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SPEEDY-ML

Fortran code for a hybrid model that combines an atmospheric general circulation model (SPEEDY) and a reservoir computing-based machine learning algorithm.

Installation Instructions

Download the SPEEDY-ML model with:

 $ git clone [email protected]:Arcomano1234/SPEEDY-ML.git

##Quick Setup

  1. Fill in the necessary information in config.sh

  2. If you want to train your model use scripts/get_training_prediction_data.sh. If you want to use an already trained model skip to step 5.

  3. Run scripts/regrid_data.sh

  4. After all of the necessary training data is downloaded and regridded to the SPEEDY horizontal and vertical grid run scripts/train_model.sh . Depending on the number of processors this can take anywhere from 40 minutes to a day.

  5. Run scripts/run_trained_model.sh . This can be used with a small number of CPUs with the only computational requiring being 32 GB of memory alotted to the program.

  6. After the predictions are done, a number of python scripts are provided to analyze the forecasts or climate simulations

Training Data

To download training data first