Argonne researchers will present a technical paper detailing the development of a scalable neural architecture search to forecast sea surface temperatures using a dataset from the National Oceanic and Atmospheric Administration. Their work to develop surrogate geophysical models has the potential to reduce the large computational cost involved in atmospheric and oceanic modeling.