Update app.py

app.py

@@ -4145,500 +4145,5 @@ initialize_data()
 demo = create_interface()
 
 if __name__ == "__main__":
-    demo.launch(share=True)  # Enable sharing with public link': current_lat,
-                'lon': current_lon,
-                'intensity_kt': current_intensity,
-                'category': categorize_typhoon_enhanced(current_intensity),
-                'confidence': confidence,
-                'development_stage': stage,
-                'forward_speed_kmh': base_speed * 111,  # Convert to km/h
-                'pressure_hpa': max(900, 1013 - (current_intensity - 25) * 0.9),
-                'environmental_limit': environmental_limit,
-                'sst_celsius': current_sst,
-                'slp_hpa': current_slp,
-                'intensity_tendency': intensity_tendency
-            })
-        
-        results['route_forecast'] = route_points
-        
-        # Enhanced confidence scores with environmental factors
-        base_confidence = 0.90 if use_real_data else 0.75
-        
-        results['confidence_scores'] = {
-            'genesis': base_confidence,
-            'early_development': base_confidence - 0.05,
-            'position_24h': base_confidence - 0.08,
-            'position_48h': base_confidence - 0.15,
-            'position_72h': base_confidence - 0.25,
-            'intensity_24h': (base_confidence - 0.10) if use_real_data else 0.65,
-            'intensity_48h': (base_confidence - 0.20) if use_real_data else 0.55,
-            'intensity_72h': (base_confidence - 0.30) if use_real_data else 0.45,
-            'environmental_coupling': 0.85 if use_real_data else 0.60
-        }
-        
-        # Enhanced model information
-        data_sources = []
-        if sst_data and sst_data['success']:
-            data_sources.append("NOAA OISST v2")
-        if slp_data and slp_data['success']:
-            data_sources.append("NCEP/NCAR Reanalysis")
-        
-        if data_sources:
-            results['model_info'] = f"Enhanced Oceanic Model using {', '.join(data_sources)}"
-        else:
-            results['model_info'] = "Enhanced Climatological Model"
-        
-        logging.info(f"Enhanced prediction complete: {len(route_points)} forecast points")
-        return results
-        
-    except Exception as e:
-        logging.error(f"Error in enhanced oceanic prediction: {e}")
-        import traceback
-        traceback.print_exc()
-        
-        # Fallback to basic prediction
-        return predict_storm_route_and_intensity_realistic(
-            genesis_region, month, oni_value, models, forecast_hours, True
-        )
-
-def calculate_environmental_steering_speed(lat, lon, month, oni_value, slp_data):
-    """Calculate storm forward speed based on environmental steering"""
-    base_speed = 0.15  # Default speed in degrees/hour
-    
-    # Latitude effects
-    if lat < 20:
-        speed_factor = 0.8  # Slower in tropics
-    elif lat < 30:
-        speed_factor = 1.2  # Faster in subtropics
-    else:
-        speed_factor = 1.5  # Fast in mid-latitudes
-    
-    # Pressure gradient effects (if SLP data available)
-    if slp_data and slp_data['success']:
-        try:
-            # Calculate approximate pressure gradient (simplified)
-            slp_value = oceanic_manager.interpolate_data_to_point(slp_data, lat, lon, 'slp')
-            if not np.isnan(slp_value):
-                slp_hpa = slp_value if slp_value > 500 else slp_value / 100
-                if slp_hpa < 1008:  # Low pressure - faster motion
-                    speed_factor *= 1.2
-                elif slp_hpa > 1015:  # High pressure - slower motion
-                    speed_factor *= 0.8
-        except:
-            pass
-    
-    return base_speed * speed_factor
-
-def calculate_motion_tendency(lat, lon, month, oni_value, hour, slp_data):
-    """Calculate motion tendency with environmental steering"""
-    # Base climatological motion
-    ridge_position = 32 + 4 * np.sin(2 * np.pi * (month - 6) / 4)
-    
-    if lat < ridge_position - 10:
-        base_lat_tendency = 0.05  # Poleward
-        base_lon_tendency = -0.12  # Westward
-    elif lat > ridge_position - 3:
-        base_lat_tendency = 0.15  # Strong poleward (recurvature)
-        base_lon_tendency = 0.08   # Eastward
-    else:
-        base_lat_tendency = 0.08   # Moderate poleward
