Aurora
Aurora is a machine learning model that can predict atmospheric variables, such as temperature. It is a foundation model, which means that it was first generally trained on a lot of data, and then can adapted to specialised atmospheric forecasting tasks with relatively little data.
They provide four such specialised versions: one for medium-resolution weather prediction, one for high-resolution weather prediction, one for air pollution prediction, and one for ocean wave prediction.
To load the model to use, see the code below:
module load gfms
module load Aurora
With using python, the model could then be used (as example below-from Aurora Document)
>>> from aurora import Aurora
>>> model = Aurora()
>>> from aurora import AuroraSmallPretrained
>>> model = AuroraSmallPretrained()
>>> model.load_checkpoint("microsoft/aurora", "aurora-0.25-small-pretrained.ckpt")
The model could also be used with jupyter notebook, see the code below and then use select kernel named "gfms_aurora":
module load jupyter
module load gfms
module load Aurora
Then start jupyter notebook in a interactive job by running:
jupyter notebook
Note the module jupyter must be loaded before Aurora to have the gfms_aurora kernel to be found. The model could also be accessed via $MODEL_DIR.