Metadata-Version: 2.4
Name: copernicus-seasonal-forecast-tools
Version: 0.1.2
Summary: CLIMADA-compatible module for generating and analyzing seasonal forecast hazards from Copernicus data
Author: Dahyann Araya
License-Expression: GPL-3.0-or-later
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Hydrology
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: <3.12,>=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: xarray
Requires-Dist: cfgrib
Requires-Dist: cdsapi
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: netCDF4
Requires-Dist: shapely
Requires-Dist: geopandas
Requires-Dist: cartopy
Dynamic: license-file

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# **Copernicus Seasonal Forecast Tools**
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This repository hosts the **copernicus-seasonal-forecast-tools**, a Python package developed to manage seasonal forecast data from the [Copernicus Climate Data Store (CDS)](https://cds.climate.copernicus.eu/) as part of the [U-CLIMADAPT project](https://www.copernicus-user-uptake.eu/user-uptake/details/responding-to-the-impact-of-climate-change-u-climadapt-488).

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](https://cds.climate.copernicus.eu/datasets/seasonal-original-single-levels?tab=overview).
The packge is tailored to integrate seamlessly with the [CLIMADA](https://climada.ethz.ch/) (CLIMate ADAptation) platform, supporting climate risk assessment and the development of effective adaptation strategies.

Users can:
- Automatically download of high-resolution seasonal forecast data via the CDS API
- Preprocess sub-daily fields into daily aggregates
- Compute heat-related indices (e.g., **heatwave days**, **tropical nights**, **TX30**)
- Generate **CLIMADA hazard objects**
- Benefit from the modular design for extending to new indices or forecast products


## **Documentation**
For full documentation of all features and functions, please refer to the [Copernicus Seasonal Forecast Tools documentation on ReadTheDocs](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/?badge=latest).


## **Getting Started**

To use this package, you must first configure access to the [Copernicus Climate Data Store (CDS)](https://cds.climate.copernicus.eu), which provides the seasonal forecast datasets.

We've prepared a comprehensive [CDS API setup guide](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/cds_api.html) to walk you through each step of the process. Once configured, you'll be ready to explore and analyze seasonal forecast data.


## **Installation**

The package requires **Python 3.10**, but versions 3.11 and 3.12 are also supported. Make sure your environment is using a compatible Python version before installation.

You can install **`copernicus-seasonal-forecast-tools`** in three ways, depending on your setup and preferences.

> **Note:** If you want to generate CLIMADA hazard objects, you must install the **optional CLIMADA dependency**.  
> For full installation instructions, see the [online documentation](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/index.html).


### 1. Install via pip (recommended for most users)

```bash
pip install copernicus-seasonal-forecast-tools
git clone https://github.com/DahyannAraya/copernicus-seasonal-forecast-tools.git (optional)
pip install -r docs/requirements.txt (optional)
```
### 2. Install via environment.yml (Conda or Mamba):
```bash
git clone https://github.com/DahyannAraya/copernicus-seasonal-forecast-tools.git
conda env create -f environment.yml
conda activate venv_forecast
```
### 3. Install directly from GitHub 
```bash
git clone https://github.com/DahyannAraya/copernicus-seasonal-forecast-tools.git
cd copernicus-seasonal-forecast-tools
pip install .
pip install -r docs/requirements.txt (optional)
```


### **CLIMADA Installation**

CLIMADA is required to generate hazard layers.

- If you installed via `environment.yml`, CLIMADA is already included.
- If you installed from PyPI and then ran `pip install -r docs/requirements.txt`, CLIMADA is also installed.

> **Note**  
> If you want to have all the functionalities of **CLIMADA**, you must install the full version.  
> 👉 For detailed instructions, follow the official CLIMADA installation guide:  
> [CLIMADA Installation Guide](https://climada-python.readthedocs.io/en/stable/guide/install.html)


## **Example of use**

This section provides practical example to help users understand how to work with the copernicus-seasonal-forecast-tools package. The notebooks demonstrate key steps including downloading data, computing climate indices, and generating CLIMADA hazard objects.

