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Validation of Improved TAMANN Neural Network for Operational Satellite-Derived Rainfall Estimation in Africa
- Article from:
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Journal of Applied Meteorology and Climatology
- Article date:
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November 1, 2006
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Copyright informationCopyright American Meteorological Society Nov 2006. Provided by ProQuest LLC. (Hide copyright information)
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ABSTRACT
Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a ...
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