifacts/models/lgbm_daily_high_schema.json)
+
+接入链路位置：
+
+- Web API 聚合：
+  - [web/analysis_service.py](/E:/web/PolyWeather/web/analysis_service.py)
+- 共享趋势引擎：
+  - [src/analysis/trend_engine.py](/E:/web/PolyWeather/src/analysis/trend_engine.py)
+
+## 4. 特征说明
+
+第一版特征固定为以下几组。
+
+### 4.1 历史日高温特征
+
+- `actual_high_lag_1`
+- `actual_high_lag_2`
+- `actual_high_lag_3`
+- `actual_high_lag_7`
+- `actual_high_mean_7`
+- `actual_high_mean_14`
+- `actual_high_trend_3`
+
+### 4.2 当天模型特征
+
+- `Open-Meteo`
+- `ECMWF`
+- `GFS`
+- `GEM`
+- `JMA`
+- `ICON`
+- `MGM`
+- `NWS`
+- `deb_prediction`
+- `model_median`
+- `model_spread`
+
+### 4.3 当前观测特征
+
+- `current_temp`
+- `max_so_far`
+- `humidity`
+- `wind_speed_kt`
+- `visibility_mi`
+
+### 4.4 时间与状态特征
+
+- `local_hour`
+- `month`
+- `weekday`
+- `peak_status_code`
+
+其中：
+
+- `before = 0`
+- `in_window = 1`
+- `past = 2`
+
+## 5. 训练数据来源
+
+训练数据主要来自两份运行时历史文件：
+
+- [data/daily_records.json](/E:/web/PolyWeather/data/daily_records.json)
+- [data/probability_training_snapshots.jsonl](/E:/web/PolyWeather/data/probability_training_snapshots.jsonl)
+
+作用分工：
+
+- `daily_records.json`
+  - 提供 `actual_high`
+  - 提供当天各模型 forecast
+  - 提供历史 `deb_prediction`
+
+- `probability_training_snapshots.jsonl`
+  - 提供 `max_so_far`
+  - 提供 `peak_status`
+  - 提供观测特征快照
+
+为后续重训，概率快照归档现在还会额外写入：
+
+- `current_temp`
+- `humidity`
+- `wind_speed_kt`
+- `visibility_mi`
+- `local_hour`
+
+对应代码：
+
+- [src/analysis/probability_snapshot_archive.py](/E:/web/PolyWeather/src/analysis/probability_snapshot_archive.py)
+
+## 6. 训练流程
+
+训练脚本：
+
+```bash
+./venv/Scripts/python.exe scripts/train_lgbm_daily_high.py
+```
+
+训练流程如下：
+
+1. 从历史文件构造监督样本
+2. 目标值固定为 `actual_high`
+3. 按日期做简单的时间顺序切分
+4. 最后约 20% 做验证集
+5. 先训练并评估验证集
+6. 再用全量样本训练最终模型
+7. 输出模型文件和 schema 文件
+
+输出产物：
+
+- [artifacts/models/lgbm_daily_high.txt](/E:/web/PolyWeather/artifacts/models/lgbm_daily_high.txt)
+- [artifacts/models/lgbm_daily_high_schema.json](/E:/web/PolyWeather/artifacts/models/lgbm_daily_high_schema.json)
+
+## 7. 如何看训练结果
+
+查看训练报告：
+
+```bash
+./venv/Scripts/python.exe scripts/report_lgbm_daily_high.py
+```
+
+这个脚本会读取 schema，并打印：
+
+- `Sample Count`
+- `Train Count`
+- `Valid Count`
+- `LGBM MAE`
+- `DEB MAE`
+- `Best Single MAE`
+- `Median MAE`
+- `Winner`
+
+当前这版训练结果是：
+
+- `sample_count = 29`
+- `validation_count = 12`
+- `validation.lgbm_mae = 2.975`
+- `validation.deb_mae = 2.267`
+- `validation.best_single_mae = 1.167`
+
+这说明：
+
+- 当前 `LGBM` 链路已经可用
+- 但现阶段验证集表现还没有超过 `DEB`
+- 所以默认配置仍建议保持关闭
+
+## 8. 线上运行逻辑
+
+运行时推理逻辑不是“直接替代 DEB”，而是：
+
+1. 先收集现有模型 forecast
+2. 先算一版基线 `DEB`
+3. 把这版 `DEB` 当作 `LGBM` 的一个输入特征
+4. 输出 `LGBM` 点预测
+5. 把 `LGBM` 注入 `current_forecasts`
+6. 重新计算最终 `DEB`
+
+这样做的原因是：
+
+- `LGBM` 需要吃到 `deb_prediction` 特征
+- 但最终 `DEB` 又要把 `LGBM` 当成一个新的输入模型
+
+## 9. 环境变量
+
+示例配置见：
+
+- [.env.example](/E:/web/PolyWeather/.env.example)
+
+相关变量：
+
+```env
+POLYWEATHER_LGBM_ENABLED=false
+POLYWEATHER_LGBM_MODEL_PATH=/app/artifacts/models/lgbm_daily_high.txt
+POLYWEATHER_LGBM_SCHEMA_PATH=/app/artifacts/models/lgbm_daily_high_schema.json
+POLYWEATHER_LGBM_MIN_HISTORY_POINTS=3
+```
+
+说明：
+
+- `POLYWEATHER_LGBM_ENABLED`
+  - 是否启用运行时推理
+- `POLYWEATHER_LGBM_MODEL_PATH`
+  - 模型文件路径
+- `POLYWEATHER_LGBM_SCHEMA_PATH`
+  - schema 文件路径
+- `POLYWEATHER_LGBM_MIN_HISTORY_POINTS`
+  - 某城市最低历史样本门槛
+
+默认是 `3`，原因不是最理想，而是当前整体样本仍然偏少。
+
+如果门槛设太高，很多城市现在根本不会触发 `LGBM`。
+
+## 10. VPS 部署建议
+
+如果你的 VPS 只有 `2GB RAM`：
+
+- 可以跑这套 `LightGBM`
+- 不要在 VPS 上训练
+- 不要起额外模型服务
+
+推荐方式：
+
+1. 在本地或开发环境训练
+2. 提交模型产物
+3. VPS 拉代码
+4. 开启 `POLYWEATHER_LGBM_ENABLED=true`
+5. 重启主服务
+
+不推荐：
+
+- 在 VPS 上跑训练脚本
+- 把 `LightGBM` 当成长任务服务单独部署
+- 同时引入大模型推理
+
+## 11. 当前结论
+
+这条链路已经完成了：
+
+- 离线训练
+- 模型产物固化
+- 运行时懒加载
+- Web / 共享分析链路注入
+- 前端模型类型兼容
+
+但当前样本量仍偏少，所以建议运营策略是：
+
+1. 先继续积累历史 `actual_high`
+2. 继续积累概率快照观测字段
+3. 定期重训
+4. 只有当验证集 `MAE` 持续接近或优于 `DEB` 时，再考虑默认线上开启
+
+## 12. 常用命令
+
+### 训练
+
+```bash
+./venv/Scripts/python.exe scripts/train_lgbm_daily_high.py
+```
+
+### 查看训练报告
+
+```bash
+./venv/Scripts/python.exe scripts/report_lgbm_daily_high.py
+```
+
+### 本地测试
+
+```bash
+./venv/Scripts/python.exe -m pytest tests/test_lgbm_features.py tests/test_lgbm_daily_high.py
+```
+
+### 编译检查
+
+```bash
+./venv/Scripts/python.exe -m compileall src web scripts tests
+```

docs/MONITORING_ZH.md

@@ -0,0 +1,123 @@
+# 外部监控与告警说明
+
+最后更新：`2026-04-01`
+
+## 1. 目标
+
+在现有轻量可观测性基础上，把 PolyWeather 补成最小可用的外部监控链路：
+
+- Prometheus 抓取 `/metrics`
+- Alertmanager 根据规则聚合告警
+- Relay 把告警推到运营频道
+- Grafana 展示趋势面板
+- 巡检脚本补健康检查
+
+## 2. 组件
+
+本仓库现在内置 4 个监控组件：
+
+- `polyweather_prometheus`
+- `polyweather_alertmanager`
+- `polyweather_alert_relay`
+- `polyweather_grafana`
+
+对应配置目录：
+
+- [monitoring/prometheus/prometheus.yml](../monitoring/prometheus/prometheus.yml)
+- [monitoring/prometheus/alerts.yml](../monitoring/prometheus/alerts.yml)
+- [monitoring/alertmanager/alertmanager.yml](../monitoring/alertmanager/alertmanager.yml)
+- [monitoring/grafana/dashboards/polyweather-overview.json](../monitoring/grafana/dashboards/polyweather-overview.json)
+
+## 3. 启动
+
+```bash
+docker compose --profile monitoring up -d polyweather_prometheus polyweather_alertmanager polyweather_alert_relay polyweather_grafana
+```
+
+默认端口：
+
+- Prometheus: `9090`
+- Alertmanager: `9093`
+- Grafana: `3001`
+- Alert relay: `9099`
+
+## 4. 环境变量
+
+在 [.env.example](../.env.example) 里新增了这些配置：
+
+```env
+POLYWEATHER_PROMETHEUS_PORT=9090
+POLYWEATHER_ALERTMANAGER_PORT=9093
+POLYWEATHER_ALERT_RELAY_PORT=9099
+POLYWEATHER_GRAFANA_PORT=3001
+POLYWEATHER_GRAFANA_ADMIN_USER=admin
+POLYWEATHER_GRAFANA_ADMIN_PASSWORD=polyweather
+POLYWEATHER_MONITORING_ALERT_CHAT_IDS=
+```
+
+说明：
+
+- `POLYWEATHER_MONITORING_ALERT_CHAT_IDS` 为空时，relay 会自动回退到：
+  - `TELEGRAM_CHAT_IDS`
+  - `TELEGRAM_CHAT_ID`
+- 告警发送仍复用现有 `TELEGRAM_BOT_TOKEN`
+
+## 5. 当前告警规则
+
+当前默认规则：
+
+- `PolyWeatherWebDown`
+- `PolyWeatherHttp5xxBurst`
+- `PolyWeatherHighSourceErrorRate`
+- `PolyWeatherOpenMeteoCooldownLoop`
+- `PolyWeatherSlowHttpAverage`
+
+规则文件：
+
+- [monitoring/prometheus/alerts.yml](../monitoring/prometheus/alerts.yml)
+
+## 6. 当前 Grafana 面板
+
+预置了一个最小仪表板：
+
+- `PolyWeather Overview`
+
+包含这些图：
+
+- HTTP Requests by Status
+- HTTP Latency
+- Source Requests by Outcome
+- Source Error Rate (15m)
+
+## 7. 巡检脚本
+
+手动巡检：
+
+```bash
+python scripts/check_ops_health.py --base-url http://127.0.0.1:8000
+```
+
+这个脚本会检查：
+
+- `/healthz`
+- `/api/system/status`
+- `/metrics`
+
+任何一项失败都会非零退出，适合挂到 crontab 或 systemd timer。
+
+## 8. 备注
+
+这套监控现在已经具备：
+
+- 外部抓取
+- 告警规则
+- Telegram 推送
+- 趋势面板
+- 巡检脚本
+
+但它仍是“最小可用版”，还没有覆盖：
+
+- 节点级 CPU / 内存 / 磁盘
+- 数据库体积趋势
+- 更细粒度支付指标
+- 按城市/来源拆分的业务 SLA

docs/OPEN_CORE_POLICY.md

@@ -1,63 +1,45 @@
-# Open-Core 与商用边界
+# AGPL-3.0 与商用边界
 
-最后更新：`2026-03-14`
+最后更新：`2026-03-30`
 
-## 1. 目标
+## 1. 当前许可证
 
-在保持社区可用性的前提下，保护商业化阶段的核心经营资产。
+- 本仓库代码自 `2026-03-30` 起采用 **GNU Affero General Public License v3.0 only**（`AGPL-3.0-only`）。
+- 该许可证适用于仓库中未另行声明许可证的源代码与文档。
+- 如果你修改本项目并通过网络向用户提供服务，需按 AGPL 第 13 条向用户提供对应源码。
 
-## 2. 仓库公开范围（可开源）
+## 2. 旧版本说明
 
-- 天气数据采集与标准化（METAR / Open-Meteo / MGM 接口层）。
-- DEB 与基础趋势分析、概率桶计算。
-- Dashboard 基础体验与 API/BFF 结构。
-- Telegram Bot 基础命令与基础积分机制。
-- 合约支付标准流程（钱包绑定、intent、提交、确认、补单）。
+- 在本次切换前已经发布的 MIT 版本，仍按其原始许可证生效。
+- 本次变更不会追溯撤销既往已发布版本的 MIT 授权。
 
-## 3. 生产私有范围（建议不公开）
+## 3. 仓库公开范围
 
-- 商业风控参数与规则库：
-  - 错价信号阈值组合、推送阈值、异常检测策略。
-- 运营策略资产：
-  - 用户分层规则、促销规则、留存策略、活动模板。
-- 付费系统敏感细节：
-  - 实时对账容错阈值、退款审计策略、内部财务映射规则。
-- 私有运维资产：
-  - 生产告警路由、内部频道映射、应急脚本与排障手册。
+- 天气数据采集与标准化（METAR / Open-Meteo / MGM / 官方结算源接口层）。
+- DEB、基础趋势分析、概率桶、历史对账、前端看板与 Bot 基础能力。
+- 标准支付流程、链上收款合约与公开 API/BFF 结构。
 
-## 4. 配置与数据安全红线
+## 4. 不在仓库许可证授权范围内的资产
 
-- 不提交：`.env`、私钥、API key、机器人 token。
-- 不提交：生产数据库、运行时状态文件、支付流水快照。
-- 不提交：用户身份信息、钱包映射、订阅原始审计日志。
+- 商标、品牌名、域名、Logo、商店素材与市场宣传文案。
+- 生产数据库、用户资料、钱包映射、订阅审计日志、内部报表。
+- 私有运营脚本、增长工具、内部风控参数、收费策略细节与内部阈值。
+- 托管服务本身、SLA、客服、运维值守与内部告警路由。
 
-## 5. 推荐发布模式
+## 5. 配置与数据安全红线
 
-### 5.1 Community Edition（开源）
+- 不提交：`.env`、私钥、API key、机器人 token、第三方 service role key。
+- 不提交：生产数据库、运行态快照、支付流水快照、用户身份信息。
+- 不提交：仅用于线上商业判断的私有规则库与内部操作手册。
 
-- 提供基础分析与基础看板。
-- 可选保留只读市场扫描。
-- 默认关闭商业化运营规则。
+## 6. 对部署者的要求
 
-### 5.2 Production Edition（私有）
+- 若你提供公开网络服务，应在产品界面中提供清晰可访问的源码入口。
+- 若你修改了本项目再对外提供网络服务，应公开与你实际运行版本对应的源码。
+- 若你使用了仓库外的私有数据、商标或运营资产，这些额外资产不因 AGPL 自动获得授权。
 
-- 启用收费、订阅、积分抵扣、风控、私有监控。
-- 仅在私有仓库维护运营策略与敏感参数。
+## 7. 法务与运营建议
 
-## 6. 文档口径规范
-
-对外文档仅描述：
-
-- 能力边界与使用方式。
-- 可公开的技术架构。
-- 不包含可被直接复刻的商业参数。
-
-不对外文档描述：
-
-- 具体策略阈值、用户分层细则、收益归因规则。
-
-## 7. 许可证与法务建议（简版）
-
-- 建议保持仓库代码许可证与商标/品牌授权分离。
-- 若提供商业服务，建议在官网补充服务条款与隐私政策。
-- 对“订阅权益”与“可用性”做明确 SLA 与免责边界。
+- 代码许可证与商标/品牌授权应继续分离管理。
+- 官网应补充服务条款、隐私政策与付费权益说明。
+- 若后续接受外部贡献，再次调整许可证前应先确认贡献者版权归属与再许可条件。

docs/OPS_ADMIN_ZH.md

@@ -0,0 +1,109 @@
+# Ops 运营后台说明
+
+最后更新：`2026-04-01`
+
+## 1. 入口
+
+前端入口：
+
+- `https://polyweather-pro.vercel.app/ops`
+
+## 2. 权限
+
+`/ops` 的写接口由后端白名单控制：
+
+```env
+POLYWEATHER_OPS_ADMIN_EMAILS=yhrsc30@gmail.com
+```
+
+可配置多个邮箱，逗号分隔。
+
+## 3. 当前能力
+
+### 只读能力
+
+- 系统健康
+- SQLite / rollout / metrics 摘要
+- 支付运行态
+- 当前会员
+- 周榜
+- 支付异常单
+- 漏斗转化面板
+
+### 写能力
+
+- 手动补分
+- 标记支付异常单“已处理”
+
+## 4. 当前会员
+
+会员列表来自：
+
+1. `subscriptions` 中的有效订阅
+2. 本地 `users` / `supabase_bindings`
+3. 若本地缺邮箱或注册时间，再回补 Supabase Auth 用户信息
+
+去重规则：
+
+- 同一个 `user_id` 只保留最晚到期那条
+
+## 5. 支付异常单
+
+当前异常单来源：
+
+- `payment_audit_events`
+- 仅筛 `payment_intent_failed`
+
+当前支持的典型失败原因：
+
+- `receiver_mismatch`
+- `sender_mismatch`
+- `event_mismatch`
+- `tx_reverted`
+
+默认只显示未处理项。
+
+## 6. 典型处理流程
+
+### 6.1 钱已到账但没开订阅
+
+先看 `/ops` 的支付异常单：
+
+- 如果是 `receiver_mismatch`
+  - 优先判定为支付打到了旧收款地址
+  - 不是缓存问题
+
+然后执行：
+
+1. 查 `payment_intents`
+2. 查 `payment_transactions`
+3. 查 `subscriptions`
+4. 跑恢复脚本：
+
+```bash
+python scripts/reconcile_subscription_by_email.py --email <user_email>
+```
+
+如果仍然失败，再人工补订阅。
+
+### 6.2 已人工处理
+
+在 `/ops` 里直接点：
+
+- `标记已处理`
+
+这不会删除审计事件，只会给原事件写：
+
+- `resolved_at`
+- `resolved_by`
+
+## 7. 备注
+
+`/ops` 是运营后台最小版，不是完整 Admin 平台。当前目标是：
+
+- 让会员、积分、支付事故、系统状态可查
+- 让常见人工操作不必再直接写 SQL
+
+外部监控与告警栈说明见：
+
+- [MONITORING_ZH.md](./MONITORING_ZH.md)

docs/PROBABILITY_SNAPSHOT_ARCHIVE_ZH.md

@@ -0,0 +1,324 @@
+# 概率训练样本归档说明（中文）
+
+## 1. 目的
+
+这份文档说明两件事：
+
+1. 为什么 `EMOS` 训练不能只依赖历史实测天气
+2. 未来如何持续沉淀“历史预测记录”，让概率引擎越训越稳
+
+一句话结论：
+
+- 历史实测天气只能补 `actual_high`
+- 真正决定 `EMOS` 训练质量的是“当时那一刻的预测快照”
+
+## 2. 什么是“历史预测记录”
+
+对 PolyWeather 来说，一条可训练的历史预测记录，至少应该包含这些字段：
+
+- `city`
+- `timestamp`
+- `date`
+- `raw_mu`
+- `raw_sigma`
+- `deb_prediction`
+- `ensemble p10 / p50 / p90`
+- `multi-model forecasts`
+- `max_so_far`
+- `peak_status`
+- `prob_snapshot`
+- 当天最终 `actual_high`
+- 当天最终 `settlement bucket`
+
+这类记录的核心价值是：
+
+- 还原“当时系统实际看到什么”
+- 再对照“后来真实发生了什么”
+
+只有这两者成对，`EMOS` 才能学习偏差。
+
+## 3. 为什么不能只用历史天气实测
+
+历史天气 CSV 只能告诉你：
+
+- 当天最高温是多少
+- 某小时温度是多少
+
+但它不能告诉你：
+
+- 当天早上 09:00 时，系统的 `mu` 是多少
+- 当时的 `ensemble spread` 是多少
+- 当时 `DEB` 怎么看
+- 当时的 top bucket 是什么
+
+所以：
+
+- 历史实测天气是标签
+- 历史预测记录才是训练输入
+
+缺少后者，EMOS 只能学到很有限的东西。
+
+## 4. 当前项目里已经有的基础
+
+### 4.1 已有历史日记录
+
+文件：
+
+- [daily_records.json](/E:/web/PolyWeather/data/daily_records.json)
+
+当前已经保存了一部分训练相关字段，例如：
+
+- `forecasts`
+- `actual_high`
+- `deb_prediction`
+- `mu`
+- `prob_snapshot`
+- `shadow_prob_snapshot`
+- `probability_calibration`
+- `probability_features`
+
+这已经是“历史预测记录”的雏形。
+
+### 4.2 已有历史天气 CSV
+
+目录：
+
+- [data/historical](/E:/web/PolyWeather/data/historical)
+
+它们可以帮助补：
+
+- `actual_high`
+- `settlement history`
+
+但不能替代预测快照归档。
+
+## 5. 未来应该怎么存历史预测记录
+
+推荐做法是：
+
+### 5.1 固定时点归档
+
+每天为每个重点城市固定存几次快照，例如：
+
+- 当地 `09:00`
+- 当地 `12:00`
+- 当地 `15:00`
+
+这样能确保每个交易日都有稳定可比样本。
+
+### 5.2 关键变化时补充归档
+
+除了固定时点，还应该在以下情况额外存一次：
+
+- `max_so_far` 创新高
+- `mu` 变化超过阈值
+- `top bucket` 发生变化
+- `shadow top bucket` 发生变化
+
+这样能捕捉真正有训练价值的转折点。
+
+### 5.3 建议的存储格式
+
+建议新增一个文件，例如：
+
+- `data/probability_training_snapshots.jsonl`
+
+每一行保存一条 JSON 记录。
+
+优点：
+
+- 追加写入简单
+- 后续导出训练集方便
+- 不容易因为单个大 JSON 文件损坏而全盘受影响
+
+## 6. 一条建议的快照结构
+
+示例：
+
+```json
+{
+  "city": "ankara",
+  "timestamp": "2026-03-20T12:00:00+03:00",
+  "date": "2026-03-20",
+  "raw_mu": 15.2,
+  "raw_sigma": 1.2,
+  "deb_prediction": 15.4,
+  "ensemble": {
+    "p10": 14.8,
+    "median": 15.8,
+    "p90": 17.9
+  },
+  "multi_model": {
+    "ECMWF": 15.8,
+    "GFS": 14.1,
+    "ICON": 15.9,
+    "GEM": 16.5,
+    "JMA": 14.5
+  },
+  "max_so_far": 15.0,
+  "peak_status": "before",
+  "prob_snapshot": [
+    {"v": 15, "p": 0.552},
+    {"v": 16, "p": 0.377}
+  ],
+  "shadow_prob_snapshot": [
+    {"v": 15, "p": 0.324},
+    {"v": 16, "p": 0.238}
+  ],
+  "probability_engine": "legacy",
+  "probability_mode": "emos_shadow",
+  "calibration_version": "emos-20260320130245"
+}
+```
+
+当天结束后，再由后处理脚本回填：
+
+- `actual_high`
+- `settlement_bucket`
+
+## 7. 现阶段你可以执行的命令
+
+### 7.1 回填历史天气 CSV
+
+```bash
+python scripts/backfill_historical_weather.py
+```
+
+作用：
+
+- 补全 30 城市历史天气时序 CSV
+
+### 7.2 从历史 CSV 构建日级结算标签
+
+```bash
+python scripts/build_settlement_history_from_csv.py
+```
+
+作用：
+
+- 生成 [settlement_history.json](/E:/web/PolyWeather/artifacts/probability_calibration/settlement_history.json)
+
+### 7.3 导出当前训练样本
+
+```bash
+python scripts/export_probability_training_dataset.py
+```
+
+作用：
+
+- 生成 [training_samples.json](/E:/web/PolyWeather/artifacts/probability_calibration/training_samples.json)
+
+### 7.4 重训 EMOS
+
+```bash
+python scripts/fit_probability_calibration.py
+```
+
+作用：
+
+- 生成新的 [default.json](/E:/web/PolyWeather/artifacts/probability_calibration/default.json)
+
+### 7.5 离线评估训练效果
+
+```bash
+python scripts/evaluate_probability_calibration.py
+```
+
+作用：
+
+- 生成 [evaluation_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/evaluation_report.json)
+
+### 7.6 回填 shadow 结果到历史记录
+
+```bash
+python scripts/backfill_probability_shadow_history.py
+```
+
+作用：
+
+- 把 `shadow_prob_snapshot` 和 `probability_calibration` 回填到 [daily_records.json](/E:/web/PolyWeather/data/daily_records.json)
+
+### 7.7 生成线上 shadow 滚动报表
+
+```bash
+python scripts/build_probability_shadow_report.py
+```
+
+作用：
+
+- 生成 [shadow_report.json](/E:/web/PolyWeather/artifacts/probability_calibration/shadow_report.json)
+
+## 8. 推荐的一整套重训流程
+
+如果过了十天、半个月，想重新训练一次，建议按这个顺序执行：
+
+```bash
+python scripts/build_settlement_history_from_csv.py
+python scripts/export_probability_training_dataset.py
+python scripts/fit_probability_calibration.py
+python scripts/evaluate_probability_calibration.py
+python scripts/backfill_probability_shadow_history.py
+python scripts/build_probability_shadow_report.py
+```
+
+如果历史天气 CSV 还没补全，再先执行：
+
+```bash
+python scripts/backfill_historical_weather.py
+```
+
+## 9. 怎么判断这次训练有没有进步
+
+重训后，不要只看一个指标。
+
+至少看这 4 个：
+
+1. `CRPS`
+- 越低越好
+
+2. `MAE`
+- 越低越好
+- 至少不要明显变差
+
+3. `Bucket Hit Rate`
+- 越高越好
+- 这是业务上非常关键的指标
+
+4. `Bucket Brier`
+- 越低越好
+- 反映概率分布质量
+
+只有同时满足下面条件，才可以说训练效果真的进步：
+
+- `CRPS` 下降
+- `MAE` 不上升
+- `Bucket Hit Rate` 不下降
+- `Bucket Brier` 不上升
+
+## 10. 当前最重要的现实判断
+
+过去的“完整历史预测记录”通常没法完全补出来，除非：
+
+1. 你之前就存过
+2. 你接入了支持 forecast archive 的商业数据源
+
+所以现实里最重要的不是“把过去全补齐”，而是：
+
+- 从现在开始系统化归档
+- 每天稳定沉淀可训练样本
+- 定期离线重训
+
+## 11. 推荐的下一步
+
+最值得做的改造是：
+
+1. 新增 `probability_training_snapshots.jsonl`
+2. 每次分析时自动追加一条快照
+3. 当天结束后自动回填 `actual_high`
+4. 每 1-2 周重新训练一次
+
+## 12. 总结
+
+如果只记住一句话，就记这个：
+
+**EMOS 要想越训越好，关键不是多下载一点历史天气，而是持续保存“当时系统看到的预测快照”。**

docs/SUPABASE_SETUP_ZH.md

@@ -1,4 +1,4 @@
-# Supabase + 登录 + 支付接入说明（v1.4.0）
+# Supabase + 登录 + 支付接入说明（v1.5.1）
 
 最后更新：`2026-03-14`
 

docs/TAF_SIGNAL_ZH.md

@@ -0,0 +1,286 @@
+# PolyWeather TAF 信号说明（TAF_SIGNAL_ZH）
+
+本文档说明 PolyWeather 当前如何把 `TAF`（机场终端预报）接入“今日日内分析”，以及这些信号在交易判断里到底代表什么。
+
+本文档只描述**当前实现**，不夸大、不脑补。
+
+---
+
+## 一、TAF 在项目中的定位
+
+在 PolyWeather 里，`TAF` 不是主温度模型，也不是结算源。
+
+它的定位是：
+
+1. **机场侧确认层**
+   - 用来补充说明机场在峰值窗口附近会不会出现云、雨、雷暴或风向切换。
+
+2. **压温 / 扰动风险提示层**
+   - 用来判断“机场最高温是否可能因为天气扰动被压低”。
+
+3. **走势图时间轴联动层**
+   - 用来在温度走势图上标出 `FM / TEMPO / BECMG / PROB30/40` 对应的时段。
+
+它**不负责**：
+
+1. 直接提供多模型最高温数值
+2. 替代 `DEB`
+3. 替代机场实况 `METAR`
+4. 替代官方结算源
+
+---
+
+## 二、后端当前怎么解析 TAF
+
+后端入口在：
+
+- [web/analysis_service.py](/E:/web/PolyWeather/web/analysis_service.py)
+
+核心函数：
+
+- `_build_taf_signal(...)`
+
+当前会解析这些时间片：
+
+1. `BASE`
+2. `FM`
+3. `TEMPO`
+4. `BECMG`
+5. `PROB30`
+6. `PROB40`
+7. `PROB30 TEMPO`
+8. `PROB40 TEMPO`
+
+并且只聚焦于：
+
+- **峰值窗口前后**
+
+当前窗口定义是：
+
+- `peak.first_h - 2h`
+- 到
+- `peak.last_h + 1h`
+
+也就是说，TAF 不是整段报文全量平铺，而是会优先关注**和今天高温兑现最相关的时段**。
+
+---
+
+## 三、当前后端真正产出的核心字段
+
+### 1. `suppression_level`
+
+表示机场端的**压温风险等级**。
+
+当前逻辑来自：
+
+1. 降水 / 雷暴关键词
+   - `TSRA`
+   - `TS`
+   - `VCTS`
+   - `SHRA`
+   - `SHSN`
+   - `SHGS`
+   - `RA`
+   - `DZ`
+   - `SN`
+
+2. 低云底
+   - 只对 `BKN / OVC` 生效
+   - 如果最低云底 `<= 4000 ft`
+   - 会把原本 `low` 的压温风险至少抬到 `medium`
+
+注意：
+
+- 不是所有 `FEW / SCT / BKN / OVC` 都会直接把风险打到 `high`
+- 当前实现里，**低云主要是把风险从 `low` 抬到 `medium`**
+- 真正更容易触发 `high` 的，还是阵雨 / 雷暴类关键词
+
+### 2. `disruption_level`
+
+表示峰值窗口附近的**扰动程度**。
+
+当前逻辑：
+
+1. 这些时间片会至少把扰动抬到 `medium`
+   - `TEMPO`
+   - `BECMG`
+   - `PROB30`
+   - `PROB40`
+   - `PROB30 TEMPO`
+   - `PROB40 TEMPO`
+
+2. 这些情况会把扰动抬到 `high`
+   - `PROB30 TEMPO`
+   - `PROB40 TEMPO`
+   - 或者该时段本身就出现强降水/雷暴类关键词
+
+注意：
+
+- **`TEMPO` 本身不等于 `high`**
+- **`PROB40` 也不等于“确定发生”**
+
+---
+
+## 四、前端怎么展示
+
+前端主要在：
+
+- [frontend/components/dashboard/FutureForecastModal.tsx](/E:/web/PolyWeather/frontend/components/dashboard/FutureForecastModal.tsx)
+- [frontend/lib/dashboard-utils.ts](/E:/web/PolyWeather/frontend/lib/dashboard-utils.ts)
+
+当前会通过三种方式展示 TAF：
+
+### 1. 图表时间轴标记
+
+在日内温度走势图上，当前会显示：
+
+- `TAF 时段 / TAF Timing`
+
+tooltip 会显示该时段摘要，例如：
+
+- `基础时段 13:00-19:00 以稳定为主`
+- `明确切换 15:00-21:00 以稳定为主`
+- `临时波动 14:00-17:00 有云雨扰动`
+
+### 2. 今日日内结构信号里的 `机场预报`
+
+会显示类似：
+
+- `防压温`
+- `看云雨`
+- `暂稳`
+
+### 3. 顶部摘要与交易动作
+
+系统会把：
+
+1. 近地面结构
+2. 高空结构
+3. `TAF`
+4. `market_signal / edge_percent / bucket crowding`
+
+合并成更贴近交易的提示，例如：
+
+- `偏暖侧`
+- `偏谨慎`
+- `先观察`
+
+---
+
+## 五、TAF 关键词当前在项目里的真实含义
+
+| TAF 关键词 | 当前展示词 | 当前项目含义 |
+| :-- | :-- | :-- |
+| `BASE` | 基础时段 | 在第一个显式变化组出现前的默认背景天气段 |
+| `FM` | 明确切换 | 从某个明确时刻开始，机场预报进入一套新的天气阶段 |
+| `TEMPO` | 临时波动 | 一段短时、非整段主导的扰动窗口 |
+| `BECMG` | 逐步转变 | 天气在该窗口内逐步过渡，不是立刻硬切 |
+| `PROB30/40` | 30% / 40% 风险窗 | 有概率触发的扰动窗口，不等于确定发生 |
+
+注意：
+
+- `FM` 不是由 `valid_match` 触发，它是按 `FMddhhmm` 独立解析出来的明确切换段
+- `PROB40` 不是“确定性信号”，仍然只是概率窗口
+
+---
+
+## 六、怎么理解“机场端压温风险偏高”
+
+这句话的意思不是：
+
+- 城区一定更冷
+- 一定会结算更低
+
+真正意思是：
+
+**在机场这个结算相关站点上，峰值窗口附近更容易因为云、阵雨或雷暴，导致最终最高温冲不上去。**
+
+对于很多按机场报文或机场相关站点结算的市场，这一点很关键。
+
+一句话：
+
+- `TAF` 提示压温高
+- 不代表一定下雨
+- 但代表“机场高温可能被压低”的概率更值得防
+
+---
+
+## 七、怎么和图表一起看
+
+### 情况 A：模型还偏热，但 TAF 给出压温高
+
+这表示：
+
+1. 数值模型仍给出较高高温
+2. 但机场端预报提示云雨/雷暴会打断峰值兑现
+
+这种情况下，更适合理解成：
+
+- **机场侧高温兑现有风险**
+- 追更高温区间要谨慎
+
+### 情况 B：TAF 没有新增压温，但总判断仍偏降温
+
+这表示：
+
+1. `TAF` 没有提供新的云雨压温利空
+2. 但近地面窗口本身已经在走弱
+
+比如：
+
+- 温度走弱
+- 风场切换
+- 气压回升
+- 露点回落
+
+所以：
+
+- `TAF 无压温`
+- **不等于**
+- `一定继续升温`
+
+当前系统已经会在摘要里把这层关系解释清楚。
+
+---
+
+## 八、当前实现边界
+
+这套 `TAF` 逻辑当前是**交易导向的轻量解码**，不是完整航空专业解码器。
+
+当前做得到：
+
+1. 识别主要时间片
+2. 找出峰值窗口附近的扰动
+3. 识别云雨压温和风向切换
+4. 联动图表时间轴
+5. 联动交易动作
+
+当前还没有做：
+
+1. 对全部 TAF 语法做完整航空级严格解释
+2. 对每个时段都做完整的逐字段人工预报学解释
+3. 把 TAF 当成温度主预测模型
+
+---
+
+## 九、产品口径总结
+
+最重要的一句：
+
+**在 PolyWeather 里，TAF 是“机场侧扰动确认层”，不是主模型，也不是结算源。**
+
+它最值钱的地方是：
+
+- 帮你判断峰值窗口附近，机场高温会不会被云雨、雷暴、低云或风向切换打断。
+
+对交易来说，更适合把它理解成：
+
+- “机场这边有没有额外的压温风险”
+
+而不是：
+
+- “TAF 直接告诉我今天结算温度是多少”
+
+---
+
+_PolyWeather 文档中心_

docs/TECH_DEBT.md

@@ -1,62 +1,71 @@
-# 技术债与工程待办（v1.4.0）
+# 技术债与工程待办（v1.5.1）
 
-最后更新：`2026-03-14`
+最后更新：`2026-03-31`
 
-目标：在收费上线后，优先保证支付可靠性、权限一致性和运营可追溯性。
+目标：在收费上线后，优先保证状态一致性、支付可靠性、可观测性和概率引擎发布可控。
 
 ## 1. 债务快照
 
-当前估计：**93% 稳定 / 7% 技术债**。
+当前估计：**95% 稳定 / 5% 技术债**。
 
 ```mermaid
 flowchart TD
     A["技术债"]
 
     subgraph P["支付与订阅"]
-        P1["异常交易自动重放策略"]
+        P1["合约 V2 升级（SafeERC20 / Pausable）"]
         P2["退款与工单流程"]
-        P3["多链结算对账"]
+        P3["多 RPC 与链上对账面板"]
     end
 
     subgraph E["权限与运营"]
         E1["前后端/Bot 权限矩阵回归"]
-        E2["积分与订阅冲突策略"]
+        E2["积分来源明细与补分审计"]
     end
 
     subgraph O["可观测性"]
-        O1["支付失败原因分层指标"]
+        O1["外部监控抓取与告警阈值"]
         O2["业务监控看板"]
     end
 
+    subgraph S["状态与概率"]
+        S1["EMOS shadow -> primary 门禁稳定化"]
+    end
+
     A --> P
     A --> E
     A --> O
+    A --> S
 ```
 
