docs: Detail multi-model consensus scoring, Open-Meteo API architecture, airport-aligned NWP queries, and ensemble divergence detection.
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AmandaloveYang
@@ -98,29 +98,63 @@ py -3.11 run.py
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| Source | Role | Coverage | Strength |
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| :---------------------- | :---------------------- | :-------------- | :-------------------------------------------------------------------------- |
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| **Multi-Model (5 NWP)** | **Consensus Scoring** | Global | ECMWF, GFS, ICON, GEM, JMA — 5 fully independent NWP models via Open-Meteo |
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| **Open-Meteo** | Base Forecast | Global | 72h hourly curves, sunrise/sunset, **sunshine duration**, **shortwave radiation** |
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| **Open-Meteo Ensemble** | **Uncertainty Range** | Global | 51-member ensemble: median, P10, P90 spread for confidence assessment |
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| **Meteoblue (MB)** | **Precision Consensus** | London Only | Multi-model aggregation; excellent for microclimates |
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| **Meteoblue (MB)** | Precision Consensus | London Only | Multi-model aggregation; excellent for microclimates |
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| **METAR** | **Settlement Standard** | Global Airports | Polymarket settlement source; real-time airport observations |
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| **NWS** | Official (US) | US Only | US National Weather Service high-fidelity forecasts |
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| **MGM** | Official (Turkey) | Ankara Only | Turkish State Met Service: pressure, cloud cover, feels-like, 24h rainfall |
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| **MGM** | Observations (Turkey) | Ankara Only | Turkish State Met Service: pressure, cloud cover, feels-like, 24h rainfall |
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> ⚠️ **All NWP model queries use airport coordinates** (matching METAR station), not city center. This eliminates systematic bias between forecast and settlement locations.
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**Open-Meteo API Architecture**: Three API calls go through the same platform, each serving a different purpose:
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```
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Open-Meteo (API Platform)
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│
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┌─────────────┼─────────────┐
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│ │ │
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┌──────┴──────┐ │ ┌──────┴──────┐
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│ /forecast │ │ │ /forecast │
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│ (default) │ │ │ ?models=... │
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│ = best_match│ │ │ = multi-model│
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└──────┬──────┘ │ └──────┬──────┘
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│ │ │
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▼ │ ▼
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Auto-selects best │ Returns each model
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model (≈ ECMWF) │ ECMWF / GFS / ICON
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→ Hourly curves │ GEM / JMA
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→ Sunrise/sunset │ → Consensus scoring
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→ Sunshine/radiation │
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┌──────┴──────┐
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│ /ensemble │
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│ 51 members │
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└──────┬──────┘
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│
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▼
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Median / P10 / P90
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→ Uncertainty range
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```
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> 💡 The OM default forecast is essentially **one of the 5 models** (auto-selected), so it is **excluded from consensus scoring** to avoid double-counting.
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### 2. ⚡ Ultra-Fresh Data (Zero-Cache)
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- **Dynamic Timestamps**: Every API request includes a unique token to force servers to bypass CDN caches.
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- **MGM Real-time Sync**: Specialized header camouflaging and timezone correction for Turkish API.
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### 3. 🎯 Model Consensus Scoring (NEW)
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### 3. 🎯 Multi-Model Consensus Scoring
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The bot automatically rates how well different forecast sources agree, using a three-tier system:
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The bot queries **5 independent NWP models** (ECMWF, GFS, ICON, GEM, JMA) to rate forecast agreement:
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| Level | Condition (°C / °F) | Meaning |
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|:---|:---|:---|
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| 🎯 **High** | Spread ≤ 0.8°C / 1.5°F | All models converge — high confidence, low risk |
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| 🎯 **High** | Spread ≤ 0.8°C / 1.5°F | All 5 models converge — high confidence, low risk |
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| ⚖️ **Medium** | Spread ≤ 1.5°C / 3.0°F | Minor disagreement — moderate confidence |
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| ⚠️ **Low** | Spread > 1.5°C / 3.0°F | Major divergence — high uncertainty, wait for more data |
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Sources compared: Open-Meteo (OM), Meteoblue (MB), NWS, MGM — only **independent** forecast sources. Ensemble median is deliberately excluded to avoid double-counting with Open-Meteo.
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Primary models: **ECMWF IFS** (Europe), **GFS** (US NOAA), **ICON** (Germany DWD), **GEM** (Canada), **JMA** (Japan). Plus Meteoblue (London) and NWS (US) when available. Ensemble median is excluded to avoid double-counting.
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### 4. 📊 Ensemble Forecast Spread (NEW)
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@@ -130,6 +164,8 @@ Fetches 51-member ensemble forecasts from Open-Meteo to quantify prediction unce
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A tight range = high confidence in the forecast. A wide range = the atmosphere is chaotic, higher risk.
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**Deterministic vs Ensemble Divergence Detection**: When the OM deterministic forecast exceeds the ensemble P90 or falls below P10, the bot flags it. If actual observations later verify the forecast, the warning upgrades to a ✅ **Forecast Verified** message.
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### 5. ⏰ Entry Timing Signal (NEW)
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A composite score combining three factors to advise on betting timing:
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@@ -190,11 +226,12 @@ graph TD
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Bot --> Collector[WeatherDataCollector]
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subgraph "Data Engine"
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Collector --> OM[Open-Meteo API]
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Collector --> MM[Multi-Model API<br/>ECMWF/GFS/ICON/GEM/JMA]
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Collector --> OM[Open-Meteo Forecast]
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Collector --> ENS[Open-Meteo Ensemble]
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Collector --> MB[Meteoblue API]
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Collector --> NOAA[METAR / NOAA]
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Collector --> MGM[Turkish MGM API]
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Collector --> MGM[MGM Observations]
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Collector --> NWS[US NWS API]
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end
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@@ -205,7 +242,9 @@ graph TD
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- **Logic Decoupling**: `weather_sources.py` handles data fetching & parsing; `bot_listener.py` handles analysis & rendering.
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- **City Config**: `city_risk_profiles.py` contains all METAR station mappings and risk assessments.
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- **Ensemble Integration**: 51-member ensemble contributes to consensus scoring and provides P10/P90 uncertainty bands.
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- **Multi-Model Consensus**: 5 independent NWP models (ECMWF, GFS, ICON, GEM, JMA) for robust consensus scoring.
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- **Ensemble Integration**: 51-member ensemble provides P10/P90 uncertainty bands and divergence detection.
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- **Airport-Aligned Coordinates**: All NWP queries target METAR station coordinates, not city centers.
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---
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@@ -222,4 +261,4 @@ graph TD
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---
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_Last updated: 2026-02-21_
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_Last updated: 2026-02-22_
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