4. Run GraphCastGFS

In order to run GraphCast in inference mode you will also need to have the model weights, normalization statistics, which are avaiable on Google Cloud Bucket Once you have input netCDF file, model weights, and statistics data, you can run the GraphCast model with a leading time (e.g., leading time 10 days will result in forecast_length of 40) using:

python run_graphcast.py --input /input/filename/with/path --output /path/to/output --weights /path/to/weights --length forecast_length

Arguments

Required:

-i or –input: /input/filename/with/path

-o or –output: /path/to/output

-w or –weights: /path/to/weights/and/stats

-l or –length: integer, the number of forecast time steps (6-hourly)

Optional:

-p or –pressure: 13 or 37, number of pressure levels (default: 13)

-u or –upload: yes or no, upload input and output files to NOAA s3 bucket (default: no)

-k or –keep: yes or no, whether to keep input and output files after uploading