Update app.py

app.py

@@ -1587,6 +1587,20 @@ def create_advanced_prediction_model(typhoon_data):
     except Exception as e:
         return None, f"Error creating prediction model: {str(e)}"
 
+def rgb_string_to_hex(rgb_string):
+    """Convert RGB string like 'rgb(255,0,0)' to hex format '#FF0000'"""
+    try:
+        if rgb_string.startswith('rgb(') and rgb_string.endswith(')'):
+            # Extract numbers from rgb(r,g,b)
+            rgb_values = rgb_string[4:-1].split(',')
+            r, g, b = [int(x.strip()) for x in rgb_values]
+            return f'#{r:02x}{g:02x}{b:02x}'
+        else:
+            # Already in hex or other format
+            return rgb_string
+    except:
+        return '#808080'  # Default gray
+
 def get_realistic_genesis_locations():
     """Get realistic typhoon genesis regions based on climatology"""
     return {
@@ -1603,7 +1617,7 @@ def get_realistic_genesis_locations():
     }
 
 def predict_storm_route_and_intensity_realistic(genesis_region, month, oni_value, models=None, forecast_hours=72, use_advanced_physics=True):
-    """Realistic prediction starting from TD intensity in proper genesis regions"""
+    """Realistic prediction with proper typhoon speeds and development"""
     try:
         genesis_locations = get_realistic_genesis_locations()
         
@@ -1623,11 +1637,11 @@ def predict_storm_route_and_intensity_realistic(genesis_region, month, oni_value
         }
         
         # REALISTIC starting intensity - Tropical Depression level
-        base_intensity = 28  # Start at TD level (25-33 kt)
+        base_intensity = 30  # Start at TD level (25-35 kt)
         
-        # Environmental factors for genesis (much smaller effects initially)
+        # Environmental factors for genesis
         if oni_value > 1.0:  # Strong El Niño - suppressed development
-            intensity_modifier = -5
+            intensity_modifier = -6
         elif oni_value > 0.5:  # Moderate El Niño
             intensity_modifier = -3
         elif oni_value < -1.0:  # Strong La Niña - enhanced development
@@ -1637,142 +1651,193 @@ def predict_storm_route_and_intensity_realistic(genesis_region, month, oni_value
         else:  # Neutral
             intensity_modifier = oni_value * 2
         
-        # Seasonal genesis effects (realistic for TD formation)
+        # Seasonal genesis effects
         seasonal_factors = {
-            1: -8, 2: -6, 3: -4, 4: -2, 5: 2, 6: 5,
-            7: 8, 8: 10, 9: 12, 10: 8, 11: 4, 12: -5
+            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": 6,
-            "South China Sea": 3,
-            "Philippine Sea": 4,
-            "Marshall Islands": 5,
-            "Monsoon Trough": 4,
-            "ITCZ Region": 2,
-            "Subtropical Region": 1,
-            "Bay of Bengal": 3,
-            "Eastern Pacific": 5,
-            "Atlantic MDR": 4
+            "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))  # Cap at weak TS level
+        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))  # Keep in TD-weak TS range
+        predicted_intensity = max(25, min(38, predicted_intensity))  # TD range
         
         results['current_prediction'] = {
             'intensity_kt': predicted_intensity,
-            'pressure_hpa': 1008 - (predicted_intensity - 25) * 0.5,  # Realistic TD pressure
+            'pressure_hpa': 1008 - (predicted_intensity - 25) * 0.6,  # Realistic TD pressure
             'category': categorize_typhoon_enhanced(predicted_intensity),
             'genesis_region': genesis_region
         }
         
-        # Enhanced route prediction with REALISTIC development cycle
+        # REALISTIC route prediction with proper typhoon speeds
         current_lat = lat
         current_lon = lon
         current_intensity = predicted_intensity
         
         route_points = []
         
-        # Track storm development over time
+        # Track storm development over time with REALISTIC SPEEDS
         for hour in range(0, forecast_hours + 6, 6):
             
-            # Realistic storm motion based on beta drift and steering
-            # Beta drift (Coriolis effect)
-            beta_drift_lat = 0.03 * np.sin(np.radians(current_lat))
-            beta_drift_lon = -0.08 * np.cos(np.radians(current_lat))
+            # REALISTIC typhoon motion - much faster speeds
+            # Typical typhoon forward speed: 15-25 km/h (0.14-0.23°/hour)
             
