This article proposes a deep diffusion model of satellite (DDMS) to establish a high-resolution convection nowcasting system using geostationary satellite data. The key highlights are:
The DDMS employs diffusion processes to effectively model the complicated spatiotemporal evolution patterns of convective clouds, significantly improving the forecast lead time up to 4 hours.
The system utilizes geostationary satellite brightness temperature data, achieving planetary-scale forecast coverage of about 20,000,000 km2.
The system delivers state-of-the-art convection nowcasting performance, outperforming existing AI-based and traditional methods in terms of accuracy, lead time, and spatiotemporal resolution (15 minutes, 4 km).
The system operates efficiently, forecasting 4 hours of convection in just 8 minutes, and is highly transferable to collaborate with multiple satellite platforms for global convection nowcasting.
The results highlight the remarkable capabilities of diffusion models in convective clouds forecasting, as well as the significant value of geostationary satellite data when empowered by AI technologies.
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by Kuai Dai,Xut... om arxiv.org 04-17-2024
https://arxiv.org/pdf/2404.10512.pdfDiepere vragen