 ## 2. 近期已关闭
 
-- P1 支付主链路已上线（intent -> submit -> confirm）。
+- 支付主链路已上线（intent -> submit -> confirm）。
 - 支付自动补单已上线（Event Loop + Confirm Loop）。
+- 支付事件重放脚本已补齐。
+- 支付运行态 API 与 SQLite 审计事件已补齐。
 - 钱包绑定支持浏览器钱包 + WalletConnect。
 - 账户中心与 Pro 权限展示链路打通。
 - 钱包异动支持独立频道路由。
+- 运行态状态/缓存与核心离线训练、评估、回填链路已完成 SQLite 主路径收口。
+- 轻量可观测性已上线（`/healthz`、`/api/system/status`、`/metrics`）。
+- EMOS/CRPS 校准链路已上线 shadow 模式。
 
 ## 3. 高优先级技术债
 
 | 项目 | 影响 | 建议动作 |
 | :-- | :-- | :-- |
-| 支付异常重放策略标准化 | 偶发确认失败需人工介入 | 建立 tx hash 自动回放 + 降级路径 |
+| EMOS 上线门禁 | 当前 `hold`，不能切 primary | 继续积累样本，重点压 `bucket_brier` |
+| 外部监控与告警 | 只有轻量指标，无外部抓取 | 接 Prometheus/Grafana 或最小巡检 |
 | 退款与售后链路 | 商业闭环不完整 | 增加退款状态机与工单系统 |
-| 订阅审计可视化 | 排障效率受限 | 建立订阅事件时间线视图 |
-| 多邮箱绑定同 TG 账户策略 | 积分归属易混淆 | 引入主账号绑定策略与迁移工具 |
 
 ## 4. 中优先级技术债
 
 | 项目 | 影响 | 建议动作 |
 | :-- | :-- | :-- |
-| 积分发放可解释性 | 用户理解成本高 | 输出积分来源明细（发言/签到/奖励） |
+| 积分发放可解释性 | 用户理解成本高 | 输出积分来源明细（发言/奖励/手动补分） |
+| 支付合约 V2 升级 | 当前仍是最小可用合约 | 升级到 SafeERC20 + Pausable + plan 绑定 |
 | 支付失败文案标准化 | 转化率受影响 | 建立错误码 -> 文案映射表 |
-| 配置收敛 | 运维出错概率高 | 将支付/推送配置集中分组管理 |
 
 ## 5. 低优先级技术债
 
@@ -67,7 +76,6 @@ flowchart TD
 
 ## 6. 下阶段里程碑
 
-1. 完成支付异常自动重放与告警分层。
-2. 上线退款/售后后台最小版。
-3. 建立商业化运营看板（支付、续费、留存）。
-4. 完成权限矩阵自动化回归测试。
+1. 稳定 EMOS shadow，达到 rollout `observe/promote` 条件。
+2. 补外部监控抓取与告警阈值。
+3. 评估并推进支付合约 V2 升级。

docs/TECH_DEBT_ZH.md

@@ -1,62 +1,71 @@
-# 技术债与工程待办（v1.4.0）
+# 技术债与工程待办（v1.5.1）
 
-最后更新：`2026-03-14`
+最后更新：`2026-03-31`
 
-目标：在收费上线后，优先保证支付可靠性、权限一致性和运营可追溯性。
+目标：在收费上线后，优先保证状态一致性、支付可靠性、可观测性和概率引擎发布可控。
 
 ## 1. 债务快照
 
-当前估计：**93% 稳定 / 7% 技术债**。
+当前估计：**95% 稳定 / 5% 技术债**。
 
 ```mermaid
 flowchart TD
     A["技术债"]
 
     subgraph P["支付与订阅"]
-        P1["异常交易自动重放策略"]
+        P1["合约 V2 升级（SafeERC20 / Pausable）"]
         P2["退款与工单流程"]
-        P3["多链结算对账"]
+        P3["多 RPC 与链上对账面板"]
     end
 
     subgraph E["权限与运营"]
         E1["前后端/Bot 权限矩阵回归"]
-        E2["积分与订阅冲突策略"]
+        E2["积分来源明细与补分审计"]
     end
 
     subgraph O["可观测性"]
-        O1["支付失败原因分层指标"]
+        O1["外部监控抓取与告警阈值"]
         O2["业务监控看板"]
     end
 
+    subgraph S["状态与概率"]
+        S1["EMOS shadow -> primary 门禁稳定化"]
+    end
+
     A --> P
     A --> E
     A --> O
+    A --> S
 ```
 
 ## 2. 近期已关闭
 
-- P1 支付主链路已上线（intent -> submit -> confirm）。
+- 支付主链路已上线（intent -> submit -> confirm）。
 - 支付自动补单已上线（Event Loop + Confirm Loop）。
+- 支付事件重放脚本已补齐。
+- 支付运行态 API 与 SQLite 审计事件已补齐。
 - 钱包绑定支持浏览器钱包 + WalletConnect。
 - 账户中心与 Pro 权限展示链路打通。
 - 钱包异动支持独立频道路由。
+- 运行态状态/缓存与核心离线训练、评估、回填链路已完成 SQLite 主路径收口。
+- 轻量可观测性已上线（`/healthz`、`/api/system/status`、`/metrics`）。
+- EMOS/CRPS 校准链路已上线 shadow 模式。
 
 ## 3. 高优先级技术债
 
 | 项目 | 影响 | 建议动作 |
 | :-- | :-- | :-- |
-| 支付异常重放策略标准化 | 偶发确认失败需人工介入 | 建立 tx hash 自动回放 + 降级路径 |
+| EMOS 上线门禁 | 当前 `hold`，不能切 primary | 继续积累样本，重点压 `bucket_brier` |
+| 外部监控与告警 | 只有轻量指标，无外部抓取 | 接 Prometheus/Grafana 或最小巡检 |
 | 退款与售后链路 | 商业闭环不完整 | 增加退款状态机与工单系统 |
-| 订阅审计可视化 | 排障效率受限 | 建立订阅事件时间线视图 |
-| 多邮箱绑定同 TG 账户策略 | 积分归属易混淆 | 引入主账号绑定策略与迁移工具 |
 
 ## 4. 中优先级技术债
 
 | 项目 | 影响 | 建议动作 |
 | :-- | :-- | :-- |
-| 积分发放可解释性 | 用户理解成本高 | 输出积分来源明细（发言/签到/奖励） |
+| 积分发放可解释性 | 用户理解成本高 | 输出积分来源明细（发言/奖励/手动补分） |
+| 支付合约 V2 升级 | 当前仍是最小可用合约 | 升级到 SafeERC20 + Pausable + plan 绑定 |
 | 支付失败文案标准化 | 转化率受影响 | 建立错误码 -> 文案映射表 |
-| 配置收敛 | 运维出错概率高 | 将支付/推送配置集中分组管理 |
 
 ## 5. 低优先级技术债
 
@@ -67,7 +76,6 @@ flowchart TD
 
 ## 6. 下阶段里程碑
 
-1. 完成支付异常自动重放与告警分层。
-2. 上线退款/售后后台最小版。
-3. 建立商业化运营看板（支付、续费、留存）。
-4. 完成权限矩阵自动化回归测试。
+1. 稳定 EMOS shadow，达到 rollout `observe/promote` 条件。
+2. 补外部监控抓取与告警阈值。
+3. 评估并推进支付合约 V2 升级。

docs/deep-research-report.md

@@ -2,23 +2,23 @@
 
 ## 执行摘要
 
-PolyWeather（仓库：`yangyuan-zhen/PolyWeather`）定位为**面向温度类结算预测市场（如 Polymarket 的温度结算合约）**的“生产级气象情报系统”，核心在于把多源天气观测/预报转化为**结算导向的概率桶（μ + bucket distribution）**，并进一步映射到市场报价完成**错价扫描**；同时提供 Web 仪表盘与 Telegram Bot 两套交互入口，并包含 Polygon 链上 USDC/USDC.e 支付、自动补单与订阅/积分体系。项目 README 明确其“Open-Core”边界：仓库公开天气聚合、基础分析、看板、Bot、标准支付流程；生产私有部分包含商业风控、阈值与运营工具等。
-从工程实现看，当前版本（README 标注 `v1.4.0`，最后更新 `2026-03-14`）已经落地关键业务闭环：多源天气采集（Open-Meteo、AviationWeather METAR、土耳其 MGM、香港 HKO、台湾 CWA、美国 NWS 等）、DEB 动态融合、趋势/概率引擎、Polymarket 只读行情层、前端缓存策略（ETag/304、force_refresh no-store）、以及支付事件监听与确认循环。
-但它也暴露出典型的“从快速迭代走向稳态生产”的结构性问题：核心模块（如 `src/data_collection/weather_sources.py`、`web/app.py`）体量巨大、职责耦合；配置/依赖/可复现性仍偏脚本化；测试覆盖存在但 CI/CD 缺失；多处自定义缓存与状态文件并发一致性风险；以及对第三方 API（Open-Meteo、AviationWeather、Supabase、Polymarket）在**配额、变更、SLA、合规**方面需要更系统的治理。
-本报告给出的改进方向按收益/风险/工作量分级，优先建议聚焦三条主线：
-第一，**模块化与工程化**：将采集/分析/市场层/支付/鉴权拆成清晰边界，补齐 CI、测试、类型与规范化配置；第二，**可观测性与可靠性**：统一缓存与状态管理、增加限流与退避策略、建立指标与告警；第三，**模型与评测体系**：围绕“结算命中率 + 偏差（MAE/RMSE）+ 概率校准（Brier/CRPS）+ 错价信号有效性（Edge/PnL 模拟）”建立基准与回归测试，并可在合规前提下评估引入更先进的气象后处理（如 EMOS）或外部 AI 预报（GraphCast/FourCastNet/Pangu-Weather 的商业许可限制需特别注意）。
+PolyWeather（仓库：`yangyuan-zhen/PolyWeather`）定位为**面向温度类结算预测市场（如 Polymarket 的温度结算合约）**的“生产级气象情报系统”，核心在于把多源天气观测/预报转化为**结算导向的概率桶（μ + bucket distribution）**，并进一步映射到市场报价完成**错价扫描**；同时提供 Web 仪表盘与 Telegram Bot 两套交互入口，并包含 Polygon 链上 USDC/USDC.e 支付、自动补单与订阅/积分体系。项目 README 现明确仓库代码采用 `AGPL-3.0-only`，同时将品牌、商标、生产私有数据与运营阈值保留在代码许可证之外。
+从工程实现看，截至 `2026-04-03`，项目已经完成一轮更明确的工程化收口：多源天气采集仍保持现有业务能力，同时已完成采集层与 Web API 大文件拆分、CI 质量门禁、配置分级（`.env.example` / `.env.secrets.example` / 中文部署文档）、EMOS/CRPS 校准链路、运行态状态与缓存迁移到 SQLite 主路径，以及最小外部监控链路（`/healthz`、`/api/system/status`、`/metrics` + Prometheus + Alertmanager + Grafana + Telegram relay）。除此之外，项目还补上了**历史真值治理**：`daily_records` 继续只保留近 14 天运行态缓存，但新增了永久真值表、真值 revision 审计表和长期训练特征表，并开始把监督真值与训练特征从“短期缓存”正式拆到“长期可追溯存储”。
+这意味着报告里最初最突出的“工程地基缺失”问题，已经有一部分被关闭：`src/data_collection/weather_sources.py` 与 `web/app.py` 不再是原来的超大单文件；GitHub Actions 已覆盖 Python、前端和 Docker build；配置与密钥治理已成体系；运行态状态不再只能依赖 JSON/JSONL 文件；EMOS 也不再只是概念，而是进入了可训练、可评估、可 shadow、可门禁判断的阶段；更重要的是，监督真值与训练特征不再只能附着在 14 天运行态缓存上。
+但项目仍处在“从可用走向稳态”的中段，而不是终局。当前真正的高优先级问题已进一步收敛：**EMOS 仍未达到生产切换标准**，当前门禁结论明确为 `hold`，阻塞原因是 shadow bucket brier 明显退化，同时历史长期特征仍处在“刚开始积累”的阶段。SQLite 迁移方面，运行态主读切换和核心离线训练/回填链路已经完成验收：在移除 `data/*.json` / `data/*.jsonl` 后，训练、评估、shadow report 与关键 backfill 脚本仍可仅依赖运行时数据库正常执行；当前保留的 legacy 文件路径主要用于迁移、导出、校验和显式回退输入。历史真值治理方面，新增的永久真值表、revision 审计表与长期训练特征表已经落地，`Taipei` / `Shenzhen` 的 `Wunderground` 历史回填也已接通，因此当前缺口已从“历史真值是否会继续丢失”转为“历史特征是否能持续增长并支撑 EMOS/LGBM 评估”。可观测性方面，最小外部监控链路已经补齐：Prometheus 抓取、Alertmanager 规则、Grafana 面板、Telegram 告警 relay 与巡检脚本均已落地；当前剩余缺口已从“有没有外部监控”转为“监控覆盖深度是否足够”，例如节点级资源、数据库体积趋势、支付细粒度指标、按城市/来源拆分的业务 SLA。支付链路方面，链下审计与容灾已明显增强：事件重放、SQLite 审计事件、RPC 多节点容灾、合约静态检查、`/ops` 支付异常单都已补齐；当前剩余风险主要集中在**链上合约本身仍是最小实现**，尚未升级到 SafeERC20、Pausable、链上套餐绑定等更强防护版本。
+因此，当前阶段最正确的策略已经不是继续做“大范围基础重构”，而是围绕**EMOS 上线门禁稳定化、长期训练特征持续积累、监控覆盖深挖、支付合约防护升级**这四条线持续收口。短中期内更高 ROI 的方向依然不是引入新的大模型，而是把现有“采集→后处理→市场映射→支付/订阅”的链路做成**状态一致、指标可见、发布可控、回退明确**的生产平台。
 ## 项目概览
 
 PolyWeather 的目标与范围在 README/README_ZH 中定义得较清楚：为温度结算市场提供气象情报（多源采集→融合→概率→对照市场报价），并提供“官方看板（Vercel 前端）+ VPS 后端 + Telegram Bot”。
 项目主功能可归纳为四层：
-**天气层（数据源/采集）**：聚合 20 个城市的实测与预报；支持 AviationWeather METAR（机场观测）、土耳其 MGM 站网、Open-Meteo（含多模型与集合预报）、美国 NWS（仅美国城市）、以及部分城市使用官方结算源（香港 HKO、台北 CWA）等。
+**天气层（数据源/采集）**：聚合 39 个城市的实测与预报；支持 AviationWeather METAR（机场观测）、土耳其 MGM 站网、Open-Meteo（含多模型与集合预报）、美国 NWS（仅美国城市）、以及部分城市使用官方结算源（香港 HKO、台北 RCSS/Wunderground、深圳 ZGSZ/Wunderground）等。
 **分析层（DEB/趋势/概率/结算口径）**：
-DEB（Dynamic Error Balancing）基于过去 N 天模型误差（MAE）倒数加权，输出融合预报；同时维护 `daily_records.json` 做历史对账、命中率/MAE 统计，并支持基于 WU（Weather Underground 口径）四舍五入的结算命中评估。
+DEB（Dynamic Error Balancing）基于过去 N 天模型误差（MAE）倒数加权，输出融合预报；运行态仍维护近 14 天 `daily_records` 缓存做当前对账，但长期监督真值与训练特征已经迁到 SQLite 永久表中，并支持基于 WU（Weather Underground 口径）四舍五入的结算命中评估。
 趋势/概率引擎在 `trend_engine.py` 中实现：综合“集合预报区间→σ/μ→高温窗口→死盘判定→温度桶概率分布→边界提示”等，用于 bot 展示与 web 结构化数据输出。
 **市场层（Polymarket 行情对照）**：只读模式从 Gamma API 发现市场、从 CLOB（`py-clob-client` 或 REST 回退）读取价格/盘口并计算 edge（模型概率 − 市场概率）生成信号标签。
 **商业化与支付**：订阅（`Pro Monthly 5 USDC`）、积分抵扣、Polygon 链上收款合约（USDC/USDC.e），并提供“事件监听 + 周期确认”的自动补单机制。
 **支持的数据集/数据源**：项目不是传统“训练数据集+模型训练”的机器学习仓库；其“数据集”本质是外部实时/预报 API 与站点观测数据。对外部数据的使用需要遵守来源方的访问与速率限制，例如 AviationWeather Data API 明确限制请求频率（含每分钟请求上限/建议降低频率与使用缓存文件）。
-**许可证**：仓库根目录 `LICENSE` 为 MIT。 同时 README 强调 Open-Core 策略与生产私有组件边界，意味着“可复现/可审计”的范围以公开部分为准。
+**许可证**：仓库根目录 `LICENSE` 当前为 `AGPL-3.0-only`。同时 README 与策略文档明确：品牌、商标、生产私有数据与运营策略不随代码许可证一并授权。
 （插图：项目 README 中包含产品截图，可用于快速理解信息架构与 UI 形态） 
 ![PolyWeather demo map](https://raw.githubusercontent.com/yangyuan-zhen/PolyWeather/main/docs/images/demo_map.png)
 
@@ -30,13 +30,15 @@ DEB（Dynamic Error Balancing）基于过去 N 天模型误差（MAE）倒数加
 | 层级 | 目录/文件 | 角色定位 | 关键说明 |
 | ------------- | ------------------------------------------------------------------------ | ------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | 运行时组件 | `frontend/` | Next.js 前端（Vercel） | 前端重构报告提到 App Router、Route Handlers（BFF）、缓存策略、支付与账户中心等。 |
-| 运行时组件 | `web/app.py` | FastAPI 后端 API | 作为前端 BFF 与 Telegram Bot 的共同 API。 |
+| 运行时组件 | `web/app.py` + `web/core.py` + `web/routes.py` + `web/analysis_service.py` | FastAPI 后端 API | 已从单文件入口拆为启动入口、核心上下文、路由层、分析服务层。 |
 | 运行时组件 | `bot_listener.py` + `src/bot/*` | Telegram Bot | 入口 `bot_listener.py` 调 `start_bot()`，并由 `StartupCoordinator` 启动多个后台 loop。 |
-| Python 域模块 | `src/data_collection/*` | 天气采集 + 城市注册 + 市场读取 | `WeatherDataCollector`、`CITY_REGISTRY`、`PolymarketReadOnlyLayer` 等。 |
+| Python 域模块 | `src/data_collection/*` | 天气采集 + 城市注册 + 市场读取 | 采集层已拆为 `weather_sources.py` 编排层 + `open_meteo_cache.py`、`settlement_sources.py`、`metar_sources.py`、`mgm_sources.py`、`nws_open_meteo_sources.py`。 |
 | Python 域模块 | `src/analysis/*` | DEB/趋势/概率/结算口径 | `deb_algorithm.py`、`trend_engine.py`、`settlement_rounding.py`。 |
-| Python 域模块 | `src/payments/*` + `contracts/*` | 支付合约 + 事件监听/补单 | Solidity 合约 + Python 侧事件扫描与确认循环。 |
+| Python 域模块 | `src/analysis/probability_calibration.py` + `src/analysis/probability_rollout.py` | 概率校准与上线门禁 | 已支持 `legacy / emos_shadow / emos_primary`，并可产出 rollout 判断。 |
+| Python 域模块 | `src/payments/*` + `contracts/*` | 支付合约 + 事件监听/补单 | Solidity 合约 + Python 侧事件扫描/确认循环 + SQLite 审计事件 + RPC 多节点容灾 + 合约静态检查。 |
 | Python 域模块 | `src/auth/*`、`docs/SUPABASE_SETUP_ZH.md`、`scripts/supabase/schema.sql` | Supabase 鉴权/订阅/积分 | 使用 `/auth/v1/user` 校验 JWT、`/rest/v1/subscriptions` 查订阅（服务端角色 key 必须保密）。 |
-| 工程与运维 | `docker-compose.yml`、`Dockerfile`、`update.sh`、`scripts/*` | 部署/验证脚本 | Compose 启两个容器（bot 与 web），脚本校验 ETag/缓存、更新重启等。 |
+| Python 域模块 | `src/database/runtime_state.py` | 运行态状态、永久真值与训练特征仓储 | 已接入 `daily_records`、`telegram_alert_state`、`probability_training_snapshots`、`open_meteo` 持久缓存，并新增永久真值表、真值修订审计表、长期训练特征表。 |
+| 工程与运维 | `docker-compose.yml`、`Dockerfile`、`.github/workflows/ci.yml`、`scripts/*` | 部署/验证脚本 | 现已具备 CI 门禁、迁移脚本、状态校验脚本、配置校验脚本与 rollout 报告脚本。 |
 
 ### 参考架构与关键工作流
 
@@ -55,8 +57,9 @@ flowchart TB
  subgraph Data
  WX[WeatherDataCollector]
  CITY[CITY_REGISTRY]
- HIST[daily_records.json<br/>DEB history]
- CACHE[open_meteo_cache.json<br/>disk cache]
+ HIST[(SQLite runtime state<br/>daily_records / cache / snapshots)]
+TRUTH[(SQLite truth tables<br/>truth_records / revisions / features)]
+JSON[Legacy JSON files<br/>migration/export/explicit fallback only]
  end
 
  subgraph ExternalAPIs
@@ -99,8 +102,11 @@ flowchart TB
  CF --> RPC
  RPC --> SOL
 
