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This is a global data-driven high-resolution weather model implemented and improved by High-Flyer AI. It is the first AI weather model, which can compare with the ECMWF Integrated Forecasting System (IFS).
Typhoon track comparison:
Water vapour comparison:
- hfai
- torch >=1.8
The raw data is from the public dataset, ERA5 , which is integrated into the dataset warehouse, hfai.datasets
.
-
pretrain
submit the task to Yinghuo HPC:
hfai python train/pretrain.py -- -n 8 -p 30
run locally:
python train/pretrain.py
-
finetune
submit the task to Yinghuo HPC:
hfai python train/fine_tune.py -- -n 8 -p 30
run locally:
python train/fine_tune.py
-
precipitation train
submit the task to Yinghuo HPC:
hfai python train/precipitation.py -- -n 8 -p 30
run locally:
python train/precipitation.py
@article{pathak2022fourcastnet,
title={Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators},
author={Pathak, Jaideep and Subramanian, Shashank and Harrington, Peter and Raja, Sanjeev and Chattopadhyay, Ashesh and Mardani, Morteza and Kurth, Thorsten and Hall, David and Li, Zongyi and Azizzadenesheli, Kamyar and others},
journal={arXiv preprint arXiv:2202.11214},
year={2022}
}