A statistical downscaling to identify the large‐scale circulation patterns associated with heavy precipitation events over southern France

Abstract

This study assesses the potential for a detection algorithm to identify discriminating analysis-based statistical predictors of a few relevant parameters that can be used to capture heavy precipitation events (HPEs), or, at least, their associated largescale circulation (LSC) patterns in a climate scenario. HPEs are defined from a sample combining 'large-scale' fields from the ECMWF ERA-40 reanalysis with local observations from the Météo-France rain-gauge network. In a first step, LSC patterns considered as significantly favouring HPE over southern France are identified and described with the greatest robustness possible. For that purpose, an objective automatic clustering of the unfiltered 500 hPa geopotential height field is performed. Four clusters are obtained. Among them, the most discriminating for heavy precipitation is characterised by a synoptic-scale deep upper-level low northwest of the area of interest, inducing a southerly flow over the western Mediterranean Sea and southern France. In a second step, other lower-scale parameters are used to refine the characteristics of the clusters. It has been found that the low-level moisture transport is a relevant low-level ingredient to regionally characterise heavy precipitation. Indeed, 'Cévennes' cases are related to more south to southeasterly flows over the Gulf of Lion, whereas 'Languedoc-Roussillon' events occurred preferentially within a more pronounced easterly wind component with two streams of low-level moisture transport. Moreover, in-depth examination of the low-level features reveals that HPEs tend to occur when the wind blows in a specific direction and for the greatest low-level moisture flux over the Gulf of Lion. Finally, the predictive skill of a detection tool for HPEs over southern France, with only synoptic-scale favourable parameters as predictors, is discussed. It is shown that this tool allows selection of HPE situations in more than 70% of cases.

Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

“…The change in spring precipitation is thus most likely due to changes in global fluxes that have different impacts on western coastal regions (Aude and Muga) and on southern coastal regions (Cevennes). Indeed, Nuissier et al (2011) explained that strong precipitation events over the west coast of the Mediterranean are mostly correlated with easterly fluxes, while strong precipitation events in the northern coastal region are correlated with south to southeasterly fluxes. Cassou et al (2016) reported that climate change will have a greater impact on easterly fluxes; this could explain the change in the annual cycle observed in Aude and Muga regions only.…”

“…Cumulative annual rainfall is around 909 mm, which, on average, falls 60 days per year (Coustau, 2011;Harader, 2015). The Lez catchment is frequently subject to flash floods caused by extreme precipitation episodes regionally known as the "Cévenols" events Nuissier et al, 2008Nuissier et al, , 2011. Cumulative extreme precipitation can locally reach 600 mm in 24 h within the river catchment (Boudevillain et al, 2011).…”

Optimising predictor domains for spatially coherent precipitation downscaling

“…Quintana Seguí et al, 2010Lavaysse et al, 2012;Kallache et al, 2011;Carreau and Vrac, 2011;Nuissier et al, 2011;Beaulant et al, 2011), western France (e.g. Timbal et al, 2003), the French Alps (e.g.…”

Evaluation of classical spatial-analysis schemes of extreme rainfall

“…This is the result of the well-known mountain-shading effect. It takes place at the north of the maps because air fluxes producing heavy rainfall at the daily time scale are from a sector from the south to southeast (Nuissier et al, 2011). A close look at the return level maps shows that over the plain and even over the foothills, all the scheme (RS ref , RS2 and RS3) estimates are very similar.…”