Add HKO official observation series for Hong Kong charts

data/probability_training_snapshots.jsonl

@@ -116,3 +116,4 @@
 {"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}

frontend/lib/dashboard-utils.ts

@@ -252,8 +252,10 @@ export function getTemperatureChartData(
   const metarObservationSource = detail.metar_today_obs?.length
     ? detail.metar_today_obs
     : detail.trend?.recent || [];
+  const allowMetarFallback =
+    settlementSource && observationCode !== "hko";
   const shouldUseMetarFallback =
-    settlementSource &&
+    allowMetarFallback &&
     officialObservationSource.length > 0 &&
     officialObservationSource.length < 3 &&
     metarObservationSource.length >= 3;
@@ -366,6 +368,12 @@ export function getTemperatureChartData(
         ? `Official ${observationTag} feed is sparse today, so the continuous observation line switches to ${metarFallbackTag}.`
         : `今日官方 ${observationTag} 点位较稀疏，连续实测线改用 ${metarFallbackTag}。`,
     );
+  } else if (observationCode === "hko") {
+    legendParts.push(
+      isEnglish(locale)
+        ? "Hong Kong uses HKO official readings. The chart keeps official HKO points instead of switching to airport METAR."
+        : "香港按 HKO 官方读数展示；图中保留 HKO 官方点位，不切换到机场 METAR 连续线。",
+    );
   } else if (observationCode === "noaa") {
     legendParts.push(
       isEnglish(locale)

src/data_collection/settlement_sources.py

@@ -1,7 +1,10 @@
 from __future__ import annotations
 
 import csv
+import json
 import math
+import os
+import threading
 import time
 from datetime import datetime, timedelta, timezone
 from typing import Any, Dict, List, Optional
@@ -113,6 +116,90 @@ class SettlementSourceMixin:
                 return row
         return rows[0] if rows else None
 
+    def _get_runtime_data_dir(self) -> str:
+        configured = str(os.getenv("POLYWEATHER_RUNTIME_DATA_DIR") or "").strip()
+        if configured:
+            return configured
+        project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+        return os.path.join(project_root, "data")
+
+    def _get_settlement_series_lock(self) -> threading.Lock:
+        lock = getattr(self, "_settlement_series_lock", None)
+        if lock is not None:
+            return lock
+        lock = threading.Lock()
+        setattr(self, "_settlement_series_lock", lock)
+        return lock
+
+    def _hko_today_obs_path(self) -> str:
+        return os.path.join(self._get_runtime_data_dir(), "hko_hong_kong_today_obs.json")
+
+    @staticmethod
+    def _sort_temp_points(points: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        def _key(item: Dict[str, Any]) -> tuple:
+            raw = str(item.get("time") or "")
+            try:
+                hh, mm = raw.split(":")
+                return int(hh), int(mm)
+            except Exception:
+                return (99, 99)
+
+        return sorted(points, key=_key)
+
+    def _update_hko_today_obs(
+        self,
+        *,
+        obs_iso: Optional[str],
+        current_temp: Optional[float],
+    ) -> List[Dict[str, Any]]:
+        if not obs_iso or current_temp is None:
+            return []
+
+        try:
+            obs_dt = datetime.fromisoformat(str(obs_iso).replace("Z", "+00:00"))
+        except Exception:
+            return []
+        if obs_dt.tzinfo is None:
+            obs_dt = obs_dt.replace(tzinfo=timezone(timedelta(hours=8)))
+        local_dt = obs_dt.astimezone(timezone(timedelta(hours=8)))
+        date_str = local_dt.strftime("%Y-%m-%d")
+        time_str = local_dt.strftime("%H:%M")
+        path = self._hko_today_obs_path()
+        os.makedirs(os.path.dirname(path), exist_ok=True)
+
+        lock = self._get_settlement_series_lock()
+        with lock:
+            payload: Dict[str, Any] = {}
+            if os.path.exists(path):
+                try:
+                    with open(path, "r", encoding="utf-8") as fh:
+                        payload = json.load(fh) or {}
+                except Exception:
+                    payload = {}
+
+            existing_date = str(payload.get("date") or "").strip()
+            if existing_date != date_str:
+                payload = {"date": date_str, "points": []}
+
+            indexed: Dict[str, Dict[str, Any]] = {}
+            for raw_point in payload.get("points") or []:
+                if not isinstance(raw_point, dict):
+                    continue
+                raw_time = str(raw_point.get("time") or "").strip()
+                raw_temp = self._safe_float(raw_point.get("temp"))
+                if not raw_time or raw_temp is None:
+                    continue
+                indexed[raw_time] = {"time": raw_time, "temp": round(raw_temp, 1)}
+
+            indexed[time_str] = {"time": time_str, "temp": round(float(current_temp), 1)}
+            points = self._sort_temp_points(list(indexed.values()))
+            payload = {"date": date_str, "station_code": "HKO", "points": points}
+
+            with open(path, "w", encoding="utf-8") as fh:
+                json.dump(payload, fh, ensure_ascii=False)
+
+            return points
+
     def fetch_hko_settlement_current(self) -> Optional[Dict[str, Any]]:
         cache_key = "hko:hong_kong"
         cached = self._get_settlement_cache(cache_key)
@@ -154,6 +241,16 @@ class SettlementSourceMixin:
             wind_dir = self._hko_compass_to_deg(
                 wind_row.get("10-Minute Mean Wind Direction(Compass points)") if wind_row else None
             )
+            today_obs = self._update_hko_today_obs(
+                obs_iso=obs_iso,
+                current_temp=current_temp,
+            )
+            derived_max_time = None
+            if today_obs and max_so_far is not None:
+                hottest = max(today_obs, key=lambda item: float(item.get("temp") or -999))
+                hottest_temp = self._safe_float(hottest.get("temp"))
+                if hottest_temp is not None and abs(hottest_temp - float(max_so_far)) <= 0.05:
+                    derived_max_time = str(hottest.get("time") or "").strip() or None
 