- **DEMO_copernicus_forecast_seasonal.ipynb**: This is the first notebook to run. It demonstrates how to install and use the `seasonal_forecast_tools` to download, process, and convert seasonal forecast data into a CLIMADA hazard object.


### Notebooks

| Notebook | Open in Colab | GitHub (Documentation) |
|----------|----------------|-----------------|
| DEMO Copernicus Seasonal Forecast | [<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="20">](https://colab.research.google.com/github/DahyannAraya/copernicus_climada_seasonal_forecast_workshop/blob/main/Modul_climada_copernicus_seasonal_forecast_workshop.ipynb) | [View in Docs](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/climada_hazard_copernicus_forecast.html) |
| Download and Process Data | [<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="20">](https://colab.research.google.com/github/DahyannAraya/copernicus_climada_seasonal_forecast_workshop/blob/main/Modul_climada_copernicus_seasonal_forecast_workshop.ipynb#scrollTo=Download_and_Process_Data) | [View in Docs](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/climada_hazard_copernicus_forecast.html#download-and-process-data) |
| Calculate Climate Indices | [<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="20">](https://colab.research.google.com/github/DahyannAraya/copernicus_climada_seasonal_forecast_workshop/blob/main/Modul_climada_copernicus_seasonal_forecast_workshop.ipynb#scrollTo=Calculate_Climate_Indices)  | [View in Docs](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/climada_hazard_copernicus_forecast.html#calculate-climate-indices) |
| Calculate a Hazard Object | [<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="20">](https://colab.research.google.com/github/DahyannAraya/copernicus_climada_seasonal_forecast_workshop/blob/main/Modul_climada_copernicus_seasonal_forecast_workshop.ipynb#scrollTo=Calculate_a_Hazard_Object)  | [View in Docs](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/climada_hazard_copernicus_forecast.html#calculate-a-hazard-object) |
| Example for Reading and Plotting Hazard | [<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="20">](https://colab.research.google.com/github/DahyannAraya/copernicus_climada_seasonal_forecast_workshop/blob/main/Modul_climada_copernicus_seasonal_forecast_workshop.ipynb#scrollTo=Example_for_reading_and_plotting_hazard) | [View in Docs](https://copernicus-seasonal-forecast-tools.readthedocs.io/en/latest/climada_hazard_copernicus_forecast.html#example-for-reading-and-plotting-hazard) |

You can find further material in [<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="20">](https://colab.research.google.com/github/DahyannAraya/copernicus_climada_seasonal_forecast_workshop/blob/main/DEMO_Modul_climada_copernicus_seasonal_forecast_workshop.ipynb), where we provide an extended demonstration.



## **License**

[GPL-3.0 license](https://github.com/DahyannAraya/copernicus-seasonal-forecast-tools/blob/main/LICENSE)


## **Resources**
- [U-CLIMADAPT Project](https://www.copernicus-user-uptake.eu/user-uptake/details/responding-to-the-impact-of-climate-change-u-climadapt-488)
- [Copernicus Seasonal Forecas Tools package on CLIMADA](https://climada-python.readthedocs.io/en/latest/user-guide/climada_hazard_copernicus_seasonal_forecast.html)
- [Copernicus Seasonal Forecast Tools package extended demostration](https://colab.research.google.com/github/DahyannAraya/climada_copernicus_seasonal_forecast_workshop/blob/main/DEMO_Modul_climada_copernicus_seasonal_forecast_workshop.ipynb)
- [Seasonal forecast daily and subdaily data on single levels](https://cds.climate.copernicus.eu/datasets/seasonal-original-single-levels?tab=overview)
- [Copernicus Climate Data Store](https://cds.climate.copernicus.eu)
- [CLIMADA Documentation](https://climada.ethz.ch/)