- WX --> CACHE
+ WX --> HIST
+ WX --> TRUTH
+ WX --> JSON
  FAST --> HIST
+ FAST --> TRUTH
  WX --> CITY
 ```
 
@@ -118,13 +124,13 @@ flowchart TB
 **概率引擎**：`trend_engine.py` 以集合预报的 p10/p90 推 σ（并考虑历史 MAE floor、风向/云量/压强的 shock_score、以及峰值窗口 time-decay），再用正态近似把连续分布映射为 WU 整数“温度桶概率”。
 **推理流水线（在线）**：
 Web/Telegram 请求 → FastAPI 调用采集器抓取/复用缓存 → 分析引擎输出结构化结果（μ、概率桶、趋势、死盘/窗口判定、DEB 预测、市场扫描）→ 前端渲染或 bot 消息格式化。
-**检查点（checkpoints）**：传统 ML checkpoint 不适用；但项目存在两类“业务状态 checkpoint”：
-`daily_records.json`（DEB 历史与评测快照）与 `open_meteo_cache.json`（Open-Meteo 预报磁盘缓存）。
+**检查点（checkpoints）**：传统 ML checkpoint 不适用；但项目现已形成两类“业务状态 checkpoint”：
+（a）SQLite 运行态存储（当前线上与核心离线链路主路径）；（b）SQLite 永久真值/训练特征表（当前监督真值与训练样本长期主存）；（c）legacy JSON/JSONL 文件（主要保留给迁移回滚、导出比对与显式回退输入）。当前设计仍支持 `POLYWEATHER_STATE_STORAGE_MODE=file|dual|sqlite`，但对线上部署与离线训练/回填而言，推荐目标状态都已经是 `sqlite`。
 ### 测试、CI/CD 与运维验证
 
 **测试**：仓库存在 `tests/test_trend_engine.py`，覆盖 μ 计算、死盘判定、预报崩盘提示、趋势方向等核心逻辑（通过 patch 隔离外部依赖）。
-**CI/CD**：从仓库检索结果看，未发现公开的 GitHub Actions 工作流（`.github/workflows` 搜索为空），需要补齐自动化质量门禁。
-**运维验收**：提供 `scripts/validate_frontend_cache.sh` 校验 `/api/cities`、`/api/city/<city>/summary`、`/api/history/<city>` 的 ETag/Cache-Control，并对 `force_refresh` 期望 `no-store`。
+**CI/CD**：已补齐 GitHub Actions 工作流，至少覆盖 Python lint/test、前端 build、Docker build 三条门禁；当前缺口不再是“有没有 CI”，而是“是否已在 GitHub 分支保护中强制执行”。
+**运维验收**：除 `scripts/validate_frontend_cache.sh` 外，现已新增配置校验、运行态迁移/核验、EMOS rollout 判断等脚本，并提供 `/healthz`、`/api/system/status`、`/metrics` 作为基础观测入口。
 **部署/更新**：Compose 用于启动服务；另有 `update.sh` 通过 `pkill` + `nohup` 重启 bot 与 web。
 ## 优势与薄弱点
 
@@ -136,13 +142,16 @@ Web/Telegram 请求 → FastAPI 调用采集器抓取/复用缓存 → 分析引
 **支付侧有“事件监听 + 确认补单”的双通路**：支付链路天然存在“交易 pending / RPC 延迟 / 日志索引不完整”等问题，项目通过 event loop 与 confirm loop 双机制提升最终一致性。
 ### 薄弱点与风险
 
-**核心文件过大导致可维护性下降**：`WeatherDataCollector` 集“多源采集 + 缓存 + 限流 + 解析 + 部分业务逻辑（城市/单位/回退策略）”于一体，规模继续增长会显著提高回归风险与重构成本。 同类问题往往也会出现在“单文件 FastAPI 应用”形态（`web/app.py`）。
-**可复现性仍偏“脚本+隐式约定”**：
-虽然给了 Docker/Compose 快速启动，但缺少一份稳定的 `.env.example` / 配置 schema（哪些变量必需、默认值、敏感级别、环境分层），导致他人复现时容易踩坑；此外 `update.sh` 以 `pkill` 强杀进程方式更新，存在误杀与状态丢失风险，建议迁移到 systemd/容器滚动更新/健康检查。
-**测试存在但依赖与 CI 缺失**：有 pytest 单测文件，但 `requirements.txt` 未体现 dev 依赖与一键运行指令，且缺少 CI 自动运行，容易出现“本地能跑、线上漂移”。
+**核心文件过大问题已明显缓解，但边界仍需继续稳定**：`WeatherDataCollector` 与 `web/app.py` 的超大文件问题已完成第一阶段拆分；当前风险已从“文件过大”转为“跨模块兼容与边界稳定性”，例如旧调用路径、兼容导出、跨层 helper 仍需持续清理。
+**可复现性已从“缺模板”进入“模板与生产对齐”的阶段**：`.env.example`、`.env.secrets.example`、中文配置文档、前端部署文档、运行时配置校验器都已存在；当前风险主要在于线上历史 `.env` 与新模板并存、旧变量命名残留、以及密钥轮换与分层是否真正落实。
+**CI 已建立，但组织级质量门禁未必完全收口**：CI 现已覆盖 Python、前端与 Docker build。当前问题不再是“缺 CI”，而是是否把这些 status check 绑定到 `main` 保护策略，以及是否逐步引入更严格的 pre-merge 审查。
+**运行态状态/缓存与核心离线链路的 SQLite 收口已完成**：`daily_records`、`telegram_alert_state`、`probability_training_snapshots`、`open_meteo` 缓存已经支持并在生产中主读 SQLite，迁移/校验脚本可用；进一步地，在临时移除 `data/*.json` / `data/*.jsonl` 后，训练集导出、概率拟合、评估报告、shadow report 和关键 backfill 脚本已验证仍可运行。当前 legacy 文件路径主要是显式回退入口，而不再是默认主输入。
+**历史真值治理已从设计缺陷修复到可追溯运行**：`daily_records` 继续作为近 14 天运行态缓存，但已经不再承担长期监督真值职责；项目新增了永久真值表、真值 revision 审计表和长期训练特征表，并为 `Taipei` / `Shenzhen` 补上了 `Wunderground` 历史回填链路。当前风险已不再是“监督真值会不会继续被 14 天裁剪吞掉”，而是“历史长期特征能否持续积累到足够支撑 EMOS/LGBM 重新评估”。
 **第三方服务合规与稳定性风险**：
 项目强依赖外部 API（Open-Meteo、AviationWeather、NWS、HKO、CWA、Polymarket、Supabase）。其中 AviationWeather Data API 有明确速率限制；Polymarket 官方说明 Gamma/Data/CLOB 三套 API 分属不同域，CLOB 交易端点需鉴权且策略可能变化；Supabase 明确强调 `service_role`/secret keys 绝不可暴露。若缺乏集中治理（重试/退避/熔断/降级/配额监控/密钥轮换），稳定性与合规不可控。
-**许可证/商业使用的潜在冲突点**：仓库自身是 MIT，但如果未来尝试引入外部 AI 预报模型，需要非常谨慎：GraphCast 仓库代码 Apache-2.0，但权重使用 CC BY-NC-SA 4.0（非商业），Pangu-Weather 权重同样 BY-NC-SA 且明确禁止商业用途；不加区分地把这些模型用于付费产品会留下法律风险。
+**可观测性最小闭环已完成，但监控深度仍待加强**：项目现在已有 `/healthz`、`/api/system/status`、`/metrics`，并已补齐 Prometheus 抓取、Alertmanager 规则、Grafana 面板、Telegram relay 与巡检脚本。与此同时，`/ops` 已经逐步演进为后台管理台而不只是状态页：除支付、会员、用户与 EMOS 门禁外，还新增了训练数据治理卡片、城市覆盖矩阵，以及 `/ops/truth-history` 这种可直接查询 `actual_high / settlement_source / station_code / truth_version / updated_by / updated_at` 的真值表浏览页。当前缺口不再是“有没有外部监控”，而是节点级资源、数据库体积趋势、更细粒度支付指标、按城市/来源拆分的业务 SLA，以及是否需要进一步补 `truth revision` 明细页、趋势图和运营日报。
+**EMOS 已完成工程接入，但未完成生产发布**：EMOS/CRPS 校准、shadow 观测、rollout report、上线门禁都已实现；当前真实门禁结果为 `hold`，阻塞原因是 shadow bucket brier 明显退化。因此概率引擎标准化并非未做，而是“工程完成、发布未通过”。
+**许可证/商业使用的潜在冲突点**：仓库自身现为 `AGPL-3.0-only`，但如果未来尝试引入外部 AI 预报模型，仍需单独核验第三方代码与权重的商用条件：GraphCast 仓库代码 Apache-2.0，但权重使用 CC BY-NC-SA 4.0（非商业），Pangu-Weather 权重同样 BY-NC-SA 且明确禁止商业用途；不加区分地把这些模型用于付费产品会留下法律风险。
 ## 对标分析
 
 为满足“至少 3 个相似开源项目或近期论文”对标，本报告选择三类代表：
@@ -153,7 +162,7 @@ Web/Telegram 请求 → FastAPI 调用采集器抓取/复用缓存 → 分析引
 
 | 项目/论文 | 解决的问题 | 输出形态 | 性能/效果（公开描述） | 易用性与依赖 | 许可证要点 |
 | --------------------------------------------------------- | ---------------------------------------------------- | ------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
-| **PolyWeather**（本仓库） | 温度结算市场气象情报：多源→概率桶→错价扫描→订阅/支付 | 生产级应用（Web+Bot+API+支付） | 以工程能力为主；内置 DEB、概率桶、死盘判定、市场扫描；覆盖 20 城市。 | 主要依赖外部 API；Docker Compose 一键启动。 | 仓库 MIT；Open-Core（部分生产规则私有）。 |
+| **PolyWeather**（本仓库） | 温度结算市场气象情报：多源→概率桶→错价扫描→订阅/支付 | 生产级应用（Web+Bot+API+支付） | 以工程能力为主；内置 DEB、概率桶、死盘判定、市场扫描；当前覆盖 39 城市，并已补齐真值治理与后台运维视图。 | 主要依赖外部 API；Docker Compose 一键启动。 | 仓库 `AGPL-3.0-only`；品牌、生产私有数据与运营规则不随代码许可证授权。 |
 | **GraphCast**（google-deepmind/graphcast） | 10 天全球中期预报（ML 替代/增强 NWP） | 模型代码+权重+notebooks | 论文与介绍提到在大量指标上优于主流确定性系统；仓库提供预训练权重与示例数据入口，并提示 ERA5/HRES 数据条款需另行遵守。 | 完整训练需 ERA5 等；更适合科研/平台级推理，不是产品级 BFF。 | 代码 Apache-2.0；权重 CC BY-NC-SA 4.0（商业限制）。 |
 | **FourCastNet**（NVlabs/FourCastNet） | 高分辨率 data-driven 全球预报（AFNO/ViT） | 模型训练/推理代码+数据/权重链接 | README 描述：0.25° 分辨率、周尺度推理非常快，并可做大规模集合；适合平台型预报。 | 训练/数据依赖大（ERA5 子集 TB 级）；工程集成成本高。 | BSD 3-Clause（代码）。 |
 | **Pangu-Weather**（198808xc/Pangu-Weather + Nature 论文） | 3D Transformer 架构的中期全球预报 | ONNX 推理代码+预训练模型 | Nature 论文称在 reanalysis 上对比 IFS 有更强确定性预报表现，并强调速度优势；仓库提供 ONNX 推理与 lite 版训练说明。 | 模型文件大（多份 ~GB 级），训练资源需求高；更适合科研推理或内部平台。 | 权重 BY-NC-SA 4.0、明确禁止商业用途。 |
@@ -164,17 +173,15 @@ Web/Telegram 请求 → FastAPI 调用采集器抓取/复用缓存 → 分析引
 **对标结论**：PolyWeather 与这类“全球 AI 预报模型”不在同一层级：PolyWeather 是“面向结算市场的产品化情报系统”，其价值核心是**将预测转成可交易/可结算的决策信息**。短中期内更高 ROI 的方向不是“自训大模型”，而是把现有“采集+后处理+市场映射”的链路做成**可复现、可观测、可评测、可扩展**的工程平台；在许可合规前提下，再评估引入外部模型推理作为额外信号源。
 ## 优先级改进建议
 
-下表给出“高/中/低”优先级的具体改进清单，包含工作量估计、主要风险与可执行步骤（假设“无特定部署约束/性能指标约束”）。
+下表按截至 `2026-04-03` 的真实状态重排优先级。已完成项不再继续列为“待做”，只保留当前仍需推进的事项。
 | 优先级 | 改进项 | 预估工作量 | 主要收益 | 主要风险 | 可执行步骤（建议顺序） |
 | ------ | --------------------------------------------------------------------------------------------------------------------------------- | -------------------: | ------------------------------------------------------------------- | ------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| 高 | **拆分 `WeatherDataCollector` 为可插拔 Provider 架构**（OpenMeteoProvider / MetarProvider / NwsProvider / SettlementProvider 等） | 1–2 周 | 降低耦合、提高可测性，便于加入新城市/新源；减少回归面 | 重构期间线上行为漂移 | 1) 定义统一接口（输入：city/lat/lon/date；输出：标准 schema）→ 2) 把缓存/限流抽为中间层（decorator）→ 3) 用现有测试补齐 provider 单测 → 4) 灰度开启（仅部分城市走新链路） |
-| 高 | **拆分 `web/app.py`：路由层/服务层/DTO/依赖注入** | 1–2 周 | API 可维护性、鉴权/限流/缓存策略更清晰；更易做 OpenAPI 文档与版本化 | 改路由可能影响前端 | 1) 抽出 `services/analysis_service.py`、`services/market_service.py`、`services/payment_service.py` → 2) 引入 Pydantic models 作为响应 schema → 3) 保持 URL 不变，先做内部重构 |
-| 高 | **建立 CI（Python + Frontend）与质量门禁**：lint/format/typecheck/test/docker build | 3–5 天 | 防回归、提高贡献效率；让 `v1.4` 之后迭代更稳 | 初期会暴露大量历史问题 | 1) Python：ruff + mypy + pytest；Node：eslint + typecheck + build → 2) GitHub Actions 两条 pipeline → 3) 给出“允许失败→逐步收紧”的迁移策略 |
-| 高 | **补齐可复现配置与密钥分级**：`.env.example` + 配置文档 + 敏感项隔离 | 2–4 天 | 新环境搭建更快、减少误配置；降低密钥泄露风险 | 需要梳理现有 env 变量 | 1) 盘点 env（Open-Meteo、Polymarket、Supabase、RPC、支付等）→ 2) `.env.example` 提供默认与说明 → 3) 标注敏感等级（尤其 `SUPABASE_SERVICE_ROLE_KEY`）并禁止前端/日志输出 |
-| 高 | **统一“状态与缓存”方案**：把 JSON 文件状态迁移到 SQLite/Postgres/Redis（至少做到原子/锁一致） | 1–2 周 | 降低并发一致性 bug（多进程/多容器）、便于观测与回放 | 迁移会引入数据兼容与历史清理问题 | 1) 为 `daily_records` 与 `open_meteo_cache` 定义表结构 → 2) 先实现写入双写（JSON+DB）→ 3) 校验一致后切换读取 → 4) 下线 JSON 文件 |
+| 高 | **稳定 EMOS shadow 并收紧上线门禁** | 1–2 周 | 让概率引擎升级具备明确发布条件，避免拍脑袋切换 | 当前 shadow bucket brier 退化明显，存在误上线风险 | 1) 持续积累 snapshot 样本 → 2) 定期重训与生成 `evaluation_report` / `shadow_report` / `rollout_report` → 3) 重点压 `bucket_brier` 退化 → 4) 只有门禁从 `hold` 进入 `observe/promote` 后才考虑上线 |
+| 高 | **持续积累长期训练特征，验证 SQLite 真值治理后的样本增长** | 1–2 周 | 让 EMOS/LGBM 的重训真正建立在长期可信样本上，而不是继续被短期特征缺口卡住 | 当前真值已长期化，但历史长期特征仍偏少，EMOS/LGBM 样本增长会滞后 | 1) 持续写入 `training_feature_records_store` → 2) 每日检查 `/ops` 训练数据与 `/ops/truth-history` → 3) 定期对 `Taipei` / `Shenzhen` 的 Wunderground 回填做抽查 → 4) 观察样本是否自然增长后再重训 |
+| 中 | **把最小外部监控继续补深**：从“可告警”提升到“可运营” | 3–7 天 | 不再只知道服务坏没坏，还能看资源趋势、来源 SLA 和支付波动 | 指标过多会带来维护噪音 | 1) 增加节点 CPU/内存/磁盘 → 2) 增加 SQLite/支付体积与事件趋势 → 3) 把 HTTP/来源指标细分到城市/来源维度 → 4) 增加日报或异常摘要 |
 | 中 | **市场层升级为 async + 类型安全**：引入 `aiopolymarket` 或在现有层加重试/backoff/连接池 | 4–7 天 | 行情层更稳，减少短时网络抖动；更易扩展更多市场/分页 | 依赖升级带来的行为差异 | 1) 把 requests.Session 替换为 aiohttp/httpx → 2) 在 Gamma/CLOB 调用侧实现指数退避 → 3) 引入 typed models，减少解析失败 |
-| 中 | **概率引擎更标准化：引入 EMOS/CRPS 拟合做校准**（替换/增强当前正态近似与规则 σ） | 1–2 周 | 概率输出更可解释、可校准；适合做长期回归评测 | 需要足够历史样本；可能改变用户体验 | 1) 以 `daily_records` 为训练集（模型预报均值/方差→实际）→ 2) 先离线拟合并与现模型对比 → 3) 线上 shadow 输出（不影响主显示）→ 4) 达标后切换 |
-| 中 | **支付合约/链上交互加强审计与防护**：事件重放、重入/授权边界、RPC 多节点容灾 | 1 周 | 提升资金链路可信度；减少链上卡单 | 合约升级需要迁移/再验证 | 1) 为 event loop 增加“最后处理区块高度”持久化与重放工具 → 2) RPC 端支持多 URL fallback → 3) 合约侧考虑 OpenZeppelin Ownable/SafeERC20（如升级）并更新验证流程 |
+| 中 | **支付合约从“最小可用”升级到“更强合约防护”** | 1–2 周 | 在已完成的链下审计与容灾之上，进一步收紧链上授权边界 | 合约升级需要重新部署、迁移配置并再次验证 | 1) 维持现有事件重放、SQLite 审计、多 RPC fallback → 2) 升级合约到 SafeERC20 + Pausable → 3) 评估链上 plan/amount/token 绑定或 EIP-712 签名校验 → 4) 迁移后更新 PolygonScan 验证与支付审计文档 |
+| 中 | **将 CI 与分支保护/发布流程真正绑定** | 1–3 天 | 让现有 CI 从“存在”变成“强制门禁” | 历史分支/热修流程可能受影响 | 1) GitHub `main` 开启 required checks → 2) 把 release/tag 流程绑定 CI → 3) 明确热修例外流程 |
 | 低 | **引入外部 AI 预报模型作为附加信号**（GraphCast/FourCastNet/Pangu-Weather 等） | 2–6 周（取决于范围） | 可能提升极端/中期预测能力与差异化 | **商业许可限制**（多为 CC BY-NC-SA/禁止商业）与算力成本 | 1) 先做合规评审（权重许可/数据条款）→ 2) 仅在研究/非商业环境评估 → 3) 若要商用，优先选择可商用权重或自研/购买授权 |
 
 ### 文档、测试与贡献流程的具体补强建议（落到仓库层面）
@@ -190,8 +197,8 @@ PolyWeather 的评测应围绕“结算场景”而非传统数值天气预报
 ### 气象预测与概率校准基准
 
 **数据集**（建议从现有生产数据演进） 
-1）`daily_records.json` 的历史快照：已包含多模型预报、`actual_high`、`deb_prediction`、`mu` 与概率快照字段，天然可转成评测数据（建议迁移到 DB 后做版本化导出）。
-2）观测“真值”统一口径：对 METAR 城市用 AviationWeather Data API；对香港/台北等按结算源（HKO/CWA）作为真值，和项目当前逻辑一致。
+1）`truth_records_store + training_feature_records_store` 的长期样本：当前长期评测主源应优先来自永久真值表与长期训练特征表；legacy 的 `daily_records.json` 与 `settlement_history.json` 更适合作为迁移恢复与对照来源，而不是长期主输入。
+2）观测“真值”统一口径：对 METAR 城市用 AviationWeather Data API；对香港按 HKO、对台北/深圳按 `Wunderground RCSS/ZGSZ` 等结算源作为真值，和项目当前逻辑一致。
 **指标** 
 1）确定性误差：MAE、RMSE（按城市、按季节、按风险等级分组）； 
 2）结算命中率：`WU_round(pred) == WU_round(actual)`（项目已有统计口径）； 
@@ -207,7 +214,7 @@ PolyWeather 的评测应围绕“结算场景”而非传统数值天气预报
 
 - 若历史样本足够，DEB 应在“系统性偏差明显”的城市提升 MAE；
 - EMOS 类方法通常能在概率校准（可靠性与 CRPS）上更稳定，尤其当 ensemble 信息可用（项目已接入 Open-Meteo ensemble/p10/p90）。
-**算力**：以上评测全部可在 CPU 上完成；数据量按“20 城市 × 180 天”级别，pandas/duckdb 即可。若引入更复杂拟合（如分层贝叶斯/分位数回归），也通常不需要 GPU。
+**算力**：以上评测全部可在 CPU 上完成；数据量按“39 城市 × 180 天”级别，pandas/duckdb 即可。若引入更复杂拟合（如分层贝叶斯/分位数回归），也通常不需要 GPU。
 ### 错价信号与市场有效性基准
 
 **数据集**
@@ -231,7 +238,7 @@ PolyWeather 的评测应围绕“结算场景”而非传统数值天气预报
 | ----------- | ----------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------- |
 | 第 1–2 周 | 工程地基：CI + 规范 + 配置可复现 | GitHub Actions；ruff/eslint；pytest 可一键跑；`.env.example`；敏感项分级说明（尤其 Supabase service role key 不可暴露）。 | 后端为主；前端补 eslint/typecheck |
 | 第 3–5 周 | 核心模块解耦：采集 Provider 化 + API 分层 | provider 接口与实现；`web/app.py` 拆分路由与服务；核心 schema（Pydantic） | 风险：行为漂移；用回放测试压住 |
-| 第 6–8 周 | 状态/缓存统一 + 可观测性 | `daily_records/open_meteo_cache` 迁移 DB；指标（请求量/429/延迟/命中率）；告警阈值 | 可先用 SQLite/Redis，后续再上 Postgres |
+| 第 6–8 周 | 状态/缓存统一 + 可观测性 | `daily_records/open_meteo_cache` 主读 SQLite；离线脚本也切到 SQLite 优先；永久真值表 / revision / 长期训练特征表落地；指标（请求量/429/延迟/命中率）；Prometheus/Alertmanager/Grafana 最小链路与告警阈值 | 可先用 SQLite/Redis，后续再上 Postgres |
 | 第 9–10 周 | 评测体系上线 | 离线评测脚本（MAE/RMSE/WU-hit/Brier/CRPS）；日报/周报自动生成 | 直接基于项目现有字段扩展 |
 | 第 11–12 周 | 概率引擎升级（可选）+ 市场层健壮性增强 | EMOS/CRPS 拟合的 shadow 输出；Gamma/CLOB 客户端增强（async、重试、分页） | 以“小步可回滚”为原则，避免一次性替换 |
 
@@ -239,9 +246,9 @@ PolyWeather 的评测应围绕“结算场景”而非传统数值天气预报
 
 **外部 API 速率限制/格式变更**：AviationWeather 明确 rate limit 与建议使用 cache 文件；Open-Meteo 也可能在不同端点策略上变化。缓解：统一“请求预算”与退避/熔断；关键响应做 schema 校验与回放测试；对高频数据优先拉取官方 cache/批量接口（若可用）。
 **密钥泄露与权限滥用**：Supabase 明确强调 `service_role` 属高权限密钥，绝不可出现在前端或公开环境。缓解：密钥分级、CI secret scan、运行时最小权限、日志脱敏。
-**支付链路最终一致性与链上不确定性**：链上事件索引延迟、RPC 不稳定、交易确认数不足都会导致误判。缓解：保持“事件监听 + 确认补单”双路径，并增加“事件重放/对账工具”、多 RPC fallback、以及链上高度持久化。
+**支付链路最终一致性与链上不确定性**：链上事件索引延迟、RPC 不稳定、交易确认数不足都会导致误判。当前项目已经补齐“事件监听 + 确认补单”双路径、事件重放脚本、SQLite 审计事件与多 RPC fallback；现阶段的主要剩余风险不再是“没有防护”，而是链上合约仍为最小实现，owner 为单地址管理，且没有 pause 开关与 SafeERC20。
 **引入外部 AI 预报模型的商业合规风险**：GraphCast/Pangu-Weather 的权重许可均带非商业限制（CC BY-NC-SA/BY-NC-SA）；若 PolyWeather 是付费产品，必须先做法务与授权评审。缓解：只在研究环境评估；商用优先选择可商用权重/购买授权/自研。
-**Open-Core 边界导致的“公开仓库与生产行为不一致”**：README 明确生产存在私有风控与阈值。缓解：把“公开核心”的可复现与评测做扎实（接口/数据 schema/测试/评测），私有策略只作为可插拔 policy layer 接入。
+**代码公开与生产私有资产边界导致的“公开仓库与生产行为不一致”**：README 明确品牌、商标、生产私有数据与运营阈值不在代码许可证授权范围内。缓解：把“公开核心”的可复现与评测做扎实（接口/数据 schema/测试/评测），私有策略只作为可插拔 policy layer 接入。
 ## 参考链接
 
 - PolyWeather 仓库（本次评估对象）：https://github.com/yangyuan-zhen/PolyWeather

docs/payments/PAYMENT_AUDIT_ZH.md

@@ -0,0 +1,244 @@
+# PolyWeather 支付审计与防护说明
+
+最后更新：`2026-03-21`
+
+## 1. 当前已落地的防护
+
+### 链下运行态
+
+- 支付事件扫描与确认循环已把运行态写入 SQLite：
+  - `payment_runtime_state`
+  - `payment_audit_events`
+- 关键循环现在会记录：
+  - `event_loop_started`
+  - `event_loop_cycle`
+  - `event_loop_error`
+  - `confirm_loop_started`
+  - `confirm_loop_cycle`
+  - `confirm_loop_error`
+
+### 事件确认边界
+
+- 后端只认链上 `OrderPaid` 事件。
+- 前端提交 intent 不会直接视为支付完成。
+- `confirm_loop` 会再次按链上交易与确认数校验 intent。
+- 若确认失败，当前会明确把 intent / transaction 落为失败态，而不是长期停留在 `submitted`。
+
+当前已显式识别的失败原因包括：
+
+- `receiver_mismatch`
+- `sender_mismatch`
+- `event_mismatch`
+- `tx_reverted`
+
+### RPC 多节点容灾
+
+- 支持 `POLYWEATHER_PAYMENT_RPC_URLS`
+- 格式示例：
+
+```env
+POLYWEATHER_PAYMENT_RPC_URLS=https://polygon-rpc.com,https://polygon-bor-rpc.publicnode.com
+```
+
+- 启动时按顺序探活。
+- 当前节点断连或收据查询失败时，会自动切换到下一个可用 RPC。
+
+### 事件重放
+
+- 已提供脚本：
+  - [replay_payment_events.py](/E:/web/PolyWeather/scripts/replay_payment_events.py)
+
+用途：
+- 审计某个区块范围内的 `OrderPaid`
+- 事后补查漏单
+- 排查 RPC 抖动导致的监听遗漏
+
+命令示例：
+
+```bash
+python scripts/replay_payment_events.py --from-block 10000000 --to-block 10001000
+```
+
+### 运行态检查
+
+- 已提供接口：
+  - `GET /api/payments/runtime`
+
+可查看：
+- checkout 配置摘要
+- 当前活跃 RPC
+- 候选 RPC 列表
+- event loop 最新状态
+- 最近审计事件
+
+### Ops 事故单
+
+现在 `/ops` 已提供单独的支付异常单列表，默认展示：
+
+- `payment_intent_failed`
+
+支持：
+
+- 按 `reason` 过滤
+- 标记已处理
+
+这让下面这类事故不再需要翻日志定位：
+
+- 已付款但未开通
+- 打到旧收款地址
+- 交易事件不匹配
+
+## 2. 当前合约的授权边界
+
+合约源码：
+- [PolyWeatherCheckout.sol](/E:/web/PolyWeather/contracts/PolyWeatherCheckout.sol)
+
+当前边界：
+
+1. `owner`
+- 可执行：
+  - `setTreasury`
+  - `setTokenAllowed`
+
+2. 普通用户
+- 只能调用：
+  - `pay(orderId, planId, amount, token)`
+
+3. 代币边界
+- 只有 `allowedToken[token] == true` 的 token 可支付
+
+4. 订单边界
+- 同一个 `orderId` 只能成功支付一次
+
+## 3. 重入与重复支付判断
+
+当前合约的 `pay` 逻辑顺序是：
+
+1. 检查 token allowlist
+2. 检查 `amount > 0`
+3. 检查 `paidOrder[orderId] == false`
+4. 先写入 `paidOrder[orderId] = true`
+5. 再执行 `transferFrom`
+6. 发出 `OrderPaid`
+
+这意味着：
+
+- 同一 `orderId` 的重复支付会被拦住
+- 典型“转账外部调用后再回调重复执行同订单”的路径会被 `paidOrder` 状态挡住
+
+但要注意：
+
+- 当前合约没有 `Pausable`
+- 当前合约没有 `SafeERC20`
+- 当前合约没有在链上校验 `planId -> amount`
+
+所以它属于：
+- **最小可用支付合约**
+- 不是“全功能强防护合约”
+
+## 4. 当前静态审计结论
+
+已提供脚本：
+- [check_payment_contract_security.py](/E:/web/PolyWeather/scripts/check_payment_contract_security.py)
+
+命令：
+
+```bash
+python scripts/check_payment_contract_security.py
+```
+
+输出会检查这些项目：
+
+- 是否有 `onlyOwner`
+- `setTreasury` / `setTokenAllowed` 是否受 owner 保护
+- constructor / setter 是否检查零地址
+- 是否校验 allowlist
+- 是否校验 `amount > 0`
+- 是否校验重复订单
+- 是否在 `transferFrom` 前写入 `paidOrder`
+- 是否有 pause 开关
+- 是否使用 SafeERC20
+- 是否在链上绑定套餐价格
+
+## 5. 当前主要剩余风险
+
+1. 单地址 owner
+- 建议把 `owner` 迁移到多签钱包
+
+2. 无暂停开关
+- 发现紧急问题时，无法直接暂停 `pay`
+
+3. 金额校验主要在链下
+- 当前 `planId / amount / token` 绑定主要靠后端 intent 和确认逻辑
+
+4. ERC20 兼容性假设
+- 当前使用 `IERC20.transferFrom`
+- 升级版合约更建议改为 OpenZeppelin `SafeERC20`
+
+## 6. 推荐操作
+
+### 每次支付配置变更后
+
+执行：
+
+```bash
+python scripts/check_payment_contract_security.py
+python scripts/replay_payment_events.py --from-block <from> --to-block <to>
+```
+
+### 线上巡检
+
+执行：
+
+```bash
+curl http://127.0.0.1:8000/api/payments/runtime
+```
+
+重点看：
+
+- `rpc.active_rpc_url`
+- `rpc.configured_rpc_count`
+- `event_loop_state.last_scanned_block`
+- `recent_audit_events`
+
+如果你在 `/ops` 或脚本里看到：
+
+- `receiver_mismatch`
+
+其含义通常不是“缓存没刷新”，而是：
+
+- 用户这笔交易的 `to` 地址不是当前生产收款合约
+- 常见原因是旧页面、旧 deployment、旧钱包会话，或历史收款地址仍被命中
+
+此时应优先做：
+
+1. 确认链上真实 `to` 地址
+2. 确认当前 `/api/payments/config` 返回的 `receiver_contract`
+3. 如确已收款，再走人工恢复或补开订阅
+
+### 按邮箱恢复最近支付
+
+已提供脚本：
+
+- [reconcile_subscription_by_email.py](/E:/web/PolyWeather/scripts/reconcile_subscription_by_email.py)
+
+命令：
+
+```bash
+docker compose exec polyweather_web python scripts/reconcile_subscription_by_email.py --email user@example.com
+```
+
+适用场景：
+
+- 用户声称已付费但未开通
+- 需要快速确认最近一笔 intent 是否能自动恢复
+
+## 7. 下一版合约建议
+
+如果后续升级合约，优先级建议：
+
+1. `Ownable` -> 多签 owner
+2. `SafeERC20`
+3. `Pausable`
+4. 链上 plan/amount/token 绑定
+5. 必要时增加 rescue/sweep 能力

docs/payments/PAYMENT_UPGRADE_V2_ZH.md

@@ -0,0 +1,197 @@
+# PolyWeather 支付合约升级方案（V2）
+
+最后更新：`2026-03-20`
+
+## 1. 目标
+
+本次 V2 方案对应三个明确目标：
+
+1. 把 `owner` 迁到多签地址
+2. 升级到 `SafeERC20 + Pausable + ReentrancyGuard`
+3. 把“链上 plan 绑定”和“EIP-712 授权支付”都纳入设计，而不是只在链下校验
+
+合约草案：
+- [PolyWeatherCheckoutV2.sol](/E:/web/PolyWeather/contracts/PolyWeatherCheckoutV2.sol)
+
+构造参数编码脚本：
+- [encode_checkout_v2_constructor.py](/E:/web/PolyWeather/scripts/encode_checkout_v2_constructor.py)
+
+## 2. V2 新增能力
+
+### 多签 owner
+
+V2 constructor 不再默认 `msg.sender` 作为唯一 owner，而是显式传入：
+
+- `initialOwner`
+- `initialTreasury`
+- `initialSigner`
+
+这意味着：
+- 部署后可直接把多签地址设为 `owner`
+- 不需要先单签部署再补 transfer
+
+### SafeERC20
+
+V2 内置最小 `SafeERC20` 封装：
+
+- `safeTransferFrom`
+- `safeTransfer`
+
+相比直接依赖 `IERC20.transferFrom -> bool`：
+- 对非标准 ERC20 的兼容性更稳
+- 出错边界更明确
+
+### Pausable
+
+V2 增加：
+
+- `pause()`
+- `unpause()`
+
+支付入口：
+
+- `payPlan(...)`
+- `payAuthorized(...)`
+
+都受 `whenNotPaused` 保护。
+
+一旦发现：
+- treasury 配置错误
+- token allowlist 配置错误
+- 签名器异常
+- 链上风控问题
+
+可以直接暂停支付入口。
+
+### ReentrancyGuard
+
+V2 增加 `nonReentrant`，保护：
+
+- `payPlan`
+- `payAuthorized`
+- `rescueToken`
+
+虽然当前订单去重已经能挡住典型重复支付路径，但 `ReentrancyGuard` 仍然是更稳的防线。
+
+### 链上套餐绑定
+
+V2 新增：
+
+- `setPlan(planId, token, amount, active)`
+- `planConfig[planId][token]`
+
+正式支付入口 `payPlan` 会：
+
+1. 校验 token 已 allowed
+2. 校验 `planId + token` 的 plan 已 active
+3. 从链上读取 amount
+4. 按链上配置收款
+
+这意味着：
+- `planId / amount / token` 绑定不再完全依赖链下
+
+### EIP-712 授权支付
+
+V2 同时保留第二条入口：
+
+- `payAuthorized(...)`
+
+它适合：
+- 临时折扣
+- 特殊活动价
+- 不想每次都上链改 `setPlan`
+
+校验字段包括：
+
+- `orderId`
+- `payer`
+- `planId`
+- `token`
+- `amount`
+- `nonce`
+- `deadline`
+
+签名人地址由：
+
+- `signer`
+
+统一控制。
+
+## 3. 两条支付路径怎么选
+
+### 路线 A：链上套餐绑定优先
+
+优点：
+- 最直观
+- 合约级约束最强
+- 更容易审计
+
+缺点：
+- 套餐改价需要 owner 交易
+
+适合：
+- 月付/季付/年付这类稳定商品
+
+### 路线 B：EIP-712 授权优先
+
+优点：
+- 活动价灵活
+- 不必每次改链上 plan
+
+缺点：
+- 需要管理 signer 密钥
+- 风险从 owner 单点，部分转移到 signer 运维
+
+适合：
+- 促销
+- 临时折扣
+- 白名单价格
+
+### 当前建议
+
+生产建议不是二选一，而是：
+
+1. **稳定套餐** 走 `payPlan`
+2. **特殊场景** 走 `payAuthorized`
+
+这样：
+- 主流程更稳
+- 特殊价仍保留灵活性
+
+## 4. 推荐迁移步骤
+
+1. 先部署 V2 到测试环境
+2. `owner` 直接用多签地址
+3. 配置 `treasury`
+4. 配置 `allowedToken`
+5. 配置 `planId/token/amount`
+6. 仅在需要活动价时再配置 `signer`
+7. 用事件重放脚本和运行态接口验证
+8. 再切生产前端/后端配置到新 `receiver_contract`
+
+## 5. 构造参数编码
+
+示例：
+
+```bash
+python scripts/encode_checkout_v2_constructor.py \
+  --owner 0xYourMultiSig \
+  --treasury 0xYourTreasury \
+  --signer 0xYourBackendSigner
+```
+
+## 6. 当前判断
+
+V2 已经把这三件事做成了明确方案：
+
+1. 多签 owner
+2. SafeERC20 + Pausable + ReentrancyGuard
+3. 链上 plan 绑定 + EIP-712 授权
+
+它现在是**升级草案**，不是现网已部署合约。
+
+如果要真正上线，下一步就是：
+
+1. 做一次测试网或本地链验证
+2. 更新 PolygonScan 验证文档
+3. 修改后端 `receiver_contract` 配置

docs/payments/POLYGONSCAN_VERIFY.md

@@ -1,11 +1,17 @@
-# PolyWeatherCheckout PolygonScan 验证（v1.4.0）
+# PolyWeatherCheckout PolygonScan 验证（v1.5.1）
 
-最后更新：`2026-03-14`
+最后更新：`2026-03-20`
 
 ## 1. 目标
 
 对生产收款合约完成源码验证，降低钱包风控误报并提升用户信任。
 
+当前说明：
+
+- **现网合约仍为 V1**：`contracts/PolyWeatherCheckout.sol`
+- **V2 只是升级草案**：`contracts/PolyWeatherCheckoutV2.sol`
+- 当前 PolygonScan 验证流程默认针对 V1
+
 ## 2. 当前部署参数（示例）
 
 - 链：Polygon Mainnet（`chainId=137`）
@@ -48,7 +54,23 @@ python scripts/encode_checkout_constructor.py \
 - USDC.e: `0x2791Bca1f2de4661ED88A30C99A7a9449Aa84174`
 - Native USDC: `0x3c499c542cef5e3811e1192ce70d8cc03d5c3359`
 
-## 7. 说明
+## 7. V2 说明（尚未部署）
+
+如果后续升级到 V2，请改用：
+
+```bash
+python scripts/encode_checkout_v2_constructor.py \
+  --owner 0xYourMultiSig \
+  --treasury 0xYourTreasury \
+  --signer 0xYourBackendSigner
+```
+
+V2 相关文档：
+
+- [PAYMENT_UPGRADE_V2_ZH.md](/E:/web/PolyWeather/docs/payments/PAYMENT_UPGRADE_V2_ZH.md)
+- [PAYMENT_AUDIT_ZH.md](/E:/web/PolyWeather/docs/payments/PAYMENT_AUDIT_ZH.md)
+
+## 8. 说明
 
 - 源码验证能显著降低“欺诈/不可信”误报，但钱包风险缓存更新存在延迟。
 - 生产商用环境可使用私有升级版合约；公开仓库保留标准实现与验证流程。

extension/README.md

@@ -1,26 +1,32 @@
-# PolyWeather 侧边栏插件（MVP）
+# PolyWeather Side Panel
 
-这是一个 Chrome / Edge 侧边栏扩展的 MVP，用于把 PolyWeather 右侧城市卡片移植到浏览器侧边栏中。
+`PolyWeather Side Panel` 是一个面向天气交易场景的 Chrome / Edge 浏览器侧边栏工具。
 
 ## 功能
 
-- 侧边栏展示：
-  - 城市选择
-  - 风险徽章
-  - 城市档案（结算源 / 距离 / 观测更新时间 / 周边站点）
-  - 今日日内走势（简版 Canvas）
-  - 多日预报
-- 快捷按钮：
-  - 今日日内分析
-  - 历史对账
-  - 打开完整网站分析
-- 自动识别城市：
-  - 监听当前激活标签页 URL（例如 Polymarket `.../event/highest-temperature-in-ankara-...`）
-  - 自动将侧边栏城市切换为 URL 对应城市
-- 设置页可配置：
-  - 网站基础地址
-  - API 基础地址
-  - Bearer Token（可选）
+1. 自动识别当前 Polymarket 页面中的城市，也支持手动切换。
+2. 展示城市档案：结算站点、站点距离、观测更新时间、周边站点数量。
+3. 展示今日日内走势（简版）：`DEB` 走势与官方观测（`METAR / HKO / CWA / NOAA`）对照，可悬停查看时间与温度。
+4. 展示多日最高温预报（简版），当前以 `DEB` 优先。
+5. 支持一键刷新，强制拉取最新温度数据。
+6. 支持本地缓存，提升打开速度；刷新时自动更新缓存。
+7. 支持一键跳转到完整网站分析页面。
+
+## 数据说明
+
+- 香港使用 `HKO`（香港天文台）结算源。
+- 其他城市按配置使用 `METAR / NOAA / 官方数据源`。
+- 城市展示名以主站返回值为准，例如 `aurora` 市场在插件中会显示为 `Denver`。
+
+## 权限说明
+
+- `tabs`：用于识别当前活动标签页 URL 并自动匹配城市。
+- `storage`：用于保存插件配置与本地缓存，仅存储在本地浏览器。
+- `sidePanel`：用于在浏览器侧边栏展示界面。
+
+## 隐私说明
+
+本扩展不要求用户登录，不收集个人身份信息，不上传浏览历史，仅在必要时请求天气接口数据以完成展示功能。
 
 ## 本地安装（开发者模式）
 
@@ -42,5 +48,8 @@
 
 ## 说明
 
-- 当前版本是 MVP，重点是“导流回站”，未接入支付链路。
+- 当前版本仍是轻量产品，重点是“监控 + 基础判断 + 导流回站”，未接入支付链路。
 - 若你的 API 做了严格鉴权，请先在设置页填写 token 再使用。
+- 插件走势图与主站保持一致：`Wunderground` 结算城市不再单独绘制结算参考线，统一显示机场 `METAR` / 官方观测点位。
+- 点击“打开网站查看更多”会回到主站继续查看完整分析。
+- 插件不会承载完整分析；完整结构判断、历史对账和更多信号仍以主站为准。

extension/manifest.json

@@ -1,8 +1,8 @@
 {
   "manifest_version": 3,
   "name": "PolyWeather Side Panel",
-  "description": "PolyWeather 右侧城市卡片（浏览器侧边栏）",
-  "version": "0.1.1",
+  "description": "Weather side panel for Polymarket.",
+  "version": "0.1.9",
   "icons": {
     "16": "icon-16.png",
     "32": "icon-32.png",

extension/sidepanel.css

@@ -66,6 +66,23 @@ body {
   margin-bottom: 12px;
 }
 
+.freshness-hint {
+  margin: -2px 0 12px;
+  padding: 8px 10px;
+  border-radius: 10px;
+  border: 1px solid rgba(245, 158, 11, 0.28);
+  background: rgba(245, 158, 11, 0.08);
+  color: #fcd34d;
+  font-size: 12px;
+  line-height: 1.4;
+}
+
+.freshness-hint.stale {
+  border-color: rgba(248, 113, 113, 0.38);
+  background: rgba(248, 113, 113, 0.1);
+  color: #fecaca;
+}
+
 .risk-badge {
   padding: 5px 9px;
   border-radius: 10px;
@@ -236,6 +253,84 @@ body {
   font-size: 12px;
 }
 
+.decision-card {
+  display: grid;
+  gap: 10px;
+  border: 1px solid var(--border);
+  border-radius: 12px;
+  background: rgba(255, 255, 255, 0.02);
+  padding: 10px;
+}
+
+.decision-top {
+  display: flex;
+  align-items: flex-start;
+  justify-content: space-between;
+  gap: 10px;
+}
+
+.decision-direction {
+  font-size: 16px;
+  font-weight: 800;
+  line-height: 1.2;
+  color: #f8fbff;
+}
+
+.decision-window {
+  margin-top: 4px;
+  color: var(--muted);
+  font-size: 11px;
+}
+
+.decision-confidence {
+  flex: 0 0 auto;
+  padding: 5px 9px;
+  border-radius: 999px;
+  border: 1px solid transparent;
+  font-size: 11px;
+  font-weight: 800;
+  letter-spacing: 0.04em;
+}
+
+.decision-confidence.high {
+  color: #86efac;
+  border-color: rgba(52, 211, 153, 0.45);
+  background: rgba(52, 211, 153, 0.12);
+}
+
+.decision-confidence.medium {
+  color: #fcd34d;
+  border-color: rgba(245, 158, 11, 0.45);
+  background: rgba(245, 158, 11, 0.12);
+}
+
+.decision-confidence.low,
+.decision-confidence.neutral {
+  color: #cbd5e1;
+  border-color: rgba(148, 163, 184, 0.28);
+  background: rgba(148, 163, 184, 0.1);
+}
+
+.decision-summary {
+  color: #dbeafe;
+  font-size: 12px;
+  line-height: 1.45;
+}
+
+.decision-reasons {
+  margin: 0;
+  padding-left: 18px;
+  display: grid;
+  gap: 6px;
+  color: var(--muted);
+  font-size: 12px;
+  line-height: 1.45;
+}
+
+.decision-reasons li {
+  margin: 0;
+}
+
 .forecast-row {
   display: grid;
   grid-template-columns: repeat(3, minmax(0, 1fr));
@@ -276,6 +371,13 @@ body {
   background: rgba(59, 130, 246, 0.15);
 }
 
+.open-full-hint {
+  margin-bottom: 10px;
+  color: var(--muted);
+  font-size: 12px;
+  line-height: 1.45;
+}
+
 .error {
   border: 1px solid rgba(248, 113, 113, 0.45);
   border-radius: 12px;

extension/sidepanel.html

@@ -26,6 +26,8 @@
         </button>
       </header>
 
+      <div id="freshnessHint" class="freshness-hint hidden"></div>
+
       <section class="section">
         <h3 id="profileTitle">城市档案</h3>
         <div class="grid2">
@@ -57,12 +59,28 @@
         <div id="chartLegend" class="legend-text">--</div>
       </section>
 
+      <section class="section">
+        <h3 id="decisionTitle">方向判断</h3>
+        <div class="decision-card">
+          <div class="decision-top">
+            <div>
+              <div id="decisionDirection" class="decision-direction">--</div>
+              <div id="decisionWindow" class="decision-window">--</div>
