Retrieval of Atmospheric Water Vapor and Temperature Profiles over Antarctica through Iterative Approach

Abstract

Retrieving atmospheric water vapor and temperature profiles presents considerable challenges over land surfaces using microwave radiometry due to uncertainties associated with estimating background surface emissions. In response, we have devised an approach that integrates the atmospheric retrieval algorithm with the background emission algorithm, establishing an iterative loop to refine the accuracy of atmospheric profiles. Leveraging optimal estimation techniques with sounding channels spanning from Ka- to G-band obtained from ATMS, we successfully retrieved atmospheric temperature and humidity profiles across space and time. These retrieved atmospheric profiles undergo continual updates throughout each iteration, exerting influence on subsequent surface retrievals. This iterative process persists until convergence is achieved in the atmospheric retrieval. The algorithm's novelty lies in its fusion of surface retrieval with atmospheric retrieval, thereby enhancing overall accuracy. We validated the retrievals against radiosonde data. Our iterative algorithm proved to be efficient and accurate in retrieving temperature profiles with surface emissivity and in detecting melting events. Though our algorithm was able to capture the water vapor variations, the results showed that to obtain accurate absolute values of the water content an independently retrieved surface emissivity is required.

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