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Development of a Nationwide, Low-Level Wind Shear Mosaic in France.

Authors :
Augros, Clotilde
Tabary, Pierre
Anquez, Adrien
Moisselin, Jean-Marc
Brovelli, Pascal
Bousquet, Olivier
Source :
Weather & Forecasting. Oct2013, Vol. 28 Issue 5, p1241-1260. 20p.
Publication Year :
2013

Abstract

An algorithm for the detection of horizontal wind shear at low levels was developed. The algorithm makes use of data collected by all radars from the Application Radar à la Météorologie Infra-Synoptique (ARAMIS) operational network, in order to build a complete mosaic of wind shear over metropolitan France. The product provides an estimation of the maximum horizontal wind shear detected in the low levels, between 0 and 2 km AGL. Examination of the wind shear mosaic for different cases shows that the product is able to retrieve small-scale wind shear signatures that can be linked to either convergence lines ahead of convective cells, which are indicative of gust fronts, or strong convergence areas inside intense cells. A statistical evaluation of the wind shear mosaic was performed, by comparing horizontal wind shear observed inside the area defined by convective objects with wind gusts recorded along their trajectory by weather stations. A link between those different observations was clearly established. Therefore, the use of wind shear for wind gust prediction was tested in combination with other parameters: an estimation of the energetic potential of density currents, the cell surface with reflectivity over 51 dB Z, relative helicity, and cell propagation speed. Different wind gust warning rules were tested on 468 convection nowcasting objects (CONOs). The results clearly highlighted the benefits of using wind shear for wind gust estimation, and also demonstrated the improvement in forecasting skill when combining different parameters. The wind shear mosaic will be produced operationally before the end of 2013 and will be used to improve wind gust warnings provided to end users. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08828156
Volume :
28
Issue :
5
Database :
Academic Search Index
Journal :
Weather & Forecasting
Publication Type :
Academic Journal
Accession number :
90562402
Full Text :
https://doi.org/10.1175/WAF-D-12-00115.1