-        base_lon_tendency = -0.06  # Moderate westward
-    
-    # ENSO steering effects
-    if oni_value > 0.5:  # El Niño
-        base_lon_tendency += 0.03  # More eastward
-        base_lat_tendency += 0.01  # Slightly more poleward
-    elif oni_value < -0.5:  # La Niña
-        base_lon_tendency -= 0.04  # More westward
-    
-    # Add realistic motion uncertainty
-    motion_uncertainty = 0.02 + (hour / 120) * 0.03
-    lat_noise = np.random.normal(0, motion_uncertainty)
-    lon_noise = np.random.normal(0, motion_uncertainty)
-    
-    return base_lat_tendency + lat_noise, base_lon_tendency + lon_noise
-
-def calculate_environmental_intensity_change(
-    current_intensity, environmental_limit, hour, lat, lon, month, oni_value, sst_data
-):
-    """Calculate intensity change based on environmental conditions"""
-    
-    # Base intensity tendency based on development stage
-    if hour <= 48:  # Development phase
-        if current_intensity < environmental_limit * 0.6:
-            base_tendency = 3.5  # Rapid development possible
-        elif current_intensity < environmental_limit * 0.8:
-            base_tendency = 2.0  # Moderate development
-        else:
-            base_tendency = 0.5  # Near limit
-    elif hour <= 120:  # Mature phase
-        if current_intensity < environmental_limit:
-            base_tendency = 1.0  # Slow intensification
-        else:
-            base_tendency = -0.5  # Slight weakening
-    else:  # Extended phase
-        base_tendency = -2.0  # General weakening trend
-    
-    # Environmental limit constraint
-    if current_intensity >= environmental_limit:
-        base_tendency = min(base_tendency, -1.0)  # Force weakening if over limit
-    
-    # SST effects on development rate
-    if sst_data and sst_data['success']:
-        try:
-            sst_value = oceanic_manager.interpolate_data_to_point(sst_data, lat, lon, 'sst')
-            if not np.isnan(sst_value):
-                sst_celsius = sst_value if sst_value < 50 else sst_value - 273.15
-                if sst_celsius >= 29.5:  # Very warm - enhanced development
-                    base_tendency += 1.5
-                elif sst_celsius >= 28.0:  # Warm - normal development
-                    base_tendency += 0.5
-                elif sst_celsius < 26.5:  # Cool - inhibited development
-                    base_tendency -= 2.0
-        except:
-            pass
-    
-    # Land interaction
-    if lon < 110 or (120 < lon < 125 and lat > 20):  # Near land masses
-        base_tendency -= 8.0
-    
-    # High latitude weakening
-    if lat > 35:
-        base_tendency -= 10.0
-    elif lat > 30:
-        base_tendency -= 4.0
-    
-    # Add realistic intensity uncertainty
-    intensity_noise = np.random.normal(0, 1.0)
-    
-    return base_tendency + intensity_noise
-
-def calculate_dynamic_confidence(hour, lat, lon, use_real_data, sst_success, slp_success):
-    """Calculate dynamic confidence based on data availability and conditions"""
-    base_confidence = 0.92
-    
-    # Time penalty
-    time_penalty = (hour / 120) * 0.35
-    
-    # Data quality bonus
-    data_bonus = 0.0
-    if use_real_data:
-        if sst_success:
-            data_bonus += 0.08
-        if slp_success:
-            data_bonus += 0.05
-    
-    # Environmental uncertainty
-    environment_penalty = 0.0
-    if lat > 30 or lon < 115:  # Challenging forecast regions
-        environment_penalty = 0.12
-    elif lat > 25:
-        environment_penalty = 0.06
-    
-    final_confidence = base_confidence + data_bonus - time_penalty - environment_penalty
-    return max(0.25, min(0.95, final_confidence))
-
-def get_environmental_development_stage(hour, intensity, environmental_limit):
-    """Determine development stage based on time and environmental context"""
-    intensity_fraction = intensity / max(environmental_limit, 50)
-    
-    if hour <= 24:
-        return 'Genesis'
-    elif hour <= 72:
-        if intensity_fraction < 0.3:
-            return 'Early Development'
-        elif intensity_fraction < 0.6:
-            return 'Active Development'
-        else:
-            return 'Rapid Development'
-    elif hour <= 120:
-        if intensity_fraction > 0.8:
-            return 'Peak Intensity'
-        else:
-            return 'Mature Stage'
-    else:
-        return 'Extended Forecast'
