Fix missing parameter errors by using defaults for removed variables

- Remove pressure (pmsl) processing since not downloaded
- Use default values for rain types, lightning, solar radiation
- Keep only downloaded parameters: temp, wind, precip, snow, clouds, cape, gusts
- Fixes KeyError crashes while maintaining fast downloads

app.py

@@ -434,15 +434,8 @@ def process_real_dwd_data(dwd_data, lat, lon):
             vmax = data['vmax_10m'][i]
             wind_gust.append(vmax if vmax is not None else wind_speed_val * 1.5)
             
-            # Pressure (convert from Pa to hPa if needed)
-            pmsl = data['pmsl'][i]
-            if pmsl is not None:
-                if pmsl > 50000:  # Pa
-                    pressure.append(pmsl / 100)
-                else:  # Already hPa
-                    pressure.append(pmsl)
-            else:
-                pressure.append(1013.25)  # Default
+            # Pressure - use default since we don't download it for speed
+            pressure.append(1013.25)  # Default pressure for faster processing
             
             # Precipitation (convert from kg/m²/s to mm/h if needed)
             tot_prec = data['tot_prec'][i]
@@ -454,35 +447,10 @@ def process_real_dwd_data(dwd_data, lat, lon):
             else:
                 precipitation.append(0.0)
             
-            # Convective rain (thunderstorm precipitation)
-            rain_con = data.get('rain_con', [None])[i] if 'rain_con' in data else None
-            if rain_con is not None:
-                if rain_con < 1:  # kg/m²/s
-                    rain_convective.append(rain_con * 3600)  # Convert to mm/h
-                else:
-                    rain_convective.append(rain_con)
-            else:
-                rain_convective.append(0.0)
-            
-            # Grid-scale rain
-            rain_gsp = data.get('rain_gsp', [None])[i] if 'rain_gsp' in data else None
-            if rain_gsp is not None:
-                if rain_gsp < 1:  # kg/m²/s
-                    rain_gridscale.append(rain_gsp * 3600)  # Convert to mm/h
-                else:
-                    rain_gridscale.append(rain_gsp)
-            else:
-                rain_gridscale.append(0.0)
-            
-            # Convective snow
-            snow_con = data.get('snow_con', [None])[i] if 'snow_con' in data else None
-            if snow_con is not None:
-                if snow_con < 1:  # kg/m²/s
-                    snow_convective.append(snow_con * 3600)  # Convert to mm/h
-                else:
-                    snow_convective.append(snow_con)
-            else:
-                snow_convective.append(0.0)
+            # Rain data - use defaults for faster processing
+            rain_convective.append(0.0)  # Default - not downloaded
+            rain_gridscale.append(0.0)   # Default - not downloaded
+            snow_convective.append(0.0)  # Default - not downloaded
             
             # Grid-scale snow
             snow_gsp = data.get('snow_gsp', [None])[i] if 'snow_gsp' in data else None
@@ -501,15 +469,11 @@ def process_real_dwd_data(dwd_data, lat, lon):
             else:
                 cape.append(0.0)
             
-            # Lightning Potential Index
-            lpi_con = data.get('lpi_con', [None])[i] if 'lpi_con' in data else None
-            if lpi_con is not None:
-                lightning_potential.append(lpi_con)
-            else:
-                lightning_potential.append(0.0)
+            # Lightning Potential - use default for faster processing
+            lightning_potential.append(0.0)  # Default - not downloaded
             
             # Cloud cover (convert from fraction to percentage if needed)
-            clct = data['clct'][i]
+            clct = data.get('clct', [None])[i] if 'clct' in data else None
             if clct is not None:
                 if clct <= 1.0:  # Fraction
                     cloud_cover.append(clct * 100)
@@ -518,12 +482,8 @@ def process_real_dwd_data(dwd_data, lat, lon):
             else:
                 cloud_cover.append(50.0)  # Default
             
-            # Solar radiation
-            asob_s = data['asob_s'][i]
-            if asob_s is not None:
-                solar_radiation.append(max(0, asob_s))  # Ensure non-negative
-            else:
-                solar_radiation.append(0.0)
+            # Solar radiation - use default for faster processing
+            solar_radiation.append(0.0)  # Default - not downloaded
         
         result = {
             'timestamps': timestamps,