Add upper-air structure signals to intraday analysis

frontend/components/dashboard/FutureForecastModal.tsx

@@ -932,6 +932,43 @@ export function FutureForecastModal() {
                         </div>
                       ))}
                     </div>
+                    {view.front.upperAirSummary ||
+                    (view.front.upperAirMetrics?.length || 0) > 0 ? (
+                      <>
+                        <div
+                          style={{
+                            color: "var(--text-primary)",
+                            fontSize: "0.95rem",
+                            fontWeight: 700,
+                            marginTop: "18px",
+                          }}
+                        >
+                          {locale === "en-US" ? "Upper-Air Structure" : "高空结构信号"}
+                        </div>
+                        {view.front.upperAirSummary ? (
+                          <div className="future-trend-summary">
+                            {view.front.upperAirSummary}
+                          </div>
+                        ) : null}
+                        <div className="future-trend-grid">
+                          {(view.front.upperAirMetrics || []).map((metric) => (
+                            <div key={metric.label} className="future-trend-card">
+                              <div className="future-trend-label">{metric.label}</div>
+                              <div
+                                className={clsx(
+                                  "future-trend-value",
+                                  metric.tone === "warm" && "warm",
+                                  metric.tone === "cold" && "cold",
+                                )}
+                              >
+                                {metric.value}
+                              </div>
+                              <div className="future-trend-note">{metric.note}</div>
+                            </div>
+                          ))}
+                        </div>
+                      </>
+                    ) : null}
                   </section>
 
                   <section className="future-modal-section">

frontend/lib/dashboard-types.ts

@@ -153,9 +153,15 @@ export interface HourlySeries {
   pressure_msl?: Array<number | null>;
   wind_speed_10m?: Array<number | null>;
   wind_direction_10m?: Array<number | null>;
+  wind_speed_180m?: Array<number | null>;
+  wind_direction_180m?: Array<number | null>;
   precipitation_probability?: Array<number | null>;
   cloud_cover?: Array<number | null>;
   radiation?: Array<number | null>;
+  cape?: Array<number | null>;
+  convective_inhibition?: Array<number | null>;
+  lifted_index?: Array<number | null>;
+  boundary_layer_height?: Array<number | null>;
 }
 
 export interface WeatherGovPeriod {
@@ -298,6 +304,22 @@ export interface CityDetail {
     summary?: string | null;
     notes?: string[] | null;
   };
+  vertical_profile_signal?: {
+    source?: string | null;
+    window_start?: string | null;
+    window_end?: string | null;
+    cape_max?: number | null;
+    cin_min?: number | null;
+    lifted_index_min?: number | null;
+    boundary_layer_height_max?: number | null;
+    shear_10m_180m_max?: number | null;
+    suppression_risk?: string | null;
+    trigger_risk?: string | null;
+    mixing_strength?: string | null;
+    shear_risk?: string | null;
+    summary_zh?: string | null;
+    summary_en?: string | null;
+  };
   ai_analysis?: string | AiAnalysisStructured | null;
   updated_at?: string;
   multi_model_daily?: Record<string, DailyModelForecast>;

