This repository documents a focused learning journey in meteorology with emphasis on nowcasting using the WRF‑ARW model. It contains Jupyter notebooks, scripts and example data for acquiring and processing atmospheric model outputs (GFS 0.25° from NOAA NOMADS and ERA5 from the Copernicus Climate Data Store), basic preprocessing, simple prediction experiments, and WRF output visualization.
- Notebooks and scripts to download and process model and reanalysis data.
- Example workflows for:
- Downloading and handling GFS 0.25° data from NOAA NOMADS.
- Downloading and processing ERA5 total precipitation (CDS).
- Preparing data for simple rainfall models (Nairobi example).
- Visualizing WRF output and building simple WRF-based nowcasts.
- wrf_data.ipynb — data download and preparation for WRF/GFS/ERA5
- [wrf model simukations/wrfpy.ipynb](wrf model simukations/wrfpy.ipynb) — WRF processing / visualization examples
- [Climate Data Store/download_era5_rain.ipynb](Climate Data Store/download_era5_rain.ipynb) — ERA5 TP download and aggregation
- [Rainfall Prediction/simple_rainfall_predict_model.ipynb](Rainfall Prediction/simple_rainfall_predict_model.ipynb) — simple rainfall prediction workflow
- WRF_OUTPUT_VISUALIZATION/09_01_2025/wrf.ipynb — visualization examples
- requirements.txt — environment dependencies
- Create and activate a Python venv.
- Install dependencies: pip install -r requirements.txt
- Open the desired notebook in Jupyter / JupyterLab / VS Code and follow cells in order.
- GFS 0.25° data: downloaded from NOAA NOMADS (processed to the formats used by the notebooks).
- ERA5 (total precipitation): retrieved using Copernicus Climate Data Store (cdsapi) and processed with xarray/pandas.
For collaboration, questions or suggestions, please contact:
- Email: [email protected]
- LinkedIn: https://www.linkedin.com/in/erick-wambugu-425a15161/
Contributions are welcome — open an issue or reach out directly.
MIT License — please see individual notebooks and files for attribution notes where applicable.