A satellite lightning observation operator for storm-scale numerical weather prediction

Abstract. This study aims at simulating satellite-measured lightning observations with numerical weather prediction (NWP) system variables. A total of eight parameters, calculated the AROME-France NWP variables, were selected from a literature review to be used as proxies for satellite observations. Two different proxy types emerged this review: microphysical and dynamical proxies. Here, we investigate which ones are best related calibrate an empirical relationship between parameters data. To obtain those relationships, fit machine learning regression models our In study, pseudo flash extent accumulation (FEA) because no actual geostationary available yet over France, non-geostationary data represent sample that is too small study. The performances each model evaluated by computing fractions skill scores (FSSs) respect observed FEA proxy-based FEA. present suggests more suited than system. multivariate also combining several after feature selection based on principal component analysis correlation but combination yielded better results alone. Finally, periods had little influence, i.e. similar FSS, model's ability reproduce future studies, microphysical-based will observation operator perform assimilation in storm-scale systems applied forecasts simulate