Global Tropical Cyclone Intensity Forecasting with Multi-modal Multi-scale Causal Autoregressive Model

arXiv:2402.13270v1 Announce Type: cross
Abstract: Accurate forecasting of Tropical cyclone (TC) intensity is crucial for formulating disaster risk reduction strategies. Current methods predominantly rely on limited spatiotemporal information from ERA5 data and neglect the causal relationships between these physical variables, failing to fully capture the spatial and temporal patterns required for intensity forecasting. To address this issue, we propose a Multi-modal multi-Scale Causal AutoRegressive model (MSCAR), which is the first model that combines causal relationships with large-scale multi-modal data for …

arxiv autoregressive model cs.ai cs.lg forecasting global intensity modal multi-modal physics.ao-ph physics.data-an scale type