Hyperspectral IR Data Inversion from IASI and CrIS over the Arctic: Assimilating Retrievals in Clear Sky and Cloudy Conditions in Numerical Weather Models

The Arctic region is a critical area of study due to its sensitivity to climate change. To improve understanding and prediction of cyclogenesis over the Arctic, remote sensing techniques using hyperspectral infrared (IR) data from satellite sensors such as IASI and CrIS have been used. However, retrieving accurate atmospheric and surface parameters from these data sets in the presence of clouds remains a significant challenge. In recent years, efforts have been made to generate retrievals of atmospheric and surface parameters from hyperspectral IR data in both clear sky and cloudy conditions. These efforts have included the development of new algorithms and the integration of multiple satellite sensors to improve accuracy and resolution. This abstract highlights the importance of hyperspectral IR data inversion from IASI and CrIS over the Arctic and emphasizes the challenges of generating retrievals in both clear sky and cloudy conditions. The paper discusses recent developments in algorithms and the integration of multiple satellite sensors, which have helped to improve the accuracy and resolution of these retrievals. The results of this study will aid in a better understanding of the Arctic region's cyclogenesis and its interaction with ice formation/depletion.