| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - OneScience |
| - Earth Science |
| - WeatherBench2 |
| - Weather Benchmark |
| - Probabilistic Evaluation |
| frameworks: PyTorch |
| --- |
| |
| <p align="center"><strong><span style="font-size: 30px;">WeatherBench2</span></strong></p> |
|
|
| # Model Introduction |
|
|
| WeatherBench2 is an evaluation benchmark for the next generation of data-driven global weather models. It covers deterministic, ensemble-probabilistic, bias, and spectral diagnostics. |
|
|
| Paper: WeatherBench 2: A Benchmark for the Next Generation of Data-Driven Global Weather Models |
| https://arxiv.org/abs/2308.15560 |
|
|
| # Model Description |
|
|
| The benchmark was proposed by teams from Google Research, Google DeepMind, and ECMWF. It uses 2020 global forecasts from ERA5, IFS, and multiple data-driven systems. It supports deterministic, probabilistic, bias, and spatial-scale evaluation of global forecasts from one to fourteen days. |
|
|
| # Use Cases |
|
|
| | Use Case | Description | |
| | :---: | :--- | |
| | Deterministic evaluation | Compute RMSE, ACC, bias, and SEEPS. | |
| | Probabilistic evaluation | Compute CRPS and spread-skill ratio. | |
| | Ensemble diagnosis | Compare ensemble means, spread, and skill. | |
| | ModelScope/OneCode execution | Validate data, training, inference, evaluation, and visualization. | |
| | Multi-GPU training | Validate a compact baseline through `torchrun`. | |
|
|
| # Usage Instructions |
|
|
| ```bash |
| hf download OneScience-Group/WeatherBench2 --local-dir ./WeatherBench2 |
| cd WeatherBench2 |
| ``` |
|
|
| ### Environment Dependencies |
|
|
| **Hardware Requirements** |
|
|
| - A GPU or DCU is recommended. |
| - A CPU can be used for connectivity validation with the default small-sample configuration. |
| - DCU users should install DTK 25.04.2 or a compatible OneScience-recommended version first. |
|
|
| **DCU Environment** |
|
|
| ```bash |
| # Activate DTK and Conda first |
| conda create -n onescience311 python=3.11 -y |
| conda activate onescience311 |
| pip install onescience[earth-dcu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai |
| ``` |
|
|
| **GPU Environment** |
|
|
| ```bash |
| # Activate Conda first |
| conda create -n onescience311 python=3.11 -y libstdcxx-ng=12 libgcc-ng=12 gcc_linux-64=12 gxx_linux-64=12 |
| conda activate onescience311 |
| pip install onescience[earth-gpu] -i http://mirrors.onescience.ai:3141/pypi/simple/ --trusted-host mirrors.onescience.ai |
| ``` |
|
|
| ### Training Data |
|
|
| WeatherBench2 evaluates 2020 global forecasts from ERA5, IFS, and data-driven systems on a common 1.5-degree grid. Synthetic data retain eight headline variables and the ensemble dimension while reducing times and grid size. |
|
|
| ```bash |
| python scripts/fake_data.py |
| ``` |
|
|
| ### Training |
|
|
| For single-process training, use: |
|
|
| ```bash |
| python scripts/train.py |
| ``` |
|
|
| For multi-process training, use: |
|
|
| ```bash |
| torchrun --standalone --nproc_per_node=2 scripts/train.py |
| ``` |
|
|
| Training results are saved to: |
|
|
| ```text |
| result/checkpoints/weatherbench2.pt |
| result/training/metrics.json |
| ``` |
|
|
| ### Trained Weights |
|
|
| No weights are bundled under `weight/`. WeatherBench2 is a benchmark rather than a single pretrained model, so there is no unified official weight artifact. |
|
|
| ### Inference |
|
|
| ```bash |
| python scripts/inference.py |
| ``` |
|
|
| Inference generates an ensemble with shape `[8,8,8,24,48]`. Results are saved to: |
|
|
| ```text |
| result/output/predictions.npz |
| ``` |
|
|
| ### Evaluation and Visualization |
|
|
| ```bash |
| python scripts/result.py |
| ``` |
|
|
| Evaluation reports RMSE, CRPS, and spread-skill ratio and creates a spatial error map. Results are saved to: |
|
|
| ```text |
| result/evaluation/metrics.json |
| result/evaluation/comparison.png |
| ``` |
|
|
| # Official OneScience Information |
|
|
| | Platform | OneScience Main Repository | Skills Repository | |
| |---|---|---| |
| | Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills | |
| | GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills | |
|
|
| # Citation and License |
|
|
| This repository is an independent engineering reproduction of the public WeatherBench2 specifications. |
|
|
| The WeatherBench2 evaluation code, ERA5, IFS, and forecast data from participating systems remain subject to the licenses and data-use terms of their respective source projects. |
|
|