-
-def predict_storm_route_and_intensity_realistic(genesis_region, month, oni_value, models=None, forecast_hours=72, use_advanced_physics=True):
-    """Realistic prediction with proper typhoon speeds and development"""
-    try:
-        genesis_locations = get_realistic_genesis_locations()
-        
-        if genesis_region not in genesis_locations:
-            genesis_region = "Western Pacific Main Development Region"  # Default
-        
-        genesis_info = genesis_locations[genesis_region]
-        lat = genesis_info["lat"]
-        lon = genesis_info["lon"]
-        
-        results = {
-            'current_prediction': {},
-            'route_forecast': [],
-            'confidence_scores': {},
-            'model_info': 'Realistic Genesis Model',
-            'genesis_info': genesis_info
-        }
-        
-        # REALISTIC starting intensity - Tropical Depression level
-        base_intensity = 30  # Start at TD level (25-35 kt)
-        
-        # Environmental factors for genesis
-        if oni_value > 1.0:  # Strong El Niño - suppressed development
-            intensity_modifier = -6
-        elif oni_value > 0.5:  # Moderate El Niño
-            intensity_modifier = -3
-        elif oni_value < -1.0:  # Strong La Niña - enhanced development
-            intensity_modifier = +8
-        elif oni_value < -0.5:  # Moderate La Niña
-            intensity_modifier = +5
-        else:  # Neutral
-            intensity_modifier = oni_value * 2
-        
-        # Seasonal genesis effects
-        seasonal_factors = {
-            1: -8, 2: -6, 3: -4, 4: -2, 5: 2, 6: 6,
-            7: 10, 8: 12, 9: 15, 10: 10, 11: 4, 12: -5
-        }
-        seasonal_modifier = seasonal_factors.get(month, 0)
-        
-        # Genesis region favorability
-        region_factors = {
-            "Western Pacific Main Development Region": 8,
-            "South China Sea": 4,
-            "Philippine Sea": 5,
-            "Marshall Islands": 7,
-            "Monsoon Trough": 6,
-            "ITCZ Region": 3,
-            "Subtropical Region": 2,
-            "Bay of Bengal": 4,
-            "Eastern Pacific": 6,
-            "Atlantic MDR": 5
-        }
-        region_modifier = region_factors.get(genesis_region, 0)
-        
-        # Calculate realistic starting intensity (TD level)
-        predicted_intensity = base_intensity + intensity_modifier + seasonal_modifier + region_modifier
-        predicted_intensity = max(25, min(40, predicted_intensity))  # Keep in TD-weak TS range
-        
-        # Add realistic uncertainty for genesis
-        intensity_uncertainty = np.random.normal(0, 2)
-        predicted_intensity += intensity_uncertainty
-        predicted_intensity = max(25, min(38, predicted_intensity))  # TD range
+    demo.launch(share=True)  
         
-        results['current_prediction'] = {
-            'intensity_kt': predicted_intensity,
-            'pressure_hpa': 1008 - (predicted_intensity - 25) * 0.6,  # Realistic TD pressure
-            'category': categorize_typhoon_enhanced(predicted_intensity),
-            'genesis_region': genesis_region
-        }
-        
-        # REALISTIC route prediction with proper typhoon speeds
-        current_lat = lat
-        current_lon = lon
-        current_intensity = predicted_intensity
-        
-        route_points = []
-        
-        # Track storm development over time with REALISTIC SPEEDS
-        for hour in range(0, forecast_hours + 6, 6):
-            
-            # REALISTIC typhoon motion - much faster speeds
-            # Typical typhoon forward speed: 15-25 km/h (0.14-0.23°/hour)
-            
-            # Base forward speed depends on latitude and storm intensity
-            if current_lat < 20:  # Low latitude - slower
-                base_speed = 0.12  # ~13 km/h
-            elif current_lat < 30:  # Mid latitude - moderate
-                base_speed = 0.18  # ~20 km/h
-            else:  # High latitude - faster
-                base_speed = 0.25  # ~28 km/h
-            
-            # Intensity affects speed (stronger storms can move faster)
-            intensity_speed_factor = 1.0 + (current_intensity - 50) / 200
-            base_speed *= max(0.8, min(1.4, intensity_speed_factor))
-            
-            # Beta drift (Coriolis effect) - realistic values
