Assessment of the sensitivity of a hyper-spectral infrared cloud property retrieval to atmospheric parameters using an optimal estimation framework

Abstract:

This work will present a combined hyper-spectral (S-HIS) and lidar (CPL) cloud property retrieval using an optimal estimation (OE) framework. The method retrieves cirrus cloud parameters (i.e. optical depth, effective radius and cloud top height) from the aircraft measurements in the infrared provided by the Scanning High-resolution Interferometer Sounder (S-HIS) and acquired during the Global Hawk HS3 flights. The OE algorithm is then utilized to investigate and quantify the sensitivity of the retrieval to atmospheric parameters such as temperature and water vapor profiles and to explore the advantages of using measurements from a hyper-spectral sensor instead of a broadband one.