nyandajr/tanzania-climate-watch

# Tanzania Climate Prediction Pipeline Real-time weather monitoring and ML forecasting for 5 Tanzanian cities, updated automatically every 15 minutes via GitHub Actions. **Live Dashboard →** --- ## Cities Covered | City | Coordinates | |------|-------------| | Dar es Salaam | -6.79°, 39.21° | | Dodoma | -6.17°, 35.74° | | Arusha | -3.39°, 36.68° | | Mwanza | -2.52°, 32.92° | | Zanzibar | -6.17°, 39.20° | ## Pipeline Architecture ``` Open-Meteo API (free, no key) │ fetch.py → data/raw/latest.json │ preprocess.py → data/processed/climate_metrics.csv │ predict.py → data/predictions/latest.json │ ml/inference_state.json anomaly.py → data/anomalies/anomaly_log.csv │ dashboard.py → docs/data.json (GitHub Pages reads this) │ GitHub Actions → git commit + push (1 commit/run) ``` ## ML Model - **Algorithm**: Ridge Regression (scikit-learn) - **Features**: cyclic hour/day encoding, temperature, humidity, pressure, windspeed - **Target**: next-hour temperature - **Metric**: MAE tracked over time per city - **Cold start**: API forecast used until 20 data points collected ## Features - Live current conditions for all 5 cities - 7-day temperature max/min forecast charts - 30-day historical temperature trends - Model accuracy (MAE) over time chart - Anomaly detection (z-score + hard thresholds) - Weekly markdown reports (auto-generated every Monday) ## Data Source Open-Meteo — free, open-source weather API, no API key required. ## Local Development ```bash pip install -r requirements.txt python scripts/fetch.py python scripts/preprocess.py python scripts/predict.py python scripts/anomaly.py python scripts/dashboard.py # open docs/index.html in browser (serve via local HTTP server) python -m http.server 8080 --directory docs ``` ## GitHub Pages Setup 1. Go to repo **Settings → Pages** 2. Source: **Deploy from a branch** 3. Branch: `main` / folder: `/docs` 4. Save — your dashboard will be live at `nyandajr.gith …