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OneScience-Group/
AIFS_Single_v1

Name: AIFS_Single_v1
Rating: 2.5 (9 reviews)

Deterministic Forecast

OneScience/ERA5

2406.01465

apache-2.0

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AIFS_Single_v1

Model Introduction

AIFS Single v1.1 is the deterministic version of the AI-powered weather forecasting system developed by the European Centre for Medium-Range Weather Forecasts (ECMWF).

Paper: AIFS — ECMWF's data-driven forecasting system, arXiv:2406.01465

https://arxiv.org/abs/2406.01465

Model Description

AIFS is built on a Graph Neural Network (GNN), pre-trained on ERA5 data and fine-tuned with NWP operational analysis data.

Use Cases

Scenario	Description
Weather Forecast Training	Train AIFS from scratch using ERA5 HDF5 data
Local Quick Validation	Use synthetic data to verify data loading, model training & inference, and inference result visualization.
ModelScope / OneCode Execution	Download as a standalone model package, install dependencies, and run scripts directly.

Usage Guide

1. OneCode Usage

Experience intelligent one-click AI4S programming through the OneCode online environment:

Click to Experience Intelligent One-Click AI4S Programming

2. Manual Installation and Usage

Hardware Requirements

A GPU or DCU is recommended.
CPU can be used for import and small-scale connectivity verification; full training and inference will be slow.
DCU users must install DTK in advance. DTK 25.04.2 or above is recommended.

Download the Model Package

bash

hf download OneScience-Group/AIFS_Single_v1 --local-dir ./AIFS_Single_v1
cd AIFS_Single_v1

Install the Runtime Environment

DCU

bash

# Please activate DTK and CONDA first
conda create -n onescience311 python=3.11 -y
conda activate onescience311
# uv installation is supported
pip install onescience[earth-dcu] -i http://mirrors.onescience.ai:3141/pypi/simple/  --trusted-host mirrors.onescience.ai

GPU

bash

# Please 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
# uv installation is supported
pip install onescience[earth-gpu] -i http://mirrors.onescience.ai:3141/pypi/simple/  --trusted-host mirrors.onescience.ai

Training Data Introduction

The OneScience community provides ERA5 data for training (due to file size limits, the current repository contains a slice of the full dataset). Users can download it with the command below and confirm that the data path in conf/config.yaml is set correctly:

hf download --repo-type dataset OneScience-Group/ERA5 --local-dir ./data

Training

python scripts/train.py

Training weights are saved to weights/model_bak.ckpt, and the normalization file computed before training is saved to weights/era5_stats.npz.

Training Weights

This repository provides weights trained on ERA5 reanalysis data in the weights/ folder. The weight files will be uploaded soon and are expected to be available in the near future.

Inference

python scripts/inference.py

The number of forecast steps is controlled by test_lead_time in conf/config.yaml (in hours; default 24 = 1 day). Inference results will be saved to the output directory.

Evaluation and Visualization

python scripts/result.py

Computes ACC / RMSE metrics and generates plots. Metrics are saved to metrics/ and figures are saved to plots/.

OneScience Official 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 & License

This repository is a reproduction of the original AIFS Single v1.1 paper.