ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Archive > Volume 35 Issue 11 > 2009,35(11):137-142. DOI:10.7519/j.issn.1000-0526.2009.11.018 Prev Next
Retrieving Atmospheric Temperature Profiles Using Artificial Neural Network Approach
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Abstract:
Highspectralresolution Atmospheric Infrared Sounder (AIRS) data can be used to retrieve the small scale vertical structure of air temperature, which provid ed a more accurate and fine initial field for the numerical forecasting and the largescale weather analysis. In the previous studies, eigenvector regression algorithm in the IMAPP (International MODIS/AIRS Preprocessing Package) was ofte n used to process the data. Because of its simplicity, the inversion precision w as limited. Applying an artificial neural network to retrieve the clear sky atm ospheric temperature profiles from AIRS simulation radiation data and comparing with the eigenvector regression algorithm, the results indicate that the neural network consumed a same time as the eigenvector regression algorithm, but it red uced the atmospheric inversion error and made improvements in temperature measur ements at various levels.
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