Implicit Assimilation of Sparse In Situ Data for Dense & Global Storm Surge Forecasting

arXiv:2404.05758v1 Announce Type: cross
Abstract: Hurricanes and coastal floods are among the most disastrous natural hazards. Both are intimately related to storm surges, as their causes and effects, respectively. However, the short-term forecasting of storm surges has proven challenging, especially when targeting previously unseen locations or sites without tidal gauges. Furthermore, recent work improved short and medium-term weather forecasting but the handling of raw unassimilated data remains non-trivial. In this paper, we tackle both challenges and demonstrate that neural networks …

abstract arxiv cs.ai cs.cv cs.lg data effects forecasting global hazards however hurricanes locations natural physics.ao-ph physics.data-an stat.ap storm targeting type