# Related Works

Here are some related packages that may be of interest.

- **`scoringrules`**
	- Open source Python package that provides verification metrics with backends for [`NumPy`](https://github.com/numpy/numpy), [`JAX`](https://github.com/jax-ml/jax), [`PyTorch`](https://github.com/pytorch/pytorch) and [`TensorFlow`](https://github.com/tensorflow/tensorflow).
	- [Software Repository](https://github.com/frazane/scoringrules); [Documentation](https://scoringrules.readthedocs.io)
	- Reference: [Zanetta and Allen (2024)](https://github.com/frazane/scoringrules?tab=readme-ov-file#citation) 	

- **`xskillscore`**
	- Open source Python package that provides verification metrics of deterministic (and probabilistic from [`properscoring`](https://github.com/properscoring/properscoring)) forecasts with xarray.
	- [Software Repository](https://github.com/xarray-contrib/xskillscore); [Documentation](https://xskillscore.readthedocs.io/en/latest/)
	- Reference: [Bell et al. (2021)](https://doi.org/10.5281/zenodo.5173153) 	

- **`climpred`**
	- Open source Python package for verification of weather and climate forecasts.
	- [Software Repository](https://github.com/pangeo-data/climpred); [Documentation](https://climpred.readthedocs.io/en/stable/) 
	- Reference: [Brady and Spring (2021)](https://doi.org/10.21105/joss.02781)

- **`Verif`**  
	- Open source command-line tool for forecast verification. Generates verification plots. Can evaluate deterministic and probabilistic predictions.
	- [Software Repository](https://github.com/WFRT/verif); [Wiki](https://github.com/WFRT/verif/wiki) 
	- Reference: [Nipen et al. (2023)](https://doi.org/10.1175/bams-d-22-0253.1)

- **`METplus`**
	- `METplus` includes a database and visualisation system, with Python and shell script wrappers to utilise the [`MET`](https://github.com/dtcenter/MET) package. Verification scores in [`MET`](https://github.com/dtcenter/MET) are implemented in C++. 
	- 	[Software Repository](https://github.com/dtcenter/METplus); [Documentation](https://metplus.readthedocs.io/en/latest/); [Website](https://dtcenter.org/community-code/metplus)
	- Reference: [Brown et al. (2021)](https://doi.org/10.1175/bams-d-19-0093.1) 

- **`Pysteps`** 
	- Open source Python library for short-term ensemble prediction systems, focusing on probabilistic nowcasting of radar precipitation fields. Includes a significant verification submodule.
	- [Software Repository](https://github.com/pySTEPS/pysteps); [Documentation](https://pysteps.readthedocs.io/en/stable/); [Website](https://pysteps.github.io/)
	- References: [Pulkkinen et al. (2019)](https://doi.org/10.5194/gmd-12-4185-2019); [Imhoff et al. (2023)](https://doi.org/10.1002/qj.4461)

- **`PyForecastTools`**
	- Open source Python module for model validation, forecast verification and plot generation. Uses dmarray data structures from [`SpacePy`](https://github.com/spacepy/spacepy).
	- [Software Repository](https://github.com/drsteve/PyForecastTools); [Documentation](https://drsteve.github.io/PyForecastTools/)
	- Reference: [Morley and Burrell (2020)](https://doi.org/10.5281/zenodo.3764117)