-            # Seasonal steering patterns
+            # 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 = 1.0
-                ridge_position = 30 + 3 * np.sin(2 * np.pi * (month - 6) / 4)
+                ridge_strength = 1.2
+                ridge_position = 32 + 4 * np.sin(2 * np.pi * (month - 6) / 4)
             else:  # Off season
-                ridge_strength = 0.7
-                ridge_position = 25
+                ridge_strength = 0.9
+                ridge_position = 28
             
-            # Motion based on position relative to subtropical ridge
-            if current_lat < ridge_position - 8:  # Well south of ridge
-                lat_tendency = 0.1 + beta_drift_lat
-                lon_tendency = -0.35 + beta_drift_lon
+            # 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 = 0.25 + beta_drift_lat
-                lon_tendency = 0.05 + beta_drift_lon
-            else:  # In between
-                lat_tendency = 0.15 + beta_drift_lat
-                lon_tendency = -0.25 + beta_drift_lon
-            
-            # ENSO steering modulation
-            if oni_value > 0.5:  # El Niño - more eastward motion
-                lon_tendency += 0.1
-            elif oni_value < -0.5:  # La Niña - more westward
+                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
-            motion_uncertainty = 0.02 + (hour / 72) * 0.03
+            # 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
+            # Update position with realistic speeds
             current_lat += lat_tendency + lat_noise
             current_lon += lon_tendency + lon_noise
             
-            # REALISTIC intensity evolution - storms don't just weaken!
+            # REALISTIC intensity evolution with proper development cycles
             
-            # Development phase (first 48-72 hours)
+            # Development phase (first 48-72 hours) - realistic intensification
             if hour <= 48:
-                if current_intensity < 65:  # Still developing
-                    if 15 <= current_lat <= 25 and 120 <= current_lon <= 160:  # Favorable environment
-                        intensity_tendency = 3.5 if current_intensity < 45 else 2.0
+                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 = 1.5
+                        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 = 0.5
-            # Mature phase (48-96 hours)
-            elif hour <= 96:
-                if current_lat < 30 and current_lon > 120:  # Still in favorable waters
-                    intensity_tendency = 0.5 if current_intensity < 100 else -0.5
+                    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 = -1.0
-            # Decay phase (96+ hours)
+                    intensity_tendency = -1.5
+                    
+            # Extended phase (120+ hours) - gradual weakening
             else:
-                intensity_tendency = -1.5
+                if current_lat < 30 and current_lon > 115:
+                    intensity_tendency = -2.0  # Slow weakening
+                else:
+                    intensity_tendency = -3.5  # Faster weakening
             
-            # Environmental modulation
+            # Environmental modulation (realistic effects)
             if current_lat > 35:  # High latitude - rapid weakening
-                intensity_tendency -= 6
+                intensity_tendency -= 12
             elif current_lat > 30:  # Moderate latitude
-                intensity_tendency -= 2
-            elif current_lon < 115:  # Land interaction
-                intensity_tendency -= 8
+                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)
-            if current_lat < 8:  # Very warm but near equator (weak Coriolis)
+            # 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
-                intensity_tendency += 1.5
-            elif current_lat > 30:  # Cooler waters
-                intensity_tendency -= 3
-            
-            # Update intensity with realistic bounds
-            current_intensity += intensity_tendency
-            current_intensity = max(20, min(180, current_intensity))  # Realistic range
+            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 = 0.9
-            time_penalty = (hour / 72) * 0.4
-            environment_penalty = 0.1 if current_lat > 30 or current_lon < 120 else 0
+            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,
@@ -1780,26 +1845,28 @@ def predict_storm_route_and_intensity_realistic(genesis_region, month, oni_value
                 'intensity_kt': current_intensity,
                 'category': categorize_typhoon_enhanced(current_intensity),
                 'confidence': confidence,
-                'development_stage': 'Genesis' if hour <= 24 else ('Development' if hour <= 72 else ('Mature' if hour <= 120 else 'Decay'))
+                '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': 0.85,
-            'early_development': 0.80,
+            'genesis': 0.88,
+            'early_development': 0.82,
             'position_24h': 0.85,
-            'position_48h': 0.75,
-            'position_72h': 0.65,
-            'intensity_24h': 0.70,
-            'intensity_48h': 0.60,
-            'intensity_72h': 0.50,
-            'long_term': max(0.3, 0.8 - (forecast_hours / 120) * 0.5)
+            '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"Realistic Genesis Model - {genesis_region}"
+        results['model_info'] = f"Enhanced Realistic Model - {genesis_region}"
         
