June 7, 2024, 4:42 a.m. | Jan Martin\r{u}, Petr \v{S}im\'anek

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.04099v1 Announce Type: new
Abstract: This study investigates the application of deep-learning diffusion models for the super-resolution of weather data, a novel approach aimed at enhancing the spatial resolution and detail of meteorological variables. Leveraging the capabilities of diffusion models, specifically the SR3 and ResDiff architectures, we present a methodology for transforming low-resolution weather data into high-resolution outputs. Our experiments, conducted using the WeatherBench dataset, focus on the super-resolution of the two-meter temperature variable, demonstrating the models' ability to generate …

abstract application architectures arxiv capabilities cs.ai cs.lg data diffusion diffusion models methodology novel predictions resolution spatial study type variables via weather weather data

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