Fix chill units: x1.1 multiplier, Israel timezone

backend/api/routes/biology.py

@@ -48,18 +48,26 @@ async def biology_chill_units(
     season_start: str = Query("2025-11-01", description="Season start (YYYY-MM-DD)"),
     hub: DataHub = Depends(get_datahub),
 ):
-    """Accumulated chill units from IMS hourly temperature.
-
-    Uses IMS air_temperature_c (full season coverage from Nov 1).
-    Model: T<=7 → +1 CU/h, 7<T<=10 → +0.5, 10<T<=18 → 0, T>18 → -1.
-    Daily totals clipped at 0.
-
-    Returns two series: "under_panels" uses IMS temp - 1°C (panels provide
-    slight thermal buffering), "open_field" uses raw IMS temp.
+    """Accumulated chill units from IMS hourly temperature (Utah model).
+
+    Model (Richardson et al. 1974):
+      T <= 7°C   → +1.0 CU/hour
+      7 < T <= 10 → +0.5
+      10 < T <= 18 → 0.0
+      T > 18      → -1.0
+    Daily totals clipped at 0 (no negative daily chill).
+    Season cumulative = running sum of daily CU from season_start.
+
+    Two series:
+      - open_field: raw IMS temperature
+      - under_panels: open_field × 1.1 (panels buffer nighttime → more chill)
+    Multiplier per Research/chill_hours/ANALYSIS_EXPLAINED.md.
     """
     import numpy as np
     import pandas as pd
 
+    PANEL_MULTIPLIER = 1.1  # under-panel chill ≈ 10% more than open field
+
     try:
         df = hub.weather._load_df()
         if df.empty:
@@ -73,42 +81,47 @@ async def biology_chill_units(
         if subset.empty or "air_temperature_c" not in subset.columns:
             return {"error": "No temperature data in season range"}
 
+        # Convert to Israel local time for correct day boundaries
+        try:
+            from zoneinfo import ZoneInfo
+            tz = ZoneInfo("Asia/Jerusalem")
+        except ImportError:
+            tz = None
+        if tz:
+            subset = subset.tz_convert(tz)
+
         # Hourly mean temperature
         hourly = subset["air_temperature_c"].resample("1h").mean().dropna()
         if hourly.empty:
             return {"error": "No hourly temperature data"}
 
-        def _chill_daily(temps_hourly):
-            temps = temps_hourly.values
-            chill_h = np.select(
-                [temps <= 7, (temps > 7) & (temps <= 10), (temps > 10) & (temps <= 18), temps > 18],
-                [1.0, 0.5, 0.0, -1.0],
-            )
-            daily = pd.Series(chill_h, index=temps_hourly.index).resample("D").sum().clip(lower=0)
-            return daily.cumsum()
-
-        # Open field = raw IMS temperature
-        cu_open = _chill_daily(hourly)
-
-        # Under panels = IMS temp offset by ~-1°C (panels buffer nighttime lows)
-        cu_panels = _chill_daily(hourly - 1.0)
+        # Compute chill per hour using Utah model
+        temps = hourly.values
+        chill_hourly = np.select(
+            [temps <= 7.0, (temps > 7.0) & (temps <= 10.0),
+             (temps > 10.0) & (temps <= 18.0), temps > 18.0],
+            [1.0, 0.5, 0.0, -1.0],
+        )
 
-        all_dates = sorted(cu_open.index.union(cu_panels.index))
+        # Daily chill = sum of hourly, clipped at 0
+        daily_chill = pd.Series(chill_hourly, index=hourly.index).resample("D").sum().clip(lower=0)
+        cu_open = daily_chill.cumsum()
+        cu_panels = (daily_chill * PANEL_MULTIPLIER).cumsum()
 
         daily = [
             {
                 "date": ts.strftime("%Y-%m-%d"),
-                "under_panels": round(float(cu_panels.get(ts, 0)), 1) if ts in cu_panels.index else None,
-                "open_field": round(float(cu_open.get(ts, 0)), 1) if ts in cu_open.index else None,
+                "under_panels": round(float(cu_panels.loc[ts]), 1),
+                "open_field": round(float(cu_open.loc[ts]), 1),
             }
-            for ts in all_dates
+            for ts in daily_chill.index
         ]
 
         return {
             "season_start": season_start,
             "latest_under_panels": round(float(cu_panels.iloc[-1]), 1) if len(cu_panels) else 0,
             "latest_open_field": round(float(cu_open.iloc[-1]), 1) if len(cu_open) else 0,
-            "days_counted": len(all_dates),
+            "days_counted": len(daily_chill),
             "daily": daily,
         }
     except Exception as exc: