The Impact of Assimilated Clear-Sky and Cloudy Retrievals on Arctic Prediction During THINICE 2022

We have demonstrated that data assimilation of satellite products derived from hyperspectral IR satellite observations from polar orbiting platforms can be implemented in a very efficient way (Cherubini et al. 2023) using transformed retrievals (TRs) (Migliorini 2008, 2012), with positive impact on model forecasts over the central North Pacific. Cloud cover over the Arctic presents a special challenge to IR hyperspectral retrieval algorithms, which work optimally in clear sky conditions. To address this challenge, our approach assimilating TRs was expanded to include hyperspectral atmospheric profiling in cloudy conditions and succeeded in deriving physical profiles above cloud top and automating this capability for WRF simulations performed in a 3-hourly RUC mode. Case studies of a Tropopause Polar Vortex (TPV) and surface cyclones observed during the 2022 THINICE field campaign over the period 8-11 August showed this expanded approach to be especially useful in providing supplemental data over the Arctic region and promises to advance Arctic prediction by improving the distribution of temperature and moisture fields in the troposphere and lower stratosphere that are important for storm energetics. The presentation will provide an overview of the assimilation system, its implementation over the Arctic region, and preliminary results for the 8-11 August IOPs.