monocongo / climate_learn

Deep learning for climate modeling.
BSD 3-Clause "New" or "Revised" License
38 stars 22 forks source link

Add model fits/tests for non-linear tendency variables #1

Open monocongo opened 5 years ago

monocongo commented 5 years ago

We now have access to new data sets for our project that use a more complicated (non-linear) forcing mechanism for temperature and also for a new moisture variable ‘Q’.

The new state variables in the ‘h0’ (feature/input) files are ‘Q’ and the large-scale rainfall rate ‘PRECL’ as a diagnostic quantity. The ‘h1’ (output/target) files now contain the new forcing ‘PTEQ’ for the moisture variable ‘Q’. Basically, PTEQ is the time tendency of the moisture, just like the time tendencies for T, U, V.

We'll incorporate this new feature variable into existing fits/tests as well as adding new model types to explore how these will perform.