Compressing multidimensional weather and climate data into neural networks. (arXiv:2210.12538v3 [cs.LG] UPDATED)

Weather and climate simulations produce petabytes of high-resolution data
that are later analyzed by researchers in order to understand climate change or
severe weather. We propose a new method of compressing this multidimensional
weather and climate data: a coordinate-based neural network is trained to
overfit the data, and the resulting parameters are taken as a compact
representation of the original grid-based data. While compression ratios range
from 300x to more than 3,000x, our method outperforms the state-of-the-art
compressor SZ3 in …

art arxiv change climate climate change compression data grid multidimensional network networks neural network neural networks representation researchers simulations state terms weather