Retrieval of Atmospheric Temperature Profiles from AMSU-A Measurement Using a Neural Network Approach

Abstract Backpropagation neural networks are applied to retrieve atmospheric temperature profiles and tropopause variables from the NOAA-15 Advanced Microwave Sounding Unit-A (AMSU-A) measurement based on two different data sources. The first case uses direct acquisition of 15-channel AMSU-A data over the eastern United States and western Atlantic Ocean for the months of July 1998 and January 1999, and the second case uses recorded global AMSU-A data for several days of January 2000. The corresponding global analysis data from the National Centers for Environmental Prediction are employed to build the neural network training sets. The retrievals yield excellent results in the atmospheric temperature profiles from the surface to the 10-hPa pressure level. For the more generalized global data retrieval case, the root-mean-square (rms) deviation of temperature retrieval is 3.2°C at the surface, only 1.0° to 1.2°C in the midtroposphere, less than 1.5°C around the tropopause, and between 1.0° and 1.5°C in the ...

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