Add open multi-model forecast sources

src/data_collection/nws_open_meteo_sources.py

@@ -2,13 +2,143 @@ from __future__ import annotations
 
 import time
 from datetime import datetime, timedelta
-from typing import Dict, Optional
+from typing import Any, Dict, Optional
 
 from loguru import logger
 
 from src.utils.metrics import record_source_call
 
 
+OPEN_METEO_MULTI_MODEL_SPECS: Dict[str, Dict[str, Any]] = {
+    "ecmwf_ifs025": {
+        "label": "ECMWF",
+        "provider": "ECMWF",
+        "model": "IFS",
+        "tier": "global",
+        "resolution_km": 25,
+        "horizon": "15d",
+    },
+    "ecmwf_aifs025_single": {
+        "label": "ECMWF AIFS",
+        "provider": "ECMWF",
+        "model": "AIFS single",
+        "tier": "global_ai",
+        "resolution_km": 25,
+        "horizon": "15d",
+    },
+    "gfs_seamless": {
+        "label": "GFS",
+        "provider": "NOAA",
+        "model": "GFS Seamless",
+        "tier": "global",
+        "resolution_km": None,
+        "horizon": "16d",
+    },
+    "icon_seamless": {
+        "label": "ICON",
+        "provider": "DWD",
+        "model": "ICON Seamless",
+        "tier": "global",
+        "resolution_km": None,
+        "horizon": "7d",
+    },
+    "icon_eu": {
+        "label": "ICON-EU",
+        "provider": "DWD",
+        "model": "ICON-EU",
+        "tier": "regional_europe",
+        "resolution_km": 7,
+        "horizon": "5d",
+    },
+    "icon_d2": {
+        "label": "ICON-D2",
+        "provider": "DWD",
+        "model": "ICON-D2",
+        "tier": "short_range_europe",
+        "resolution_km": 2.2,
+        "horizon": "2d",
+    },
+    "gem_seamless": {
+        "label": "GEM",
+        "provider": "ECCC",
+        "model": "GEM Seamless",
+        "tier": "global",
+        "resolution_km": None,
+        "horizon": "10d",
+    },
+    "gem_global": {
+        "label": "GDPS",
+        "provider": "ECCC",
+        "model": "GEM Global / GDPS",
+        "tier": "global",
+        "resolution_km": 15,
+        "horizon": "10d",
+    },
+    "gem_regional": {
+        "label": "RDPS",
+        "provider": "ECCC",
+        "model": "GEM Regional / RDPS",
+        "tier": "regional_north_america",
+        "resolution_km": 10,
+        "horizon": "3d",
+    },
+    "gem_hrdps_continental": {
+        "label": "HRDPS",
+        "provider": "ECCC",
+        "model": "HRDPS Continental",
+        "tier": "short_range_north_america",
+        "resolution_km": 2.5,
+        "horizon": "2d",
+    },
+    "jma_seamless": {
+        "label": "JMA",
+        "provider": "JMA",
+        "model": "JMA Seamless",
+        "tier": "global",
+        "resolution_km": None,
+        "horizon": "11d",
+    },
+}
+
+OPEN_METEO_MULTI_MODEL_ORDER = tuple(OPEN_METEO_MULTI_MODEL_SPECS.keys())
+
+
+def _parse_open_meteo_multi_model_daily(
+    daily: Dict[str, Any],
+) -> tuple[list[str], Dict[str, Dict[str, float]], Dict[str, Dict[str, Any]], Dict[str, str]]:
+    dates = daily.get("time", [])
+    if not isinstance(dates, list):
+        dates = []
+
+    model_metadata: Dict[str, Dict[str, Any]] = {}
+    model_keys: Dict[str, str] = {}
+    daily_forecasts: Dict[str, Dict[str, float]] = {}
+
+    for day_idx, date_str in enumerate(dates):
+        day_data: Dict[str, float] = {}
+        for model_key, spec in OPEN_METEO_MULTI_MODEL_SPECS.items():
+            label = str(spec["label"])
+            key = f"temperature_2m_max_{model_key}"
+            values = daily.get(key, [])
+            if not isinstance(values, list):
+                continue
+            if day_idx >= len(values) or values[day_idx] is None:
+                continue
+            try:
+                day_data[label] = round(float(values[day_idx]), 1)
+            except (TypeError, ValueError):
+                continue
+            model_metadata[label] = {
+                **spec,
+                "open_meteo_model": model_key,
+            }
+            model_keys[label] = model_key
+        if day_data:
+            daily_forecasts[str(date_str)] = day_data
+
+    return [str(d) for d in dates], daily_forecasts, model_metadata, model_keys
+
+
 class NwsOpenMeteoSourceMixin:
     def fetch_nws(self, lat: float, lon: float) -> Optional[Dict]:
         """
@@ -468,10 +598,10 @@ class NwsOpenMeteoSourceMixin:
         用于真正的多模型共识评分
 
