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Operational Implementation of the 1D13D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model

Abstract : The extremes of precipitation and river flow obtained using three different statistical downscaling methods applied to the same regional climate simulation have been compared. The methods compared are the anomaly method, quantile mapping and a weather typing. The hydrological model used in the study is distributed and it is applied to the Mediterranean basins of France. The study shows that both quantile mapping and weather typing methods are able to reproduce the high and low precipitation extremes in the region of interest. The study also shows that when the hydrological model is forced with these downscaled data, there are important differences in the outputs. This shows that the model amplifies the differences and that the downscaling of other atmospheric variables might be very relevant when simulating river discharges. In terms of river flow, the method of the anomalies, which is very simple, performs better than expected. The methods produce qualitatively similar future scenarios of the extremes of river flow. However, quantitatively, there are still significant differences between them for each individual gauging station. According to these scenarios, it is expected that in the middle of the 21st century (2035-2064), the monthly low flows will have diminished almost everywhere in the region of our study by as much as 20 %. Regarding high flows, there will be important increases in the area of the C'evennes, which is already seriously affected by flash-floods. For some gauging stations in this area, the frequency of what was a 10-yr return flood at the end of the 20th century is expected to increase, with such return floods then occurring every two years in the middle of the 21st century. Similarly, the 10-yr return floods at that time are expected to carry 100% more water than the 10-yr return floods experienced at the end of the 20th century. In the northern part of the Rhône basin, these extremes will be reduced.
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Eric Wattrelot, Olivier Caumont, Jean-Francois Mahfouf. Operational Implementation of the 1D13D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model. Monthly Weather Review, 2013, 142, pp.1852-1871. ⟨10.1175/MWR-D-13-00230.1⟩. ⟨meteo-01001390⟩



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