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AI models advance high-resolution precipitation nowcasting

Two new research papers propose advanced deep learning architectures for high-resolution precipitation nowcasting. The first, GenONet, utilizes a Generative Adversarial Network (GAN) framework combined with a Deep Operator Network (DeepONet) to improve long-range forecasts up to three hours, focusing on sharp and physically consistent results. The second, exPreCast-ENS, employs a diffusion-based refinement method to enhance kilometer-scale probabilistic nowcasting, correcting systematic errors and providing finer spatial detail with ensemble members. Both approaches aim to overcome limitations of current models in predicting rapid storm evolution and extreme weather events. AI

IMPACT These models offer improved accuracy and detail for predicting extreme weather events, potentially aiding disaster preparedness and mitigation efforts.

RANK_REASON Two academic papers published on arXiv detailing new deep learning models for precipitation nowcasting.

Read on arXiv cs.LG →

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AI models advance high-resolution precipitation nowcasting

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Two academic papers published on arXiv detailing new deep learning models for precipitation nowcasting.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Mohammad Kian Golkar, Luciano Alves de Oliveira, Mohammad Khanjani ·

    GenONet: A Generative operator Network for High-Resolution Precipitation Nowcasting

    arXiv:2609.00544v1 Announce Type: new Abstract: High-resolution precipitation nowcasting is critical for reducing the impacts of severe weather but remains difficult because of rapid storm evolution. Deep learning models have shown great promise for this task, but their predictiv…

  2. arXiv cs.LG TIER_1 English(EN) · Dohyun Park, Changhoon Song, Tengyuan Chang, Yoo-Geun Ham, Youngjoon Hong ·

    Diffusion-Based Refinement for Kilometer-Scale Probabilistic Precipitation Nowcasting

    arXiv:2608.30205v1 Announce Type: new Abstract: Localized extreme precipitation is a major trigger of urban flash floods and landslides, yet producing nowcasts that combine fine spatial detail with probabilistic uncertainty remains challenging. Here we introduce exPreCast-ENS, a …