Leveraging RALI‐THINICE Observations to Assess How the ICOLMDZ Model Simulates Clouds Embedded in Arctic Cyclones.

Despite their essential role in the high‐latitude climate, the representation of mixed‐phase clouds is still a challenge for Global Climate Models (GCMs)'s cloud schemes. In this study we propose a methodology for robustly assessing Arctic mixed‐phase cloud properties in a climate model using airborne measurements. We leverage data collected during the RALI‐THINICE airborne campaign that took place near Svalbard in August 2022 to evaluate the simulation of mid‐level clouds associated with Arctic cyclones. Simulations are carried out with the new limited‐area configuration of the ICOLMDZ model which combines the recent icosahedral dynamical core DYNAMICO and the physics of LMDZ, the atmospheric component of the IPSL‐CM Earth System Model. Airborne radar and microphysical probes measurements are then used to evaluate the simulated clouds. A comparison method has been set‐up to guarantee as much as possible the spatiotemporal co‐location between observed and simulated cloud fields. We mostly focus on the representation of ice and liquid in‐cloud contents and on their vertical distribution. Results show that the model overestimates the amount of cloud condensates and exhibits a poor cloud phase spatial distribution, with too much liquid water far from cloud top and too much ice close to it. The downward gradual increase in snowfall flux is also not captured by the model. This in‐depth model evaluation thereby pinpoints priorities for further improvements in the ICOLMDZ cloud scheme. Plain Language Summary: Mixed‐phase clouds, where ice crystals and supercooled liquid droplets coexist at sub‐zero temperatures, are ubiquitous in the polar regions. Albeit essential for the high‐latitude climate, they are still poorly represented by climate models. In this study, original measurements from the RALI‐THINICE airborne campaign, which took place in the Svalbard region in August 2022, are used to assess how the ICOLMDZ atmospheric model represents Arctic mixed phase clouds. A methodology is developed to make robust and co‐located model‐aircraft observation comparisons. In situ cloud probes and onboard radars are then used to evaluate the simulated amounts of liquid water and ice in clouds as well as the snowfall flux in deep clouds associated with the transit of Arctic cyclones. The results of the model evaluation show an overall overestimation of cloud condensates with too much liquid water far from cloud top and too much ice close to it. Key Points: Airborne RALI‐THINICE observations are used to evaluate Arctic clouds in the new limited area version of the ICOLMDZ modelA methodology has been developed to make robust and co‐located model‐observation comparisonsICOLMDZ simulates overly high amounts of liquid and ice in clouds particularly near cloud top [ABSTRACT FROM AUTHOR]