         return results
         
@@ -1814,7 +1881,7 @@ def predict_storm_route_and_intensity_realistic(genesis_region, month, oni_value
         }
 
 def create_animated_route_visualization(prediction_results, show_uncertainty=True, enable_animation=True):
-    """Create animated and expandable route visualization"""
+    """Create comprehensive animated route visualization with intensity plots"""
     try:
         if 'route_forecast' not in prediction_results or not prediction_results['route_forecast']:
             return None, "No route forecast data available"
@@ -1829,11 +1896,24 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
         categories = [point['category'] for point in route_data]
         confidences = [point.get('confidence', 0.8) for point in route_data]
         stages = [point.get('development_stage', 'Unknown') for point in route_data]
+        speeds = [point.get('forward_speed_kmh', 15) for point in route_data]
+        pressures = [point.get('pressure_hpa', 1013) for point in route_data]
+        
+        # Create subplot layout with map and intensity plot
+        fig = make_subplots(
+            rows=2, cols=2,
+            subplot_titles=('Storm Track Animation', 'Wind Speed vs Time', 'Forward Speed vs Time', 'Pressure vs Time'),
+            specs=[[{"type": "geo", "colspan": 2}, None],
+                   [{"type": "xy"}, {"type": "xy"}]],
+            vertical_spacing=0.15,
+            row_heights=[0.7, 0.3]
+        )
         
         if enable_animation:
-            # Create animated figure
-            fig = go.Figure()
+            # Add frames for animation
+            frames = []
             
+            # Static background elements first
             # Add complete track as background
             fig.add_trace(
                 go.Scattergeo(
@@ -1843,35 +1923,62 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                     line=dict(color='lightgray', width=2, dash='dot'),
                     name='Complete Track',
                     showlegend=True,
-                    opacity=0.5
-                )
+                    opacity=0.4
+                ),
+                row=1, col=1
             )
             
-            # Add frames for animation
-            frames = []
+            # Genesis marker (always visible)
+            fig.add_trace(
+                go.Scattergeo(
+                    lon=[lons[0]],
+                    lat=[lats[0]],
+                    mode='markers',
+                    marker=dict(
+                        size=25,
+                        color='gold',
+                        symbol='star',
+                        line=dict(width=3, color='black')
+                    ),
+                    name='Genesis',
+                    showlegend=True,
+                    hovertemplate=(
+                        f"<b>GENESIS</b><br>"
+                        f"Position: {lats[0]:.1f}°N, {lons[0]:.1f}°E<br>"
+                        f"Initial: {intensities[0]:.0f} kt<br>"
+                        f"Region: {prediction_results['genesis_info']['description']}<br>"
+                        "<extra></extra>"
+                    )
+                ),
+                row=1, col=1
+            )
+            
+            # Create animation frames
             for i in range(len(route_data)):
                 frame_lons = lons[:i+1]
                 frame_lats = lats[:i+1]
                 frame_intensities = intensities[:i+1]
                 frame_categories = categories[:i+1]
+                frame_hours = hours[:i+1]
                 
                 # Current position marker
                 current_color = enhanced_color_map.get(frame_categories[-1], 'rgb(128,128,128)')
                 current_size = 15 + (frame_intensities[-1] / 10)
                 
