In order to assess climate change at regional scales suitable to viticulture, the outputs of ARPEGE_Climat global model (resolution 0.5°) were downscaled using the Regional Atmospheric Modeling System (RAMS) and nested grids, providing downscaled datasets of 5 km resolution over France. Simulations were performed for two periods: 1991-2000, to assess the method against observations and quantify the large-scale induced biases; and 2041-2050 as near future climate projection under the SRES A2 scenario conditions. Results for July maximum temperatures, focussing on 6 wine regions, show RAMS contribution in reducing the large-scale bias, leading to a better assessment of climate change, yet with spatial differences.
Authors: Valérie BONNARDOT (1), Sylvie CAUTENET (2), Guy CAUTENET (3), Hervé QUENOL (1)
(1) LETG-Rennes COSTEL (UMR 6554 CNRS), Université Rennes 2, Place du Recteur Henri le Moal, 35043 Rennes Cedex, France
(2) Laboratoire de Météorologie Physique (LaMP), UMR 6016 CNRS, Université Blaise Pascal, 24 avenue des Landais, 63177 Aubière Cedex, France
Email: valerie.bonnardot@uhb.fr
Keywords: Mesoscale climate modeling, SRES A2 scenario, July maximum temperature, wine regions, France