Rain Nowcasting from Multiscale Radar Images

Aniss Zebiri, Dominique Béréziat, Etienne Huot, Isabelle Herlin

Abstract

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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Paper Citation


in Harvard Style

Zebiri A., Béréziat D., Huot E. and Herlin I. (2019). Rain Nowcasting from Multiscale Radar Images.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 892-900. DOI: 10.5220/0007566908920900


in Bibtex Style

@conference{visapp19,
author={Aniss Zebiri and Dominique Béréziat and Etienne Huot and Isabelle Herlin},
title={Rain Nowcasting from Multiscale Radar Images},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={892-900},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007566908920900},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Rain Nowcasting from Multiscale Radar Images
SN - 978-989-758-354-4
AU - Zebiri A.
AU - Béréziat D.
AU - Huot E.
AU - Herlin I.
PY - 2019
SP - 892
EP - 900
DO - 10.5220/0007566908920900