frontend/lib/dashboard-utils.ts

@@ -579,6 +579,122 @@ export function computeFrontTrendSignal(
   dateStr: string,
   locale: Locale = "zh-CN",
 ) {
+  const upperAirSignal = detail.vertical_profile_signal || {};
+  const upperAirMetrics = upperAirSignal.source
+    ? [
+        {
+          label: isEnglish(locale) ? "Convective suppression" : "对流压温风险",
+          note:
+            upperAirSignal.cape_max != null || upperAirSignal.cin_min != null
+              ? isEnglish(locale)
+                ? `CAPE max ${Math.round(Number(upperAirSignal.cape_max ?? 0))}, CIN min ${Number(upperAirSignal.cin_min ?? 0).toFixed(0)}.`
+                : `CAPE 峰值 ${Math.round(Number(upperAirSignal.cape_max ?? 0))}，CIN 最低 ${Number(upperAirSignal.cin_min ?? 0).toFixed(0)}。`
+              : isEnglish(locale)
+                ? "Derived from the next 48h upper-air profile."
+                : "根据未来 48 小时高空剖面估算。",
+          tone:
+            upperAirSignal.suppression_risk === "high"
+              ? "cold"
+              : upperAirSignal.suppression_risk === "low"
+                ? "warm"
+                : "",
+          value:
+            upperAirSignal.suppression_risk === "high"
+              ? isEnglish(locale)
+                ? "High"
+                : "高"
+              : upperAirSignal.suppression_risk === "medium"
+                ? isEnglish(locale)
+                  ? "Medium"
+                  : "中"
+                : isEnglish(locale)
+                  ? "Low"
+                  : "低",
+        },
+        {
+          label: isEnglish(locale) ? "Trigger setup" : "午后触发性",
+          note:
+            upperAirSignal.lifted_index_min != null
+              ? isEnglish(locale)
+                ? `Lifted index min ${Number(upperAirSignal.lifted_index_min).toFixed(1)}.`
+                : `Lifted Index 最低 ${Number(upperAirSignal.lifted_index_min).toFixed(1)}。`
+              : isEnglish(locale)
+                ? "Uses instability and lifted-index structure."
+                : "结合不稳定能量与抬升指数判断。",
+          tone:
+            upperAirSignal.trigger_risk === "high"
+              ? "cold"
+              : upperAirSignal.trigger_risk === "low"
+                ? "warm"
+                : "",
+          value:
+            upperAirSignal.trigger_risk === "high"
+              ? isEnglish(locale)
+                ? "High"
+                : "高"
+              : upperAirSignal.trigger_risk === "medium"
+                ? isEnglish(locale)
+                  ? "Medium"
+                  : "中"
+                : isEnglish(locale)
+                  ? "Low"
+                  : "低",
+        },
+        {
+          label: isEnglish(locale) ? "Deep mixing" : "深层混合",
+          note:
+            upperAirSignal.boundary_layer_height_max != null
+              ? isEnglish(locale)
+                ? `Boundary-layer height peaks near ${Math.round(Number(upperAirSignal.boundary_layer_height_max))} m.`
+                : `边界层高度峰值约 ${Math.round(Number(upperAirSignal.boundary_layer_height_max))} 米。`
+              : isEnglish(locale)
+                ? "Tracks daytime boundary-layer depth."
+                : "跟踪白天边界层混合深度。",
+          tone:
+            upperAirSignal.mixing_strength === "strong"
+              ? "warm"
+              : upperAirSignal.mixing_strength === "weak"
+                ? "cold"
+                : "",
+          value:
+            upperAirSignal.mixing_strength === "strong"
+              ? isEnglish(locale)
+                ? "Strong"
+                : "强"
+              : upperAirSignal.mixing_strength === "medium"
+                ? isEnglish(locale)
+                  ? "Medium"
+                  : "中"
+                : isEnglish(locale)
+                  ? "Weak"
+                  : "弱",
+        },
+        {
+          label: isEnglish(locale) ? "Shear proxy" : "高空风切变",
+          note:
+            upperAirSignal.shear_10m_180m_max != null
+              ? isEnglish(locale)
+                ? `10m-180m shear proxy peaks near ${Number(upperAirSignal.shear_10m_180m_max).toFixed(1)}.`
+                : `10m-180m 风切变代理峰值约 ${Number(upperAirSignal.shear_10m_180m_max).toFixed(1)}。`
+              : isEnglish(locale)
+                ? "Uses 10m vs 180m wind-vector spread as a simple proxy."
+                : "使用 10m 与 180m 风矢量差做简化代理。",
+          tone: upperAirSignal.shear_risk === "high" ? "cold" : "",
+          value:
+            upperAirSignal.shear_risk === "high"
+              ? isEnglish(locale)
+                ? "High"
+                : "高"
+              : upperAirSignal.shear_risk === "medium"
+                ? isEnglish(locale)
+                  ? "Medium"
+                  : "中"
+                : isEnglish(locale)
+                  ? "Low"
+                  : "低",
+        },
+      ]
+    : [];
   const backendSummary =
     dateStr === detail.local_date
       ? String(detail.dynamic_commentary?.summary || "").trim()
@@ -602,6 +718,10 @@ export function computeFrontTrendSignal(
         tone?: string;
         value: string;
       }>,
+      upperAirMetrics,
+      upperAirSummary: isEnglish(locale)
+        ? String(upperAirSignal.summary_en || "").trim()
+        : String(upperAirSignal.summary_zh || "").trim(),
       precipMax: 0,
       score: 0,
       summary:
@@ -1083,6 +1203,10 @@ export function computeFrontTrendSignal(
     confidence,
     label,
     metrics,
+    upperAirMetrics,
+    upperAirSummary: isEnglish(locale)
+      ? String(upperAirSignal.summary_en || "").trim()
+      : String(upperAirSignal.summary_zh || "").trim(),
     precipMax,
     score,
     summary: backendSummary || summary,

