Issue |
E3S Web Conf.
Volume 50, 2018
XII Congreso Internacional Terroir
|
|
---|---|---|
Article Number | 02013 | |
Number of page(s) | 4 | |
Section | Valorización del Terroir | |
DOI | https://doi.org/10.1051/e3sconf/20185002013 | |
Published online | 22 August 2018 |
Radar Quantitative Precipitation Estimation improvement in Champagne vineyard.
1
Comité Champagne,
17 rue Chandon Moët
51200
Epernay,
France
2
Airmet Conception,
151 rue d'Auxonne
21000
Dijon,
France
*
Corresponding author : basile.pauthier@civc.fr
Rainfall has a crucial importance in viticulture, especially in Champagne vineyards, where irrigation is prohibited. Rainfall directly influences the phytosanitary pressure, nitrogen mineralization, flowering conditions, parcel practicability, soil erosion etc… In these conditions, implementing a weather stations network is the solution that the Comité Champagne chose to monitor rainfall all over the Champagne appellation since the 1990's. This networks is actually composed of 42 weather stations implemented in order to have the best spatial coverage as possible. The Comité Champagne also obtain some weather stations data from Météo France, the French national weather service. Even with that network, capturing all rainfall events accurately is difficult, especially in convective cases. Therefore, the interest in radar data has increased, to capture rainfall everywhere. Some tests have been previously made with PANTHERE radar data from Météo France with a resolution of 1 km2, results were promising, but presented inaccuracies particularly in convective events. In this article, we use a radar merging technique similar to the ANTILOPE method from Météo France, with a higher resolution network. The tool employed is the Estimages toolbox merger, based on krigine with external drift (KED) which has been demonstrated to give good results in quantitative precipitation estimation (QPE) improvement.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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