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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]

Real midlatitude meteorological cases are simulated over western Europe with the cloud mesoscale model Méso-NH, and the outputs are used to calculate brightness temperatures at microwave frequencies with the Atmospheric Transmission at Microwave (ATM) radiative transfer model. Satellite-observed brightness temperatures (TBs) from the Advanced Microwave Scanning Unit B (AMSU-B) and the Special Sensor Microwave Imager (SSM/I) are compared to the simulated ones. In this paper, one specific situation is examined in detail. The infrared responses have also been calculated and compared to the Meteosat coincident observations. Overall agreement is obtained between the simulated and the observed brightness temperatures in the microwave and in the infrared. The large-scale dynamical structure of the cloud system is well captured by Méso-NH. However, in regions with large quantities of frozen hydrometeors, the comparison shows that the simulated microwave TBs are higher than the measured ones in the window channels at high frequencies, indicating that the calculation does not predict enough scattering. The factors responsible for the scattering (frozen particle distribution, calculation of particle dielectric properties, and nonsphericity of the particles) are analyzed. To assess the quality of the cloud and precipitation simulations by Méso-NH, the microphysical fields predicted by the German Lokal-Modell are also considered. Results show that in these midlatitude situations, the treatment of the snow category has a high impact on the simulated brightness temperatures. The snow scattering parameters are tuned to match the discrete dipole approximation calculations and to obtain a good agreement between simulations and observations even in the areas with significant frozen particles. Analysis of the other meteorological simulations confirms these results. Comparing simulations and observations in the microwave provides a powerful evaluation of resolved clouds in mesoscale models, especially the precipitating ice phase. [ABSTRACT FROM AUTHOR]