             payload: Dict[str, Any] = {
                 "source": "hko",
@@ -164,12 +261,13 @@ class SettlementSourceMixin:
                 "current": {
                     "temp": round(current_temp, 1) if current_temp is not None else None,
                     "max_temp_so_far": round(max_so_far, 1) if max_so_far is not None else None,
-                    "max_temp_time": None,
+                    "max_temp_time": derived_max_time,
                     "today_low": round(min_so_far, 1) if min_so_far is not None else None,
                     "humidity": round(humidity, 1) if humidity is not None else None,
                     "wind_speed_kt": wind_speed_kt,
                     "wind_dir": wind_dir,
                 },
+                "today_obs": today_obs,
                 "unit": "celsius",
             }
             self._set_settlement_cache(cache_key, payload)

web/analysis_service.py

@@ -138,14 +138,31 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
 
     settlement_today_obs = []
     if use_settlement_current:
-        if obs_time_str and cur_temp is not None:
+        explicit_settlement_obs = settlement_current.get("today_obs") or []
-            settlement_today_obs.append({"time": obs_time_str, "temp": cur_temp})
+        normalized_obs = []
-        if (
+        for item in explicit_settlement_obs:
-            max_temp_time
+            if isinstance(item, dict):
-            and max_so_far is not None
+                raw_time = str(item.get("time") or "").strip()
-            and str(max_temp_time) != str(obs_time_str)
+                raw_temp = _sf(item.get("temp"))
-        ):
+            elif isinstance(item, (list, tuple)) and len(item) >= 2:
-            settlement_today_obs.append({"time": str(max_temp_time), "temp": max_so_far})
+                raw_time = str(item[0] or "").strip()
+                raw_temp = _sf(item[1])
+            else:
+                continue
+            if not raw_time or raw_temp is None:
+                continue
+            normalized_obs.append({"time": raw_time, "temp": raw_temp})
+        if normalized_obs:
+            settlement_today_obs = normalized_obs
+        else:
+            if obs_time_str and cur_temp is not None:
+                settlement_today_obs.append({"time": obs_time_str, "temp": cur_temp})
+            if (
+                max_temp_time
+                and max_so_far is not None
+                and str(max_temp_time) != str(obs_time_str)
+            ):
+                settlement_today_obs.append({"time": str(max_temp_time), "temp": max_so_far})
 
     metar_today_obs_payload = [
         {"time": t, "temp": v}