Bris-HourGlass
This repository contains the Bris-HourGlass (hourly temporal downscaler) checkpoints with matching training configs.
The intended use is training with Anemoi and forecast inference from the published model artifacts.
Contents
configs/Bris-HourGlass_o96.yaml: global o96 pre-training configconfigs/Bris-HourGlass_n320.yaml: global n320 fine-tuning configconfigs/Bris-HourGlass_stretched.yaml: global+regional n320+2.5km stretched grid fine-tuning configBris-HourGlass_n320_inference.ckpt: global n320 inference checkpointBris-HourGlass_n320_training.ckpt: global n320 training checkpoint (for further fine-tuning)Bris-HourGlass_stretched_inference.ckpt: stretched grid inference checkpointBris-HourGlass_stretched_training.ckpt: stretched grid training checkpoint
Scope
This is an artifact repository. It provides model weights and configs, but not input datasets.
The source code used for training is open and available through Anemoi Core: https://github.com/ecmwf/anemoi-core
Usage
Training is performed with the Anemoi codebase.
Training and fine-tuning of this model was done on the Anemoi Core branch ecmwf/anemoi-core/tree/feature/ens_interp.
https://github.com/ecmwf/anemoi-core/tree/feature/ens_interp
Porting the checkpoints to a newer version is not supported, but the functionality in that branch is now all on the main Anemoi Core, so for training new models, using main is recommended.
Notes
bris-crpsfft_inference.ckptis the checkpoint intended for inference.bris-crpsfft_training.ckptis kept as a training artifact.- The configs are included to make the artifacts easier to interpret and reuse.
Citation
If you use these artifacts, cite: https://arxiv.org/abs/2607.11457