+            </div>
+            <div id="decisionConfidence" class="decision-confidence neutral">--</div>
+          </div>
+          <div id="decisionSummary" class="decision-summary">--</div>
+          <ul id="decisionReasons" class="decision-reasons"></ul>
+        </div>
+      </section>
+
       <section class="section">
         <h3 id="forecastTitle">多日预报</h3>
         <div id="forecastRow" class="forecast-row"></div>
       </section>
 
       <section class="section">
+        <div id="openFullHint" class="open-full-hint"></div>
         <button id="openFullBtn" class="btn btn-open-full">打开完整网站分析</button>
       </section>
 

extension/sidepanel.js

@@ -4,7 +4,7 @@ const DEFAULT_CONFIG = {
   selectedCity: "",
   siteBase: "https://polyweather-pro.vercel.app"
 };
-const CACHE_VERSION = "v1";
+const CACHE_VERSION = "v2";
 const locale = String(navigator.language || "en").toLowerCase().startsWith("zh")
   ? "zh"
   : "en";
@@ -20,6 +20,8 @@ const I18N = {
     settlementAirport: "结算机场",
     hko: "香港天文台 (HKO)",
     cwa: "交通部中央气象署 (CWA)",
+    noaa: "NOAA 官方时序",
+    wunderground: "Wunderground 结算站",
     city: "城市",
     refresh: "刷新数据",
     cityProfile: "城市档案",
@@ -27,19 +29,47 @@ const I18N = {
     obsUpdate: "观测更新",
     nearbyStations: "周边站点",
     intradayTrend: "今日日内走势（简版）",
+    directionTitle: "方向判断",
     forecast: "多日预报",
-    openFull: "打开完整网站分析",
+    openFull: "打开网站查看更多",
+    openFullHint: "插件只提供基础判断；更多分析请到网站查看。",
     noTrendData: "暂无趋势数据",
     noForecast: "暂无多日预报",
     noContinuousObs: "暂无连续观测",
     nearbyMonitoringSuffix: "个参与监控",
     today: "今天",
-    debSeries: "DEB",
+    omSeries: "OM预测",
+    noaaSettlementRef: "NOAA 结算参考",
+    noaaSettlementLegend:
+      "该城市按 NOAA 最终完成质控后的最高整度读数结算；图中曲线仅作结算参考。",
     loadCityDetailFailed: "加载城市详情失败",
     refreshFailed: "刷新温度数据失败",
     initFailed: "初始化失败",
     publicReadHint: "当前插件是公开读模式，Token 可留空。请检查后端是否仍开启了接口鉴权。",
-    publicModeHint: "公开模式只需配置 API Base；Token 可留空。"
+    publicModeHint: "公开模式只需配置 API Base；Token 可留空。",
+    freshnessRecent: "数据约 {minutes} 分钟前更新。",
+    freshnessWarn: "数据已 {minutes} 分钟未更新，建议点右上角刷新。",
+    freshnessStale: "数据已 {minutes} 分钟未更新，当前结果可能偏旧，请立即刷新。",
+    directionWarmer: "未来偏升温",
+    directionCooler: "未来偏降温",
+    directionFlat: "方向不清",
+    confidenceHigh: "高置信",
+    confidenceMedium: "中置信",
+    confidenceLow: "低置信",
+    confidenceNeutral: "待观察",
+    decisionWindow: "未来约 {hours} 小时",
+    reasonDebAbove: "DEB 路径高于当前实测，未来窗口上沿约 {delta}{symbol}。",
+    reasonDebBelow: "DEB 路径低于当前实测，未来窗口下沿约 {delta}{symbol}。",
+    reasonObsAboveOm: "当前实测高于 OM 基线约 {delta}{symbol}，短时偏暖。",
+    reasonObsBelowOm: "当前实测低于 OM 基线约 {delta}{symbol}，短时偏冷。",
+    reasonNearPeak: "当前已接近日内高点，继续上冲空间有限。",
+    reasonRoomToPeak: "当前距日内预测高点仍有约 {delta}{symbol} 空间。",
+    reasonRangeWide: "未来窗口振幅偏大，波动仍可能反复。",
+    reasonRangeTight: "未来窗口振幅较小，更像缓慢推进而非急变。",
+    reasonNoObs: "当前连续实测偏少，方向判断主要依赖短窗预测。",
+    decisionSummaryWarmer: "未来几小时更可能缓慢抬升，板面更容易向高温侧移动。",
+    decisionSummaryCooler: "未来几小时更可能回落，板面更容易向低温侧移动。",
+    decisionSummaryFlat: "未来几小时更像震荡整理，短时升降温方向不够清晰。"
   },
   en: {
     loadingWeather: "Loading weather data...",
@@ -52,6 +82,8 @@ const I18N = {
     settlementAirport: "Settlement Airport",
     hko: "Hong Kong Observatory (HKO)",
     cwa: "Central Weather Administration (CWA)",
+    noaa: "NOAA official timeseries",
+    wunderground: "Wunderground settlement station",
     city: "City",
     refresh: "Refresh data",
     cityProfile: "City Profile",
@@ -59,19 +91,47 @@ const I18N = {
     obsUpdate: "Observation Update",
     nearbyStations: "Nearby Stations",
     intradayTrend: "Today's Intraday Trend",
+    directionTitle: "Direction Bias",
     forecast: "Forecast",
-    openFull: "Open Full Site Analysis",
+    openFull: "Open Website for More",
+    openFullHint: "The extension only provides a basic bias. Visit the site for more analysis.",
     noTrendData: "No trend data available",
     noForecast: "No multi-day forecast",
     noContinuousObs: "No continuous observations",
     nearbyMonitoringSuffix: " stations monitored",
     today: "Today",
-    debSeries: "DEB",
+    omSeries: "OM Forecast",
+    noaaSettlementRef: "NOAA Settlement Reference",
+    noaaSettlementLegend:
+      "This city settles on NOAA using the finalized highest rounded reading; the plotted line is only a settlement reference.",
     loadCityDetailFailed: "Failed to load city detail",
     refreshFailed: "Failed to refresh weather data",
     initFailed: "Initialization failed",
     publicReadHint: "The extension is in public read mode. Token can be empty. Check whether the backend still requires auth.",
-    publicModeHint: "In public mode only API Base is required; Token can be empty."
+    publicModeHint: "In public mode only API Base is required; Token can be empty.",
+    freshnessRecent: "Data updated about {minutes} min ago.",
+    freshnessWarn: "Data is {minutes} min old. Consider refreshing.",
+    freshnessStale: "Data is {minutes} min old and may be stale. Refresh now.",
+    directionWarmer: "Bias Warmer",
+    directionCooler: "Bias Cooler",
+    directionFlat: "Direction Unclear",
+    confidenceHigh: "High Conviction",
+    confidenceMedium: "Medium Conviction",
+    confidenceLow: "Low Conviction",
+    confidenceNeutral: "Watch",
+    decisionWindow: "Next ~{hours}h",
+    reasonDebAbove: "DEB path sits above current observation, with about {delta}{symbol} upside in the window.",
+    reasonDebBelow: "DEB path sits below current observation, with about {delta}{symbol} downside in the window.",
+    reasonObsAboveOm: "Current observation runs about {delta}{symbol} above the OM baseline, keeping the short-term tone warmer.",
+    reasonObsBelowOm: "Current observation runs about {delta}{symbol} below the OM baseline, keeping the short-term tone cooler.",
+    reasonNearPeak: "Current temperature is already close to the intraday peak, limiting further upside.",
+    reasonRoomToPeak: "There is still about {delta}{symbol} room to the projected intraday peak.",
+    reasonRangeWide: "The next-window range is wide, so the path can still swing around.",
+    reasonRangeTight: "The next-window range is tight, pointing to a gradual move rather than a sharp break.",
+    reasonNoObs: "Continuous observations are sparse, so the bias relies more on the short-window forecast.",
+    decisionSummaryWarmer: "The next few hours are more likely to drift warmer, so the board should lean toward the hotter side.",
+    decisionSummaryCooler: "The next few hours are more likely to ease lower, so the board should lean toward the cooler side.",
+    decisionSummaryFlat: "The next few hours look more range-bound, so there is no clear temperature direction yet."
   }
 };
 
@@ -107,6 +167,7 @@ const els = {
   forecastRow: document.getElementById("forecastRow"),
   errorBox: document.getElementById("errorBox"),
   openFullBtn: document.getElementById("openFullBtn"),
+  openFullHint: document.getElementById("openFullHint"),
   loadingOverlay: document.getElementById("loadingOverlay"),
   loadingText: document.getElementById("loadingText"),
   cityLabel: document.getElementById("cityLabel"),
@@ -115,7 +176,14 @@ const els = {
   obsTimeLabel: document.getElementById("obsTimeLabel"),
   nearbyLabel: document.getElementById("nearbyLabel"),
   trendTitle: document.getElementById("trendTitle"),
-  forecastTitle: document.getElementById("forecastTitle")
+  decisionTitle: document.getElementById("decisionTitle"),
+  decisionDirection: document.getElementById("decisionDirection"),
+  decisionWindow: document.getElementById("decisionWindow"),
+  decisionConfidence: document.getElementById("decisionConfidence"),
+  decisionSummary: document.getElementById("decisionSummary"),
+  decisionReasons: document.getElementById("decisionReasons"),
+  forecastTitle: document.getElementById("forecastTitle"),
+  freshnessHint: document.getElementById("freshnessHint")
 };
 
 function normalizeBase(url) {
@@ -188,6 +256,37 @@ function getCityAliasTokens(rawCityName) {
     aliases.add("buenos-aires");
     aliases.add("buenosaires");
   }
+  if (normalized === "aurora") {
+    aliases.add("denver");
+    aliases.add("denver-co");
+    aliases.add("buckley");
+    aliases.add("kbkf");
+  }
+  if (normalized === "los angeles") {
+    aliases.add("los-angeles");
+    aliases.add("lax");
+    aliases.add("klax");
+  }
+  if (normalized === "san francisco") {
+    aliases.add("san-francisco");
+    aliases.add("sfo");
+    aliases.add("ksfo");
+  }
+  if (normalized === "austin") {
+    aliases.add("aus");
+    aliases.add("kaus");
+  }
+  if (normalized === "houston") {
+    aliases.add("hou");
+    aliases.add("hobby");
+    aliases.add("khou");
+  }
+  if (normalized === "mexico city") {
+    aliases.add("mexicocity");
+    aliases.add("ciudad-de-mexico");
+    aliases.add("cdmx");
+    aliases.add("mmmx");
+  }
 
   return [...aliases].filter((item) => item && item.length >= 2);
 }
@@ -258,6 +357,14 @@ function showError(message) {
   els.errorBox.classList.remove("hidden");
 }
 
+function tf(key, params = {}) {
+  let text = t(key);
+  for (const [name, value] of Object.entries(params)) {
+    text = text.replace(`{${name}}`, String(value));
+  }
+  return text;
+}
+
 function clearError() {
   els.errorBox.textContent = "";
   els.errorBox.classList.add("hidden");
@@ -366,6 +473,7 @@ function riskText(level) {
 
 function getSettlementSourceDisplay(detail) {
   const source = String(detail?.current?.settlement_source || "").toLowerCase();
+  const sourceLabel = String(detail?.current?.settlement_source_label || "").trim();
   if (source === "hko") {
     return {
       label: t("settlementSource"),
@@ -378,6 +486,20 @@ function getSettlementSourceDisplay(detail) {
       value: t("cwa")
     };
   }
+  if (source === "noaa") {
+    return {
+      label: t("settlementSource"),
+      value: t("noaa")
+    };
+  }
+  if (source === "wunderground") {
+    const stationLabel = sourceLabel || t("wunderground");
+    const station = String(detail?.current?.station_code || detail?.risk?.icao || "").trim();
+    return {
+      label: t("settlementSource"),
+      value: station ? `${stationLabel} (${station})` : stationLabel
+    };
+  }
   const airport = detail?.risk?.airport || "--";
   const icao = detail?.risk?.icao ? ` (${detail.risk.icao})` : "";
   return {
@@ -400,6 +522,44 @@ function formatForecastDate(day, index) {
   return `${m[2]}/${m[3]}`;
 }
 
+function parseIsoDate(value) {
+  const text = String(value || "").trim();
+  if (!text) return null;
+  const date = new Date(text);
+  if (Number.isNaN(date.getTime())) return null;
+  return date;
+}
+
+function renderFreshness(detail) {
+  if (!els.freshnessHint) return;
+  const updatedAt = parseIsoDate(detail?.updated_at);
+  if (!updatedAt) {
+    els.freshnessHint.classList.add("hidden");
+    els.freshnessHint.classList.remove("stale");
+    els.freshnessHint.textContent = "";
+    return;
+  }
+
+  const minutes = Math.max(
+    0,
+    Math.round((Date.now() - updatedAt.getTime()) / 60000)
+  );
+
+  if (minutes < 8) {
+    els.freshnessHint.classList.add("hidden");
+    els.freshnessHint.classList.remove("stale");
+    els.freshnessHint.textContent = "";
+    return;
+  }
+
+  const isStale = minutes >= 20;
+  els.freshnessHint.classList.remove("hidden");
+  els.freshnessHint.classList.toggle("stale", isStale);
+  els.freshnessHint.textContent = isStale
+    ? tf("freshnessStale", { minutes })
+    : tf("freshnessWarn", { minutes });
+}
+
 function parseTimeToMinute(value) {
   const text = String(value || "");
   const m = text.match(/(\d{1,2}):(\d{2})/);
@@ -412,7 +572,9 @@ function parseTimeToMinute(value) {
 }
 
 function getObservationRows(detail) {
-  const obsSource = Array.isArray(detail?.settlement_today_obs) && detail.settlement_today_obs.length
+  const sourceCode = String(detail?.current?.settlement_source || "").toLowerCase();
+  const useSettlementSource = sourceCode && sourceCode !== "wunderground";
+  const obsSource = useSettlementSource && Array.isArray(detail?.settlement_today_obs) && detail.settlement_today_obs.length
     ? detail.settlement_today_obs
     : Array.isArray(detail?.metar_today_obs)
       ? detail.metar_today_obs
@@ -575,7 +737,10 @@ function drawTrendChart(detail) {
   const points = [...trend, ...obs];
   const hoverPoints = [];
   const tempSymbol = detail?.temp_symbol || "°C";
-  const obsSeriesLabel = String(detail?.current?.settlement_source_label || "OBS").toUpperCase();
+  const sourceCode = String(detail?.current?.settlement_source || "").toLowerCase();
+  const obsSeriesLabel = sourceCode === "noaa"
+    ? t("noaaSettlementRef")
+    : String(detail?.current?.settlement_source_label || "OBS").toUpperCase();
   if (!points.length) {
     setChartHover([], tempSymbol);
     ctx.fillStyle = "#8ba0be";
@@ -635,7 +800,7 @@ function drawTrendChart(detail) {
     trend.forEach((p, idx) => {
       const x = canUseMinuteAxis ? xFromMinute(p.m) : xFromIndex(idx, trend.length);
       const y = yFromValue(p.v);
-      hoverPoints.push({ x, y, time: p.t, value: p.v, series: t("debSeries") });
+      hoverPoints.push({ x, y, time: p.t, value: p.v, series: t("omSeries") });
       if (idx === 0) ctx.moveTo(x, y);
       else ctx.lineTo(x, y);
     });
@@ -688,12 +853,129 @@ function drawTrendChart(detail) {
   setChartHover(hoverPoints, tempSymbol);
 }
 
+function renderDecision(detail) {
+  if (!els.decisionDirection || !els.decisionConfidence || !els.decisionSummary || !els.decisionReasons) {
+    return;
+  }
+
+  const symbol = detail?.temp_symbol || "°C";
+  const currentTemp = Number(detail?.current?.temp);
+  const maxSoFar = Number(detail?.current?.max_temp_so_far);
+  const trendRows = extractTrendSeries(detail).trend;
+  const obsRows = getObservationRows(detail);
+  const obsLatest = obsRows.length ? obsRows[obsRows.length - 1] : null;
+  const currentMinute = Number.isFinite(obsLatest?.minute)
+    ? obsLatest.minute
+    : parseTimeToMinute(detail?.current?.obs_time);
+  const futureRows = trendRows.filter((row) => Number.isFinite(row.m) && Number.isFinite(currentMinute) ? row.m >= currentMinute : true);
+  const shortWindow = futureRows.slice(0, 4);
+  const hours = Math.max(1, Math.min(4, shortWindow.length || 4));
+  const baseTemp = Number.isFinite(currentTemp)
+    ? currentTemp
+    : (obsLatest && Number.isFinite(obsLatest.temp) ? obsLatest.temp : NaN);
+
+  let directionKey = "directionFlat";
+  let summaryKey = "decisionSummaryFlat";
+  let confidenceKey = "confidenceNeutral";
+  let confidenceClass = "neutral";
+  const reasons = [];
+
+  const futureTemps = shortWindow.map((row) => Number(row.v)).filter(Number.isFinite);
+  const futureMax = futureTemps.length ? Math.max(...futureTemps) : Number.NaN;
+  const futureMin = futureTemps.length ? Math.min(...futureTemps) : Number.NaN;
+  const futureEnd = futureTemps.length ? futureTemps[futureTemps.length - 1] : Number.NaN;
+  const projectedDelta = Number.isFinite(baseTemp) && Number.isFinite(futureEnd)
+    ? futureEnd - baseTemp
+    : Number.NaN;
+  const windowAmplitude = Number.isFinite(futureMax) && Number.isFinite(futureMin)
+    ? futureMax - futureMin
+    : Number.NaN;
+
+  if (Number.isFinite(projectedDelta)) {
+    if (projectedDelta >= 0.8) {
+      directionKey = "directionWarmer";
+      summaryKey = "decisionSummaryWarmer";
+      confidenceKey = projectedDelta >= 1.8 ? "confidenceHigh" : projectedDelta >= 1.2 ? "confidenceMedium" : "confidenceLow";
+      confidenceClass = projectedDelta >= 1.8 ? "high" : projectedDelta >= 1.2 ? "medium" : "low";
+    } else if (projectedDelta <= -0.8) {
+      directionKey = "directionCooler";
+      summaryKey = "decisionSummaryCooler";
+      const absDelta = Math.abs(projectedDelta);
+      confidenceKey = absDelta >= 1.8 ? "confidenceHigh" : absDelta >= 1.2 ? "confidenceMedium" : "confidenceLow";
+      confidenceClass = absDelta >= 1.8 ? "high" : absDelta >= 1.2 ? "medium" : "low";
+    } else {
+      confidenceKey = Math.abs(projectedDelta) >= 0.4 ? "confidenceLow" : "confidenceNeutral";
+      confidenceClass = Math.abs(projectedDelta) >= 0.4 ? "low" : "neutral";
+    }
+  }
+
+  if (Number.isFinite(baseTemp) && Number.isFinite(futureMax)) {
+    const upside = futureMax - baseTemp;
+    const downside = baseTemp - futureMin;
+    if (directionKey === "directionWarmer" && upside > 0.3) {
+      reasons.push(tf("reasonDebAbove", { delta: upside.toFixed(1), symbol }));
+    } else if (directionKey === "directionCooler" && downside > 0.3) {
+      reasons.push(tf("reasonDebBelow", { delta: downside.toFixed(1), symbol }));
+    }
+  }
+
+  if (Number.isFinite(baseTemp) && trendRows.length) {
+    const nearest = trendRows.reduce((best, row) => {
+      if (!Number.isFinite(row.m) || !Number.isFinite(currentMinute)) return best;
+      if (!best) return row;
+      return Math.abs(row.m - currentMinute) < Math.abs(best.m - currentMinute) ? row : best;
+    }, null);
+    if (nearest && Number.isFinite(nearest.v)) {
+      const omGap = baseTemp - nearest.v;
+      if (omGap >= 0.8) {
+        reasons.push(tf("reasonObsAboveOm", { delta: omGap.toFixed(1), symbol }));
+      } else if (omGap <= -0.8) {
+        reasons.push(tf("reasonObsBelowOm", { delta: Math.abs(omGap).toFixed(1), symbol }));
+      }
+    }
+  }
+
+  if (Number.isFinite(baseTemp) && Number.isFinite(maxSoFar)) {
+    const gapToPeak = maxSoFar - baseTemp;
+    if (gapToPeak <= 0.6) {
+      reasons.push(t("reasonNearPeak"));
+    } else if (gapToPeak >= 1.2) {
+      reasons.push(tf("reasonRoomToPeak", { delta: gapToPeak.toFixed(1), symbol }));
+    }
+  }
+
+  if (Number.isFinite(windowAmplitude)) {
+    if (windowAmplitude >= 2.2) reasons.push(t("reasonRangeWide"));
+    else if (windowAmplitude <= 1.0) reasons.push(t("reasonRangeTight"));
+  }
+
+  if (!obsRows.length) {
+    reasons.push(t("reasonNoObs"));
+  }
+
+  els.decisionDirection.textContent = t(directionKey);
+  els.decisionWindow.textContent = tf("decisionWindow", { hours });
+  els.decisionConfidence.textContent = t(confidenceKey);
+  els.decisionConfidence.classList.remove("high", "medium", "low", "neutral");
+  els.decisionConfidence.classList.add(confidenceClass);
+  els.decisionSummary.textContent = t(summaryKey);
+  els.decisionReasons.innerHTML = "";
+  for (const reason of reasons.slice(0, 3)) {
+    const li = document.createElement("li");
+    li.textContent = reason;
+    els.decisionReasons.appendChild(li);
+  }
+}
+
 function renderForecast(detail) {
   const symbol = detail?.temp_symbol || "°C";
   const daily = Array.isArray(detail?.forecast?.daily) ? detail.forecast.daily : [];
+  const dailyDeb = detail?.multi_model_daily || {};
   els.forecastRow.innerHTML = "";
   for (let i = 0; i < Math.min(daily.length, 6); i += 1) {
     const day = daily[i];
+    const debValue = dailyDeb?.[day?.date]?.deb?.prediction;
+    const displayTemp = debValue ?? day?.max_temp;
     const card = document.createElement("div");
     card.className = `forecast-card ${i === 0 ? "today" : ""}`;
 
@@ -704,7 +986,7 @@ function renderForecast(detail) {
 
     const v = document.createElement("div");
     v.className = "f-temp";
-    v.textContent = formatTemp(day?.max_temp, symbol);
+    v.textContent = formatTemp(displayTemp, symbol);
     card.appendChild(v);
 
     els.forecastRow.appendChild(card);
@@ -717,6 +999,8 @@ function renderForecast(detail) {
 function renderDetail(detail) {
   state.detail = detail;
   renderRiskBadge(detail);
+  renderFreshness(detail);
+  const tempSymbol = detail?.temp_symbol || "°C";
 
   const profile = getSettlementSourceDisplay(detail);
   els.settlementLabel.textContent = profile.label;
@@ -731,16 +1015,26 @@ function renderDetail(detail) {
     : `${nearby}${t("nearbyMonitoringSuffix")}`;
 
   drawTrendChart(detail);
+  renderDecision(detail);
   renderForecast(detail);
 
-  const sourceTag = String(detail?.current?.settlement_source_label || "").toUpperCase() || "OBS";
+  const sourceCode = String(detail?.current?.settlement_source || "").toLowerCase();
+  const sourceTag = sourceCode === "noaa"
+    ? t("noaaSettlementRef")
+    : String(detail?.current?.settlement_source_label || "").toUpperCase() || "OBS";
   const obs = getObservationRows(detail);
   if (obs.length >= 2) {
     const first = obs[0];
     const last = obs[obs.length - 1];
-    els.chartLegend.textContent = `${sourceTag}: ${first.temp}°C@${first.time} -> ${last.temp}°C@${last.time}`;
+    els.chartLegend.textContent =
+      sourceCode === "noaa"
+        ? `${sourceTag}: ${first.temp}${tempSymbol}@${first.time} -> ${last.temp}${tempSymbol}@${last.time} | ${t("noaaSettlementLegend")}`
+        : `${sourceTag}: ${first.temp}${tempSymbol}@${first.time} -> ${last.temp}${tempSymbol}@${last.time}`;
   } else {
-    els.chartLegend.textContent = `${sourceTag}: ${t("noContinuousObs")}`;
+    els.chartLegend.textContent =
+      sourceCode === "noaa"
+        ? `${sourceTag}: ${t("noContinuousObs")} | ${t("noaaSettlementLegend")}`
+        : `${sourceTag}: ${t("noContinuousObs")}`;
   }
 }
 
@@ -777,6 +1071,10 @@ function normalizeAggregateDetail(payload) {
     forecast: {
       daily: Array.isArray(timeseries.forecast_daily) ? timeseries.forecast_daily : []
     },
+    multi_model_daily:
+      timeseries.multi_model_daily && typeof timeseries.multi_model_daily === "object"
+        ? timeseries.multi_model_daily
+        : {},
     hourly: timeseries.hourly || { times: [], temps: [] },
     metar_today_obs: timeseries.metar_today_obs || [],
     settlement_today_obs: timeseries.settlement_today_obs || [],
@@ -793,8 +1091,10 @@ function applyStaticTranslations() {
   if (els.obsTimeLabel) els.obsTimeLabel.textContent = t("obsUpdate");
   if (els.nearbyLabel) els.nearbyLabel.textContent = t("nearbyStations");
   if (els.trendTitle) els.trendTitle.textContent = t("intradayTrend");
+  if (els.decisionTitle) els.decisionTitle.textContent = t("directionTitle");
   if (els.forecastTitle) els.forecastTitle.textContent = t("forecast");
   if (els.openFullBtn) els.openFullBtn.textContent = t("openFull");
+  if (els.openFullHint) els.openFullHint.textContent = t("openFullHint");
   if (els.refreshBtn) {
     els.refreshBtn.title = t("refresh");
     els.refreshBtn.setAttribute("aria-label", t("refresh"));
@@ -893,11 +1193,14 @@ async function loadCities(options = {}) {
   }
 }
 
-function getActiveTabUrl() {
+function getActiveTabInfo() {
   return new Promise((resolve) => {
     chrome.tabs.query({ active: true, currentWindow: true }, (tabs) => {
       const first = Array.isArray(tabs) && tabs.length ? tabs[0] : null;
-      resolve(String(first?.url || ""));
+      resolve({
+        url: String(first?.url || ""),
+        title: String(first?.title || "")
+      });
     });
   });
 }
@@ -906,12 +1209,12 @@ async function syncCityFromActiveUrl() {
   if (state.syncBusy || !state.cities.length) return;
   state.syncBusy = true;
   try {
-    const url = await getActiveTabUrl();
+    const { url, title } = await getActiveTabInfo();
     if (!url) return;
     if (url === state.lastActiveUrl) return;
     state.lastActiveUrl = url;
 
-    const inferred = inferCityFromUrl(url);
+    const inferred = inferCityFromUrl(url) || matchCityInText(title);
     if (!inferred) return;
     if (inferred === state.config.selectedCity) return;
     await setSelectedCity(inferred, { persist: true, reloadDetail: true });
@@ -944,10 +1247,8 @@ function bindUrlSync() {
 }
 
 function openMainSite(view) {
-  const city = encodeURIComponent(state.config.selectedCity || "");
   const siteBase = normalizeBase(state.config.siteBase || state.config.apiBase);
-  const url = `${siteBase}/?city=${city}&view=${encodeURIComponent(view || "dashboard")}`;
-  chrome.tabs.create({ url });
+  chrome.tabs.create({ url: siteBase });
 }
 
 function bindEvents() {

frontend/.env.example

@@ -1,12 +1,35 @@
+# PolyWeather 前端最小配置（本地 / Vercel）
+# 只部署天气看板时，先填下面 4 项即可。
+
+# 必填：后端 FastAPI 基础地址
 POLYWEATHER_API_BASE_URL=http://127.0.0.1:8000
-# Supabase Auth (Google + Email)
+
+# 必填：Supabase 前端公钥（鉴权开启时必须）
 NEXT_PUBLIC_SUPABASE_URL=
 NEXT_PUBLIC_SUPABASE_ANON_KEY=
+
+# 常用：前端鉴权开关
+# true: 启用 Supabase 登录
+# false: 关闭登录能力，访客模式
 POLYWEATHER_AUTH_ENABLED=false
-# If true: middleware forces login; if false: optional login mode (guests allowed).
+
+# 常用：是否强制登录
+# true: middleware 强制登录后才能访问主页面
+# false: 登录可选，访客可浏览
 POLYWEATHER_AUTH_REQUIRED=false
-# Optional dashboard guard (Next.js middleware)
-# If set, open dashboard with: /?access_token=<token>
+
+# 可选：分享式看板访问令牌
+# 设置后，可通过 /?access_token=<token> 打开受保护看板
 POLYWEATHER_DASHBOARD_ACCESS_TOKEN=
-# Shared secret forwarded by Next API routes to backend
+
+# 可选：前端 API Route 转发到后端时附带的共享令牌
+# 仅当后端启用了 entitlement / 订阅校验时需要
 POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
+
+# 可选：钱包支付 / Telegram 入口
+NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID=
+NEXT_PUBLIC_WALLETCONNECT_POLYGON_RPC_URL=https://polygon-bor-rpc.publicnode.com
+NEXT_PUBLIC_PAYMENT_ALLOWED_HOSTS=polyweather-pro.vercel.app
+POLYWEATHER_OPS_ADMIN_EMAILS=yhrsc30@gmail.com
+NEXT_PUBLIC_TELEGRAM_GROUP_URL=https://t.me/your_group
+NEXT_PUBLIC_TELEGRAM_BOT_URL=https://t.me/WeatherQuant_bot

frontend/README.md

@@ -19,6 +19,20 @@ PolyWeather Pro 的生产前端工程。
 2. Next Route Handlers（`/api/*`）-> FastAPI 后端
 3. FastAPI -> 分析服务 / 支付服务
 
+## 当前前端能力
+
+- 主站 Dashboard 支持地图、城市详情、今日日内分析、历史准确率对账和账户中心
+- `/docs` 已提供公开双语产品文档中心，解释日内结构信号、TAF、结算来源和历史对账
+- 今日日内分析支持：
+  - 峰值窗口感知的近地面结构信号
+  - 高空结构信号
+  - 交易动作卡
+  - 非香港机场城市的 `TAF` 时段提示与走势图联动
+- 历史对账支持：
+  - `DEB / 最佳单模型 / 实测最高温` 对比
+  - 峰值前 12 小时 `DEB` 参考（近似）
+- `/ops` 已支持桌面表格 + 手机端卡片化视图
+
 ## 本地开发
 
