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Forecasting the electrical activity of a storm is a difficult task because of the complexity of cloud electrification processes and the unforeseeable characteristics of lightning flashes. Nowadays, very few models are able to simulate explicitly the entire life cycle of the electric charges in clouds, which is a result of the balance between the charge separation rates (microphysics) and the charge neutralization rates by lightning flashes (physics of streamer discharges). The main objective of this study is to investigate which particular dynamical and/or microphysical parameter can serve as the best proxy for the total lightning activity. With this aim, eight storms were simulated with Meso‐NH and its cloud electrical scheme. This model‐to‐model approach guarantees a full consistency between the dynamics, the microphysics and the lightning activity. Two approaches are followed to analyse the results. The first one considers the entire domain of simulation, while the second one concentrates on individual convective cells. Linear regressions between predicted flash rates and recorded parameters or proxies (total graupel mass, updraught volume with vertical velocity higher than 10 m/s, product of precipitating and non‐precipitating ice mass flux and maximum updraught speed) are analysed to show the benefit of the cell‐scale approach. Then, in order to evaluate the relationships, the HyMeX storm case of 24 September 2012 was simulated. The mass of graupel best represents the overall location of the lightning activity (RMSE of the flash rate density better than 10−2 fl min−1km−2) and locates the peak lightning flash rate well. The three other proxies tend to cause false alarms due to the y‐intercept value of the regression equation. [ABSTRACT FROM AUTHOR]

The goal of this paper is to present and evaluate the new LIMA (Liquid Ice Multiple Aerosols) microphysical scheme, which predicts six water species (water vapour, cloud water, rainwater, primary ice crystals, snow aggregates, and graupel). LIMA uses a two‐moment parametrization for three hydrometeor species (ice crystals, cloud droplets, and raindrops), and is derived from the one‐moment scheme ICE3 used daily in the AROME cloud‐resolving operational model at Météo‐France. In addition, it integrates a prognostic representation of the aerosol population. To evaluate the scheme, we simulate two well‐documented Heavy Precipitation Events from the HyMeX (Hydrological cycle in the Mediterranean Experiment) campaign. The LIMA simulations are compared to ICE3 simulations and to a large variety of observations, such as rainfall accumulation from rain gauges, particle size distributions from disdrometers, airborne in situ measurements of ice particles, and dual‐polarization radar variables. The evaluation suggests that the rain mixing ratio prognosed by LIMA is more realistic than that prognosed by ICE3. Comparisons with disdrometers and dual‐polarization radars highlight the better representation of the rain microphysical variability when using LIMA and also its overprediction of raindrops with large diameters. The vertical composition of the convective cells is also improved by the two‐moment ice parametrization in the LIMA scheme, which impacts the contents of the one‐moment parametrized snow and graupel species. This evaluation of LIMA suggests ways to improve the hydrometeor representation, focusing especially on the description of the particle size distributions for different water species. This paper evaluates the two‐moment microphysical scheme LIMA in comparison to the already validated one‐moment ICE3 scheme using a large variety of observations. First, it is shown that using the LIMA scheme improves both the hydrometeor contents and the representation of the observed microphysical variability. Then, statistical studies of the detailed microphysical observations suggest ways to improve the hydrometeor representation, focusing especially on the description of the particle size distributions for different water species. [ABSTRACT FROM AUTHOR]