Temporal evolution of features that control 10-m wind gusts in moist baroclinic wave simulations identified using non-linear regression

A majority of insured losses over Europe are related to Extra-Tropical Cyclones (ETC) which are characterised by strong winds, heavy precipitation and powerful ocean waves. Baroclinic wave simulations (BWS) are used to study ETC by varying their background state and measuring their different intensities. However, two main issues limit an exhaustive exploration of ETC intensity and background state relationship: 1) the dimensionality of the feature space, 2) a large number of intensity measures. To alleviate this issue, this study proposes to use a wrapper Feature Selection Algorithm (wFSA) combined with a non-linear regressor applied to an intensity measure. The selected subsets are analysed through time.

BWS was performed in the moist case using OpenIFS version Cy43r3v2 configured as an aqua planet with full physics and the radiation scheme deactivated. The atmospheric state proposed by Jablonowski and Williamson was used. The spatial resolution of the simulation was set to TL319/L137 and the time resolution to 20 minutes for 15 days. The initial perturbation was located in 40°N 20°E. A number of 55 measures -called features- were extracted from the BWS and the 10-m wind gust was selected as the intensity measure. A stable wFSA was performed using weighted Random Forest Regressor in the framework proposed by Meinshausen and Bühlmann. The regression was run 10 times on 60% of randomly selected points in the northern hemisphere to infer the 10-m wind gust. Finally, the average feature importance and its variance were computed for each feature every 12 hours.

The forecast surface roughness and the specific humidity were the most important features for the first 2 days. Afterwards, mean sea level pressure became predominant for 5 days. For the remaining days, forecast surface roughness, specific humidity and large scale precipitation were the most important features to infer 10-m wind gust. Further work will aim at increasing the number of BWS by modifying the average temperature of the background state. All results will be compared to propose an efficient dimension reduction to study BWS and their evolution.