 ```bash
@@ -28,30 +42,55 @@ npm install
 npm run dev
 ```
 
-## 必需环境变量
+## Vercel 最小部署配置
+
+只跑看板和基础鉴权时，先填这 4 项：
 
 ```env
 POLYWEATHER_API_BASE_URL=https://<your-fastapi-host>
-NEXT_PUBLIC_SUPABASE_URL=
-NEXT_PUBLIC_SUPABASE_ANON_KEY=
+NEXT_PUBLIC_SUPABASE_URL=https://<your-supabase-project>.supabase.co
+NEXT_PUBLIC_SUPABASE_ANON_KEY=<your-anon-key>
 POLYWEATHER_AUTH_ENABLED=true
-POLYWEATHER_AUTH_REQUIRED=false
-POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
 ```
 
-WalletConnect：
+建议显式补：
 
 ```env
+POLYWEATHER_AUTH_REQUIRED=true
+```
+
+如果你只是开放游客浏览，可改成：
+
+```env
+POLYWEATHER_AUTH_ENABLED=false
+POLYWEATHER_AUTH_REQUIRED=false
+```
+
+## 可选环境变量
+
+仅在对应功能启用时填写：
+
+```env
+# 看板分享令牌
+POLYWEATHER_DASHBOARD_ACCESS_TOKEN=
+
+# 前端 API 转发到后端时使用的共享令牌
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
+
+# 钱包支付
 NEXT_PUBLIC_WALLETCONNECT_PROJECT_ID=
 NEXT_PUBLIC_WALLETCONNECT_POLYGON_RPC_URL=https://polygon-bor-rpc.publicnode.com
-```
+NEXT_PUBLIC_PAYMENT_ALLOWED_HOSTS=polyweather-pro.vercel.app
+POLYWEATHER_OPS_ADMIN_EMAILS=yhrsc30@gmail.com
 
