copernicus-seasonal-forecast-tools 0.1.0

CLIMADA-compatible module for generating and analyzing seasonal forecast hazards from Copernicus data

Copernicus Seasonal Forecast Module

This repository hosts the copernicus_climada_seasonal_forecast package, a Python module developed as part of the U-CLIMADAPT project.

The module connects seasonal forecast data from the Copernicus Climate Data Store (CDS) with flexible data processing and climate impact modeling tools. It includes robust functionality to download hourly seasonal forecast data and automatically convert it to daily resolution, enabling a wide range of climate analyses beyond just heat-related indices.

Users can leverage the package to:

• Convert raw Copernicus seasonal forecasts into usable daily datasets.
• Compute custom or predefined climate indices (e.g., Heatwaves, Tropical Nights).
• Generate CLIMADA-compatible hazard objects from processed data to support impact-based forecasting and risk assessment workflows.

While the package is not part of the core CLIMADA platform, it is designed for tight integration with it, supporting end-to-end workflows from raw data acquisition to risk estimation and adaptation planning.

Documentation

Installation

You can install copernicus-seasonal-forecast-tools in three ways:

1. Install via pip (recommended for most users)

pip install copernicus-seasonal-forecast-tools

2. Install via conda or mamba

conda install -c conda-forge copernicus-seasonal-forecast-tools

3. Install directly from GitHub

git clone https://github.com/your-username/copernicus-seasonal-forecast-tools.git
cd climada_copernicus_seasonal_forecast
pip install .

CLIMADA Installation

If you want to create a hazard object, you need to install CLIMADA as a dependency.

Follow the steps below:

# 1. Clone the CLIMADA repository

git clone https://github.com/CLIMADA-project/climada_python.git

# 2. Install CLIMADA in development mode
cd climada_python
pip install -e .
cd ..

# 3. Update your environment with the rest of the dependencies if needed
pip install -e .

# 4. Verify the installation
python -c "from climada.hazard import Hazard; print('Hazard module successfully imported!')"

Example of use

This repository provides Jupyter Notebooks to work with CLIMADA and the Copernicus seasonal forecast module.

There are two notebooks available:

• Modul_climada_copernicus_seasonal_forecast_workshop.ipynb: This is the first notebook to run. It demonstrates how to install and use the copernicus_interface module to download, process, and convert seasonal forecast data into a CLIMADA hazard object.
• DEMO_Modul_climada_copernicus_seasonal_forecast_workshop.ipynb: This is the second notebook. It provides a full example application of the seasonal forecast hazard data in an end-to-end climate impact assessment pipeline.

Notebooks

Notebook	Open in Colab	GitHub Link
Modul_climada_copernicus_seasonal_forecast_workshop.ipynb		View on GitHub
DEMO_Modul_climada_copernicus_seasonal_forecast_workshop.ipynb		View on GitHub

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Run in Colab

1. Click on Open in Colab for the notebook of interest.
2. Make sure you follow all the setup cells in the notebook to install CLIMADA and its dependencies.

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Run Locally

If you plan to run this notebook locally, you must first install CLIMADA and all required dependencies on your system.
👉 For detailed instructions, follow the official CLIMADA installation guide:
CLIMADA Installation Guide

After installing CLIMADA, you should also install the seasonal forecast module by following the instructions in the document below:
👉 Copernicus Forecast Module Installation Instructions (PDF)

Alternatively, you can install the module manually by cloning the repository:

git clone https://github.com/DahyannAraya/climada_copernicus_seasonal_forecast_workshop.git
cd climada_copernicus_seasonal_forecast_workshop

References

• Copernicus Seasonal Forecast Module
• Seasonal forecast daily and subdaily data on single levels
• Copernicus Climate Data Store
• CLIMADA Documentation
• U-CLIMADAPT Project