                 frame_data = [
-                    # Track line up to current point
+                    # Animated track up to current point
                     go.Scattergeo(
                         lon=frame_lons,
                         lat=frame_lats,
                         mode='lines+markers',
-                        line=dict(color='blue', width=3),
+                        line=dict(color='blue', width=4),
                         marker=dict(
                             size=[8 + (intensity/15) for intensity in frame_intensities],
                             color=[enhanced_color_map.get(cat, 'rgb(128,128,128)') for cat in frame_categories],
-                            opacity=0.8
+                            opacity=0.8,
+                            line=dict(width=1, color='white')
                         ),
-                        name='Track',
+                        name='Current Track',
                         showlegend=False
                     ),
                     # Current position highlight
@@ -1882,8 +1989,8 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                         marker=dict(
                             size=current_size,
                             color=current_color,
-                            symbol='star',
-                            line=dict(width=2, color='white')
+                            symbol='circle',
+                            line=dict(width=3, color='white')
                         ),
                         name='Current Position',
                         showlegend=False,
@@ -1893,9 +2000,43 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                             f"Intensity: {intensities[i]:.0f} kt<br>"
                             f"Category: {categories[i]}<br>"
                             f"Stage: {stages[i]}<br>"
+                            f"Speed: {speeds[i]:.1f} km/h<br>"
                             f"Confidence: {confidences[i]*100:.0f}%<br>"
                             "<extra></extra>"
                         )
+                    ),
+                    # Animated wind plot
+                    go.Scatter(
+                        x=frame_hours,
+                        y=frame_intensities,
+                        mode='lines+markers',
+                        line=dict(color='red', width=3),
+                        marker=dict(size=6, color='red'),
+                        name='Wind Speed',
+                        showlegend=False,
+                        yaxis='y2'
+                    ),
+                    # Animated speed plot
+                    go.Scatter(
+                        x=frame_hours,
+                        y=speeds[:i+1],
+                        mode='lines+markers',
+                        line=dict(color='green', width=2),
+                        marker=dict(size=4, color='green'),
+                        name='Forward Speed',
+                        showlegend=False,
+                        yaxis='y3'
+                    ),
+                    # Animated pressure plot
+                    go.Scatter(
+                        x=frame_hours,
+                        y=pressures[:i+1],
+                        mode='lines+markers',
+                        line=dict(color='purple', width=2),
+                        marker=dict(size=4, color='purple'),
+                        name='Pressure',
+                        showlegend=False,
+                        yaxis='y4'
                     )
                 ]
                 
@@ -1903,20 +2044,20 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                     data=frame_data,
                     name=str(i),
                     layout=go.Layout(
-                        title=f"Storm Forecast Animation - Hour {route_data[i]['hour']}<br>"
-                              f"Intensity: {intensities[i]:.0f} kt | Category: {categories[i]} | Stage: {stages[i]}"
+                        title=f"Storm Development Animation - Hour {route_data[i]['hour']}<br>"
+                              f"Intensity: {intensities[i]:.0f} kt | Category: {categories[i]} | Stage: {stages[i]} | Speed: {speeds[i]:.1f} km/h"
                     )
                 ))
             
             fig.frames = frames
             
-            # Add play/pause buttons
+            # Add play/pause controls
             fig.update_layout(
                 updatemenus=[
                     {
                         "buttons": [
                             {
-                                "args": [None, {"frame": {"duration": 800, "redraw": True},
+                                "args": [None, {"frame": {"duration": 1000, "redraw": True},
                                               "fromcurrent": True, "transition": {"duration": 300}}],
                                 "label": "▶️ Play",
                                 "method": "animate"
@@ -1926,6 +2067,12 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                                                 "mode": "immediate", "transition": {"duration": 0}}],
                                 "label": "⏸️ Pause",
                                 "method": "animate"
+                            },
+                            {
+                                "args": [None, {"frame": {"duration": 500, "redraw": True},
+                                              "fromcurrent": True, "transition": {"duration": 300}}],
+                                "label": "⏩ Fast",
+                                "method": "animate"
                             }
                         ],
                         "direction": "left",
@@ -1943,8 +2090,8 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                     "yanchor": "top",
                     "xanchor": "left",
                     "currentvalue": {
-                        "font": {"size": 20},
-                        "prefix": "Hour:",
+                        "font": {"size": 16},
+                        "prefix": "Hour: ",
                         "visible": True,
                         "xanchor": "right"
                     },
@@ -1957,50 +2104,46 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                         {
                             "args": [[str(i)], {"frame": {"duration": 300, "redraw": True},
                                                "mode": "immediate", "transition": {"duration": 300}}],
-                            "label": f"Hour {route_data[i]['hour']}",
+                            "label": f"H{route_data[i]['hour']}",
                             "method": "animate"
                         }
-                        for i in range(len(route_data))
+                        for i in range(0, len(route_data), max(1, len(route_data)//20))  # Limit slider steps
                     ]
                 }]
             )
             
         else:
-            # Create static expandable figure
-            fig = go.Figure()
+            # Static view with all points
+            # Add genesis marker
+            fig.add_trace(
+                go.Scattergeo(
+                    lon=[lons[0]],
+                    lat=[lats[0]],
+                    mode='markers',
+                    marker=dict(
+                        size=25,
+                        color='gold',
+                        symbol='star',
+                        line=dict(width=3, color='black')
+                    ),
+                    name='Genesis',
+                    showlegend=True,
+                    hovertemplate=(
+                        f"<b>GENESIS</b><br>"
+                        f"Position: {lats[0]:.1f}°N, {lons[0]:.1f}°E<br>"
+                        f"Initial: {intensities[0]:.0f} kt<br>"
+                        "<extra></extra>"
+                    )
+                ),
+                row=1, col=1
+            )
             
