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A growing number of people in the weather and climate community are interested in how deep learning can help improve climate and weather modelling.

Researchers from Rice University introduced a data-driven framework that: 1) formulates extreme weather prediction as a pattern recognition problem, and 2) employs state-of-the-art deep learning techniques.

Their findings were published in the February 2020 edition of the American Geophysical Union's Journal of Advances in Modeling Earth Systems.

To obtain their results, the researchers analyzed large data sets and employed machine learning codes on supercomputers at TACC and PSC. In addition, they used data that had already been produced by supercomputers at NCAR as input for the deep learning models.


Faith Singer

Communications Manager

Jorge Salazar

Technical Writer/Editor