         模型列表:
-        - ECMWF IFS (欧洲中期天气预报中心)
+        - ECMWF IFS / AIFS
         - GFS (美国 NOAA)
-        - ICON (德国气象局 DWD)
+        - ICON Seamless / ICON-EU / ICON-D2 (德国气象局 DWD)
-        - GEM (加拿大气象局)
+        - GEM Seamless / GDPS / RDPS / HRDPS (加拿大 ECCC)
         - JMA (日本气象厅)
 
         返回 3 天的预报数据，支持今日+明日共识分析
@@ -510,7 +640,7 @@ class NwsOpenMeteoSourceMixin:
                     return dict(cached_data)
         try:
             url = "https://api.open-meteo.com/v1/forecast"
-            models = "ecmwf_ifs025,gfs_seamless,icon_seamless,gem_seamless,jma_seamless"
+            models = ",".join(OPEN_METEO_MULTI_MODEL_ORDER)
             params = {
                 "latitude": lat,
                 "longitude": lon,
@@ -532,27 +662,11 @@ class NwsOpenMeteoSourceMixin:
             data = response.json()
 
             daily = data.get("daily", {})
-            dates = daily.get("time", [])
+            if not isinstance(daily, dict):
-
+                daily = {}
-            model_labels = {
+            dates, daily_forecasts, model_metadata, model_keys = (
-                "ecmwf_ifs025": "ECMWF",
+                _parse_open_meteo_multi_model_daily(daily)
-                "gfs_seamless": "GFS",
+            )
-                "icon_seamless": "ICON",
-                "gem_seamless": "GEM",
-                "jma_seamless": "JMA",
-            }
-
-            # 按天提取每个模型的预报
-            daily_forecasts = {}  # {"2026-02-23": {"ECMWF": 7.9, "GFS": 6.5, ...}, ...}
-            for day_idx, date_str in enumerate(dates):
-                day_data = {}
-                for model_key, label in model_labels.items():
-                    key = f"temperature_2m_max_{model_key}"
-                    values = daily.get(key, [])
-                    if day_idx < len(values) and values[day_idx] is not None:
-                        day_data[label] = round(values[day_idx], 1)
-                if day_data:
-                    daily_forecasts[date_str] = day_data
 
             if not daily_forecasts:
                 logger.warning("Multi-model: 无有效模型数据")
@@ -570,10 +684,14 @@ class NwsOpenMeteoSourceMixin:
 
             result = {
                 "source": "multi_model",
+                "provider": "open-meteo",
                 "forecasts": forecasts,  # 今天 {"ECMWF": 12.3, "GFS": 11.8, ...} (向后兼容)
                 "daily_forecasts": daily_forecasts,  # 按天 {"2026-02-23": {...}, "2026-02-24": {...}}
+                "model_metadata": model_metadata,
+                "model_keys": model_keys,
                 "dates": dates,
                 "unit": "fahrenheit" if use_fahrenheit else "celsius",
+                "attribution": "Open-Meteo forecast model API; underlying models from ECMWF, DWD, ECCC, NOAA and JMA.",
             }
             with self._multi_model_cache_lock:
                 self._multi_model_cache[cache_key] = {