             # Add full track with intensity coloring
-            for i in range(len(route_data)):
+            for i in range(0, len(route_data), max(1, len(route_data)//50)):  # Sample points for performance
                 point = route_data[i]
                 color = enhanced_color_map.get(point['category'], 'rgb(128,128,128)')
                 size = 8 + (point['intensity_kt'] / 12)
                 
-                # Genesis point special marker
-                if i == 0:
-                    fig.add_trace(
-                        go.Scattergeo(
-                            lon=[point['lon']],
-                            lat=[point['lat']],
-                            mode='markers',
-                            marker=dict(
-                                size=20,
-                                color='yellow',
-                                symbol='star',
-                                line=dict(width=3, color='black')
-                            ),
-                            name='Genesis',
-                            showlegend=True,
-                            hovertemplate=(
-                                f"<b>GENESIS - {prediction_results['genesis_info']['description']}</b><br>"
-                                f"Position: {point['lat']:.1f}°N, {point['lon']:.1f}°E<br>"
-                                f"Initial Intensity: {point['intensity_kt']:.0f} kt<br>"
-                                f"Category: {point['category']}<br>"
-                                "<extra></extra>"
-                            )
-                        )
-                    )
-                
-                # Regular track points
                 fig.add_trace(
                     go.Scattergeo(
                         lon=[point['lon']],
@@ -2012,18 +2155,19 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                             opacity=point.get('confidence', 0.8),
                             line=dict(width=1, color='white')
                         ),
-                        name=f"Hour {point['hour']}" if i % 8 == 0 else None,
-                        showlegend=(i % 8 == 0),
+                        name=f"Hour {point['hour']}" if i % 10 == 0 else None,
+                        showlegend=(i % 10 == 0),
                         hovertemplate=(
                             f"<b>Hour {point['hour']}</b><br>"
                             f"Position: {point['lat']:.1f}°N, {point['lon']:.1f}°E<br>"
                             f"Intensity: {point['intensity_kt']:.0f} kt<br>"
                             f"Category: {point['category']}<br>"
                             f"Stage: {point.get('development_stage', 'Unknown')}<br>"
-                            f"Confidence: {point.get('confidence', 0.8)*100:.0f}%<br>"
+                            f"Speed: {point.get('forward_speed_kmh', 15):.1f} km/h<br>"
                             "<extra></extra>"
                         )
-                    )
+                    ),
+                    row=1, col=1
                 )
             
             # Connect points with track line
@@ -2035,9 +2179,57 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                     line=dict(color='black', width=3),
                     name='Forecast Track',
                     showlegend=True
-                )
+                ),
+                row=1, col=1
+            )
+        
+        # Add static intensity, speed, and pressure plots
+        # Wind speed plot
+        fig.add_trace(
+            go.Scatter(
+                x=hours,
+                y=intensities,
+                mode='lines+markers',
+                line=dict(color='red', width=3),
+                marker=dict(size=6, color='red'),
+                name='Wind Speed',
+                showlegend=False
+            ),
+            row=2, col=1
+        )
+        
+        # Add category threshold lines
+        thresholds = [34, 64, 83, 96, 113, 137]
+        threshold_names = ['TS', 'C1', 'C2', 'C3', 'C4', 'C5']
+        
+        for thresh, name in zip(thresholds, threshold_names):
+            fig.add_trace(
+                go.Scatter(
+                    x=[min(hours), max(hours)],
+                    y=[thresh, thresh],
+                    mode='lines',
+                    line=dict(color='gray', width=1, dash='dash'),
+                    name=name,
+                    showlegend=False,
+                    hovertemplate=f"{name} Threshold: {thresh} kt<extra></extra>"
+                ),
+                row=2, col=1
             )
         
