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Communication Dans Un Congrès Année : 2019

Rain Nowcasting from Multiscale Radar Images

Résumé

Rainfall forecasting is a major issue for anticipating severe meteorological events and for agriculture management. Weather radar imaging has been identified in the literature as the best way to measure rainfall on a large domain, with a fine spatial and temporal resolution. This paper describes two methods allowing to improve rain nowcast from radar images at two different scales. These methods are further compared to an operational chain relying on only one type of radar observation. The comparison is led with regional and local criteria. For both, significant improvements are quantified compared to the original method.
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Dates et versions

hal-02048500 , version 1 (25-02-2019)

Identifiants

Citer

Aniss Zébiri, Dominique Béréziat, Etienne Huot, Isabelle Herlin. Rain Nowcasting from Multiscale Radar Images. VISAPP 2019 - 14th International Conference on Computer Vision Theory and Applications, Feb 2019, Prague, Czech Republic. pp.1-9, ⟨10.5220/0007566908920900⟩. ⟨hal-02048500⟩
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