-浮层链接：
-
-```env
+# 社群入口
 NEXT_PUBLIC_TELEGRAM_GROUP_URL=https://t.me/<your_group>
+NEXT_PUBLIC_TELEGRAM_BOT_URL=https://t.me/WeatherQuant_bot
 ```
 
+更完整的 Vercel 配置说明见：
+- [docs/FRONTEND_DEPLOYMENT_ZH.md](/E:/web/PolyWeather/docs/FRONTEND_DEPLOYMENT_ZH.md)
+
 ## 路由处理器
 
 天气：
@@ -77,17 +116,65 @@ NEXT_PUBLIC_TELEGRAM_GROUP_URL=https://t.me/<your_group>
 - `POST /api/payments/intents/[intentId]/submit`
 - `POST /api/payments/intents/[intentId]/confirm`
 
+Ops：
+
+- `GET /ops`
+- `GET /api/ops/users`
+- `GET /api/ops/leaderboard/weekly`
+- `GET /api/ops/memberships`
+- `GET /api/ops/payments/incidents`
+- `POST /api/ops/users/grant-points`
+- `POST /api/ops/payments/incidents/[eventId]/resolve`
+
+## Ops 管理后台
+
+当前前端已内置轻量管理页：
+
+- [https://polyweather-pro.vercel.app/ops](https://polyweather-pro.vercel.app/ops)
+
+页面当前支持：
+
+- 系统状态
+- SQLite / rollout / 支付运行态
+- 用户查询
+- 当前会员
+- 本周积分榜
+- 手动补分
+- 支付异常单筛选与标记已处理
+- 手机端卡片化视图
+
+注意：
+
+- `/ops` 现在是前后端双层管理员限制
+- Vercel 前端和后端都应配置相同的 `POLYWEATHER_OPS_ADMIN_EMAILS`
+- 前端登录邮箱本身不会自动获得管理员权限
+
+## 支付安全补充
+
+为降低“旧页面/旧配置导致打到旧收款地址”的风险，支付区现在会：
+
+1. 点击支付前重新请求 `/api/payments/config`
+2. 若 `receiver_contract` 已更新，先切到最新地址
+3. 若后端返回的 `tx_payload.to` 与最新地址不一致，直接阻断支付
+4. 仅允许在 `NEXT_PUBLIC_PAYMENT_ALLOWED_HOSTS` 白名单域名上创建 payment intent
+5. 支付区会明确显示当前账号、付款钱包和收款合约，避免账号/钱包/地址混淆
+
+这意味着：
+
+- 旧标签页风险已明显降低
+- 但支付地址变更后，仍建议在 Vercel 上 redeploy 当前 production，并清理明显过期 deployment
+
 ## 缓存行为
 
 - `cities` / `summary` / `history`：`ETag + Cache-Control`
 - `summary?force_refresh=true`：`no-store`
 - 支付相关路由：`no-store`
 
-## 开源边界说明
+## AGPL 与商用边界说明
 
-此前端仓库包含通用产品界面和标准支付体验。
-商业策略调优、私有运营流程和敏感生产参数不在公开文档范围内。
+此前端代码随仓库一起采用 `AGPL-3.0-only`。
+生产私有运营流程、商业策略调优、敏感生产参数、品牌与托管服务能力不在代码许可证授权范围内。
 
 详见根目录策略文档：`docs/OPEN_CORE_POLICY.md`
 
-最后更新：`2026-03-14`
+最后更新：`2026-03-24`

frontend/app/api/analytics/events/route.ts

@@ -0,0 +1,51 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+const ANALYTICS_ENABLED =
+  process.env.NEXT_PUBLIC_POLYWEATHER_APP_ANALYTICS === "true";
+
+export async function POST(req: NextRequest) {
+  if (!ANALYTICS_ENABLED) {
+    return new NextResponse(null, { status: 204 });
+  }
+
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const body = await req.json();
+    const auth = await buildBackendRequestHeaders(req);
+    const headers = new Headers(auth.headers);
+    headers.set("Content-Type", "application/json");
+    const res = await fetch(`${API_BASE}/api/analytics/events`, {
+      method: "POST",
+      headers,
+      body: JSON.stringify(body ?? {}),
+      cache: "no-store",
+    });
+    if (!res.ok) {
+      const raw = await res.text();
+      const response = NextResponse.json(
+        { error: `Backend returned ${res.status}`, detail: raw.slice(0, 260) },
+        { status: res.status },
+      );
+      return applyAuthResponseCookies(response, auth.response);
+    }
+    const data = await res.json();
+    const response = NextResponse.json(data);
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to track analytics event", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/auth/me/route.ts

@@ -20,6 +20,14 @@ export async function GET(req: NextRequest) {
       headers: auth.headers,
       cache: "no-store",
     });
+    if (res.status === 401 || res.status === 403) {
+      const response = NextResponse.json({
+        authenticated: false,
+        subscription_active: false,
+        points: 0,
+      });
+      return applyAuthResponseCookies(response, auth.response);
+    }
     if (!res.ok) {
       const raw = await res.text();
       const response = NextResponse.json(

frontend/app/api/cities/route.ts

@@ -18,10 +18,15 @@ export async function GET(req: NextRequest) {
   }
 
   try {
-    const auth = await buildBackendRequestHeaders(req);
-    const res = await fetch(`${API_BASE}/api/cities`, {
+    const auth = await buildBackendRequestHeaders(req, {
+      includeSupabaseIdentity: false,
+    });
+    const fetchOptions = {
       headers: auth.headers,
-      cache: "no-store",
+      next: { revalidate: 300 },
+    } as const;
+    const res = await fetch(`${API_BASE}/api/cities`, {
+      ...fetchOptions,
     });
     if (!res.ok) {
       const raw = await res.text();

frontend/app/api/city/[name]/route.ts

@@ -23,7 +23,9 @@ export async function GET(
   const url = `${API_BASE}/api/city/${encodeURIComponent(name)}?force_refresh=${forceRefresh}`;
 
   try {
-    const auth = await buildBackendRequestHeaders(req);
+    const auth = await buildBackendRequestHeaders(req, {
+      includeSupabaseIdentity: false,
+    });
     const res = await fetch(url, {
       headers: auth.headers,
       cache: "no-store",

frontend/app/api/city/[name]/summary/route.ts

@@ -25,10 +25,21 @@ export async function GET(
   const url = `${API_BASE}/api/city/${encodeURIComponent(name)}/summary?force_refresh=${forceRefresh}`;
 
   try {
-    const auth = await buildBackendRequestHeaders(req);
+    const auth = await buildBackendRequestHeaders(req, {
+      includeSupabaseIdentity: false,
+    });
+    const fetchOptions =
+      bypassCache
+        ? {
+            headers: auth.headers,
+            cache: "no-store" as const,
+          }
+        : {
+            headers: auth.headers,
+            next: { revalidate: 20 },
+          };
     const res = await fetch(url, {
-      headers: auth.headers,
-      cache: "no-store",
+      ...fetchOptions,
     });
     if (!res.ok) {
       const raw = await res.text();

frontend/app/api/healthz/route.ts

@@ -0,0 +1,40 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req, {
+      includeSupabaseIdentity: false,
+    });
+    const res = await fetch(`${API_BASE}/healthz`, {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch healthz", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/history/[name]/route.ts

@@ -24,9 +24,12 @@ export async function GET(
 
   try {
     const auth = await buildBackendRequestHeaders(req);
-    const res = await fetch(url, {
+    const fetchOptions = {
       headers: auth.headers,
-      cache: "no-store",
+      next: { revalidate: 60 },
+    } as const;
+    const res = await fetch(url, {
+      ...fetchOptions,
     });
     if (!res.ok) {
       const raw = await res.text();

frontend/app/api/ops/analytics/funnel/route.ts

@@ -0,0 +1,43 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const url = new URL(`${API_BASE}/api/ops/analytics/funnel`);
+    const days = req.nextUrl.searchParams.get("days");
+    if (days) {
+      url.searchParams.set("days", days);
+    }
+    const res = await fetch(url.toString(), {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch analytics funnel", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/leaderboard/weekly/route.ts

@@ -0,0 +1,42 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const url = new URL(`${API_BASE}/api/ops/leaderboard/weekly`);
+    const limit = req.nextUrl.searchParams.get("limit");
+    if (limit) url.searchParams.set("limit", limit);
+
+    const res = await fetch(url.toString(), {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch weekly leaderboard", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/memberships/route.ts

@@ -0,0 +1,42 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const url = new URL(`${API_BASE}/api/ops/memberships`);
+    const limit = req.nextUrl.searchParams.get("limit");
+    if (limit) url.searchParams.set("limit", limit);
+
+    const res = await fetch(url.toString(), {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch memberships", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/payments/incidents/[eventId]/resolve/route.ts

@@ -0,0 +1,44 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+type RouteContext = {
+  params: Promise<{ eventId: string }>;
+};
+
+export async function POST(req: NextRequest, context: RouteContext) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const { eventId } = await context.params;
+    const res = await fetch(`${API_BASE}/api/ops/payments/incidents/${eventId}/resolve`, {
+      method: "POST",
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to resolve payment incident", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/payments/incidents/route.ts

@@ -0,0 +1,42 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const url = new URL(`${API_BASE}/api/ops/payments/incidents`);
+    const limit = req.nextUrl.searchParams.get("limit");
+    if (limit) url.searchParams.set("limit", limit);
+
+    const res = await fetch(url.toString(), {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch payment incidents", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/truth-history/route.ts

@@ -0,0 +1,44 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const url = new URL(`${API_BASE}/api/ops/truth-history`);
+    for (const key of ["city", "date_from", "date_to", "limit"]) {
+      const value = req.nextUrl.searchParams.get(key);
+      if (value) url.searchParams.set(key, value);
+    }
+
+    const res = await fetch(url.toString(), {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch truth history", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/users/grant-points/route.ts

@@ -0,0 +1,44 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function POST(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const body = await req.text();
+    const res = await fetch(`${API_BASE}/api/ops/users/grant-points`, {
+      method: "POST",
+      headers: {
+        ...auth.headers,
+        "Content-Type": "application/json",
+      },
+      body,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to grant points", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/ops/users/route.ts

@@ -0,0 +1,44 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const url = new URL(`${API_BASE}/api/ops/users`);
+    const q = req.nextUrl.searchParams.get("q");
+    const limit = req.nextUrl.searchParams.get("limit");
+    if (q) url.searchParams.set("q", q);
+    if (limit) url.searchParams.set("limit", limit);
+
+    const res = await fetch(url.toString(), {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "Content-Type": res.headers.get("content-type") || "application/json",
+        "Cache-Control": "no-store",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch ops users", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/payments/intents/route.ts

@@ -3,6 +3,7 @@ import {
   applyAuthResponseCookies,
   buildBackendRequestHeaders,
 } from "@/lib/backend-auth";
+import { isPaymentHostAllowed } from "@/lib/payment-host";
 
 const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
 
@@ -13,6 +14,20 @@ export async function POST(req: NextRequest) {
       { status: 500 },
     );
   }
+  const requestHost =
+    req.headers.get("x-forwarded-host") ||
+    req.headers.get("host") ||
+    req.nextUrl.hostname;
+  if (!isPaymentHostAllowed(requestHost)) {
+    return NextResponse.json(
+      {
+        error:
+          "Payments are disabled on this host. Please return to the main production site and retry.",
+        host: requestHost,
+      },
+      { status: 409 },
+    );
+  }
   try {
     const body = await req.json();
     const auth = await buildBackendRequestHeaders(req);

frontend/app/api/payments/reconcile-latest/route.ts

@@ -0,0 +1,39 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function POST(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const res = await fetch(`${API_BASE}/api/payments/reconcile-latest`, {
+      method: "POST",
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    const raw = await res.text();
+    const response = new NextResponse(raw, {
+      status: res.status,
+      headers: {
+        "content-type":
+          res.headers.get("content-type") || "application/json; charset=utf-8",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to reconcile latest payment", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/payments/runtime/route.ts

@@ -0,0 +1,43 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const res = await fetch(`${API_BASE}/api/payments/runtime`, {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    if (!res.ok) {
+      const raw = await res.text();
+      const response = NextResponse.json(
+        { error: `Backend returned ${res.status}`, detail: raw.slice(0, 500) },
+        { status: res.status },
+      );
+      return applyAuthResponseCookies(response, auth.response);
+    }
+
+    const data = await res.json();
+    const response = NextResponse.json(data, {
+      headers: { "Cache-Control": "no-store" },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch payment runtime", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/system/status/route.ts

@@ -0,0 +1,43 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export async function GET(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  try {
+    const auth = await buildBackendRequestHeaders(req);
+    const res = await fetch(`${API_BASE}/api/system/status`, {
+      headers: auth.headers,
+      cache: "no-store",
+    });
+    if (!res.ok) {
+      const raw = await res.text();
+      const response = NextResponse.json(
+        { error: `Backend returned ${res.status}`, detail: raw.slice(0, 500) },
+        { status: res.status },
+      );
+      return applyAuthResponseCookies(response, auth.response);
+    }
+
+    const data = await res.json();
+    const response = NextResponse.json(data, {
+      headers: { "Cache-Control": "no-store" },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    return NextResponse.json(
+      { error: "Failed to fetch system status", detail: String(error) },
+      { status: 500 },
+    );
+  }
+}

frontend/app/api/vitals/route.ts

@@ -5,6 +5,9 @@ import {
   recordVitalsSample,
 } from "@/lib/vitals-store";
 
+const WEB_VITALS_ENABLED =
+  process.env.NEXT_PUBLIC_POLYWEATHER_WEB_VITALS === "true";
+
 type VitalsPayload = {
   id?: string;
   metric?: string;
@@ -15,6 +18,10 @@ type VitalsPayload = {
 };
 
 export async function POST(request: Request) {
+  if (!WEB_VITALS_ENABLED) {
+    return new NextResponse(null, { status: 204 });
+  }
+
   try {
     const payload = (await request.json()) as VitalsPayload;
     const metric = normalizeMetricName(payload.metric);
@@ -56,6 +63,16 @@ export async function POST(request: Request) {
 }
 
 export async function GET(request: Request) {
+  if (!WEB_VITALS_ENABLED) {
+    return NextResponse.json({
+      ok: true,
+      disabled: true,
+      generatedAt: Date.now(),
+      sampleCount: 0,
+      routes: {},
+    });
+  }
+
   const { searchParams } = new URL(request.url);
   const targetRoute = String(searchParams.get("route") || "").trim();
   const summary = getVitalsSummary();

frontend/app/docs/[...slug]/page.tsx

@@ -0,0 +1,27 @@
+import { notFound } from "next/navigation";
+import { DocsScreen } from "@/components/docs/DocsScreen";
+import { DOCS_PAGES, getDocsPage } from "@/content/docs/docs";
+
+export function generateStaticParams() {
+  return DOCS_PAGES.map((page) => ({ slug: [page.slug] }));
+}
+
+export default async function DocsDetailPage({
+  params,
+}: {
+  params: Promise<{ slug?: string[] }>;
+}) {
+  const resolvedParams = await params;
+  if ((resolvedParams.slug?.length || 0) > 1) {
+    notFound();
+  }
+
+  const slug = resolvedParams.slug?.[0] || "intro";
+  const page = getDocsPage(slug);
+
+  if (!page) {
+    notFound();
+  }
+
+  return <DocsScreen page={page} />;
+}

frontend/app/docs/layout.tsx

@@ -0,0 +1,5 @@
+import { I18nProvider } from "@/hooks/useI18n";
+
+export default function DocsLayout({ children }: { children: React.ReactNode }) {
+  return <I18nProvider>{children}</I18nProvider>;
+}

frontend/app/docs/page.tsx

@@ -0,0 +1,5 @@
+import { redirect } from "next/navigation";
+
+export default function DocsIndexPage() {
+  redirect("/docs/intro");
+}

frontend/app/layout.tsx

@@ -1,7 +1,4 @@
 import type { Metadata } from "next";
-import { Analytics } from "@vercel/analytics/react";
-import { SpeedInsights } from "@vercel/speed-insights/next";
-import { WebVitalsReporter } from "@/components/observability/WebVitalsReporter";
 import "./globals.css";
 
 export const metadata: Metadata = {
@@ -33,12 +30,7 @@ export default function RootLayout({
           rel="stylesheet"
         />
       </head>
-      <body className="min-h-screen font-sans antialiased">
-        {children}
-        <WebVitalsReporter />
-        <Analytics />
-        <SpeedInsights />
-      </body>
+      <body className="min-h-screen font-sans antialiased">{children}</body>
     </html>
   );
 }

frontend/app/loading.tsx

@@ -0,0 +1,5 @@
+import { DashboardShellSkeleton } from "@/components/dashboard/DashboardShellSkeleton";
+
+export default function Loading() {
+  return <DashboardShellSkeleton />;
+}

frontend/app/ops/page.tsx

@@ -0,0 +1,13 @@
+import type { Metadata } from "next";
+import { OpsDashboard } from "@/components/ops/OpsDashboard";
+import { requireOpsAdmin } from "@/lib/ops-admin";
+
+export const metadata: Metadata = {
+  title: "PolyWeather Ops",
+  description: "PolyWeather lightweight operations dashboard.",
+};
+
+export default async function OpsPage() {
+  await requireOpsAdmin("/ops");
+  return <OpsDashboard />;
+}

frontend/app/ops/truth-history/page.tsx

@@ -0,0 +1,13 @@
+import type { Metadata } from "next";
+import { TruthHistoryDashboard } from "@/components/ops/TruthHistoryDashboard";
+import { requireOpsAdmin } from "@/lib/ops-admin";
+
+export const metadata: Metadata = {
+  title: "PolyWeather Truth History",
+  description: "Admin truth history viewer for PolyWeather.",
+};
+
+export default async function TruthHistoryPage() {
+  await requireOpsAdmin("/ops/truth-history");
+  return <TruthHistoryDashboard />;
+}

frontend/components/account/AccountCenter.module.css

@@ -390,6 +390,10 @@
   .cards {
     grid-template-columns: 1fr;
   }
+
+  .metaList dd {
+    max-width: 56%;
+  }
 }
 
 @media (max-width: 560px) {
@@ -414,5 +418,74 @@
     flex-direction: column;
     align-items: stretch;
   }
+
+  .ghostBtn,
+  .primaryBtn {
+    min-height: 40px;
+    justify-content: center;
+  }
+
+  .title {
+    font-size: 22px;
+  }
+
+  .subtitle {
+    font-size: 12px;
+  }
+
+  .heroCard {
+    grid-template-columns: 1fr;
+    gap: 12px;
+  }
+
+  .avatar {
+    width: 56px;
+    height: 56px;
+    border-radius: 16px;
+    font-size: 20px;
+  }
+
+  .heroMain h2 {
+    font-size: 22px;
+  }
+
+  .updatedText {
+    text-align: left;
+  }
+
+  .metaList > div {
+    flex-direction: column;
+    align-items: flex-start;
+    gap: 4px;
+  }
+
+  .metaList dd {
+    max-width: 100%;
+    text-align: left;
+  }
+
+  .commandRow {
+    flex-direction: column;
+    align-items: stretch;
+  }
+
+  .command {
+    flex: 1 1 auto;
+    width: 100%;
+    min-height: 48px;
+    padding: 10px 12px;
+  }
+
+  .copyBtn {
+    width: 100%;
+    justify-content: center;
+  }
+
+  .noticeRow,
+  .errorRow {
+    width: 100%;
+    align-items: flex-start;
+    line-height: 1.5;
+  }
 }
 

frontend/components/auth/LoginClient.tsx

@@ -71,6 +71,9 @@ export function LoginClient({ nextPath }: LoginClientProps) {
     signupCheckEmail: isEn
       ? "Sign-up successful. Please verify your email before signing in."
       : "注册成功，请检查邮箱并完成验证后登录。",
+    trialPromo: isEn
+      ? "New users unlock a free 3-day Pro trial after sign-up."
+      : "新用户注册后可免费体验 3 天 Pro。",
   } as const;
 
   useEffect(() => {
@@ -190,6 +193,9 @@ export function LoginClient({ nextPath }: LoginClientProps) {
           </div>
           <h1 className="text-3xl font-bold tracking-tight text-white">PolyWeather</h1>
           <p className="mt-2 text-sm text-slate-400">{copy.subtitle}</p>
+          <div className="mt-4 inline-flex items-center rounded-full border border-cyan-400/30 bg-cyan-400/10 px-4 py-1.5 text-xs font-semibold text-cyan-200 shadow-[0_0_20px_rgba(34,211,238,0.08)]">
+            {copy.trialPromo}
+          </div>
         </div>
 
         <button

frontend/components/dashboard/CitySidebar.tsx

@@ -4,7 +4,7 @@ import { startTransition, useEffect, useMemo, useState } from "react";
 import clsx from "clsx";
 import { useDashboardStore } from "@/hooks/useDashboardStore";
 import { useI18n } from "@/hooks/useI18n";
-import { CityListItem } from "@/lib/dashboard-types";
+import { CityListItem, DeviationMonitor } from "@/lib/dashboard-types";
 
 type RiskGroupKey = "high" | "medium" | "low" | "other";
 
@@ -21,6 +21,10 @@ function toRiskGroup(level?: string): RiskGroupKey {
   return "other";
 }
 
+function toPerformanceGroup(city: CityListItem): RiskGroupKey {
+  return toRiskGroup(city.deb_recent_tier);
+}
+
 function normalizeExpandedGroups(
   value: unknown,
 ): Record<RiskGroupKey, boolean> {
@@ -50,7 +54,7 @@ function normalizeExpandedGroups(
 
 export function CitySidebar() {
   const store = useDashboardStore();
-  const { t } = useI18n();
+  const { locale, t } = useI18n();
   const selectedCity = store.selectedCity;
   const riskOrder = { high: 0, medium: 1, low: 2, other: 3 };
   const [expandedGroups, setExpandedGroups] = useState<
@@ -60,11 +64,17 @@ export function CitySidebar() {
   const sortedCities = useMemo(
     () =>
       [...store.cities].sort((a, b) => {
-        const aGroup = toRiskGroup(a.risk_level);
-        const bGroup = toRiskGroup(b.risk_level);
+        const aGroup = toPerformanceGroup(a);
+        const bGroup = toPerformanceGroup(b);
+        const aHitRate = Number(a.deb_recent_hit_rate ?? -1);
+        const bHitRate = Number(b.deb_recent_hit_rate ?? -1);
+        const aSamples = Number(a.deb_recent_sample_count ?? 0);
+        const bSamples = Number(b.deb_recent_sample_count ?? 0);
         return (
           (riskOrder[aGroup] ?? 3) -
             (riskOrder[bGroup] ?? 3) ||
+          bHitRate - aHitRate ||
+          bSamples - aSamples ||
           a.display_name.localeCompare(b.display_name)
         );
       }),
@@ -79,7 +89,7 @@ export function CitySidebar() {
       other: [],
     };
     sortedCities.forEach((city) => {
-      groups[toRiskGroup(city.risk_level)].push(city);
+      groups[toPerformanceGroup(city)].push(city);
     });
     return groups;
   }, [sortedCities]);
@@ -88,7 +98,7 @@ export function CitySidebar() {
     if (!selectedCity) return;
     const selected = store.cities.find((city) => city.name === selectedCity);
     if (!selected) return;
-    const groupKey = toRiskGroup(selected.risk_level);
+    const groupKey = toPerformanceGroup(selected);
     setExpandedGroups((current) =>
       current[groupKey] ? current : { ...current, [groupKey]: true },
     );
@@ -114,6 +124,16 @@ export function CitySidebar() {
     } catch {}
   }, [expandedGroups]);
 
+  const formatDeviationText = (monitor?: DeviationMonitor | null) => {
+    if (!monitor?.available) return "";
+    const label =
+      locale === "en-US" ? monitor.label_en : monitor.label_zh;
+    const trendLabel =
+      locale === "en-US" ? monitor.trend_label_en : monitor.trend_label_zh;
+    if (!label) return "";
+    return trendLabel ? `${label} · ${trendLabel}` : label;
+  };
+
   const groupMeta: Array<{ key: RiskGroupKey; label: string }> = [
     { key: "high", label: t("sidebar.group.high") },
     { key: "medium", label: t("sidebar.group.medium") },
@@ -165,6 +185,32 @@ export function CitySidebar() {
                   const summary = store.citySummariesByName[city.name];
                   const snapshot = detail || summary;
                   const isActive = store.selectedCity === city.name;
+                  const tempSymbol = snapshot?.temp_symbol || "°C";
+                  const currentTempText =
+                    snapshot?.current?.temp != null
+                      ? t("sidebar.currentTemp", {
+                          temp: `${snapshot.current.temp}${tempSymbol}`,
+                        })
+                      : t("common.na");
+                  const deviationText = formatDeviationText(
+                    snapshot?.deviation_monitor,
+                  );
+                  const peakTempText =
+                    detail?.current?.max_so_far != null &&
+                    detail.current.max_temp_time
+                      ? t("sidebar.peakTempAt", {
+                          temp: `${detail.current.max_so_far}${tempSymbol}`,
+                          time: detail.current.max_temp_time,
+                        })
+                      : detail?.current?.max_temp_time
+                        ? t("sidebar.peakAt", { time: detail.current.max_temp_time })
+                        : "";
+                  const deviationDirection =
+                    snapshot?.deviation_monitor?.direction || "normal";
+                  const deviationSeverity =
+                    snapshot?.deviation_monitor?.severity || "normal";
+                  const secondaryText = deviationText || peakTempText;
+                  const performanceTier = toPerformanceGroup(city);
 
                   return (
                     <button
@@ -178,7 +224,7 @@ export function CitySidebar() {
                       }
                     >
                       <div className="city-item-main">
-                        <span className={clsx("risk-dot", city.risk_level)} />
+                        <span className={clsx("risk-dot", performanceTier)} />
                         <span className="city-name-text">{city.display_name}</span>
                         <span
                           className={clsx(
@@ -186,9 +232,7 @@ export function CitySidebar() {
                             snapshot?.current?.temp != null && "loaded",
                           )}
                         >
-                          {snapshot?.current?.temp != null
-                            ? `${snapshot.current.temp}${snapshot.temp_symbol || "°C"}`
-                            : t("common.na")}
+                          {currentTempText}
                         </span>
                       </div>
 
@@ -196,10 +240,18 @@ export function CitySidebar() {
                         <span className="city-local-time">
                           {snapshot?.local_time ? `🕒 ${snapshot.local_time}` : ""}
                         </span>
-                        <span className="city-max-info">
-                          {detail?.current?.max_temp_time
-                            ? t("sidebar.peakAt", { time: detail.current.max_temp_time })
-                            : ""}
+                        <span
+                          className={clsx(
+                            "city-max-info",
+                            deviationText && "city-deviation-info",
+                            deviationText &&
+                              `city-deviation-${deviationDirection}`,
+                            deviationText &&
+                              deviationSeverity === "strong" &&
+                              "strong",
+                          )}
+                        >
+                          {secondaryText}
                         </span>
                       </div>
                     </button>

frontend/components/dashboard/DashboardEntry.tsx

@@ -1,6 +1,7 @@
 "use client";
 
 import dynamic from "next/dynamic";
+import { DashboardShellSkeleton } from "@/components/dashboard/DashboardShellSkeleton";
 
 const PolyWeatherDashboard = dynamic(
   () =>
@@ -9,6 +10,7 @@ const PolyWeatherDashboard = dynamic(
     ),
   {
     ssr: false,
+    loading: () => <DashboardShellSkeleton />,
   },
 );
 

frontend/components/dashboard/DashboardShellSkeleton.tsx

@@ -0,0 +1,105 @@
+"use client";
+
+import { Skeleton } from "@/components/ui/skeleton";
+
+export function DashboardShellSkeleton() {
+  return (
+    <div
+      style={{
+        background:
+          "radial-gradient(circle at top, rgba(30,41,59,0.45), rgba(2,6,23,0.98) 55%)",
+        height: "100vh",
+        overflow: "hidden",
+        position: "relative",
+        width: "100vw",
+      }}
+    >
+      <div
+        style={{
+          alignItems: "center",
+          backdropFilter: "blur(16px)",
+          background: "rgba(10,14,26,0.78)",
+          borderBottom: "1px solid rgba(99,102,241,0.15)",
+          display: "flex",
+          height: 56,
+          justifyContent: "space-between",
+          left: 0,
+          padding: "0 24px",
+          position: "fixed",
+          right: 0,
+          top: 0,
+          zIndex: 20,
+        }}
+      >
+        <div style={{ display: "flex", flexDirection: "column", gap: 8 }}>
+          <Skeleton className="h-6 w-40 bg-zinc-700/60" />
+          <Skeleton className="h-3 w-28 bg-zinc-800/70" />
+        </div>
+        <div style={{ display: "flex", gap: 10 }}>
+          <Skeleton className="h-8 w-20 rounded-full bg-zinc-800/70" />
+          <Skeleton className="h-8 w-28 rounded-full bg-zinc-800/70" />
+        </div>
+      </div>
+
+      <div
+        style={{
+          bottom: 24,
+          display: "flex",
+          gap: 24,
+          left: 24,
+          position: "absolute",
+          right: 24,
+          top: 80,
+        }}
+      >
+        <div
+          style={{
+            display: "flex",
+            flexDirection: "column",
+            gap: 14,
+            maxWidth: 280,
+            width: "22vw",
+          }}
+        >
+          <Skeleton className="h-10 w-40 rounded-xl bg-zinc-800/80" />
+          {Array.from({ length: 6 }).map((_, index) => (
+            <Skeleton
+              key={index}
+              className="h-14 w-full rounded-2xl bg-zinc-900/75"
+            />
+          ))}
+        </div>
+
+        <div style={{ flex: 1, position: "relative" }}>
+          <Skeleton className="h-full w-full rounded-[28px] bg-zinc-950/55" />
+          {Array.from({ length: 8 }).map((_, index) => (
+            <Skeleton
+              key={index}
+              className="absolute rounded-full bg-cyan-500/20"
+              style={{
+                height: 18,
+                left: `${10 + index * 10}%`,
+                top: `${20 + ((index * 9) % 45)}%`,
+                width: 18,
+              }}
+            />
+          ))}
+        </div>
+
+        <div
+          style={{
+            display: "flex",
+            flexDirection: "column",
+            gap: 14,
+            maxWidth: 420,
+            width: "30vw",
+          }}
+        >
+          <Skeleton className="h-16 w-full rounded-3xl bg-zinc-900/80" />
+          <Skeleton className="h-48 w-full rounded-3xl bg-zinc-900/70" />
+          <Skeleton className="h-32 w-full rounded-3xl bg-zinc-900/70" />
+        </div>
+      </div>
+    </div>
+  );
+}

frontend/components/dashboard/DetailPanel.tsx

@@ -2,13 +2,17 @@
 
 import type { ChartConfiguration } from "chart.js";
 import clsx from "clsx";
+import { useRouter } from "next/navigation";
 import { useEffect, useMemo, useRef, useState } from "react";
 import { ForecastTable } from "@/components/dashboard/PanelSections";
 import { useChart } from "@/hooks/useChart";
 import { useDashboardStore } from "@/hooks/useDashboardStore";
 import { useI18n } from "@/hooks/useI18n";
+import { getOfficialSourceLinks } from "@/lib/dashboard-official-sources";
 import { getCityScenery } from "@/lib/dashboard-scenery";
 import { CityDetail } from "@/lib/dashboard-types";
+import { trackAppEvent } from "@/lib/app-analytics";
+import { getTodayPolymarketUrl } from "@/lib/polymarket-market-links";
 import {
   getCityProfileStats,
   getRiskBadgeLabel,
@@ -129,25 +133,78 @@ function DetailMiniTemperatureChart({ detail }: { detail: CityDetail }) {
 export function DetailPanel() {
   const store = useDashboardStore();
   const { locale, t } = useI18n();
+  const router = useRouter();
   const detail = store.selectedDetail;
+  const selectedCityItem = useMemo(
+    () =>
+      store.selectedCity
+        ? store.cities.find((city) => city.name === store.selectedCity) || null
+        : null,
+    [store.cities, store.selectedCity],
+  );
+  const selectedSummary = useMemo(
+    () =>
+      store.selectedCity
+        ? store.citySummariesByName[store.selectedCity] || null
+        : null,
+    [store.citySummariesByName, store.selectedCity],
+  );
   const isPro = store.proAccess.subscriptionActive;
+  const isAuthenticated = store.proAccess.authenticated;
+  const isProStateLoading = store.proAccess.loading;
   const panelRef = useRef<HTMLElement | null>(null);
   const [heavyContentReady, setHeavyContentReady] = useState(false);
   const isOverlayOpen =
     Boolean(store.futureModalDate) ||
-    store.historyState.isOpen ||
-    store.isGuideOpen;
+    store.historyState.isOpen;
   const isVisible =
     store.isPanelOpen &&
     Boolean(store.selectedCity) &&
-    Boolean(detail) &&
-    !store.loadingState.cityDetail &&
     !isOverlayOpen;
+  const hasBasicPanelContent = Boolean(
+    detail || selectedSummary || selectedCityItem,
+  );
+  const panelDisplayName =
+    detail?.display_name ||
+    selectedSummary?.display_name ||
+    selectedCityItem?.display_name ||
+    store.selectedCity ||
+    "...";
+  const panelRiskLevel =
+    detail?.risk?.level ||
+    selectedSummary?.risk?.level ||
+    selectedCityItem?.risk_level ||
+    "low";
   const profileStats = useMemo(
     () => (detail ? getCityProfileStats(detail, locale) : []),
     [detail, locale],
   );
+  const officialLinks = useMemo(
+    () => (detail ? getOfficialSourceLinks(detail) : []),
+    [detail],
+  );
+  const marketUrl = useMemo(
+    () => getTodayPolymarketUrl(detail, locale),
+    [detail, locale],
+  );
   const scenery = getCityScenery(detail?.name);
+  const basicCurrentTemp = selectedSummary?.current?.temp;
+  const basicObsTime = selectedSummary?.current?.obs_time;
+  const basicDeb = selectedSummary?.deb?.prediction;
+  const basicSettlementLabel =
+    selectedSummary?.current?.settlement_source_label ||
+    selectedCityItem?.settlement_source_label ||
+    selectedCityItem?.settlement_source ||
+    (locale === "en-US" ? "Settlement source pending" : "结算口径待确认");
+  const basicAirportLabel =
+    selectedCityItem?.airport ||
+    selectedSummary?.icao ||
+    (locale === "en-US" ? "Airport pending" : "机场待确认");
+  const isBasicSummaryLoading =
+    !detail && !selectedSummary && store.loadingState.cityDetail;
+  const shouldShowSyncCard =
+    !detail &&
+    (store.loadingState.cityDetail || isProStateLoading || isAuthenticated);
   const blurActiveElement = () => {
     if (typeof document === "undefined") return;
     const active = document.activeElement;
@@ -155,6 +212,38 @@ export function DetailPanel() {
       active.blur();
     }
   };
+  const handleFeatureAccess = (feature: "today" | "history") => {
+    blurActiveElement();
+
+    if (!isPro) {
+      trackAppEvent("paywall_feature_clicked", {
+        entry: "detail_panel",
+        feature,
+        city: store.selectedCity,
+        user_state: isAuthenticated ? "logged_in" : "guest",
+      });
+    }
+
+    if (isPro) {
+      if (feature === "today") {
+        void store.openTodayModal();
+        return;
+      }
+      void store.openHistory();
+      return;
+    }
+
+    if (isAuthenticated) {
+      router.push("/account");
+      return;
+    }
+
+    if (feature === "today") {
+      void store.openTodayModal();
+      return;
+    }
+    void store.openHistory();
+  };
 
   useEffect(() => {
     const panel = panelRef.current;
@@ -231,12 +320,37 @@ export function DetailPanel() {
           ×
         </button>
         <div className="panel-title-area">
-          <h2>{detail?.display_name?.toUpperCase() || "..."}</h2>
+          <h2>{panelDisplayName.toUpperCase()}</h2>
+          {store.loadingState.cityDetail && (
+            <div className="panel-loading-hint" role="status" aria-live="polite">
+              <span className="panel-loading-spinner" aria-hidden="true" />
+              <span>
+                {locale === "en-US"
+                  ? `Syncing ${panelDisplayName}...`
+                  : `正在同步 ${panelDisplayName}...`}
+              </span>
+            </div>
+          )}
           <div className="panel-meta">
-            <span className={clsx("risk-badge", detail?.risk?.level || "low")}>
-              {getRiskBadgeLabel(detail?.risk?.level, locale)}
+            <span className={clsx("risk-badge", panelRiskLevel)}>
+              {getRiskBadgeLabel(panelRiskLevel, locale)}
             </span>
             <div className="relative group">
+              {marketUrl ? (
+                <a
+                  className="history-btn"
+                  href={marketUrl}
+                  target="_blank"
+                  rel="noreferrer"
+                  title={
+                    locale === "en-US"
+                      ? "Open today's Polymarket market"
+                      : "打开今日 Polymarket 题目页"
+                  }
+                >
+                  {locale === "en-US" ? "Open Market" : "打开 Polymarket"}
+                </a>
+              ) : null}
               <button
                 type="button"
                 className={clsx("history-btn", !isPro && "pro-locked")}
@@ -245,11 +359,8 @@ export function DetailPanel() {
                     ? t("detail.todayAnalysis")
                     : `${t("detail.todayAnalysis")} (Pro)`
                 }
-                onClick={() => {
-                  blurActiveElement();
-                  void store.openTodayModal();
-                }}
-                disabled={!detail}
+                onClick={() => handleFeatureAccess("today")}
+                disabled={!store.selectedCity}
               >
                 {isPro
                   ? t("detail.todayAnalysis")
@@ -261,11 +372,8 @@ export function DetailPanel() {
                 title={
                   isPro ? t("detail.history") : `${t("detail.history")} (Pro)`
                 }
-                onClick={() => {
-                  blurActiveElement();
-                  void store.openHistory();
-                }}
-                disabled={!detail}
+                onClick={() => handleFeatureAccess("history")}
+                disabled={!store.selectedCity}
               >
                 {isPro ? t("detail.history") : `${t("detail.history")} · Pro`}
               </button>
@@ -275,7 +383,7 @@ export function DetailPanel() {
       </div>
 
       <div className="panel-body">
-        {!detail ? (
+        {!hasBasicPanelContent ? (
           <section>
             <div style={{ color: "var(--text-muted)", fontSize: "13px" }}>
               {store.loadingState.cityDetail
@@ -283,6 +391,90 @@ export function DetailPanel() {
                 : t("detail.emptyHint")}
             </div>
           </section>
+        ) : !detail ? (
+          <>
+            <section className="detail-section">
+              <h3>{locale === "en-US" ? "City Snapshot" : "城市概览"}</h3>
+              {isBasicSummaryLoading ? (
+                <div className="detail-mini-meta">
+                  {locale === "en-US"
+                    ? "Syncing public city snapshot..."
+                    : "正在同步城市基础信息..."}
+                </div>
+              ) : null}
+              <div className="detail-grid">
+                <div className="detail-card">
+                  <span className="detail-label">
+                    {locale === "en-US" ? "Current temp" : "当前温度"}
+                  </span>
+                  <span className="detail-value">
+                    {basicCurrentTemp != null
+                      ? `${basicCurrentTemp}${selectedSummary?.temp_symbol || ""}`
+                      : locale === "en-US"
+                        ? "--"
+                        : "--"}
+                  </span>
+                </div>
+                <div className="detail-card">
+                  <span className="detail-label">
+                    {locale === "en-US" ? "Observed" : "观测时间"}
+                  </span>
+                  <span className="detail-value">
+                    {basicObsTime || (locale === "en-US" ? "Pending" : "待更新")}
+                  </span>
+                </div>
+                <div className="detail-card">
+                  <span className="detail-label">DEB</span>
+                  <span className="detail-value">
+                    {basicDeb != null
+                      ? `${basicDeb}${selectedSummary?.temp_symbol || ""}`
+                      : locale === "en-US"
+                        ? isBasicSummaryLoading
+                          ? "Syncing..."
+                          : "Pending"
+                        : isBasicSummaryLoading
+                          ? "同步中..."
+                          : "待更新"}
+                  </span>
+                </div>
+                <div className="detail-card">
+                  <span className="detail-label">
+                    {locale === "en-US" ? "Settlement" : "结算口径"}
+                  </span>
+                  <span className="detail-value">{basicSettlementLabel}</span>
+                </div>
+                <div className="detail-card">