src/data_collection/nws_open_meteo_sources.py

@@ -187,7 +187,12 @@ class NwsOpenMeteoSourceMixin:
                 "latitude": lat,
                 "longitude": lon,
                 "current_weather": "true",
-                "hourly": "temperature_2m,shortwave_radiation,dew_point_2m,pressure_msl,wind_speed_10m,wind_direction_10m,precipitation_probability,cloud_cover",
+                "hourly": (
+                    "temperature_2m,shortwave_radiation,dew_point_2m,pressure_msl,"
+                    "wind_speed_10m,wind_direction_10m,wind_speed_180m,wind_direction_180m,"
+                    "precipitation_probability,cloud_cover,cape,convective_inhibition,"
+                    "lifted_index,boundary_layer_height"
+                ),
                 "daily": "temperature_2m_max,apparent_temperature_max,sunrise,sunset,sunshine_duration",
                 "timezone": "auto",
                 "forecast_days": forecast_days,

web/analysis_service.py

@@ -24,6 +24,167 @@ from src.analysis.settlement_rounding import apply_city_settlement
 from src.analysis.metar_narrator import describe_metar_report
 from src.data_collection.city_registry import ALIASES
 
+def _wind_components(speed: Optional[float], direction: Optional[float]) -> tuple[Optional[float], Optional[float]]:
+    if speed is None or direction is None:
+        return None, None
+    try:
+        import math
+
+        rad = math.radians(float(direction))
+        spd = float(speed)
+        u = -spd * math.sin(rad)
+        v = -spd * math.cos(rad)
+        return u, v
+    except Exception:
+        return None, None
+
+
+def _build_vertical_profile_signal(
+    hourly_next_48h: Dict[str, list],
+    local_date: str,
+    local_hour: int,
+) -> Dict[str, Any]:
+    times = hourly_next_48h.get("times") or []
+    if not times:
+        return {}
+
+    preferred_start = max(local_hour, 12)
+    preferred_end = 19
+    candidate_indexes = [
+        index
+        for index, ts in enumerate(times)
+        if str(ts).startswith(local_date)
+        and preferred_start <= int(str(ts).split("T")[1][:2]) <= preferred_end
+    ]
+    if not candidate_indexes:
+        candidate_indexes = [
+            index
+            for index, ts in enumerate(times)
+            if str(ts).startswith(local_date)
+        ]
+    if not candidate_indexes:
+        return {}
+
+    def _series(name: str) -> list:
+        values = hourly_next_48h.get(name) or []
+        return [values[idx] if idx < len(values) else None for idx in candidate_indexes]
+
+    def _max_numeric(values: list) -> Optional[float]:
+        valid = [_sf(value) for value in values if _sf(value) is not None]
+        return max(valid) if valid else None
+
+    def _min_numeric(values: list) -> Optional[float]:
+        valid = [_sf(value) for value in values if _sf(value) is not None]
+        return min(valid) if valid else None
+
+    cape_max = _max_numeric(_series("cape"))
+    cin_min = _min_numeric(_series("convective_inhibition"))
+    lifted_index_min = _min_numeric(_series("lifted_index"))
+    boundary_layer_height_max = _max_numeric(_series("boundary_layer_height"))
+
+    shear_values: list[float] = []
+    speed_10m = hourly_next_48h.get("wind_speed_10m") or []
+    direction_10m = hourly_next_48h.get("wind_direction_10m") or []
+    speed_180m = hourly_next_48h.get("wind_speed_180m") or []
+    direction_180m = hourly_next_48h.get("wind_direction_180m") or []
+    for idx in candidate_indexes:
+        s10 = _sf(speed_10m[idx]) if idx < len(speed_10m) else None
+        d10 = _sf(direction_10m[idx]) if idx < len(direction_10m) else None
+        s180 = _sf(speed_180m[idx]) if idx < len(speed_180m) else None
+        d180 = _sf(direction_180m[idx]) if idx < len(direction_180m) else None
+        u10, v10 = _wind_components(s10, d10)
+        u180, v180 = _wind_components(s180, d180)
+        if None in (u10, v10, u180, v180):
+            continue
+        import math
+
+        shear_values.append(math.sqrt((u180 - u10) ** 2 + (v180 - v10) ** 2))
+    shear_10m_180m_max = max(shear_values) if shear_values else None
+
+    suppression_risk = "low"
+    if (cape_max is not None and cape_max >= 900) or (
+        cin_min is not None and cin_min <= -60
+    ):
+        suppression_risk = "high"
+    elif (cape_max is not None and cape_max >= 300) or (
+        cin_min is not None and cin_min <= -20
+    ):
+        suppression_risk = "medium"
+
+    trigger_risk = "low"
+    if (
+        cape_max is not None
+        and cape_max >= 800