src/data_collection/weather_sources.py

@@ -161,8 +161,8 @@ class WeatherDataCollector(OpenMeteoCacheMixin, SettlementSourceMixin, MetarSour
             os.getenv("OPEN_METEO_MULTI_MODEL_CACHE_TTL_SEC", "900")
         )
         self.multi_model_cache_version = str(
-            os.getenv("OPEN_METEO_MULTI_MODEL_CACHE_VERSION", "v2")
+            os.getenv("OPEN_METEO_MULTI_MODEL_CACHE_VERSION", "v3")
-        ).strip() or "v2"
+        ).strip() or "v3"
         self._open_meteo_cache: Dict[str, Dict] = {}
         self._ensemble_cache: Dict[str, Dict] = {}
         self._multi_model_cache: Dict[str, Dict] = {}

tests/test_multi_model_sources.py

@@ -0,0 +1,46 @@
+from src.data_collection.nws_open_meteo_sources import (
+    OPEN_METEO_MULTI_MODEL_ORDER,
+    _parse_open_meteo_multi_model_daily,
+)
+
+
+def test_multi_model_parser_exposes_open_recommended_models():
+    daily = {
+        "time": ["2026-04-17", "2026-04-18"],
+        "temperature_2m_max_ecmwf_ifs025": [20.1, 21.1],
+        "temperature_2m_max_ecmwf_aifs025_single": [20.2, 21.2],
+        "temperature_2m_max_icon_eu": [20.3, 21.3],
+        "temperature_2m_max_icon_d2": [20.4, None],
+        "temperature_2m_max_gem_global": [19.8, 20.8],
+        "temperature_2m_max_gem_regional": [21.0, 22.0],
+        "temperature_2m_max_gem_hrdps_continental": [21.5, None],
+    }
+
+    dates, forecasts, metadata, model_keys = _parse_open_meteo_multi_model_daily(daily)
+
+    assert dates == ["2026-04-17", "2026-04-18"]
+    assert forecasts["2026-04-17"]["ECMWF"] == 20.1
+    assert forecasts["2026-04-17"]["ECMWF AIFS"] == 20.2
+    assert forecasts["2026-04-17"]["ICON-EU"] == 20.3
+    assert forecasts["2026-04-17"]["ICON-D2"] == 20.4
+    assert forecasts["2026-04-17"]["GDPS"] == 19.8
+    assert forecasts["2026-04-17"]["RDPS"] == 21.0
+    assert forecasts["2026-04-17"]["HRDPS"] == 21.5
+    assert "ICON-D2" not in forecasts["2026-04-18"]
+    assert metadata["ECMWF AIFS"]["provider"] == "ECMWF"
+    assert metadata["HRDPS"]["resolution_km"] == 2.5
+    assert model_keys["RDPS"] == "gem_regional"
+
+
+def test_multi_model_order_includes_legacy_and_new_sources():
+    assert "ecmwf_ifs025" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "ecmwf_aifs025_single" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "gfs_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "icon_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "icon_eu" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "icon_d2" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "gem_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "gem_global" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "gem_regional" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "gem_hrdps_continental" in OPEN_METEO_MULTI_MODEL_ORDER
+    assert "jma_seamless" in OPEN_METEO_MULTI_MODEL_ORDER

web/analysis_service.py

@@ -2313,6 +2313,14 @@ def _analyze(
         },
         "source_forecasts": {
             "weather_gov": raw.get("nws") or {},
+            "open_meteo_multi_model": {
+                "source": mm.get("source"),
+                "provider": mm.get("provider"),
+                "dates": mm.get("dates") or [],
+                "model_metadata": mm.get("model_metadata") or {},
+                "model_keys": mm.get("model_keys") or {},
+                "attribution": mm.get("attribution"),
+            } if isinstance(mm, dict) and mm else {},
         },
         "multi_model": {k: v for k, v in current_forecasts.items() if v is not None},
         "multi_model_daily": multi_model_daily,