PolyWeather is a multi-source weather analysis and quantification tool. It aggregates high-precision forecasts, real-time airport METAR observations, a math-based probability engine, and AI-driven decision support to provide deep insights for weather-related risk assessment and data-driven decision making.
- **Global Overview**: Real-time Leaflet-based dark-themed map pinpointed to official Polymarket settlement airport coordinates.
- **Progressive Background Loading**: Intelligently fetches multi-source data across all cities without hitting API rate limits.
- **Rich Visualization**: Chart.js-powered temperature trends with METAR scatter overlay, multi-model comparison bars, Gaussian probability distribution, and dynamic risk badges.
- **Zoom-based Intelligence**: Map automatically filters minor cities (e.g., Atlanta/Ankara) and local station labels at lower zoom levels to maintain clarity, showing only major global hubs when zoomed out.
- **Technical Guide Interface**: Features an interactive on-map technical guide explaining DEB prediction curves, probability bands, and risk factors.
- **Cinematic Interaction & Sync**: City selection triggers a smooth fly-to zoom animation. The **Multi-Model Forecast** panel automatically synchronizes with the selected day in the 5-day forecast table, showing historical model performance and future projections.
- **Forced Sync & Cache Control**: For specific regions like Ankara, the dashboard supports a 60-second real-time cache TTL with a manual "Force Refresh" button to bypass global caches and fetch the absolute latest MGM/METAR data.
- **Dual-Engine Architecture**: Runs concurrently with the Telegram bot via a FastAPI backend, sharing the same data collection, analysis logic (`analyze_weather_trend`), and AI prompt pipeline.
- **Error-Based Weighting**: Dynamically adjusts model weights based on their Mean Absolute Error (MAE) over the past 7 days. Lower error = higher weight.
- **Blended Forecast**: Provides a bias-corrected "DEB Blended High Temperature" recommendation.
- **Multi-Source Training**: Integrates official regional sources (like Turkey's MGM) into the training pipeline alongside international models (ECMWF, GFS, etc.).
- **Accuracy Tracking**: Use the `/deb` command to view DEB's historical settlement hit rate and MAE, compared against individual models.
- **Reality-Anchored μ**: When actual max temperature is significantly below forecasts during/after the peak window (forecast bust), μ anchors on the observed max instead of failed predictions. Otherwise, uses a weighted average of DEB/multi-model median (70%) and ensemble median (30%).
- **P0 Forecast Bust Detection** (highest priority): Graded severity (light/medium/heavy) when actual temps diverge from forecasts. Requires slope + wind/cloud verification before declaring settlement locked. "Bust ≠ locked" — still checks for second-wave warming.
- **P1 Real-Time Rhythm**: 2 consecutive METAR highs → still warming; 2 non-highs with slope ≤ 0 → dead market. Low-radiation warming → multi-factor (advection/mixing layer/heat island), no single-factor attribution.
- **P2 Inhibitors** (city-aware): Precipitation → strong suppression. High humidity + thick clouds sustained 2+ reports → possible suppression, but thresholds vary by city type (maritime vs. continental). Single factor insufficient.
- **P3 Probability Cross-Check**: References settlement probability for consistency check with P1. Contradictions explained with deviation rationale.
- **P4 Forecast Background**: DEB/forecasts for ceiling estimation; silenced when actuals significantly deviate.
- **Single Source of Truth**: Both web and Telegram bot share the same `analyze_weather_trend` function and `get_ai_analysis` prompt — identical context, identical decisions.
- **High Availability**: Auto-retry + fallback model degradation (70B → 8B). Proxy support for restricted networks.
- **Live Passthrough**: Bypasses CDN caching via dynamic headers and randomized timestamps to obtain first-hand METAR/MGM reports.
- **Settlement Warning**: Automatically calculates the rounding boundary for integer-based settlement (X.5 line).
- **MGM Primary (Ankara)**: For Turkish cities like Ankara, PolyWeather uses official MGM data as a primary source for both real-time observations and 5-day hourly forecasts, ensuring maximum local accuracy.
- Includes `fetch_history.py` to retrieve up to 3 years of hourly historical weather data (temperature, humidity, radiation, pressure, 10+ dimensions), providing data foundation for future ML models (XGBoost/MOS).
_(Note: The `update.sh` script automatically fetches the latest code, kills old processes, clears ports, and launches both `bot_listener.py` and `web/app.py` via `nohup`.)_
| `/city [city_name]` | Get weather analysis, settlement probabilities, METAR tracking, and AI insights. (Includes "Bölge/Center" detail for Ankara). |
1. **Real-time Rhythm First**: AI analysis follows P0→P4 priority. If live METAR trends (P1) conflict with math probabilities (P3), always prioritize the live trend.
2. **Watch Settlement Probabilities**: Based on Gaussian models, direction is most certain when a temperature has > 70% probability while P1 rhythm is flat.
3. **Reference DEB Bias**: Use `/deb` to check for systematic bias. If a city is consistently "underestimated," habitually bid one WU notch higher.
4. **Identify Dead Market Signals**: When the system declares a "Dead Market," probability collapses to 100% at the settled value. Warming power is exhausted.
5. **Mind the Boundaries**: When the observed high is near X.5 (e.g., 7.50°C), be wary of rounding up due to tiny fluctuations.
6. **Forecast Bust Awareness**: When the AI reports a forecast bust (especially medium/heavy grade), all model predictions have lost reference value. Focus exclusively on METAR actuals.