+                  <span className="detail-label">
+                    {locale === "en-US" ? "Airport" : "结算机场"}
+                  </span>
+                  <span className="detail-value">{basicAirportLabel}</span>
+                </div>
+              </div>
+            </section>
+
+            <section className="detail-section">
+              <div className="detail-card">
+                <span className="detail-label">
+                  {shouldShowSyncCard
+                    ? locale === "en-US"
+                      ? "Detail sync"
+                      : "详情同步"
+                    : locale === "en-US"
+                      ? "Pro features"
+                      : "Pro 功能"}
+                </span>
+                <span className="detail-value" style={{ fontSize: "15px" }}>
+                  {shouldShowSyncCard
+                    ? locale === "en-US"
+                      ? "Full city detail is still syncing. The deeper panel will appear automatically."
+                      : "完整城市详情仍在同步中，深度面板会自动补齐。"
+                    : locale === "en-US"
+                      ? "Intraday analysis, history reconciliation, and deeper structure signals require Pro."
+                      : "今日日内分析、历史对账和更深入的结构信号需要 Pro。"}
+                </span>
+              </div>
+            </section>
+          </>
         ) : (
           <>
             <section className="detail-scenery-card">
@@ -291,12 +483,12 @@ export function DetailPanel() {
                   <img
                     className="detail-scenery-image"
                     src={scenery.imageUrl}
-                    alt={t("detail.sceneryAlt", { city: detail.display_name })}
+                    alt={t("detail.sceneryAlt", { city: detail?.display_name || "" })}
                   />
                   <div className="detail-scenery-overlay">
                     <div className="detail-scenery-copy">
                       <span className="detail-scenery-kicker">
-                        {detail.display_name}
+                        {detail?.display_name}
                       </span>
                     </div>
                     <a
@@ -312,7 +504,7 @@ export function DetailPanel() {
               ) : (
                 <div className="detail-scenery-fallback">
                   <span className="detail-scenery-kicker">
-                    {detail.display_name}
+                    {detail?.display_name}
                   </span>
                   <strong className="detail-scenery-title">
                     {t("detail.sceneryTitle")}
@@ -336,10 +528,37 @@ export function DetailPanel() {
               </div>
             </section>
 
+            {officialLinks.length > 0 ? (
+              <section className="detail-section">
+                <h3>{locale === "en-US" ? "Official Sources" : "官方参考"}</h3>
+                <p className="detail-source-note">
+                  {locale === "en-US"
+                    ? "AGENCY = national meteorological service, METAR = airport observation, AIRPORT = airport official page."
+                    : "AGENCY = 国家气象机构，METAR = 机场实测报文，AIRPORT = 机场官网页面。"}
+                </p>
+                <div className="detail-source-list">
+                  {officialLinks.map((link) => (
+                    <a
+                      key={`${link.label}-${link.href}`}
+                      className="detail-source-link"
+                      href={link.href}
+                      target="_blank"
+                      rel="noreferrer"
+                    >
+                      <span className="detail-source-kind">
+                        {link.kind.toUpperCase()}
+                      </span>
+                      <span className="detail-source-label">{link.label}</span>
+                    </a>
+                  ))}
+                </div>
+              </section>
+            ) : null}
+
             <section className="detail-section rounded-2xl">
               <h3>{t("detail.todayMiniTrend")}</h3>
               {heavyContentReady ? (
-                <DetailMiniTemperatureChart detail={detail} />
+                <DetailMiniTemperatureChart detail={detail!} />
               ) : (
                 <div className="detail-mini-meta">{t("detail.loading")}</div>
               )}

frontend/components/dashboard/GuideModal.tsx

@@ -1,105 +0,0 @@
-"use client";
-
-import { useDashboardStore } from "@/hooks/useDashboardStore";
-import { useI18n } from "@/hooks/useI18n";
-
-const GUIDE_CARDS = {
-  "zh-CN": [
-    {
-      body: "Dynamic Ensemble Blending 是系统的核心预测层。它不是对 ECMWF、GFS、ICON、GEM、JMA 等模型的简单平均，而是结合近期样本表现、当前实况与城市偏置后得到的动态加权结果。",
-      title: "DEB 动态融合预测",
-    },
-    {
-      body: "右侧的结算概率分布基于 DEB 预测值与多模型离散度动态计算。μ 代表当前分布中心，会随着模型、实况和时间变化而变化，不是固定结算值。",
-      title: "结算概率引擎",
-    },
-    {
-      body: "结算源按城市市场定义：米兰(LIMC)、华沙(EPWA)、马德里(LEMD)使用机场 METAR；香港市场使用香港天文台(HKO)；台北市场使用交通部中央气象署(CWA)。系统仍会保留 METAR/MGM 作为临近结构参考，并区分观测时间与接收时间。",
-      title: "结算点与主观测源",
-    },
-    {
-      body: "Ankara 不走通用城市逻辑。结算主站以 LTAC / Esenboğa 为准，周边领先信号优先参考 Turkish MGM 站网，其中 Ankara (Bölge/Center) 是重点监控站，不用 Etimesgut 代替。",
-      title: "Ankara 专属增强",
-    },
-    {
-      body: "点击多日预报后的模态框，主要用于分析下一个交易日。6-48 小时趋势以 weather.gov 和 Open-Meteo 为主；0-2 小时临近判断优先看 METAR 与周边站。",
-      title: "未来日期分析",
-    },
-    {
-      body: "历史准确率对账只统计已结算样本。网页端采用近 15 天滚动视图，不把当天尚未结算的样本算入胜率和 MAE。",
-      title: "历史对账规则",
-    },
-  ],
-  "en-US": [
-    {
-      body: "Dynamic Ensemble Blending (DEB) is the core prediction layer. It is not a simple average across ECMWF/GFS/ICON/GEM/JMA, but a dynamically weighted blend adjusted by recent model performance, current observations, and city bias.",
-      title: "DEB Dynamic Fusion",
-    },
-    {
-      body: "Settlement probability distribution is dynamically computed from DEB forecast and model spread. μ is the current distribution center and shifts with model updates, observations, and time.",
-      title: "Settlement Probability Engine",
-    },
-    {
-      body: "Settlement source follows market rule by city: Milan (LIMC), Warsaw (EPWA), and Madrid (LEMD) settle on airport METAR, Hong Kong settles on HKO, and Taipei settles on CWA. METAR/MGM are still kept for intraday structure tracking with observation time vs receipt time separated.",
-      title: "Settlement Source Logic",
-    },
-    {
-      body: "Ankara does not follow the generic city path. LTAC / Esenboğa is the settlement station, with Turkish MGM network for leading signals. Ankara (Bölge/Center) is a key station and is not replaced by Etimesgut.",
-      title: "Ankara-specific Enhancement",
-    },
-    {
-      body: "The multi-day modal focuses on next-session analysis. 6-48h trend mainly relies on weather.gov and Open-Meteo; 0-2h nowcast prioritizes METAR and nearby stations.",
-      title: "Future-date Analysis",
-    },
-    {
-      body: "History reconciliation only uses settled samples. The web dashboard uses a rolling 15-day window and excludes same-day unsettled samples from hit-rate and MAE.",
-      title: "History Rules",
-    },
-  ],
-} as const;
-
-export function GuideModal() {
-  const store = useDashboardStore();
-  const { locale, t } = useI18n();
-
-  if (!store.isGuideOpen) return null;
-
-  return (
-    <div
-      className="modal-overlay"
-      role="dialog"
-      aria-modal="true"
-      aria-labelledby="guide-modal-title"
-      onClick={(event) => {
-        if (event.target === event.currentTarget) {
-          store.closeGuide();
-        }
-      }}
-    >
-      <div className="modal-content large">
-        <div className="modal-header">
-          <h2 id="guide-modal-title">{t("guide.title")}</h2>
-          <button
-            type="button"
-            className="modal-close"
-            aria-label={t("guide.closeAria")}
-            onClick={store.closeGuide}
-          >
-            ×
-          </button>
-        </div>
-        <div className="modal-body">
-          <div className="guide-grid">
-            {GUIDE_CARDS[locale].map((card) => (
-              <div key={card.title} className="guide-card">
-                <h3>{card.title}</h3>
-                <p>{card.body}</p>
-              </div>
-            ))}
-          </div>
-          <div className="guide-footer">{t("guide.footer")}</div>
-        </div>
-      </div>
-    </div>
-  );
-}

frontend/components/dashboard/HeaderBar.tsx

@@ -1,49 +1,35 @@
 "use client";
 
-import { useEffect, useState } from "react";
 import Link from "next/link";
+import { usePathname } from "next/navigation";
 import clsx from "clsx";
 import { LogIn, UserRound } from "lucide-react";
 import { useDashboardStore } from "@/hooks/useDashboardStore";
 import { useI18n } from "@/hooks/useI18n";
-import {
-  getSupabaseBrowserClient,
-  hasSupabasePublicEnv,
-} from "@/lib/supabase/client";
+
+function parseExpiryInfo(raw?: string | null) {
+  const text = String(raw || "").trim();
+  if (!text) return null;
+  const dt = new Date(text);
+  if (Number.isNaN(dt.getTime())) return null;
+  const diffMs = dt.getTime() - Date.now();
+  const daysLeft = Math.ceil(diffMs / 86_400_000);
+  return {
+    date: dt,
+    daysLeft,
+    expired: diffMs <= 0,
+  };
+}
 
 export function HeaderBar() {
   const store = useDashboardStore();
   const { locale, setLocale, t } = useI18n();
-  const [isAuthenticated, setIsAuthenticated] = useState(false);
-  const supabaseReady = hasSupabasePublicEnv();
-
-  useEffect(() => {
-    let mounted = true;
-
-    if (!supabaseReady) {
-      setIsAuthenticated(false);
-      return;
-    }
-
-    const supabase = getSupabaseBrowserClient();
-
-    void supabase.auth.getSession().then(({ data }) => {
-      if (!mounted) return;
-      setIsAuthenticated(Boolean(data.session?.user?.id));
-    });
-
-    const {
-      data: { subscription },
-    } = supabase.auth.onAuthStateChange((_event, session) => {
-      if (!mounted) return;
-      setIsAuthenticated(Boolean(session?.user?.id));
-    });
-
-    return () => {
-      mounted = false;
-      subscription.unsubscribe();
-    };
-  }, [supabaseReady]);
+  const pathname = usePathname();
+  const isAuthenticated = store.proAccess.authenticated;
+  const docsHref = "/docs/intro";
+  const docsActive = pathname?.startsWith("/docs");
+  const trialPromoLabel =
+    locale === "en-US" ? "New users get 3-day Pro trial" : "新用户可免费体验 3 天 Pro";
 
   const accountHref = isAuthenticated
     ? "/account"
@@ -52,6 +38,36 @@ export function HeaderBar() {
   const accountAria = isAuthenticated
     ? t("header.accountAria")
     : t("header.signInAria");
+  const expiryInfo = parseExpiryInfo(store.proAccess.subscriptionExpiresAt);
+  const isTrialPlan = /trial/i.test(
+    String(store.proAccess.subscriptionPlanCode || ""),
+  );
+  const showRenewReminder =
+    isAuthenticated &&
+    !store.proAccess.loading &&
+    (
+      (store.proAccess.subscriptionActive &&
+        expiryInfo &&
+        expiryInfo.daysLeft <= 3) ||
+      (!store.proAccess.subscriptionActive && Boolean(expiryInfo))
+    );
+  const renewReminderLabel = !showRenewReminder
+    ? ""
+    : !store.proAccess.subscriptionActive
+      ? isTrialPlan
+        ? locale === "en-US"
+          ? "Trial ended"
+          : "试用已结束"
+        : locale === "en-US"
+          ? "Pro expired"
+          : "Pro 已到期"
+      : isTrialPlan
+        ? locale === "en-US"
+          ? `Trial ${Math.max(expiryInfo?.daysLeft || 0, 0)}d left`
+          : `试用剩余 ${Math.max(expiryInfo?.daysLeft || 0, 0)} 天`
+        : locale === "en-US"
+          ? `Pro ${Math.max(expiryInfo?.daysLeft || 0, 0)}d left`
+          : `Pro 还剩 ${Math.max(expiryInfo?.daysLeft || 0, 0)} 天`;
 
   return (
     <header className="header">
@@ -78,6 +94,24 @@ export function HeaderBar() {
           </button>
         </div>
 
+        <Link
+          href={docsHref}
+          className={clsx("info-btn", docsActive && "active")}
+          title={t("header.docsAria")}
+          aria-label={t("header.docsAria")}
+        >
+          {t("header.docs")}
+        </Link>
+
+        <Link
+          href="/account"
+          className="trial-promo-badge"
+          title={trialPromoLabel}
+          aria-label={trialPromoLabel}
+        >
+          <span>{trialPromoLabel}</span>
+        </Link>
+
         <Link
           href={accountHref}
           className="account-btn"
@@ -88,15 +122,19 @@ export function HeaderBar() {
           <span>{accountLabel}</span>
         </Link>
 
-        <button
-          type="button"
-          className="info-btn"
-          title={t("header.infoAria")}
-          aria-label={t("header.infoAria")}
-          onClick={store.openGuide}
-        >
-          {t("header.info")}
-        </button>
+        {showRenewReminder ? (
+          <Link
+            href="/account"
+            className={clsx(
+              "account-renew-badge",
+              !store.proAccess.subscriptionActive && "expired",
+            )}
+            title={renewReminderLabel}
+            aria-label={renewReminderLabel}
+          >
+            <span>{renewReminderLabel}</span>
+          </Link>
+        ) : null}
 
         <div className="live-badge" id="liveBadge">
           <span className="pulse-dot" />
@@ -115,4 +153,4 @@ export function HeaderBar() {
       </div>
     </header>
   );
-}
+}

frontend/components/dashboard/HistoryModal.tsx

@@ -12,12 +12,23 @@ function HistoryChart() {
   const store = useDashboardStore();
   const { locale } = useI18n();
   const { data } = useHistoryData();
+  const isNoaaSettlement =
+    store.selectedDetail?.current?.settlement_source === "noaa" ||
+    store.selectedDetail?.current?.settlement_source_label === "NOAA";
+  const noaaStationCode = String(
+    store.selectedDetail?.current?.station_code ||
+      store.selectedDetail?.risk?.icao ||
+      "NOAA",
+  )
+    .trim()
+    .toUpperCase();
   const summary = useMemo(
     () => getHistorySummary(data, store.selectedDetail?.local_date),
     [data, store.selectedDetail?.local_date],
   );
   const hasMgm =
     store.selectedCity === "ankara" &&
+    summary.mgmSeriesComplete &&
     summary.mgms.some((value) => value != null);
   const hasBestBaseline =
     Boolean(summary.bestModelName) &&
@@ -33,7 +44,13 @@ function HistoryChart() {
         borderColor: "#f87171",
         borderWidth: 2,
         data: summary.actuals,
-        label: locale === "en-US" ? "Observed High" : "实测最高温",
+        label: isNoaaSettlement
+          ? locale === "en-US"
+            ? `NOAA Settled High (${noaaStationCode})`
+            : `NOAA 结算最高温 (${noaaStationCode})`
+          : locale === "en-US"
+            ? "Observed High"
+            : "实测最高温",
         pointBackgroundColor: "#f87171",
         pointBorderColor: "#fff",
         pointHoverRadius: 7,
@@ -135,7 +152,7 @@ function HistoryChart() {
       },
       type: "line",
     } satisfies ChartConfiguration<"line">;
-  }, [hasBestBaseline, hasMgm, summary, locale]);
+  }, [hasBestBaseline, hasMgm, isNoaaSettlement, noaaStationCode, summary, locale]);
 
   if (!summary.recentData.length) return null;
 
@@ -148,14 +165,40 @@ function HistoryChart() {
 
 export function HistoryModal() {
   const store = useDashboardStore();
-  const { t } = useI18n();
+  const { t, locale } = useI18n();
   const { data, error, isLoading, isOpen } = useHistoryData();
   const isPro = store.proAccess.subscriptionActive;
   const isProLoading = store.proAccess.loading;
+  const isNoaaSettlement =
+    store.selectedDetail?.current?.settlement_source === "noaa" ||
+    store.selectedDetail?.current?.settlement_source_label === "NOAA";
+  const noaaStationCode = String(
+    store.selectedDetail?.current?.station_code ||
+      store.selectedDetail?.risk?.icao ||
+      "NOAA",
+  )
+    .trim()
+    .toUpperCase();
+  const noaaStationName =
+    String(store.selectedDetail?.current?.station_name || "").trim() ||
+    String(store.selectedDetail?.risk?.airport || "").trim() ||
+    noaaStationCode;
   const summary = useMemo(
     () => getHistorySummary(data, store.selectedDetail?.local_date),
     [data, store.selectedDetail?.local_date],
   );
+  const settledPeakRows = useMemo(
+    () =>
+      summary.recentData
+        .filter(
+          (row) =>
+            row.actual != null &&
+            row.actual_peak_time &&
+            row.deb_at_peak_minus_12h != null,
+        )
+        .reverse(),
+    [summary.recentData],
+  );
 
   if (!isOpen) return null;
 
@@ -200,20 +243,70 @@ export function HistoryModal() {
             </button>
           </div>
           <div className="modal-body">
-            <div className="history-stats">
-              {isLoading ? (
-                <span style={{ color: "var(--text-muted)" }}>
-                  {t("history.loading")}
-                </span>
-              ) : error ? (
+            {isNoaaSettlement && (
+              <div
+                style={{
+                  marginBottom: "16px",
+                  padding: "12px 14px",
+                  border: "1px solid rgba(56, 189, 248, 0.24)",
+                  borderRadius: "12px",
+                  background: "rgba(14, 165, 233, 0.08)",
+                  color: "var(--text-secondary)",
+                  fontSize: "13px",
+                  lineHeight: 1.6,
+                }}
+              >
+                {t("lang") === "en-US"
+                  ? `${store.selectedDetail?.display_name || store.selectedCity || "This city"} historical actuals are aligned to NOAA ${noaaStationCode} (${noaaStationName}) settlement rules: use the highest rounded whole-degree Celsius reading after the date is finalized.`
+                  : `${store.selectedDetail?.display_name || store.selectedCity || "该城市"}历史对账已按 NOAA ${noaaStationCode}（${noaaStationName}）结算口径对齐：采用该日最终完成质控后的最高整度摄氏值。`}
+              </div>
+            )}
+            {isLoading ? (
+              <div className="history-modal-loading">
+                <div className="history-fetch-loading">
+                  <div className="history-fetch-scan" aria-hidden="true">
+                    <span className="history-fetch-ring history-fetch-ring-1" />
+                    <span className="history-fetch-ring history-fetch-ring-2" />
+                    <span className="history-fetch-sweep" />
+                    <span className="history-fetch-core" />
+                  </div>
+                  <div className="history-fetch-bars" aria-hidden="true">
+                    <span className="history-fetch-bar history-fetch-bar-1" />
+                    <span className="history-fetch-bar history-fetch-bar-2" />
+                    <span className="history-fetch-bar history-fetch-bar-3" />
+                    <span className="history-fetch-bar history-fetch-bar-4" />
+                  </div>
+                  <div className="history-fetch-lines" aria-hidden="true">
+                    <span className="history-fetch-line history-fetch-line-1" />
+                    <span className="history-fetch-line history-fetch-line-2" />
+                    <span className="history-fetch-line history-fetch-line-3" />
+                  </div>
+                  <div className="history-fetch-copy">
+                    <strong>
+                      {locale === "en-US"
+                        ? "Scanning archived settlement history"
+                        : "正在扫描历史结算档案"}
+                    </strong>
+                    <span>
+                      {locale === "en-US"
+                        ? "Reconciling settled highs, DEB traces, and baseline forecasts..."
+                        : "正在对齐实测高温、DEB 轨迹与基线预报..."}
+                    </span>
+                  </div>
+                </div>
+              </div>
+            ) : (
+              <>
+                <div className="history-stats">
+                  {error ? (
                 <span style={{ color: "var(--accent-red)" }}>
                   {t("history.error")}
                 </span>
-              ) : !summary.recentData.length ? (
+                  ) : !summary.recentData.length ? (
                 <span style={{ color: "var(--text-muted)" }}>
                   {t("history.empty")}
                 </span>
-              ) : (
+                  ) : (
                 <>
                   <div className="h-stat-card">
                     <span className="label">{t("history.debHitRate")}</span>
@@ -254,9 +347,69 @@ export function HistoryModal() {
                     </span>
                   </div>
                 </>
-              )}
-            </div>
-            {!isLoading && !error && <HistoryChart />}
+                  )}
+                </div>
+                {!error && <HistoryChart />}
+                {!error && settledPeakRows.length > 0 && (
+              <div className="history-peak-reference">
+                <div className="history-peak-reference-title">
+                  {locale === "en-US"
+                    ? "Peak-12h DEB Reference (Approx.)"
+                    : "峰值前 12 小时 DEB 参考（近似）"}
+                </div>
+                <div className="history-peak-reference-scroll">
+                  {settledPeakRows.map((row) => (
+                    <div key={row.date} className="history-peak-reference-row">
+                      <div className="history-peak-reference-date">
+                        {row.date}
+                      </div>
+                      <div className="history-peak-reference-meta">
+                        <div>
+                          {locale === "en-US" ? "Peak ref" : "峰值参考"}:{" "}
+                          <span style={{ color: "var(--text-primary)" }}>
+                            {row.actual}
+                            {store.selectedDetail?.temp_symbol || "°C"} @{" "}
+                            {row.actual_peak_time}
+                          </span>
+                        </div>
+                        <div>
+                          {locale === "en-US" ? "DEB@-12h" : "峰值前12小时 DEB"}:{" "}
+                          <span style={{ color: "var(--text-primary)" }}>
+                            {row.deb_at_peak_minus_12h}
+                            {store.selectedDetail?.temp_symbol || "°C"} @{" "}
+                            {row.deb_at_peak_minus_12h_time}
+                          </span>
+                        </div>
+                        <div>
+                          {locale === "en-US" ? "Actual" : "最终实测"}:{" "}
+                          <span style={{ color: "var(--text-primary)" }}>
+                            {row.actual}
+                            {store.selectedDetail?.temp_symbol || "°C"}
+                          </span>
+                        </div>
+                        <div>
+                          {locale === "en-US" ? "Error" : "误差"}:{" "}
+                          <span
+                            style={{
+                              color:
+                                (row.deb_at_peak_minus_12h_error ?? 0) > 0
+                                  ? "#f59e0b"
+                                  : "#34d399",
+                            }}
+                          >
+                            {row.deb_at_peak_minus_12h_error != null
+                              ? `${row.deb_at_peak_minus_12h_error > 0 ? "+" : ""}${row.deb_at_peak_minus_12h_error}${store.selectedDetail?.temp_symbol || "°C"}`
+                              : "--"}
+                          </span>
+                        </div>
+                      </div>
+                    </div>
+                  ))}
+                </div>
+              </div>
+                )}
+              </>
+            )}
           </div>
         </div>
       )}

frontend/components/dashboard/IntradaySignalScene.tsx

@@ -0,0 +1,217 @@
+"use client";
+
+import { useEffect, useRef } from "react";
+import * as THREE from "three";
+import { usePrefersReducedMotion } from "@/hooks/usePrefersReducedMotion";
+
+export interface IntradaySignalMetric {
+  key: string;
+  label: string;
+  value: string;
+  hint: string;
+  fill: number | null;
+  tone: string;
+}
+
+function clamp(value: number, min: number, max: number) {
+  return Math.min(Math.max(value, min), max);
+}
+
+function getToneColor(tone: string) {
+  if (tone === "cyan") return "#22d3ee";
+  if (tone === "blue") return "#60a5fa";
+  if (tone === "amber") return "#f59e0b";
+  return "#94a3b8";
+}
+
+export function IntradaySignalScene({
+  metrics,
+  score,
+}: {
+  metrics: IntradaySignalMetric[];
+  score: number;
+}) {
+  const containerRef = useRef<HTMLDivElement | null>(null);
+  const prefersReducedMotion = usePrefersReducedMotion();
+
+  useEffect(() => {
+    const host = containerRef.current;
+    if (!host) return;
+
+    const renderer = new THREE.WebGLRenderer({
+      alpha: true,
+      antialias: true,
+      powerPreference: "low-power",
+    });
+    renderer.setClearColor(0x000000, 0);
+    renderer.setPixelRatio(Math.min(window.devicePixelRatio || 1, 1.5));
+
+    const scene = new THREE.Scene();
+    const camera = new THREE.PerspectiveCamera(34, 1, 0.1, 100);
+    camera.position.set(0, 2.8, 7.2);
+    camera.lookAt(0, 1.2, 0);
+
+    const ambient = new THREE.AmbientLight(0xbfe8ff, 1.25);
+    const keyLight = new THREE.PointLight(0x67e8f9, 22, 18, 2);
+    keyLight.position.set(-3.8, 5.6, 4.8);
+    const warmLight = new THREE.PointLight(0xf59e0b, 12, 16, 2);
+    warmLight.position.set(4.2, 2.8, 4);
+    scene.add(ambient, keyLight, warmLight);
+
+    const stage = new THREE.Group();
+    scene.add(stage);
+
+    const floor = new THREE.Mesh(
+      new THREE.CylinderGeometry(3.3, 3.8, 0.12, 48),
+      new THREE.MeshStandardMaterial({
+        color: new THREE.Color(score >= 0 ? "#10263b" : "#2c1d12"),
+        emissive: new THREE.Color(score >= 0 ? "#0e7490" : "#b45309"),
+        emissiveIntensity: 0.18 + clamp(Math.abs(score) / 8, 0, 0.24),
+        metalness: 0.2,
+        roughness: 0.78,
+      }),
+    );
+    floor.position.y = -0.12;
+    stage.add(floor);
+
+    const ring = new THREE.Mesh(
+      new THREE.TorusGeometry(2.8, 0.03, 18, 100),
+      new THREE.MeshBasicMaterial({
+        color: new THREE.Color(score >= 0 ? "#22d3ee" : "#f59e0b"),
+        transparent: true,
+        opacity: 0.5,
+      }),
+    );
+    ring.rotation.x = Math.PI / 2;
+    ring.position.y = 0.03;
+    stage.add(ring);
+
+    const barGeometry = new THREE.BoxGeometry(0.8, 1, 0.8);
+    const capGeometry = new THREE.SphereGeometry(0.16, 16, 16);
+    const bars: Array<{
+      mesh: THREE.Mesh;
+      cap: THREE.Mesh;
+      glow: THREE.Mesh;
+      baseY: number;
+      targetHeight: number;
+    }> = [];
+
+    const xPositions = [-1.8, -0.6, 0.6, 1.8];
+    metrics.slice(0, 4).forEach((metric, index) => {
+      const height = 0.5 + ((metric.fill ?? 20) / 100) * 2.8;
+      const color = new THREE.Color(getToneColor(metric.tone));
+      const material = new THREE.MeshStandardMaterial({
+        color,
+        emissive: color,
+        emissiveIntensity: 0.22,
+        metalness: 0.14,
+        roughness: 0.38,
+      });
+      const mesh = new THREE.Mesh(barGeometry, material);
+      mesh.position.set(xPositions[index] || 0, height / 2, 0);
+      mesh.scale.y = height;
+      stage.add(mesh);
+
+      const cap = new THREE.Mesh(
+        capGeometry,
+        new THREE.MeshBasicMaterial({
+          color,
+          transparent: true,
+          opacity: 0.95,
+        }),
+      );
+      cap.position.set(mesh.position.x, height + 0.2, 0);
+      stage.add(cap);
+
+      const glow = new THREE.Mesh(
+        new THREE.CylinderGeometry(0.46, 0.58, 0.08, 32),
+        new THREE.MeshBasicMaterial({
+          color,
+          transparent: true,
+          opacity: 0.22,
+        }),
+      );
+      glow.position.set(mesh.position.x, 0.06, 0);
+      stage.add(glow);
+
+      bars.push({ mesh, cap, glow, baseY: cap.position.y, targetHeight: height });
+    });
+
+    const resize = () => {
+      const width = Math.max(host.clientWidth, 1);
+      const height = Math.max(host.clientHeight, 1);
+      renderer.setSize(width, height, false);
+      camera.aspect = width / height;
+      camera.updateProjectionMatrix();
+    };
+
+    resize();
+    host.appendChild(renderer.domElement);
+
+    const clock = new THREE.Clock();
+    let frameId = 0;
+
+    const renderFrame = () => {
+      frameId = window.requestAnimationFrame(renderFrame);
+      const elapsed = clock.getElapsedTime();
+      stage.rotation.y = Math.sin(elapsed * 0.35) * 0.16;
+      ring.material.opacity = 0.38 + Math.sin(elapsed * 0.8) * 0.08;
+
+      bars.forEach((bar, index) => {
+        const pulse = prefersReducedMotion
+          ? 0
+          : Math.sin(elapsed * 1.5 + index * 0.8) * 0.08;
+        bar.cap.position.y = bar.baseY + pulse;
+        bar.glow.scale.x = 1 + Math.sin(elapsed * 1.2 + index) * 0.06;
+        bar.glow.scale.z = 1 + Math.sin(elapsed * 1.2 + index) * 0.06;
+      });
+
+      renderer.render(scene, camera);
+    };
+
+    const observer = new ResizeObserver(resize);
+    observer.observe(host);
+    frameId = window.requestAnimationFrame(renderFrame);
+
+    return () => {
+      observer.disconnect();
+      window.cancelAnimationFrame(frameId);
+      stage.traverse((child) => {
+        if (child instanceof THREE.Mesh) {
+          child.geometry.dispose();
+          if (Array.isArray(child.material)) {
+            child.material.forEach((material) => material.dispose());
+          } else {
+            child.material.dispose();
+          }
+        }
+      });
+      renderer.dispose();
+      if (renderer.domElement.parentNode === host) {
+        host.removeChild(renderer.domElement);
+      }
+    };
+  }, [metrics, prefersReducedMotion, score]);
+
+  return (
+    <div className="intraday-scene-shell">
+      <div ref={containerRef} className="intraday-scene-frame" aria-hidden="true" />
+      <div className="intraday-scene-legend">
+        {metrics.slice(0, 4).map((metric) => (
+          <div key={metric.key} className="intraday-scene-chip">
+            <span
+              className="intraday-scene-chip-dot"
+              style={{ backgroundColor: getToneColor(metric.tone) }}
+            />
+            <div className="intraday-scene-chip-copy">
+              <strong>{metric.label}</strong>
+              <span>
+                {metric.value} · {metric.hint}
+              </span>
+            </div>
+          </div>
+        ))}
+      </div>
+    </div>
+  );
+}

frontend/components/dashboard/MapCanvas.tsx

@@ -21,8 +21,7 @@ export function MapCanvas() {
     selectedDetail: store.selectedDetail,
     suspendMotion:
       Boolean(store.futureModalDate) ||
-      store.historyState.isOpen ||
-      store.isGuideOpen,
+      store.historyState.isOpen,
     isLoadingDetail: store.loadingState.cityDetail,
   });
 

frontend/components/dashboard/PanelSections.tsx

@@ -19,7 +19,6 @@ import {
   getRiskBadgeLabel,
   getTemperatureChartData,
   getWeatherSummary,
-  parseAiAnalysis,
 } from "@/lib/dashboard-utils";
 
 function EmptyState({ text }: { text: string }) {
@@ -610,6 +609,7 @@ export function ModelForecast({
     ([, value]) =>
       value !== null && value !== undefined && Number.isFinite(Number(value)),
   );
+  const hasSingleModelOnly = modelEntries.length === 1;
 
   // 如果没有任何数值，给出提示
   if (modelEntries.length === 0) {
@@ -638,6 +638,19 @@ export function ModelForecast({
     <section className="models-section">
       {!hideTitle && <h3>{t("section.models")}</h3>}
       <div className="model-bars">
+        {hasSingleModelOnly && (
+          <div
+            style={{
+              color: "var(--text-secondary)",
+              fontSize: "11px",
+              marginBottom: "8px",
+            }}
+          >
+            {locale === "en-US"
+              ? "Single-model fallback: waiting for the rest of the model cluster."
+              : "当前处于单模型回退，其他模型结果还没回传。"}
+          </div>
+        )}
         {modelEntries
           .sort((a, b) => Number(b[1] || 0) - Number(a[1] || 0))
           .map(([name, value]) => {
@@ -711,9 +724,28 @@ export function ForecastTable() {
   if (!data) return null;
 
   const daily = data.forecast?.daily || [];
+  const isSparseDaily = daily.length <= 1;
+  const resolveForecastTemp = (date: string, fallback: number | null | undefined) => {
+    const debPrediction = data.multi_model_daily?.[date]?.deb?.prediction;
+    return debPrediction ?? fallback ?? null;
+  };
   return (
     <section className="forecast-section">
       <h3>{t("forecast.title")}</h3>
+      {isSparseDaily && (
+        <div
+          className="forecast-inline-note"
+          style={{
+            color: "var(--text-secondary)",
+            fontSize: "12px",
+            marginBottom: "10px",
+          }}
+        >
+          {store.loadingState.cityDetail
+            ? "多日预报同步中，正在刷新完整日序列。"
+            : "当前只收到当日预报，其他日期结果暂未回传。"}
+        </div>
+      )}
       <div className="forecast-table">
         {daily.length === 0 ? (
           <EmptyState text={t("forecast.empty")} />
@@ -744,7 +776,7 @@ export function ForecastTable() {
                     : day.date.substring(5).replace("-", "/")}
                 </div>
                 <div className="f-temp">
-                  {day.max_temp}
+                  {resolveForecastTemp(day.date, day.max_temp)}
                   {data.temp_symbol}
                 </div>
               </button>
@@ -756,35 +788,6 @@ export function ForecastTable() {
   );
 }
 
-export function AiAnalysis() {
-  const { data } = useCityData();
-  const { t } = useI18n();
-  if (!data) return null;
-  const ai = parseAiAnalysis(data.ai_analysis);
-
-  return (
-    <section className="ai-section">
-      <h3>{t("section.ai")}</h3>
-      <div className="ai-box">
-        {!ai.summary && ai.bullets.length === 0 ? (
-          <span className="ai-placeholder">{t("section.aiEmpty")}</span>
-        ) : (
-          <>
-            {ai.summary && <div className="ai-summary">{ai.summary}</div>}
-            {ai.bullets.length > 0 && (
-              <ul className="ai-list">
-                {ai.bullets.map((item) => (
-                  <li key={item}>{item}</li>
-                ))}
-              </ul>
-            )}
-          </>
-        )}
-      </div>
-    </section>
-  );
-}
-
 export function RiskInfo() {
   const { data } = useCityData();
   const { t } = useI18n();

frontend/components/dashboard/PolyWeatherDashboard.tsx

@@ -1,7 +1,6 @@
 "use client";
-
-import { useEffect } from "react";
 import dynamic from "next/dynamic";
+import { useEffect } from "react";
 import styles from "./Dashboard.module.css";
 import {
   DashboardStoreProvider,
@@ -21,15 +20,6 @@ const MapCanvas = dynamic(
   },
 );
 
-const GuideModal = dynamic(
-  () =>
-    import("@/components/dashboard/GuideModal").then((module) => module.GuideModal),
-  {
-    ssr: false,
-    loading: () => null,
-  },
-);
-
 const HistoryModal = dynamic(
   () =>
     import("@/components/dashboard/HistoryModal").then(
@@ -55,6 +45,11 @@ const FutureForecastModal = dynamic(
 function DashboardScreen() {
   const store = useDashboardStore();
   const { t } = useI18n();
+  const activeCityName =
+    store.selectedDetail?.display_name ||
+    store.cities.find((city) => city.name === store.selectedCity)?.display_name ||
+    store.selectedCity ||
+    "";
 
   useEffect(() => {
     const onKeyDown = (event: KeyboardEvent) => {
@@ -67,10 +62,6 @@ function DashboardScreen() {
         store.closeHistory();
         return;
       }
-      if (store.isGuideOpen) {
-        store.closeGuide();
-        return;
-      }
       if (store.isPanelOpen) {
         store.closePanel();
       }
@@ -85,7 +76,6 @@ function DashboardScreen() {
   // Avoid full-page flashing on initial load; only show this overlay for manual refresh.
   const showLoading =
     store.loadingState.cities ||
-    store.loadingState.cityDetail ||
     store.loadingState.refresh;
 
   return (
@@ -94,13 +84,54 @@ function DashboardScreen() {
       <HeaderBar />
       <CitySidebar />
       <DetailPanel />
-      {store.isGuideOpen && <GuideModal />}
+      {store.loadingState.cityDetail && activeCityName ? (
+        <div className="city-loading-toast" role="status" aria-live="polite">
+          <span className="city-loading-dot" aria-hidden="true" />
+          <span className="city-loading-copy">
+            {t("dashboard.loading")} {activeCityName}
+          </span>
+        </div>
+      ) : null}
       {store.historyState.isOpen && <HistoryModal />}
       {store.futureModalDate && <FutureForecastModal />}
       {showLoading && (
         <div className="loading-overlay">
-          <div className="loading-spinner" />
-          <span>{t("dashboard.loading")}</span>
+          <div className="loading-card">
+            <div className="loading-clouds" aria-hidden="true">
+              <span className="loading-cloud loading-cloud-1" />
+              <span className="loading-cloud loading-cloud-2" />
+            </div>
+            <div className="loading-windfield" aria-hidden="true">
+              <span className="loading-windline loading-windline-1" />
+              <span className="loading-windline loading-windline-2" />
+              <span className="loading-windline loading-windline-3" />
+            </div>
+            <div className="loading-radar" aria-hidden="true">
+              <div className="loading-radar-core" />
+              <div className="loading-radar-ring loading-radar-ring-1" />
+              <div className="loading-radar-ring loading-radar-ring-2" />
+              <div className="loading-radar-sweep" />
+              <div className="loading-radar-blip loading-radar-blip-1" />
+              <div className="loading-radar-blip loading-radar-blip-2" />
+            </div>
+            <div className="loading-thermals" aria-hidden="true">
+              <span className="loading-thermal loading-thermal-1" />
+              <span className="loading-thermal loading-thermal-2" />
+              <span className="loading-thermal loading-thermal-3" />
+              <span className="loading-thermal loading-thermal-4" />
+            </div>
+            <div className="loading-drizzle" aria-hidden="true">
+              <span className="loading-drizzle-drop loading-drizzle-drop-1" />
+              <span className="loading-drizzle-drop loading-drizzle-drop-2" />
+              <span className="loading-drizzle-drop loading-drizzle-drop-3" />
+              <span className="loading-drizzle-drop loading-drizzle-drop-4" />
+              <span className="loading-drizzle-drop loading-drizzle-drop-5" />
+            </div>
+            <div className="loading-copy">
+              <strong>PolyWeather</strong>
+              <span>{t("dashboard.loading")}</span>
+            </div>
+          </div>
         </div>
       )}
     </div>

frontend/components/dashboard/ProFeaturePaywall.tsx

@@ -1,10 +1,11 @@
 "use client";
 
-import { useMemo, useState } from "react";
+import { useEffect, useMemo, useState } from "react";
 import { useRouter } from "next/navigation";
 import { useI18n } from "@/hooks/useI18n";
 import { useDashboardStore } from "@/hooks/useDashboardStore";
 import { UnlockProOverlay } from "@/components/subscription/UnlockProOverlay";
+import { trackAppEvent } from "@/lib/app-analytics";
 
 const TELEGRAM_GROUP_URL = String(
   process.env.NEXT_PUBLIC_TELEGRAM_GROUP_URL ||
@@ -63,6 +64,14 @@ export function ProFeaturePaywall({
       ? "Sign In to Unlock Pro"
       : "先登录再开通 Pro";
 
+  useEffect(() => {
+    trackAppEvent("paywall_viewed", {
+      entry: "feature_gate",
+      feature,
+      user_state: isAuthenticated ? "logged_in" : "guest",
+    });
+  }, [feature, isAuthenticated]);
+
   return (
     <div className="flex w-full flex-col items-center justify-center py-6 md:py-10 z-30 p-4">
       <UnlockProOverlay

frontend/components/dashboard/WeatherAuraLayer.tsx

@@ -0,0 +1,500 @@
+"use client";
+
+import { CSSProperties, useEffect, useRef, useState } from "react";
+import * as THREE from "three";
+import { useDashboardStore } from "@/hooks/useDashboardStore";
+import { usePrefersReducedMotion } from "@/hooks/usePrefersReducedMotion";
+import { getWeatherAuraProfile } from "@/lib/weather-aura";
+import styles from "./Dashboard.module.css";
+
+function hexToRgba(hex: string, alpha: number) {
+  const sanitized = hex.replace("#", "");
+  const normalized =
+    sanitized.length === 3
+      ? sanitized
+          .split("")
+          .map((char) => `${char}${char}`)
+          .join("")
+      : sanitized.padEnd(6, "0");
+  const numeric = Number.parseInt(normalized, 16);
+  const r = (numeric >> 16) & 255;
+  const g = (numeric >> 8) & 255;
+  const b = numeric & 255;
+  return `rgba(${r}, ${g}, ${b}, ${alpha})`;
+}
+
+export function WeatherAuraLayer() {
+  const store = useDashboardStore();
