Optimal ATMS Remapping Algorithm for Climate Research

In this paper, the Backus-Gilbert (B-G) method was used for the conversion from Advanced Technology Microwave Sounder (ATMS) FOVs to AMSU-A FOVs. This method provides not only an optimal combination of measurements within a specified region but also a quantitative measure of the tradeoff between resolution and noise. Based on a subpixel microwave antenna temperature simulation technique, ATMS observations at a specified FOV size with 1.1° sampling interval are simulated. Errors of remapping results were quantified by using simulated data sets and real AMSU observations. It is shown that the biases and/or standard deviations of brightness temperatures are significantly reduced by using the B-G generated remapping coefficients. For K/Ka bands, a resolution enhancement by the remap of ATMS observations introduces about 0.6 K increase in noise. For other bands, the channel sensitivity was improved for the remapped data.