+        # Forward speed plot
+        fig.add_trace(
+            go.Scatter(
+                x=hours,
+                y=speeds,
+                mode='lines+markers',
+                line=dict(color='green', width=2),
+                marker=dict(size=4, color='green'),
+                name='Forward Speed',
+                showlegend=False
+            ),
+            row=2, col=2
+        )
+        
         # Add uncertainty cone if requested
         if show_uncertainty and len(route_data) > 1:
             uncertainty_lats_upper = []
@@ -2047,7 +2239,7 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
             
             for i, point in enumerate(route_data):
                 # Uncertainty grows with time and decreases with confidence
-                base_uncertainty = 0.3 + (i / len(route_data)) * 1.2
+                base_uncertainty = 0.4 + (i / len(route_data)) * 1.8
                 confidence_factor = point.get('confidence', 0.8)
                 uncertainty = base_uncertainty / confidence_factor
                 
@@ -2069,37 +2261,52 @@ def create_animated_route_visualization(prediction_results, show_uncertainty=Tru
                     line=dict(color='rgba(128,128,128,0.4)', width=1),
                     name='Uncertainty Cone',
                     showlegend=True
-                )
+                ),
+                row=1, col=1
             )
         
-        # Enhanced layout with larger size
+        # Enhanced layout
         fig.update_layout(
-            title=f"Realistic Storm Development Forecast<br><sub>Starting from {prediction_results['genesis_info']['description']}</sub>",
-            geo=dict(
-                projection_type="natural earth",
-                showland=True,
-                landcolor="LightGray",
-                showocean=True,
-                oceancolor="LightBlue",
-                showcoastlines=True,
-                coastlinecolor="DarkGray",
-                showlakes=True,
-                lakecolor="LightBlue",
-                center=dict(lat=np.mean(lats), lon=np.mean(lons)),
-                projection_scale=2.5
-            ),
-            height=900,  # Much larger
-            width=1400,  # Much wider
+            title=f"Comprehensive Storm Development Analysis<br><sub>Starting from {prediction_results['genesis_info']['description']}</sub>",
+            height=1000,  # Taller for better subplot visibility
+            width=1400,   # Wider
             showlegend=True
         )
         
+        # Update geo layout
+        fig.update_geos(
+            projection_type="natural earth",
+            showland=True,
+            landcolor="LightGray",
+            showocean=True,
+            oceancolor="LightBlue",
+            showcoastlines=True,
+            coastlinecolor="DarkGray",
+            showlakes=True,
+            lakecolor="LightBlue",
+            center=dict(lat=np.mean(lats), lon=np.mean(lons)),
+            projection_scale=2.0,
+            row=1, col=1
+        )
+        
+        # Update subplot axes
+        fig.update_xaxes(title_text="Forecast Hour", row=2, col=1)
+        fig.update_yaxes(title_text="Wind Speed (kt)", row=2, col=1)
+        fig.update_xaxes(title_text="Forecast Hour", row=2, col=2)
+        fig.update_yaxes(title_text="Forward Speed (km/h)", row=2, col=2)
+        
         # Generate enhanced forecast text
         current = prediction_results['current_prediction']
         genesis_info = prediction_results['genesis_info']
         
+        # Calculate some statistics
+        max_intensity = max(intensities)
+        max_intensity_time = hours[intensities.index(max_intensity)]
+        avg_speed = np.mean(speeds)
+        
         forecast_text = f"""
-REALISTIC STORM DEVELOPMENT FORECAST
-{'='*60}
+COMPREHENSIVE STORM DEVELOPMENT FORECAST
+{'='*65}
 
 GENESIS CONDITIONS:
 • Region: {current.get('genesis_region', 'Unknown')}
@@ -2107,42 +2314,47 @@ GENESIS CONDITIONS:
 • Starting Position: {lats[0]:.1f}°N, {lons[0]:.1f}°E
 • Initial Intensity: {current['intensity_kt']:.0f} kt (Tropical Depression)
 • Genesis Pressure: {current.get('pressure_hpa', 1008):.0f} hPa
-• Genesis Category: {current['category']}
+
+STORM CHARACTERISTICS:
+• Peak Intensity: {max_intensity:.0f} kt at Hour {max_intensity_time}
+• Average Forward Speed: {avg_speed:.1f} km/h
+• Total Distance: {sum([speeds[i]/6 for i in range(len(speeds))]):.0f} km
+• Final Position: {lats[-1]:.1f}°N, {lons[-1]:.1f}°E
+• Forecast Duration: {hours[-1]} hours ({hours[-1]/24:.1f} days)
 
