Fix advisories generation error in NOAA text forecasting

- Fix ValueError in generate_advisories when finding max wind speed
- Correct event property access using proper dictionary keys
- Add additional advisory types (freeze warning, heat advisory)
- Improve error handling for empty event sequences

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

app.py

@@ -843,23 +843,30 @@ def generate_advisories(events):
     """
     advisories = []
     
-    # Check for significant events
-    max_wind = max([e.get('wind_speed', 0) for e in events if 'wind_speed' in str(e)])
-    max_precip = max([e.get('precipitation', 0) for e in events if 'precipitation' in str(e)])
-    severe_events = [e for e in events if e['severity'] == 'significant']
-    
-    if any('very_windy' in str(e) for e in events):
+    # Check for significant events based on wind descriptors and conditions
+    if any(e.get('wind_descriptor') == 'very_windy' for e in events):
         advisories.append("• **Wind Advisory:** Sustained winds 15-25 m/s with gusts up to 30 m/s possible")
     
-    if any('heavy_rain' in str(e) for e in events):
+    if any(e.get('precipitation_type') == 'heavy_rain' for e in events):
         advisories.append("• **Heavy Rain:** Rainfall rates may exceed 5mm/h, leading to localized flooding")
     
-    if any('thunderstorms' in str(e) for e in events):
+    if any(e.get('precipitation_type') == 'thunderstorms' for e in events):
         advisories.append("• **Thunderstorm Watch:** Conditions favorable for thunderstorm development")
     
-    if any('snow' in str(e) for e in events):
+    if any(e.get('precipitation_type') == 'snow' for e in events):
         advisories.append("• **Winter Weather:** Snow accumulation possible, use caution when traveling")
     
+    if any(e.get('temperature_descriptor') == 'freezing' for e in events):
+        advisories.append("• **Freeze Warning:** Temperatures at or below freezing expected")
+    
+    if any(e.get('temperature_descriptor') == 'hot' for e in events):
+        advisories.append("• **Heat Advisory:** High temperatures may cause heat stress")
+    
+    # Check for significant severity events
+    severe_events = [e for e in events if e.get('severity') == 'significant']
+    if severe_events and not advisories:
+        advisories.append("• **Weather Advisory:** Significant weather conditions expected")
+    
     return '\n'.join(advisories)
 
 def create_forecast_plot(forecast_data):