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

Retrieving atmospheric water vapor and temperature profiles presents considerable challenges over land surfaces using microwave radiometry due to uncertainties in estimating background surface emissions. To address this, we developed an approach that integrates the atmospheric retrieval algorithm with the background emission algorithm in an iterative loop to refine the accuracy of atmospheric profiles. The atmosphere profiles are retrieved using optimal estimation techniques with sounding channels from 23GHz to 183GHz obtained from ATMS. Surface emissivity is computed by modeling ice sheet properties, including density, temperature, scattering characteristics, and liquid water content. These ice sheet properties are retrieved using Markov Chain Monte Carlo (MCMC) methods, with data from AMSR2 channels ranging from 6 GHz to 89 GHz. The coupling of the atmospheric retrieval and surface emission algorithms in an iterative loop allows for continual updates to the atmospheric temperature and humidity profiles throughout the iterations, which in turn influence subsequent surface retrievals. This process continues until convergence is reached. The novelty of this algorithm lies in the integration of surface and atmospheric retrievals, leading to enhanced overall accuracy. We validated our retrievals against radiosonde data.