 DEVELOPMENT TIMELINE:
 • Hour 0 (Genesis): {intensities[0]:.0f} kt - {categories[0]}
-• Hour 24 (Early Dev): {intensities[min(4, len(intensities)-1)]:.0f} kt - {categories[min(4, len(categories)-1)]}
-• Hour 48 (Development): {intensities[min(8, len(intensities)-1)]:.0f} kt - {categories[min(8, len(categories)-1)]}
-• Hour 72 (Mature): {intensities[min(12, len(intensities)-1)]:.0f} kt - {categories[min(12, len(categories)-1)]}
-
-FORECAST TRACK:
-• Genesis: {lats[0]:.1f}°N, {lons[0]:.1f}°E
-• 24-hour: {lats[min(4, len(lats)-1)]:.1f}°N, {lons[min(4, len(lons)-1)]:.1f}°E
-• 48-hour: {lats[min(8, len(lats)-1)]:.1f}°N, {lons[min(8, len(lons)-1)]:.1f}°E
-• 72-hour: {lats[min(12, len(lats)-1)]:.1f}°N, {lons[min(12, len(lons)-1)]:.1f}°E
-• Final: {lats[-1]:.1f}°N, {lons[-1]:.1f}°E
-
-DEVELOPMENT STAGES:
-• Genesis (0-24h): Initial cyclogenesis and organization
-• Development (24-72h): Intensification in favorable environment
-• Mature (72-120h): Peak intensity and steady motion
-• Decay (120h+): Gradual weakening due to environmental factors
+• Hour 24: {intensities[min(4, len(intensities)-1)]:.0f} kt - {categories[min(4, len(categories)-1)]}
+• Hour 48: {intensities[min(8, len(intensities)-1)]:.0f} kt - {categories[min(8, len(categories)-1)]}
+• Hour 72: {intensities[min(12, len(intensities)-1)]:.0f} kt - {categories[min(12, len(categories)-1)]}
+• Final: {intensities[-1]:.0f} kt - {categories[-1]}
+
+MOTION ANALYSIS:
+• Initial Motion: {speeds[0]:.1f} km/h
+• Peak Speed: {max(speeds):.1f} km/h at Hour {hours[speeds.index(max(speeds))]}
+• Final Motion: {speeds[-1]:.1f} km/h
 
 CONFIDENCE ASSESSMENT:
 • Genesis Likelihood: {prediction_results['confidence_scores'].get('genesis', 0.85)*100:.0f}%
-• Early Development: {prediction_results['confidence_scores'].get('early_development', 0.80)*100:.0f}%
 • 24-hour Track: {prediction_results['confidence_scores'].get('position_24h', 0.85)*100:.0f}%
 • 48-hour Track: {prediction_results['confidence_scores'].get('position_48h', 0.75)*100:.0f}%
 • 72-hour Track: {prediction_results['confidence_scores'].get('position_72h', 0.65)*100:.0f}%
+• Long-term: {prediction_results['confidence_scores'].get('long_term', 0.50)*100:.0f}%
+
+FEATURES:
+{"✅ Animation Enabled - Use controls to watch development" if enable_animation else "📊 Static Analysis - All time steps displayed"}
+✅ Realistic Forward Speeds (15-25 km/h typical)
+✅ Environmental Coupling (ENSO, SST, Shear)
+✅ Multi-stage Development Cycle
+✅ Uncertainty Quantification
 
 MODEL: {prediction_results['model_info']}
-ANIMATION: {"Enabled - Use controls below map" if enable_animation else "Static view - All time steps shown"}
         """
         
         return fig, forecast_text.strip()
         
     except Exception as e:
-        error_msg = f"Error creating animated route visualization: {str(e)}"
+        error_msg = f"Error creating comprehensive visualization: {str(e)}"
         logging.error(error_msg)
         import traceback
         traceback.print_exc()
@@ -2882,12 +3094,13 @@ def create_interface():
                             pred_month = gr.Slider(1, 12, label="Month", value=9, info="Peak season: Jul-Oct")
                             pred_oni = gr.Number(label="ONI Value", value=0.0, info="ENSO index (-3 to 3)")
                         with gr.Row():
-                            forecast_hours = gr.Slider(
-                                6, 240, 
+                            forecast_hours = gr.Number(
                                 label="Forecast Length (hours)", 
                                 value=72, 
+                                minimum=20,
+                                maximum=1000,
                                 step=6,
-                                info="Extended forecasting up to 10 days"
+                                info="Extended forecasting: 20-1000 hours (42 days max)"
                             )
                             advanced_physics = gr.Checkbox(
                                 label="Advanced Physics", 
@@ -2965,17 +3178,26 @@ def create_interface():
                 prediction_info_text = """
                 ### 🌊 Realistic Storm Genesis Features:
                 - **Climatological Genesis Regions**: 10 realistic development zones based on historical data
-                - **Tropical Depression Starting Point**: Storms begin at realistic 25-35 kt intensities
-                - **Animated Development**: Watch storm evolution from genesis through maturity to decay
-                - **Extended Forecasting**: Up to 240 hours (10 days) with realistic development cycles
+                - **Tropical Depression Starting Point**: Storms begin at realistic 25-38 kt intensities
+                - **Realistic Typhoon Speeds**: Forward motion 15-25 km/h (matching observations)
+                - **Extended Time Range**: 20-1000 hours (up to 42 days) with user input control
+                - **Comprehensive Animation**: Watch development with wind/speed/pressure plots
                 - **Environmental Coupling**: Advanced physics with ENSO, SST, shear, β-drift, ridge patterns
-                - **Realistic Intensity Evolution**: Natural intensification/weakening cycles, not just decay
                 
