[Paper] Generating physically-consistent high-resolution climate data with hard-constrained neural networks

openclimatefix / graph_weather

PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)

MIT License

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[Paper] Generating physically-consistent high-resolution climate data with hard-constrained neural networks #52

Open jacobbieker opened 1 year ago

jacobbieker commented 1 year ago

https://www.climatechange.ai/papers/aaaifss2022/5

Interesting work on making sure the outputs of high-resolution models are physically consistent. Might be good to include some of their work in this

branberry commented 1 year ago

Hello! I am interested in working on this issue. What would be a good way to reach out to you about questions I may have on implementing this enhancement?

jacobbieker commented 1 year ago

Hi, just posting on here would work well!

paulaharder commented 1 year ago

Hi! Great to see that our idea might be used for this. Wanted to let you know that we just released our code on it: https://github.com/RolnickLab/constrained-downscaling and also a new preprint: https://arxiv.org/abs/2208.05424 . Don't hesitate to contact me if there are any questions!

MadJokkerr commented 3 months ago

i would like to work on this issue please assign this to me