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Copernicus Seasonal Forecast Tools

GitHub repo License PyPI version Supported Python versions Documentation Status

Overview

Welcome to the Copernicus Seasonal Forecast Tools!

This Python package, developed to manage seasonal forecast data from the Copernicus Climate Data Store (CDS) as part of the U-CLIMADAPT project. We designed this package to make working with climate forecasts more accessible for researchers and practitioners.

It offers comprehensive tools for downloading, processing, computing climate indices, and generating hazard objects based on seasonal forecast datasets, particularly Seasonal forecast daily and subdaily data on single levels. The package is tailored to integrate seamlessly with the CLIMADA (CLIMate ADAptation) platform, supporting climate risk assessment and the development of effective adaptation strategies.

Key features include:

  • Download Copernicus CDS seasonal forecasts (subdaily)

  • Convert to daily resolution automatically

  • Calculate heat-related climate indices (e.g., Heatwaves, Tropical Nights)

  • Integrate with CLIMADA hazard workflows

  • Extending functionality through a modular design (e.g., for new indices or forecast products)

Getting Started

For a quick start, install the package and its requirements

conda create -c conda-forge -n copernicus_with python=3.11 pip climada
conda activate copernicus_with
pip install copernicus-seasonal-forecast-tools

For detailed installation instructions, see Installation.

Note

Seasonal forecast data can be accessed through the Copernicus Climate Data Store (CDS), which offers a variety of datasets including those compatible with this tool. Access requires a free CDS account and proper API configuration. You need a CDS account, API credentials, and to accept the dataset’s terms and conditions. We’ve prepared a comprehensive CDS API setup guide to walk you through each step of the process. Once configured, you’ll be ready to explore and analyze seasonal forecast data.

License

GPL-3.0 license