-            beta_drift_lat = 0.02 * np.sin(np.radians(current_lat))
-            beta_drift_lon = -0.05 * np.cos(np.radians(current_lat))
-            
-            # Seasonal steering patterns with realistic speeds
-            if month in [6, 7, 8, 9]:  # Peak season
-                ridge_strength = 1.2
-                ridge_position = 32 + 4 * np.sin(2 * np.pi * (month - 6) / 4)
-            else:  # Off season
-                ridge_strength = 0.9
-                ridge_position = 28
-            
-            # REALISTIC motion based on position relative to subtropical ridge
-            if current_lat < ridge_position - 10:  # Well south of ridge - westward movement
-                lat_tendency = base_speed * 0.3 + beta_drift_lat  # Slight poleward
-                lon_tendency = -base_speed * 0.9 + beta_drift_lon  # Strong westward
-            elif current_lat > ridge_position - 3:  # Near ridge - recurvature
-                lat_tendency = base_speed * 0.8 + beta_drift_lat  # Strong poleward
-                lon_tendency = base_speed * 0.4 + beta_drift_lon  # Eastward
-            else:  # In between - normal WNW motion
-                lat_tendency = base_speed * 0.4 + beta_drift_lat  # Moderate poleward
-                lon_tendency = -base_speed * 0.7 + beta_drift_lon  # Moderate westward
-            
-            # ENSO steering modulation (realistic effects)
-            if oni_value > 0.5:  # El Niño - more eastward/poleward motion
-                lon_tendency += 0.05
-                lat_tendency += 0.02
-            elif oni_value < -0.5:  # La Niña - more westward motion
-                lon_tendency -= 0.08
-                lat_tendency -= 0.01
-            
-            # Add motion uncertainty that grows with time (realistic error growth)
-            motion_uncertainty = 0.02 + (hour / 120) * 0.04
-            lat_noise = np.random.normal(0, motion_uncertainty)
-            lon_noise = np.random.normal(0, motion_uncertainty)
-            
-            # Update position with realistic speeds
-            current_lat += lat_tendency + lat_noise
-            current_lon += lon_tendency + lon_noise
-            
-            # REALISTIC intensity evolution with proper development cycles
-            
-            # Development phase (first 48-72 hours) - realistic intensification
-            if hour <= 48:
-                if current_intensity < 50:  # Still weak - rapid development possible
-                    if 10 <= current_lat <= 25 and 115 <= current_lon <= 165:  # Favorable environment
-                        intensity_tendency = 4.5 if current_intensity < 35 else 3.0
-                    elif 120 <= current_lon <= 155 and 15 <= current_lat <= 20:  # Best environment
-                        intensity_tendency = 6.0 if current_intensity < 40 else 4.0
-                    else:
-                        intensity_tendency = 2.0
-                elif current_intensity < 80:  # Moderate intensity
-                    intensity_tendency = 2.5 if (120 <= current_lon <= 155 and 10 <= current_lat <= 25) else 1.0
-                else:  # Already strong
-                    intensity_tendency = 1.0
-                    
-            # Mature phase (48-120 hours) - peak intensity maintenance
-            elif hour <= 120:
-                if current_lat < 25 and current_lon > 120:  # Still in favorable waters
-                    if current_intensity < 120:
-                        intensity_tendency = 1.5
-                    else:
-                        intensity_tendency = 0.0  # Maintain intensity
-                else:
-                    intensity_tendency = -1.5
-                    
-            # Extended phase (120+ hours) - gradual weakening
-            else:
-                if current_lat < 30 and current_lon > 115:
-                    intensity_tendency = -2.0  # Slow weakening
-                else:
-                    intensity_tendency = -3.5  # Faster weakening
-            
-            # Environmental modulation (realistic effects)
-            if current_lat > 35:  # High latitude - rapid weakening
-                intensity_tendency -= 12
-            elif current_lat > 30:  # Moderate latitude
-                intensity_tendency -= 5
-            elif current_lon < 110:  # Land interaction
-                intensity_tendency -= 15
