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wass2s documentation
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A python-based tool for seasonal climate forecast in West Africa and the Sahel.

The wass2s tool is designed to facilitate implementation of the new generation of seasonal forecasts in West Africa and the Sahel using various statistical and machine learning methods. New generation of seasonal forecasts aligns with the World Meteorological Organization's (WMO) guidelines for objective, operational, and scientifically rigorous seasonal forecasting methods. wass2s helps forecaster to download GCM, reanalysis, and satellite/observation data, build statistical or machine learning models, verify the models using cross-validation, and forecast. 
A user-friendly `jupyter-lab notebook <https://github.com/hmandela/WASS2S_notebooks>`_  streamlines the forecasting process .

**Features**

* Automated Forecasting
* Reproducibility
* Modularity
* Exploration of Machine Learning Models.


.. toctree::
   :maxdepth: 1
   :caption: Contents:

   Installation
   Usage
   api