A GPS RO based ATMS/AMSU-A warm core retrieval method

What is it about?

A GPS RO based temperature retrieval algorithm is proposed in this study. A limb correction method are first implemented to both AMSU-A and ATMS measurements to remove the scan dependent patterns in observations. The beam width of ATMS is then manipulated with a Fourier transform based remapping algorithm to make ATMS observations 1) consistent with AMSU-A observations and 2) much less noisy. For better accuracies, GPS RO temperature profiles are then used to train regression coefficients and validations with samples independent from the training.

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Why is it important?

GPS RO has been known as an accurate source of temperature profiles in a global range. An ATMS/AMSU-A temperature retrieval algorithm trained and validated with GPS RO profiles are proposed in this study that is applicable to a global range. A remapping method is applied to ATMS observations to ensure consistencies between ATMS and AMSU-A and also less noisy ATMS observations. With AMSU-A on NOAA-15, -18, -19, Metop-A, and Metop-B and ATMS onboard Suomi-NPP and NOAA-20, temperature profiels throughout the globe, including those beneath non precipitating clouds, can be retrieved a dozen times daily. This is feasible to weather event like hurricanes demonstrated with Hurricane Matthew in the paper.

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