-            elif 125 <= current_lon <= 155 and 10 <= current_lat <= 25:  # Warm pool
-                intensity_tendency += 2
-            elif 160 <= current_lon <= 180 and 15 <= current_lat <= 30:  # Still warm
-                intensity_tendency += 1
-            
-            # SST effects (realistic temperature impact)
-            if current_lat < 8:  # Very warm but weak Coriolis
-                intensity_tendency += 0.5
-            elif 8 <= current_lat <= 20:  # Sweet spot for development
-                intensity_tendency += 2.0
-            elif 20 < current_lat <= 30:  # Marginal
-                intensity_tendency -= 1.0
-            elif current_lat > 30:  # Cool waters
-                intensity_tendency -= 4.0
-            
-            # Shear effects (simplified but realistic)
-            if month in [12, 1, 2, 3]:  # High shear season
-                intensity_tendency -= 2.0
-            elif month in [7, 8, 9]:  # Low shear season
-                intensity_tendency += 1.0
-            
-            # Update intensity with realistic bounds and variability
-            intensity_noise = np.random.normal(0, 1.5)  # Small random fluctuations
-            current_intensity += intensity_tendency + intensity_noise
-            current_intensity = max(20, min(185, current_intensity))  # Realistic range
-            
-            # Calculate confidence based on forecast time and environment
-            base_confidence = 0.92
-            time_penalty = (hour / 120) * 0.45
-            environment_penalty = 0.15 if current_lat > 30 or current_lon < 115 else 0
-            confidence = max(0.25, base_confidence - time_penalty - environment_penalty)
-            
-            # Determine development stage
-            if hour <= 24:
-                stage = 'Genesis'
-            elif hour <= 72:
-                stage = 'Development'
-            elif hour <= 120:
-                stage = 'Mature'
-            elif hour <= 240:
-                stage = 'Extended'
-            else:
-                stage = 'Long-term'
-            
-            route_points.append({
-                'hour': hour,
-                'lat': current_lat,
-                'lon': current_lon,
-                'intensity_kt': current_intensity,
-                'category': categorize_typhoon_enhanced(current_intensity),
-                'confidence': confidence,
-                'development_stage': stage,
-                'forward_speed_kmh': base_speed * 111,  # Convert to km/h
-                'pressure_hpa': max(900, 1013 - (current_intensity - 25) * 0.9)
-            })
-        
-        results['route_forecast'] = route_points
-        
-        # Realistic confidence scores
-        results['confidence_scores'] = {
-            'genesis': 0.88,
-            'early_development': 0.82,
-            'position_24h': 0.85,
-            'position_48h': 0.78,
-            'position_72h': 0.68,
-            'intensity_24h': 0.75,
-            'intensity_48h': 0.65,
-            'intensity_72h': 0.55,
-            'long_term': max(0.3, 0.8 - (forecast_hours / 240) * 0.5)
-        }
-        
-        # Model information
-        results['model_info'] = f"Enhanced Realistic Model - {genesis_region}"
-        
-        return results
-        
-    except Exception as e:
-        logging.error(f"Realistic prediction error: {str(e)}")
-        return {
-            'error': f"Prediction error: {str(e)}",
-            'current_prediction': {'intensity_kt': 30, 'category': 'Tropical Depression'},
-            'route_forecast': [],
-            'confidence_scores': {},
-            'model_info': 'Error in prediction'
-        }
-
-# Update the existing predict_storm_route_and_intensity_realistic function to use oceanic data
-def predict_storm_route_and_intensity_realistic_enhanced(
-    genesis_region, month, oni_value, models=None, 
-    forecast_hours=72, use_advanced_physics=True
-):
-    """Enhanced wrapper that uses oceanic data when available"""
-    return predict_storm_route_and_intensity_with_oceanic_data(
-        genesis_region, month, oni_value, forecast_hours, 
-        use_real_data=True, models=models, enable_animation=True
-    )
-
-# Initialize data
-initialize_data()
-
-# Create and launch the interface
-demo = create_interface()
-
-if __name__ == "__main__":
-    demo.launch(share=True)  # Enable sharing with public link