                 ### 📊 Enhanced Development Stages:
                 - **Genesis (0-24h)**: Initial cyclogenesis at Tropical Depression level
-                - **Development (24-72h)**: Natural intensification in favorable environment
+                - **Development (24-72h)**: Rapid intensification in favorable environment (3-6 kt/h)
                 - **Mature (72-120h)**: Peak intensity phase with environmental modulation
-                - **Decay (120h+)**: Realistic weakening due to latitude/land/cooler waters
+                - **Extended (120-240h)**: Continued tracking with realistic weakening
+                - **Long-term (240h+)**: Extended forecasting for research and planning
+                
+                ### 🏃‍♂️ Realistic Motion Physics:
+                - **Low Latitude (< 20°N)**: 12-15 km/h typical speeds
+                - **Mid Latitude (20-30°N)**: 18-22 km/h moderate speeds  
+                - **High Latitude (> 30°N)**: 25-30 km/h fast extratropical transition
+                - **Intensity Effects**: Stronger storms can move faster in steering flow
+                - **Beta Drift**: Coriolis-induced poleward and westward motion
+                - **Ridge Interaction**: Realistic recurvature patterns
                 
                 ### 🌍 Genesis Region Selection:
                 - **Western Pacific MDR**: Peak activity zone near Guam (12.5°N, 145°E)
@@ -2985,20 +3207,21 @@ def create_interface():
                 - **Monsoon Trough**: Monsoon-driven genesis (10°N, 130°E)
                 - **Other Basins**: Bay of Bengal, Eastern Pacific, Atlantic options
                 
-                ### 🔬 Enhanced Physics Model:
-                - **Beta Drift**: Coriolis-induced storm motion (latitude-dependent)
-                - **Ridge Interaction**: Seasonal subtropical ridge position effects
-                - **ENSO Modulation**: Non-linear intensity and steering effects
-                - **SST Coupling**: Ocean temperature impact on intensification
-                - **Shear Analysis**: Environmental wind shear impact assessment
-                - **Recurvature Physics**: Advanced extratropical transition modeling
-                
-                ### 🎬 Animation Features:
+                ### 🎬 Enhanced Animation Features:
                 - **Real-time Development**: Watch TD evolve to typhoon intensity
-                - **Interactive Controls**: Play/pause buttons and time slider
+                - **Multi-plot Display**: Track + Wind Speed + Forward Speed plots
+                - **Interactive Controls**: Play/pause/fast buttons and time slider
                 - **Stage Tracking**: Visual indicators for development phases
-                - **Confidence Evolution**: See how uncertainty grows with time
-                - **Genesis Highlighting**: Special markers for initial development location
+                - **Speed Analysis**: Forward motion tracking throughout lifecycle
+                - **Performance Optimized**: Smooth animation even for 1000+ hour forecasts
+                
+                ### 🔬 Advanced Physics Model:
+                - **Realistic Intensification**: 3-6 kt/h development rates in favorable conditions
+                - **Environmental Coupling**: SST, wind shear, Coriolis effects
+                - **Steering Flow**: Subtropical ridge position and ENSO modulation
+                - **Motion Variability**: Growing uncertainty with forecast time
+                - **Pressure-Wind Relationship**: Realistic intensity-pressure coupling
+                - **Long-term Climatology**: Extended forecasting using seasonal patterns
                 """
                 gr.Markdown(prediction_info_text)