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- W2087365513 abstract "Artificial neural networks are used to retrieve vertical profiles of atmospheric temperature from simulated microwave radiometer data. The global and local retrieval algorithms are compared. The global retrieval experiments show that the overall root mean square error in the retrieved profiles of a test dataset is about 7% better than the overall error using a linear statistical retrieval, and the retrieval errors are about 0.5K better at 200and 250-hPa levels. The local experiments show that the differences between the results of neural network and linear statistical retrieval approaches are different from region to region but are not remarkable. In comparison with the global retrieval, the local retrieval is well." @default.
- W2087365513 created "2016-06-24" @default.
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- W2087365513 date "2005-01-01" @default.
- W2087365513 modified "2023-09-27" @default.
- W2087365513 title "Retrieving Atmospheric Temperature Profiles from Simulated Microwave Radiometer Data with Artificial Neural Networks" @default.
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- W2087365513 doi "https://doi.org/10.1142/9789812702869_0032" @default.
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