+  const prefersReducedMotion = usePrefersReducedMotion();
+  const [isDesktop, setIsDesktop] = useState(false);
+  const containerRef = useRef<HTMLDivElement | null>(null);
+
+  const aura = getWeatherAuraProfile(store.selectedDetail, store.cities);
+
+  useEffect(() => {
+    if (typeof window === "undefined" || !window.matchMedia) {
+      return;
+    }
+
+    const mediaQuery = window.matchMedia("(min-width: 1024px)");
+    const apply = () => {
+      setIsDesktop(mediaQuery.matches);
+    };
+
+    apply();
+    mediaQuery.addEventListener("change", apply);
+    return () => {
+      mediaQuery.removeEventListener("change", apply);
+    };
+  }, []);
+
+  useEffect(() => {
+    const host = containerRef.current;
+    if (!host || !isDesktop || prefersReducedMotion) {
+      return;
+    }
+
+    const renderer = new THREE.WebGLRenderer({
+      alpha: true,
+      antialias: true,
+      powerPreference: "low-power",
+    });
+    renderer.setClearColor(0x000000, 0);
+    renderer.setPixelRatio(Math.min(window.devicePixelRatio || 1, 1.5));
+
+    const scene = new THREE.Scene();
+    const camera = new THREE.OrthographicCamera(-1, 1, 1, -1, 0.1, 10);
+    camera.position.z = 2;
+
+    const clock = new THREE.Clock();
+    const cleanupMaterials = new Set<THREE.Material>();
+    const particleGroups: Array<{
+      kind: "flow" | "rain" | "snow" | "fog" | "cloud";
+      geometry: THREE.BufferGeometry;
+      positions: Float32Array;
+      baseY: Float32Array;
+      drift: Float32Array;
+      phase: Float32Array;
+      material: THREE.Material;
+      mesh: THREE.Object3D;
+    }> = [];
+    const effectLights: THREE.Light[] = [];
+    const flashOverlay = new THREE.Mesh(
+      new THREE.PlaneGeometry(2.2, 2.2),
+      new THREE.MeshBasicMaterial({
+        color: new THREE.Color("#e0f2fe"),
+        transparent: true,
+        opacity: 0,
+        blending: THREE.AdditiveBlending,
+      }),
+    );
+    flashOverlay.position.z = -0.3;
+    scene.add(flashOverlay);
+    cleanupMaterials.add(flashOverlay.material as THREE.Material);
+
+    function createParticleField(
+      count: number,
+      pointSize: number,
+      opacity: number,
+      depthShift: number,
+    ) {
+      const geometry = new THREE.BufferGeometry();
+      const positions = new Float32Array(count * 3);
+      const colors = new Float32Array(count * 3);
+      const baseY = new Float32Array(count);
+      const drift = new Float32Array(count);
+      const phase = new Float32Array(count);
+      const primaryColor = new THREE.Color(aura.primary);
+      const secondaryColor = new THREE.Color(aura.secondary);
+      const tertiaryColor = new THREE.Color(aura.tertiary);
+
+      for (let index = 0; index < count; index += 1) {
+        const offset = index * 3;
+        const x = Math.random() * 2.6 - 1.3;
+        const y = Math.random() * 1.8 - 0.9;
+        const z = (Math.random() * 0.8 - 0.4) + depthShift;
+        positions[offset] = x;
+        positions[offset + 1] = y;
+        positions[offset + 2] = z;
+        baseY[index] = y;
+        drift[index] = (0.00045 + Math.random() * 0.0012) * aura.drift;
+        phase[index] = Math.random() * Math.PI * 2;
+
+        const mixedColor = primaryColor
+          .clone()
+          .lerp(secondaryColor, Math.random() * 0.65)
+          .lerp(tertiaryColor, Math.random() * 0.4);
+        colors[offset] = mixedColor.r;
+        colors[offset + 1] = mixedColor.g;
+        colors[offset + 2] = mixedColor.b;
+      }
+
+      geometry.setAttribute("position", new THREE.BufferAttribute(positions, 3));
+      geometry.setAttribute("color", new THREE.BufferAttribute(colors, 3));
+
+      const material = new THREE.PointsMaterial({
+        size: pointSize,
+        transparent: true,
+        opacity,
+        vertexColors: true,
+        depthWrite: false,
+        blending: THREE.AdditiveBlending,
+        sizeAttenuation: true,
+      });
+
+      const points = new THREE.Points(geometry, material);
+      scene.add(points);
+      cleanupMaterials.add(material);
+      particleGroups.push({
+        geometry,
+        positions,
+        baseY,
+        drift,
+        phase,
+        kind: "flow",
+        material,
+        mesh: points,
+      });
+    }
+
+    function createRainField(count: number) {
+      const geometry = new THREE.BufferGeometry();
+      const positions = new Float32Array(count * 3);
+      const baseY = new Float32Array(count);
+      const drift = new Float32Array(count);
+      const phase = new Float32Array(count);
+
+      for (let index = 0; index < count; index += 1) {
+        const offset = index * 3;
+        positions[offset] = Math.random() * 2.8 - 1.4;
+        positions[offset + 1] = Math.random() * 2.2 - 1.1;
+        positions[offset + 2] = Math.random() * 0.4 - 0.2;
+        baseY[index] = positions[offset + 1];
+        drift[index] = (0.018 + Math.random() * 0.016) * aura.effectIntensity;
+        phase[index] = 0.004 + Math.random() * 0.004;
+      }
+
+      geometry.setAttribute("position", new THREE.BufferAttribute(positions, 3));
+      const material = new THREE.PointsMaterial({
+        size: 0.018,
+        color: new THREE.Color("#7dd3fc"),
+        transparent: true,
+        opacity: 0.72,
+        depthWrite: false,
+        blending: THREE.AdditiveBlending,
+      });
+      const points = new THREE.Points(geometry, material);
+      scene.add(points);
+      cleanupMaterials.add(material);
+      particleGroups.push({
+        geometry,
+        positions,
+        baseY,
+        drift,
+        phase,
+        kind: "rain",
+        material,
+        mesh: points,
+      });
+    }
+
+    function createSnowField(count: number) {
+      const geometry = new THREE.BufferGeometry();
+      const positions = new Float32Array(count * 3);
+      const baseY = new Float32Array(count);
+      const drift = new Float32Array(count);
+      const phase = new Float32Array(count);
+
+      for (let index = 0; index < count; index += 1) {
+        const offset = index * 3;
+        positions[offset] = Math.random() * 2.8 - 1.4;
+        positions[offset + 1] = Math.random() * 2.1 - 1.05;
+        positions[offset + 2] = Math.random() * 0.35 - 0.18;
+        baseY[index] = positions[offset + 1];
+        drift[index] = (0.0045 + Math.random() * 0.0045) * aura.effectIntensity;
+        phase[index] = Math.random() * Math.PI * 2;
+      }
+
+      geometry.setAttribute("position", new THREE.BufferAttribute(positions, 3));
+      const material = new THREE.PointsMaterial({
+        size: 0.024,
+        color: new THREE.Color("#f8fafc"),
+        transparent: true,
+        opacity: 0.85,
+        depthWrite: false,
+        blending: THREE.AdditiveBlending,
+      });
+      const points = new THREE.Points(geometry, material);
+      scene.add(points);
+      cleanupMaterials.add(material);
+      particleGroups.push({
+        geometry,
+        positions,
+        baseY,
+        drift,
+        phase,
+        kind: "snow",
+        material,
+        mesh: points,
+      });
+    }
+
+    function createFogField(count: number) {
+      const geometry = new THREE.BufferGeometry();
+      const positions = new Float32Array(count * 3);
+      const baseY = new Float32Array(count);
+      const drift = new Float32Array(count);
+      const phase = new Float32Array(count);
+
+      for (let index = 0; index < count; index += 1) {
+        const offset = index * 3;
+        positions[offset] = Math.random() * 2.6 - 1.3;
+        positions[offset + 1] = Math.random() * 0.9 - 0.45;
+        positions[offset + 2] = Math.random() * 0.45 - 0.2;
+        baseY[index] = positions[offset + 1];
+        drift[index] = (0.0014 + Math.random() * 0.001) * aura.effectIntensity;
+        phase[index] = Math.random() * Math.PI * 2;
+      }
+
+      geometry.setAttribute("position", new THREE.BufferAttribute(positions, 3));
+      const material = new THREE.PointsMaterial({
+        size: 0.12,
+        color: new THREE.Color("#cbd5e1"),
+        transparent: true,
+        opacity: 0.18,
+        depthWrite: false,
+        blending: THREE.AdditiveBlending,
+      });
+      const points = new THREE.Points(geometry, material);
+      scene.add(points);
+      cleanupMaterials.add(material);
+      particleGroups.push({
+        geometry,
+        positions,
+        baseY,
+        drift,
+        phase,
+        kind: "fog",
+        material,
+        mesh: points,
+      });
+    }
+
+    function createCloudField(count: number) {
+      const geometry = new THREE.BufferGeometry();
+      const positions = new Float32Array(count * 3);
+      const baseY = new Float32Array(count);
+      const drift = new Float32Array(count);
+      const phase = new Float32Array(count);
+
+      for (let index = 0; index < count; index += 1) {
+        const offset = index * 3;
+        positions[offset] = Math.random() * 2.7 - 1.35;
+        positions[offset + 1] = Math.random() * 0.75 + 0.1;
+        positions[offset + 2] = Math.random() * 0.3 - 0.15;
+        baseY[index] = positions[offset + 1];
+        drift[index] = (0.0012 + Math.random() * 0.0009) * aura.effectIntensity;
+        phase[index] = Math.random() * Math.PI * 2;
+      }
+
+      geometry.setAttribute("position", new THREE.BufferAttribute(positions, 3));
+      const material = new THREE.PointsMaterial({
+        size: 0.1,
+        color: new THREE.Color("#dbeafe"),
+        transparent: true,
+        opacity: 0.13,
+        depthWrite: false,
+        blending: THREE.AdditiveBlending,
+      });
+      const points = new THREE.Points(geometry, material);
+      scene.add(points);
+      cleanupMaterials.add(material);
+      particleGroups.push({
+        geometry,
+        positions,
+        baseY,
+        drift,
+        phase,
+        kind: "cloud",
+        material,
+        mesh: points,
+      });
+    }
+
+    createParticleField(90, 0.018, aura.particleOpacity * 0.9, -0.1);
+    createParticleField(60, 0.026, aura.particleOpacity * 0.65, 0.08);
+
+    if (aura.effect === "rain" || aura.effect === "storm") {
+      createRainField(aura.effect === "storm" ? 240 : 170);
+    } else if (aura.effect === "snow") {
+      createSnowField(150);
+    } else if (aura.effect === "fog") {
+      createFogField(90);
+    } else if (aura.effect === "cloud" || aura.effect === "wind") {
+      createCloudField(aura.effect === "wind" ? 80 : 54);
+    }
+
+    if (aura.effect === "storm") {
+      const flashLight = new THREE.PointLight(0xdbeafe, 0, 6, 2);
+      flashLight.position.set(0.2, 0.9, 1.1);
+      scene.add(flashLight);
+      effectLights.push(flashLight);
+    }
+
+    const resize = () => {
+      const width = host.clientWidth || window.innerWidth;
+      const height = host.clientHeight || window.innerHeight;
+      renderer.setSize(width, height, false);
+    };
+
+    resize();
+    host.appendChild(renderer.domElement);
+
+    let frameId = 0;
+    let lastFrameAt = 0;
+
+    const renderFrame = (timestamp: number) => {
+      frameId = window.requestAnimationFrame(renderFrame);
+      if (timestamp - lastFrameAt < 40) {
+        return;
+      }
+      lastFrameAt = timestamp;
+
+      const elapsed = clock.getElapsedTime();
+      for (const field of particleGroups) {
+        for (let index = 0; index < field.baseY.length; index += 1) {
+          const offset = index * 3;
+          if (field.kind === "flow") {
+            let nextX = field.positions[offset] + field.drift[index];
+            if (nextX > 1.35) {
+              nextX = -1.35;
+              field.baseY[index] = Math.random() * 1.8 - 0.9;
+            }
+            field.positions[offset] = nextX;
+            field.positions[offset + 1] =
+              field.baseY[index] +
+              Math.sin(elapsed * 0.45 + field.phase[index] + nextX * 2.4) *
+                0.06 *
+                aura.intensity;
+          } else if (field.kind === "rain") {
+            let nextY = field.positions[offset + 1] - field.drift[index];
+            let nextX = field.positions[offset] + field.phase[index] * aura.drift;
+            if (nextY < -1.12 || nextX > 1.45) {
+              nextY = 1.15 + Math.random() * 0.25;
+              nextX = Math.random() * 2.9 - 1.45;
+            }
+            field.positions[offset] = nextX;
+            field.positions[offset + 1] = nextY;
+          } else if (field.kind === "snow") {
+            let nextY = field.positions[offset + 1] - field.drift[index];
+            let nextX =
+              field.positions[offset] +
+              Math.sin(elapsed * 0.9 + field.phase[index]) * 0.0024 * aura.effectIntensity;
+            if (nextY < -1.1) {
+              nextY = 1.12 + Math.random() * 0.2;
+              nextX = Math.random() * 2.8 - 1.4;
+            }
+            field.positions[offset] = nextX;
+            field.positions[offset + 1] = nextY;
+          } else if (field.kind === "fog" || field.kind === "cloud") {
+            let nextX = field.positions[offset] + field.drift[index];
+            if (nextX > 1.38) {
+              nextX = -1.38;
+              field.baseY[index] =
+                field.kind === "cloud"
+                  ? Math.random() * 0.75 + 0.1
+                  : Math.random() * 0.9 - 0.45;
+            }
+            field.positions[offset] = nextX;
+            field.positions[offset + 1] =
+              field.baseY[index] +
+              Math.sin(elapsed * 0.3 + field.phase[index]) *
+                (field.kind === "cloud" ? 0.03 : 0.05);
+          }
+        }
+
+        field.geometry.attributes.position.needsUpdate = true;
+      }
+
+      if (effectLights.length > 0) {
+        const flashPulse = Math.max(0, Math.sin(elapsed * 2.1) - 0.78) * 20;
+        for (const light of effectLights) {
+          if (light instanceof THREE.PointLight) {
+            light.intensity = flashPulse;
+          }
+        }
+        (flashOverlay.material as THREE.MeshBasicMaterial).opacity = Math.min(
+          0.18,
+          flashPulse / 120,
+        );
+      } else {
+        (flashOverlay.material as THREE.MeshBasicMaterial).opacity = 0;
+      }
+
+      renderer.render(scene, camera);
+    };
+
+    frameId = window.requestAnimationFrame(renderFrame);
+    window.addEventListener("resize", resize);
+
+    return () => {
+      window.cancelAnimationFrame(frameId);
+      window.removeEventListener("resize", resize);
+      for (const child of [...scene.children]) {
+        scene.remove(child);
+      }
+      for (const field of particleGroups) {
+        field.geometry.dispose();
+      }
+      cleanupMaterials.forEach((material) => material.dispose());
+      renderer.dispose();
+      if (renderer.domElement.parentNode === host) {
+        host.removeChild(renderer.domElement);
+      }
+    };
+  }, [
+    aura.drift,
+    aura.intensity,
+    aura.particleOpacity,
+    aura.primary,
+    aura.secondary,
+    aura.tertiary,
+    aura.effect,
+    aura.effectIntensity,
+    isDesktop,
+    prefersReducedMotion,
+  ]);
+
+  if (!isDesktop) {
+    return null;
+  }
+
+  const overlayStyle = {
+    backgroundImage: [
+      `radial-gradient(circle at 18% 22%, ${hexToRgba(aura.primary, 0.18 * aura.intensity)}, transparent 32%)`,
+      `radial-gradient(circle at 78% 20%, ${hexToRgba(aura.secondary, 0.14 * aura.intensity)}, transparent 34%)`,
+      `radial-gradient(circle at 52% 78%, ${hexToRgba(aura.tertiary, 0.12 * aura.intensity)}, transparent 38%)`,
+      aura.effect === "rain" || aura.effect === "storm"
+        ? `linear-gradient(180deg, ${hexToRgba("#67e8f9", 0.06 * aura.effectIntensity)}, transparent 45%)`
+        : aura.effect === "snow"
+          ? `linear-gradient(180deg, ${hexToRgba("#e2e8f0", 0.06 * aura.effectIntensity)}, transparent 45%)`
+          : aura.effect === "fog"
+            ? `radial-gradient(circle at 50% 56%, ${hexToRgba("#cbd5e1", 0.08 * aura.effectIntensity)}, transparent 60%)`
+            : aura.effect === "cloud"
+              ? `linear-gradient(180deg, ${hexToRgba("#dbeafe", 0.04 * aura.effectIntensity)}, transparent 40%)`
+              : "none",
+    ].join(", "),
+  } as CSSProperties;
+
+  return (
+    <div
+      ref={containerRef}
+      aria-hidden="true"
+      className={styles.weatherAura}
+      data-reduced-motion={prefersReducedMotion ? "true" : "false"}
+      style={overlayStyle}
+    >
+      <div className={styles.weatherAuraScrim} />
+    </div>
+  );
+}

frontend/components/docs/DocsLayout.module.css

@@ -0,0 +1,344 @@
+.docsShell {
+  min-height: 100vh;
+  color: rgba(226, 232, 240, 0.94);
+}
+
+.docsHeader {
+  position: sticky;
+  top: 0;
+  z-index: 40;
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 16px;
+  padding: 18px 24px;
+  background: rgba(2, 6, 23, 0.82);
+  border-bottom: 1px solid rgba(148, 163, 184, 0.12);
+  backdrop-filter: blur(16px);
+}
+
+.brandWrap {
+  display: flex;
+  align-items: baseline;
+  gap: 12px;
+}
+
+.brandLink {
+  color: #67e8f9;
+  font-size: 1.9rem;
+  font-weight: 800;
+  text-decoration: none;
+}
+
+.brandSubtitle {
+  color: rgba(148, 163, 184, 0.88);
+  font-size: 0.95rem;
+}
+
+.headerActions {
+  display: flex;
+  align-items: center;
+  gap: 10px;
+}
+
+.headerButton,
+.headerGhost {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  min-height: 38px;
+  padding: 0 14px;
+  border-radius: 999px;
+  border: 1px solid rgba(148, 163, 184, 0.18);
+  background: rgba(15, 23, 42, 0.75);
+  color: rgba(226, 232, 240, 0.95);
+  text-decoration: none;
+  font-size: 0.92rem;
+  font-weight: 600;
+}
+
+.headerGhost {
+  background: transparent;
+}
+
+.langSwitch {
+  display: flex;
+  border: 1px solid rgba(148, 163, 184, 0.18);
+  border-radius: 999px;
+  overflow: hidden;
+}
+
+.langButton {
+  min-width: 54px;
+  min-height: 38px;
+  border: 0;
+  background: transparent;
+  color: rgba(148, 163, 184, 0.92);
+  font-weight: 700;
+}
+
+.langButtonActive {
+  background: rgba(34, 211, 238, 0.16);
+  color: #67e8f9;
+}
+
+.docsFrame {
+  display: grid;
+  grid-template-columns: 280px minmax(0, 1fr) 220px;
+  gap: 28px;
+  padding: 24px;
+}
+
+.sidebar {
+  position: sticky;
+  top: 86px;
+  align-self: start;
+  max-height: calc(100vh - 110px);
+  overflow: auto;
+  padding: 20px;
+  border: 1px solid rgba(148, 163, 184, 0.12);
+  border-radius: 20px;
+  background: rgba(15, 23, 42, 0.72);
+}
+
+.sidebarGroup + .sidebarGroup {
+  margin-top: 24px;
+}
+
+.sidebarTitle {
+  margin: 0 0 10px;
+  color: rgba(148, 163, 184, 0.92);
+  font-size: 0.8rem;
+  font-weight: 700;
+  letter-spacing: 0.08em;
+  text-transform: uppercase;
+}
+
+.sidebarLink {
+  display: block;
+  margin-bottom: 6px;
+  padding: 10px 12px;
+  border-radius: 12px;
+  color: rgba(226, 232, 240, 0.88);
+  text-decoration: none;
+  font-size: 0.95rem;
+}
+
+.sidebarLinkActive {
+  background: rgba(34, 211, 238, 0.12);
+  color: #67e8f9;
+}
+
+.content {
+  min-width: 0;
+}
+
+.contentInner {
+  padding: 12px 0 48px;
+}
+
+.pageTitle {
+  margin: 0;
+  font-size: clamp(2.1rem, 4vw, 3.2rem);
+  font-weight: 800;
+  letter-spacing: -0.03em;
+}
+
+.pageDescription {
+  max-width: 820px;
+  margin: 14px 0 0;
+  color: rgba(191, 219, 254, 0.9);
+  font-size: 1.03rem;
+  line-height: 1.75;
+}
+
+.section {
+  margin-top: 40px;
+  scroll-margin-top: 110px;
+}
+
+.sectionTitle {
+  margin: 0 0 16px;
+  font-size: 1.65rem;
+  font-weight: 750;
+}
+
+.paragraph {
+  margin: 0 0 16px;
+  color: rgba(226, 232, 240, 0.94);
+  line-height: 1.9;
+}
+
+.callout {
+  margin: 18px 0;
+  padding: 18px 20px;
+  border: 1px solid rgba(148, 163, 184, 0.16);
+  border-radius: 18px;
+  background: rgba(15, 23, 42, 0.72);
+}
+
+.calloutInfo {
+  border-color: rgba(34, 211, 238, 0.24);
+  background: rgba(8, 47, 73, 0.26);
+}
+
+.calloutWarning {
+  border-color: rgba(251, 191, 36, 0.24);
+  background: rgba(120, 53, 15, 0.2);
+}
+
+.calloutSuccess {
+  border-color: rgba(52, 211, 153, 0.24);
+  background: rgba(6, 78, 59, 0.22);
+}
+
+.calloutTitle {
+  margin: 0 0 8px;
+  font-size: 0.98rem;
+  font-weight: 700;
+}
+
+.calloutText {
+  margin: 0;
+  line-height: 1.8;
+}
+
+.list {
+  margin: 0;
+  padding-left: 20px;
+  color: rgba(226, 232, 240, 0.94);
+  line-height: 1.85;
+}
+
+.list li + li {
+  margin-top: 8px;
+}
+
+.linkCard {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  min-height: 42px;
+  padding: 0 16px;
+  border-radius: 999px;
+  border: 1px solid rgba(34, 211, 238, 0.34);
+  background: rgba(8, 47, 73, 0.3);
+  color: #67e8f9;
+  text-decoration: none;
+  font-weight: 700;
+}
+
+.linkCard:hover {
+  background: rgba(34, 211, 238, 0.12);
+}
+
+.linkCaption {
+  margin: 10px 0 0;
+  color: rgba(148, 163, 184, 0.92);
+  line-height: 1.75;
+}
+
+.toc {
+  position: sticky;
+  top: 86px;
+  align-self: start;
+  padding: 20px;
+  border: 1px solid rgba(148, 163, 184, 0.12);
+  border-radius: 20px;
+  background: rgba(15, 23, 42, 0.64);
+}
+
+.tocTitle {
+  margin: 0 0 12px;
+  color: rgba(148, 163, 184, 0.92);
+  font-size: 0.82rem;
+  font-weight: 700;
+  letter-spacing: 0.08em;
+  text-transform: uppercase;
+}
+
+.tocLink {
+  display: block;
+  color: rgba(226, 232, 240, 0.86);
+  text-decoration: none;
+  line-height: 1.7;
+  font-size: 0.92rem;
+}
+
+.mobileMenuButton {
+  display: none;
+}
+
+.mobileSidebarBackdrop {
+  display: none;
+}
+
+@media (max-width: 1200px) {
+  .docsFrame {
+    grid-template-columns: 260px minmax(0, 1fr);
+  }
+
+  .toc {
+    display: none;
+  }
+}
+
+@media (max-width: 900px) {
+  .docsHeader {
+    align-items: flex-start;
+    flex-direction: column;
+  }
+
+  .docsFrame {
+    grid-template-columns: minmax(0, 1fr);
+  }
+
+  .mobileMenuButton {
+    display: inline-flex;
+  }
+
+  .sidebar {
+    position: fixed;
+    top: 0;
+    left: 0;
+    z-index: 60;
+    width: min(320px, 88vw);
+    height: 100vh;
+    max-height: none;
+    border-radius: 0 20px 20px 0;
+    transform: translateX(-100%);
+    transition: transform 180ms ease-out;
+  }
+
+  .sidebarOpen {
+    transform: translateX(0);
+  }
+
+  .mobileSidebarBackdrop {
+    position: fixed;
+    inset: 0;
+    z-index: 50;
+    background: rgba(2, 6, 23, 0.52);
+    display: block;
+  }
+}
+
+@media (max-width: 640px) {
+  .docsHeader {
+    padding: 16px;
+  }
+
+  .docsFrame {
+    padding: 16px;
+  }
+
+  .brandWrap {
+    flex-direction: column;
+    align-items: flex-start;
+    gap: 4px;
+  }
+
+  .pageDescription {
+    font-size: 0.98rem;
+  }
+}

frontend/components/docs/DocsScreen.tsx

@@ -0,0 +1,197 @@
+"use client";
+
+import Link from "next/link";
+import { useMemo, useState } from "react";
+import { usePathname } from "next/navigation";
+import clsx from "clsx";
+import styles from "./DocsLayout.module.css";
+import {
+  DocsLocale,
+  DocsPage,
+  DocsPageContent,
+} from "@/content/docs/docs";
+import { DOCS_GROUPS } from "@/content/docs/docs.config";
+import { DOCS_PAGES } from "@/content/docs/docs";
+import { useI18n } from "@/hooks/useI18n";
+
+function DocsHeader() {
+  const { locale, setLocale } = useI18n();
+
+  return (
+    <header className={styles.docsHeader}>
+      <div className={styles.brandWrap}>
+        <Link href="/" className={styles.brandLink}>
+          PolyWeather
+        </Link>
+        <span className={styles.brandSubtitle}>
+          {locale === "zh-CN" ? "产品文档中心" : "Product Documentation"}
+        </span>
+      </div>
+
+      <div className={styles.headerActions}>
+        <Link href="/" className={styles.headerGhost}>
+          {locale === "zh-CN" ? "返回主站" : "Back to App"}
+        </Link>
+        <div className={styles.langSwitch} role="group" aria-label="Language switch">
+          <button
+            type="button"
+            className={clsx(styles.langButton, locale === "zh-CN" && styles.langButtonActive)}
+            onClick={() => setLocale("zh-CN")}
+          >
+            中文
+          </button>
+          <button
+            type="button"
+            className={clsx(styles.langButton, locale === "en-US" && styles.langButtonActive)}
+            onClick={() => setLocale("en-US")}
+          >
+            EN
+          </button>
+        </div>
+      </div>
+    </header>
+  );
+}
+
+function DocsSidebar({
+  currentSlug,
+  locale,
+  open,
+  onClose,
+}: {
+  currentSlug: string;
+  locale: DocsLocale;
+  open: boolean;
+  onClose: () => void;
+}) {
+  return (
+    <>
+      {open && <button type="button" className={styles.mobileSidebarBackdrop} onClick={onClose} aria-label="Close menu" />}
+      <aside className={clsx(styles.sidebar, open && styles.sidebarOpen)}>
+        {DOCS_GROUPS.map((group) => {
+          const pages = DOCS_PAGES.filter((page) => page.group === group.id);
+          return (
+            <div key={group.id} className={styles.sidebarGroup}>
+              <div className={styles.sidebarTitle}>{group.title[locale]}</div>
+              {pages.map((page) => {
+                const title = page.content[locale].title;
+                const href = `/docs/${page.slug}`;
+                return (
+                  <Link
+                    key={page.slug}
+                    href={href}
+                    className={clsx(styles.sidebarLink, currentSlug === page.slug && styles.sidebarLinkActive)}
+                    onClick={onClose}
+                  >
+                    {title}
+                  </Link>
+                );
+              })}
+            </div>
+          );
+        })}
+      </aside>
+    </>
+  );
+}
+
+function DocsToc({ page, locale }: { page: DocsPageContent; locale: DocsLocale }) {
+  return (
+    <aside className={styles.toc}>
+      <div className={styles.tocTitle}>{locale === "zh-CN" ? "本页目录" : "On this page"}</div>
+      {page.sections.map((section) => (
+        <a key={section.id} href={`#${section.id}`} className={styles.tocLink}>
+          {section.title}
+        </a>
+      ))}
+    </aside>
+  );
+}
+
+function BlockRenderer({ block }: { block: DocsPageContent["sections"][number]["blocks"][number] }) {
+  switch (block.type) {
+    case "paragraph":
+      return <p className={styles.paragraph}>{block.text}</p>;
+    case "callout":
+      return (
+        <div className={clsx(styles.callout, block.tone === "warning" && styles.calloutWarning, block.tone === "success" && styles.calloutSuccess, (!block.tone || block.tone === "info") && styles.calloutInfo)}>
+          {block.title ? <div className={styles.calloutTitle}>{block.title}</div> : null}
+          <p className={styles.calloutText}>{block.text}</p>
+        </div>
+      );
+    case "bullets":
+    case "steps":
+      return (
+        <ul className={styles.list}>
+          {block.items.map((item) => (
+            <li key={item}>{item}</li>
+          ))}
+        </ul>
+      );
+    case "link":
+      return (
+        <div>
+          <a
+            href={block.href}
+            target="_blank"
+            rel="noreferrer"
+            className={styles.linkCard}
+          >
+            {block.label}
+          </a>
+          {block.caption ? <p className={styles.linkCaption}>{block.caption}</p> : null}
+        </div>
+      );
+    case "image":
+      return (
+        <figure>
+          <img src={block.src} alt={block.alt} />
+          {block.caption ? <figcaption>{block.caption}</figcaption> : null}
+        </figure>
+      );
+    default:
+      return null;
+  }
+}
+
+export function DocsScreen({ page }: { page: DocsPage }) {
+  const pathname = usePathname();
+  const { locale } = useI18n();
+  const [mobileSidebarOpen, setMobileSidebarOpen] = useState(false);
+  const localizedPage = useMemo(() => page.content[locale], [locale, page]);
+  const currentSlug = pathname?.split("/").filter(Boolean).at(-1) || page.slug;
+
+  return (
+    <div className={styles.docsShell}>
+      <DocsHeader />
+      <div className={styles.docsFrame}>
+        <DocsSidebar
+          currentSlug={currentSlug}
+          locale={locale}
+          open={mobileSidebarOpen}
+          onClose={() => setMobileSidebarOpen(false)}
+        />
+
+        <main className={styles.content}>
+          <div className={styles.contentInner}>
+            <button type="button" className={clsx(styles.headerButton, styles.mobileMenuButton)} onClick={() => setMobileSidebarOpen(true)}>
+              {locale === "zh-CN" ? "打开导航" : "Open navigation"}
+            </button>
+            <h1 className={styles.pageTitle}>{localizedPage.title}</h1>
+            <p className={styles.pageDescription}>{localizedPage.description}</p>
+            {localizedPage.sections.map((section) => (
+              <section key={section.id} id={section.id} className={styles.section}>
+                <h2 className={styles.sectionTitle}>{section.title}</h2>
+                {section.blocks.map((block, index) => (
+                  <BlockRenderer key={`${section.id}-${index}`} block={block} />
+                ))}
+              </section>
+            ))}
+          </div>
+        </main>
+
+        <DocsToc page={localizedPage} locale={locale} />
+      </div>
+    </div>
+  );
+}

frontend/components/observability/WebVitalsReporter.tsx

@@ -4,10 +4,16 @@ import { usePathname } from "next/navigation";
 import { useReportWebVitals } from "next/web-vitals";
 
 const TRACKED_METRICS = new Set(["INP", "LCP", "FCP"]);
+const WEB_VITALS_ENABLED =
+  process.env.NEXT_PUBLIC_POLYWEATHER_WEB_VITALS === "true";
 
 export function WebVitalsReporter() {
   const pathname = usePathname();
 
+  if (!WEB_VITALS_ENABLED) {
+    return null;
+  }
+
   useReportWebVitals((metric) => {
     if (!TRACKED_METRICS.has(metric.name)) {
       return;

frontend/components/ops/TruthHistoryDashboard.tsx

@@ -0,0 +1,269 @@
+"use client";
+
+import Link from "next/link";
+import { useCallback, useEffect, useMemo, useState } from "react";
+import { RefreshCcw } from "lucide-react";
+import { Badge } from "@/components/ui/badge";
+import { Button } from "@/components/ui/button";
+import { Card, CardContent, CardDescription, CardHeader, CardTitle } from "@/components/ui/card";
+
+type TruthHistoryItem = {
+  city: string;
+  display_name?: string;
+  target_date: string;
+  actual_high?: number | null;
+  settlement_source?: string | null;
+  settlement_station_code?: string | null;
+  settlement_station_label?: string | null;
+  truth_version?: string | null;
+  updated_by?: string | null;
+  truth_updated_at?: number | null;
+  is_final?: boolean | null;
+};
+
+type TruthHistoryPayload = {
+  items?: TruthHistoryItem[];
+  available_cities?: Array<{ city: string; name?: string }>;
+  filters?: {
+    city?: string | null;
+    date_from?: string | null;
+    date_to?: string | null;
+    limit?: number;
+  };
+  filtered_count?: number;
+};
+
+function formatUnixDateTime(value?: number | null) {
+  if (!value) return "-";
+  const date = new Date(value * 1000);
+  if (Number.isNaN(date.getTime())) return "-";
+  return date.toLocaleString("zh-CN", { hour12: false });
+}
+
+async function readJson<T>(url: string): Promise<T> {
+  const response = await fetch(url, { cache: "no-store" });
+  if (!response.ok) {
+    const raw = await response.text();
+    throw new Error(`${url} -> HTTP ${response.status} ${raw.slice(0, 180)}`);
+  }
+  return response.json() as Promise<T>;
+}
+
+export function TruthHistoryDashboard() {
+  const [city, setCity] = useState("");
+  const [dateFrom, setDateFrom] = useState("");
+  const [dateTo, setDateTo] = useState("");
+  const [limit, setLimit] = useState("200");
+  const [payload, setPayload] = useState<TruthHistoryPayload | null>(null);
+  const [loading, setLoading] = useState(true);
+  const [error, setError] = useState<string | null>(null);
+
+  const load = useCallback(async () => {
+    setLoading(true);
+    setError(null);
+    try {
+      const url = new URL("/api/ops/truth-history", window.location.origin);
+      if (city.trim()) url.searchParams.set("city", city.trim());
+      if (dateFrom.trim()) url.searchParams.set("date_from", dateFrom.trim());
+      if (dateTo.trim()) url.searchParams.set("date_to", dateTo.trim());
+      if (limit.trim()) url.searchParams.set("limit", limit.trim());
+      const data = await readJson<TruthHistoryPayload>(url.toString());
+      setPayload(data);
+    } catch (loadError) {
+      setError(String(loadError));
+    } finally {
+      setLoading(false);
+    }
+  }, [city, dateFrom, dateTo, limit]);
+
+  useEffect(() => {
+    void load();
+  }, [load]);
+
+  const items = payload?.items || [];
+  const availableCities = payload?.available_cities || [];
+  const stats = useMemo(() => {
+    const uniqueCities = new Set(items.map((item) => item.city)).size;
+    const finalCount = items.filter((item) => item.is_final).length;
+    return {
+      rows: items.length,
+      filtered: payload?.filtered_count ?? items.length,
+      uniqueCities,
+      finalCount,
+    };
+  }, [items, payload?.filtered_count]);
+
+  return (
+    <main className="min-h-screen bg-slate-950 px-3 py-6 text-slate-100 sm:px-6 sm:py-8 lg:px-8">
+      <div className="mx-auto flex max-w-7xl flex-col gap-5 sm:gap-6">
+        <section className="rounded-3xl border border-slate-800 bg-slate-900/80 p-4 shadow-2xl backdrop-blur-xl sm:p-6">
+          <div className="flex flex-col gap-4 lg:flex-row lg:items-end lg:justify-between">
+            <div className="space-y-3">
+              <div className="flex flex-wrap items-center gap-3">
+                <Badge variant="secondary">Ops</Badge>
+                <Badge variant="secondary">Truth History</Badge>
+                <Link
+                  href="/ops"
+                  className="inline-flex items-center rounded-full border border-slate-700 bg-slate-950/70 px-3 py-1 text-xs font-semibold text-slate-300 transition hover:border-cyan-400/50 hover:text-white"
+                >
+                  返回 /ops
+                </Link>
+              </div>
+              <div>
+                <h1 className="text-2xl font-black tracking-tight sm:text-3xl">真值历史浏览</h1>
+                <p className="mt-2 max-w-3xl text-sm text-slate-400">
+                  面向后台运营/研究的历史真值表格页，支持按城市和日期范围过滤，直接查看最终 `actual_high` 与来源口径。
+                </p>
+              </div>
+            </div>
+            <Button onClick={() => void load()} disabled={loading} className="gap-2">
+              <RefreshCcw className="h-4 w-4" />
+              {loading ? "加载中" : "刷新"}
+            </Button>
+          </div>
+        </section>
+
+        <section className="grid gap-4 md:grid-cols-2 xl:grid-cols-4">
+          <Card>
+            <CardHeader>
+              <CardTitle>当前结果</CardTitle>
+              <CardDescription>本次筛选实际返回的记录条数。</CardDescription>
+            </CardHeader>
+            <CardContent className="text-2xl font-black text-slate-100">{stats.rows}</CardContent>
+          </Card>
+          <Card>
+            <CardHeader>
+              <CardTitle>匹配总数</CardTitle>
+              <CardDescription>过滤后总命中条数，返回结果受 limit 限制。</CardDescription>
+            </CardHeader>
+            <CardContent className="text-2xl font-black text-slate-100">{stats.filtered}</CardContent>
+          </Card>
+          <Card>
+            <CardHeader>
+              <CardTitle>覆盖城市</CardTitle>
+              <CardDescription>本次结果涉及的城市数量。</CardDescription>
+            </CardHeader>
+            <CardContent className="text-2xl font-black text-slate-100">{stats.uniqueCities}</CardContent>
+          </Card>
+          <Card>
+            <CardHeader>
+              <CardTitle>Final Rows</CardTitle>
+              <CardDescription>当前返回里标记为最终真值的条数。</CardDescription>
+            </CardHeader>
+            <CardContent className="text-2xl font-black text-slate-100">{stats.finalCount}</CardContent>
+          </Card>
+        </section>
+
+        <Card>
+          <CardHeader>
+            <CardTitle>筛选器</CardTitle>
+            <CardDescription>按 city / date range 查历史真值。</CardDescription>
+          </CardHeader>
+          <CardContent className="grid gap-3 lg:grid-cols-[1.4fr_1fr_1fr_160px_auto]">
+            <select
+              value={city}
+              onChange={(event) => setCity(event.target.value)}
+              className="rounded-2xl border border-slate-700 bg-slate-950 px-3 py-2 text-sm text-slate-200"
+            >
+              <option value="">全部城市</option>
+              {availableCities.map((item) => (
+                <option key={item.city} value={item.city}>
+                  {item.name || item.city}
+                </option>
+              ))}
+            </select>
+            <input
+              type="date"
+              value={dateFrom}
+              onChange={(event) => setDateFrom(event.target.value)}
+              className="rounded-2xl border border-slate-700 bg-slate-950 px-3 py-2 text-sm text-slate-200"
+            />
+            <input
+              type="date"
+              value={dateTo}
+              onChange={(event) => setDateTo(event.target.value)}
+              className="rounded-2xl border border-slate-700 bg-slate-950 px-3 py-2 text-sm text-slate-200"
+            />
+            <input
+              type="number"
+              min={1}
+              max={1000}
+              value={limit}
+              onChange={(event) => setLimit(event.target.value)}
+              className="rounded-2xl border border-slate-700 bg-slate-950 px-3 py-2 text-sm text-slate-200"
+            />
+            <Button onClick={() => void load()} disabled={loading}>
+              应用筛选
+            </Button>
+          </CardContent>
+        </Card>
+
+        {error ? (
+          <Card className="border-rose-500/30 bg-rose-500/10">
+            <CardHeader>
+              <CardTitle className="text-rose-300">加载失败</CardTitle>
+              <CardDescription className="text-rose-200/80">{error}</CardDescription>
+            </CardHeader>
+          </Card>
+        ) : null}
+
+        <Card>
+          <CardHeader>
+            <CardTitle>历史真值表</CardTitle>
+            <CardDescription>
+              字段包括 `actual_high`、`settlement_source`、`station_code`、`truth_version`、`updated_by`、`updated_at`。
+            </CardDescription>
+          </CardHeader>
+          <CardContent>
+            <div className="overflow-x-auto rounded-2xl border border-slate-800 bg-slate-950/70">
+              <table className="min-w-full divide-y divide-slate-800 text-left text-sm">
+                <thead className="bg-slate-900/80 text-xs uppercase tracking-[0.14em] text-slate-500">
+                  <tr>
+                    <th className="px-4 py-3">Date</th>
+                    <th className="px-4 py-3">City</th>
+                    <th className="px-4 py-3">Actual</th>
+                    <th className="px-4 py-3">Source</th>
+                    <th className="px-4 py-3">Station</th>
+                    <th className="px-4 py-3">Version</th>
+                    <th className="px-4 py-3">Updated By</th>
+                    <th className="px-4 py-3">Updated At</th>
+                  </tr>
+                </thead>
+                <tbody className="divide-y divide-slate-800">
+                  {items.map((item) => (
+                    <tr key={`${item.city}-${item.target_date}`}>
+                      <td className="px-4 py-3">{item.target_date}</td>
+                      <td className="px-4 py-3">
+                        <div className="font-semibold text-slate-100">{item.display_name || item.city}</div>
+                        <div className="mt-1 text-xs text-slate-500">{item.city}</div>
+                      </td>
+                      <td className="px-4 py-3">
+                        <div className="font-semibold text-slate-100">{item.actual_high ?? "-"}</div>
+                        <div className="mt-1 text-xs text-slate-500">{item.is_final ? "final" : "non-final"}</div>
+                      </td>
+                      <td className="px-4 py-3">{item.settlement_source || "-"}</td>
+                      <td className="px-4 py-3">
+                        <div>{item.settlement_station_code || "-"}</div>
+                        <div className="mt-1 text-xs text-slate-500">{item.settlement_station_label || "-"}</div>
+                      </td>
+                      <td className="px-4 py-3">{item.truth_version || "-"}</td>
+                      <td className="px-4 py-3">{item.updated_by || "-"}</td>
+                      <td className="px-4 py-3">{formatUnixDateTime(item.truth_updated_at)}</td>
+                    </tr>
+                  ))}
+                  {!items.length ? (
+                    <tr>
+                      <td className="px-4 py-4 text-slate-500" colSpan={8}>
+                        当前筛选条件下没有历史真值记录
+                      </td>
+                    </tr>
+                  ) : null}
+                </tbody>
+              </table>
+            </div>
+          </CardContent>
+        </Card>
+      </div>
+    </main>
+  );
+}