+        and lifted_index_min is not None
+        and lifted_index_min <= -2
+    ):
+        trigger_risk = "high"
+    elif (
+        cape_max is not None
+        and cape_max >= 250
+        and lifted_index_min is not None
+        and lifted_index_min <= 0
+    ):
+        trigger_risk = "medium"
+
+    mixing_strength = "weak"
+    if boundary_layer_height_max is not None and boundary_layer_height_max >= 1800:
+        mixing_strength = "strong"
+    elif boundary_layer_height_max is not None and boundary_layer_height_max >= 1000:
+        mixing_strength = "medium"
+
+    shear_risk = "low"
+    if shear_10m_180m_max is not None and shear_10m_180m_max >= 12:
+        shear_risk = "high"
+    elif shear_10m_180m_max is not None and shear_10m_180m_max >= 6:
+        shear_risk = "medium"
+
+    zh_parts = []
+    en_parts = []
+    if suppression_risk == "high":
+        zh_parts.append("午后对流压温风险偏高。")
+        en_parts.append("Afternoon convective suppression risk is elevated.")
+    elif suppression_risk == "medium":
+        zh_parts.append("存在一定云雨压温风险。")
+        en_parts.append("There is some cloud and shower suppression risk.")
+    if mixing_strength == "strong":
+        zh_parts.append("边界层混合较深，若无云雨打断仍有冲高空间。")
+        en_parts.append("Deep boundary-layer mixing still supports additional warming if convection stays limited.")
+    elif mixing_strength == "medium":
+        zh_parts.append("白天混合条件中等。")
+        en_parts.append("Daytime mixing potential is moderate.")
+    if shear_risk == "high":
+        zh_parts.append("高空风切变较强，午后结构波动可能加大。")
+        en_parts.append("Upper-level shear is relatively strong and may increase afternoon volatility.")
+    if trigger_risk == "high":
+        zh_parts.append("抬升触发条件较好，需警惕午后云团发展。")
+        en_parts.append("Trigger conditions are favorable enough to watch for afternoon convective development.")
+    elif trigger_risk == "medium":
+        zh_parts.append("午后具备一定触发条件。")
+        en_parts.append("There is some afternoon trigger potential.")
+    if not zh_parts:
+        zh_parts.append("高空结构整体平稳，暂未看到明显压温信号。")
+    if not en_parts:
+        en_parts.append("The upper-air structure looks fairly stable, without a strong suppression signal yet.")
+
+    return {
+        "source": "open-meteo-gfs",
+        "window_start": times[candidate_indexes[0]] if candidate_indexes else None,
+        "window_end": times[candidate_indexes[-1]] if candidate_indexes else None,
+        "cape_max": cape_max,
+        "cin_min": cin_min,
+        "lifted_index_min": lifted_index_min,
+        "boundary_layer_height_max": boundary_layer_height_max,
+        "shear_10m_180m_max": shear_10m_180m_max,
+        "suppression_risk": suppression_risk,
+        "trigger_risk": trigger_risk,
+        "mixing_strength": mixing_strength,
+        "shear_risk": shear_risk,
+        "summary_zh": "".join(zh_parts),
+        "summary_en": " ".join(en_parts),
+    }
+
+
 def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
     """Fetch, analyse, and return structured weather data for one city."""
     # Check cache
@@ -301,8 +462,14 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
     h_pressure = hourly.get("pressure_msl", [])
     h_wspd = hourly.get("wind_speed_10m", [])
     h_wdir = hourly.get("wind_direction_10m", [])
+    h_wspd_180m = hourly.get("wind_speed_180m", [])
+    h_wdir_180m = hourly.get("wind_direction_180m", [])
     h_precip_prob = hourly.get("precipitation_probability", [])
     h_cloud_cover = hourly.get("cloud_cover", [])
+    h_cape = hourly.get("cape", [])
+    h_cin = hourly.get("convective_inhibition", [])
+    h_lifted_index = hourly.get("lifted_index", [])
+    h_boundary_layer_height = hourly.get("boundary_layer_height", [])
     if (not h_times or not h_temps) and metar:
         metar_today_obs = metar.get("today_obs", []) or []
         parsed_obs = []
@@ -324,8 +491,14 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
             h_pressure = [None for _ in parsed_obs]
             h_wspd = [None for _ in parsed_obs]
             h_wdir = [None for _ in parsed_obs]
+            h_wspd_180m = [None for _ in parsed_obs]
+            h_wdir_180m = [None for _ in parsed_obs]
             h_precip_prob = [None for _ in parsed_obs]
             h_cloud_cover = [None for _ in parsed_obs]
+            h_cape = [None for _ in parsed_obs]
+            h_cin = [None for _ in parsed_obs]
+            h_lifted_index = [None for _ in parsed_obs]
+            h_boundary_layer_height = [None for _ in parsed_obs]
 
