Earth Sciences

Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data

M. Wegmann and F. Jaume-santero

Dive into the fascinating world of climate science! This research by Martin Wegmann and Fernando Jaume-Santero introduces a machine learning method using Recurrent Neural Networks to reconstruct climate variability from sparse data, yielding realistic temperature patterns efficiently. Discover how this innovative approach can adapt to various regions and time periods!