Assessing atmospheric moisture effects on heavy precipitation during HyMeX IOP16 using GPS nudging and dynamical downscaling

Abstract

Abstract. Gaining insight into the interaction between atmospheric moisture and convection is determinant for improving the model representation of heavy precipitation, a weather phenomenon that causes casualties and monetary losses in the western Mediterranean region every year. Given the large variability of atmospheric moisture, an accurate representation of its distribution is expected to reduce the errors related to the representation of moist convective processes. In this study, we use a diagnostic approach to assess the sensitivity of convective precipitation and underlying mechanisms during a heavy precipitation event (Hydrological cycle in the Mediterranean eXperiment Intensive Observation Period; HyMeX IOP16) to variations of the atmospheric moisture spatio-temporal distribution. Sensitivity experiments are carried out by nudging a homogenized data set of the Global Positioning System-derived zenith total delay (GPS-ZTD) with sub-hourly temporal resolution (10 min) in 7 and 2.8 km simulations with the COnsortium for Small-scale MOdeling in CLimate Mode (COSMO-CLM) model over the western Mediterranean region. The analysis shows that (a) large atmospheric moisture amounts (integrated water vapour; IWV ∼ 40 mm) precede heavy precipitation in the affected areas. This occurs 12 h prior to initiation over southern France and 4 h over Sardinia, north-eastern Italy and Corsica, which is our main study area. (b) We found that the moisture is swept from the Atlantic by a westerly large-scale front associated with an upper level low on the one hand and evaporated from the Mediterranean Sea and north Africa on the other. The latter moisture transport occurs in the 1 to 4 km layer. (c) COSMO-CLM overestimated the atmospheric humidity over the study region (Corsica), and this was, to a good extent, corrected by the GPS-ZTD nudging. This reduced maximum precipitation (−49 % for 7 km and −16 % for 2.8 km) drastically, considerably improving the precipitation representation in the 7 km simulation. The convection-permitting simulation (2.8 km) without the GPS-ZTD nudging already did a good job in representing the precipitation amount. (d) The two processes that exerted the largest control on precipitation reduction were the decrease of atmospheric instability over Corsica (convective available potential energy; CAPE −35 %) and the drying of the lower free troposphere bringing additional dry air entrainment. In addition, the 7 km simulation showed a weakening of the represented low-pressure system and the associated cyclonic wind circulation. This ultimately reduced the intensity and number of convective updrafts represented over the island. These results highlight the large impact exerted by moisture corrections on precipitating convection and the chain of processes leading to it across scales.