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README.md

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+---
+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.