An object-based method to study the life cycle of mesoscale convective systems and their environment from cloud-resolving AROME-France simulations
Arnould, Gabriel ; Montmerle, Thibaut ; Rottner, Lucie ; Moisselin, Jean-Marc
An object-based methodology is used to study the mesoscale convective systems (MCSs) developing in France and the interactions they have with their environment during their life cycle. MCSs are detected from images of radar reflectivity and satellite 10.8-?m brightness temperature with a deep-learning segmentation method. The ability of the Application of Research to Operations at Mesoscale (AROME-France) numerical weather prediction model in representing MCSs is first assessed by comparing statistically the attributes of objects tracked in simulated and observed images of severe convective situations between 2018 and 2022. The MCS environment is then studied by averaging ambient variables simulated by AROME-France within a 100-km wide area and calculating original ring-shaped composite maps adapted to the geometry of each object. Based on this methodology, it is shown that MCSs generally develop in unstable areas with low-level convergence and strong wind aloft. Ambient instability correlates best with MCS severity and maintenance. It undergoes the greatest decrease throughout the life cycle, in relation with low-level cooling and drying. Further comparisons are made between quasi-stationary Mediterranean and other MCSs, and particular attention is paid to the impact of the system on its own environment. We finally emphasise three relevant predictors for MCS nowcasting in France: (1) the trend in system size and convective activity, (2) the ambient instability, and (3) the midlevel wind to anticipate MCS movement.</p>
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