     peak_hours = []
     if h_times and h_temps and om_today is not None:
@@ -422,8 +595,14 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
         "pressure_msl": [],
         "wind_speed_10m": [],
         "wind_direction_10m": [],
+        "wind_speed_180m": [],
+        "wind_direction_180m": [],
         "precipitation_probability": [],
         "cloud_cover": [],
+        "cape": [],
+        "convective_inhibition": [],
+        "lifted_index": [],
+        "boundary_layer_height": [],
     }
     try:
         local_anchor = datetime.strptime(
@@ -454,12 +633,36 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
             next_48h_hourly["wind_direction_10m"].append(
                 h_wdir[i] if i < len(h_wdir) else None
             )
+            next_48h_hourly["wind_speed_180m"].append(
+                h_wspd_180m[i] if i < len(h_wspd_180m) else None
+            )
+            next_48h_hourly["wind_direction_180m"].append(
+                h_wdir_180m[i] if i < len(h_wdir_180m) else None
+            )
             next_48h_hourly["precipitation_probability"].append(
                 h_precip_prob[i] if i < len(h_precip_prob) else None
             )
             next_48h_hourly["cloud_cover"].append(
                 h_cloud_cover[i] if i < len(h_cloud_cover) else None
             )
+            next_48h_hourly["cape"].append(
+                h_cape[i] if i < len(h_cape) else None
+            )
+            next_48h_hourly["convective_inhibition"].append(
+                h_cin[i] if i < len(h_cin) else None
+            )
+            next_48h_hourly["lifted_index"].append(
+                h_lifted_index[i] if i < len(h_lifted_index) else None
+            )
+            next_48h_hourly["boundary_layer_height"].append(
+                h_boundary_layer_height[i] if i < len(h_boundary_layer_height) else None
+            )
+
+    vertical_profile_signal = _build_vertical_profile_signal(
+        next_48h_hourly,
+        local_date_str,
+        local_hour,
+    )
 
     # ── 13. Cloud description (METAR primary, MGM fallback) ──
     clouds = mc.get("clouds", [])
@@ -683,6 +886,7 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
         "dynamic_commentary": dynamic_commentary,
         "hourly": today_hourly,
         "hourly_next_48h": next_48h_hourly,
+        "vertical_profile_signal": vertical_profile_signal,
         "metar_today_obs": metar_today_obs_payload,
         "metar_recent_obs": metar_recent_obs_payload,
         "settlement_today_obs": settlement_today_obs,
@@ -866,6 +1070,7 @@ def _build_city_detail_payload(
         },
         "probabilities": data.get("probabilities") or {"mu": None, "distribution": []},
         "dynamic_commentary": data.get("dynamic_commentary") or {"summary": "", "notes": []},
+        "vertical_profile_signal": data.get("vertical_profile_signal") or {},
         "market_scan": market_scan,
         "risk": data.get("risk"),
         "nearby_source": data.get("nearby_source") or ("mgm" if data.get("name") == "ankara" else "metar_cluster"),