Modelling Cold Air Outbreak Clouds from the Cold-Air Outbreak Experiment in the Sub-Arctic Region (CAESAR) Campaign

Cold-air outbreak (CAO) events are an understudied yet common aspect of the Arctic climatology. By creating relatively shallow boundary layers with wide zonal and narrow meridional scales, they often fall in the grey zone of forecasting. Numerical weather and climate models tend to overlook CAOs, potentially leading to the Arctic’s large discrepancy between forecasts and observations. The Cold-Air Outbreak Experiment in the Sub-Arctic Region (CAESAR) aircraft campaign funded by the US National Science Foundation aimed to characterize CAOs coming off of the Arctic sea ice by gathering valuable in-situ and remotely-sensed data. The CAESAR dataset provides a powerful modeling test bed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

In this study, the Weather Research and Forecasting (WRF) model is utilized to simulate one of the ten CAESAR research flights (RFs): RF07 on March 16th, 2024 which sampled a very cold CAO event west of two polar lows close to Scandinavia. Thirty nine AVAPS dropsondes were released during RF07. The convection-permitting WRF simulations, with a 3 km horizontal resolution inner nest, were driven by ERA5 reanalysis data. Results show that the WRF simulation captured general characteristics of the CAO event from RF07 fairly well whereas the simulated intensity of mixed-phase CAO clouds was overestimated. The verification against dropsonde observations shows that the WRF simulation is able to reproduce the vertical profiles of potential temperature and relative humidity for roughly half of the soundings. The simulated wind speed and direction variables are consistently similar to the observed ones for most of the soundings.