---
license: apache-2.0
language:
- en

tags:
  - weather-forecasting
  - weather
  - meteorology
  - ensemble-forecasting
  - probabilistic-forecasting
  - temporal downscaling
---

# 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 config
- `configs/Bris-HourGlass_n320.yaml`: global n320 fine-tuning config
- `configs/Bris-HourGlass_stretched.yaml`: global+regional n320+2.5km stretched grid fine-tuning config
- `Bris-HourGlass_n320_inference.ckpt`: global n320 inference checkpoint
- `Bris-HourGlass_n320_training.ckpt`: global n320 training checkpoint (for further fine-tuning)
- `Bris-HourGlass_stretched_inference.ckpt`: stretched grid inference checkpoint
- `Bris-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.ckpt` is the checkpoint intended for inference.
- `bris-crpsfft_training.ckpt` is 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

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