Seeing Inside the Storm: Improving Nowcasting by Integrating Meteorological Drivers
Most nowcasting systems, built on radar reflectivity, focus on current precipitation, ignoring the atmospheric precursors -- such as low-level convergence, turbulent eddies, and latent heating -- that offer a fleeting window to foresee storm birth. We introduce MeteoLogist, a physics-inspired radar intelligence framework that models the full life cycle of convection -- from its precursors to organized storm evolution. However, exploiting these precursors is non-trivial: they originate from multiple meteorological drivers -- thermodynamic, kinematic, and microphysical -- that evolve asynchronously (C1) and remain spatially fragmented (C2). To this end, MeteoLogist designs three tightly int...
| Authors | Minghui Qiu, Jun Chen, Lin Chen et al. |
|---|---|
| Primary category | physics.ao-ph |
| Published | 22 May 2026 |
| Last updated at source | 22 May 2026 |
Models and datasets referencing this paper
- whyeb4449/gridrad2020-2022Dataset
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