Retrieving atmospheric temperature profiles from simulated DMSP sounder data with a neural network

Charles T. Butler; R. V.Z. Meredith

doi:10.1117/12.140062

16 September 1992 Retrieving atmospheric temperature profiles from simulated DMSP sounder data with a neural network

Charles T. Butler, R. V.Z. Meredith

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.140062
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

We have used neural networks to separately retrieve atmospheric temperature and moisture vertical profiles from simulated microwave sounder data. Backpropagation networks, implemented on a PC or Sun SPARCstation 2, were trained on data that simulated the multichannel output of either the SSM/T-1 temperature- or SSM/T-2 moisture-sensing radiometers on board current Air Force DMSP weather satellites. Ground-truth information was obtained from the Phillips data, a collection of approximately 1600 validated radio- and rocketsonde measurements. Radiometer outputs were simulated from the ground-truth data using the Air Force program RADTRAN. For each temperature or moisture profile in the Phillips data, RADTRAN generated a corresponding simulated sounder output. These simulated radiometer outputs were combined with the ground truth to produce training and testing sets for the neural networks. For both temperature and moisture, the neural method produces atmospheric profiles from unfamiliar data that are comparable to or better than those obtained with current operational methods. Networks, however, were able to retrieve profiles from a much broader range of geographic areas and seasons than standard methods, and to do this using less externally supplied geographic or season information.

Citation Download Citation

Charles T. Butler and R. V.Z. Meredith "Retrieving atmospheric temperature profiles from simulated DMSP sounder data with a neural network", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140062

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