Machine learning and data assimilation with a quasigeostrophic vorticity system
This repository contains code for investigating machine learning and data assimilation with a quasigeostrophic vorticity model.
aicontains scripts for training a neural net to replace the numerical model.
assimilationcontains scripts for running data assimilation with the numerical model and the trained model.
forecastcontains scripts for comparing "weather forecasts" run with the numerical model and the trained model.
numerical_modelcontains FORTRAN90 code for running the numerical model. This is compiled with f2py so it can be called from Python.
- Set up conda environment. Run
conda activate lorenz96_machine_learning.
source setup.shfrom the root directory. This will build the numerical model and add it to the Python path.