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- W2772003292 abstract "In typhoon conditions, air-sea interactions are fierce, the wind speeds are quite high and usually tangled with complex rains. Under such circumstances, the combined observations of scatterometer and radiometer would be able to provide good information although traditional wind filed retrieving methods for them, i.e. MLE based on GMF (Geographical Modelling Function) for scatterometer and RTM(Radiative Transfer Method) which are originated from low or median wind conditions will not be applicable. In this paper, a neural network was employed to combine the observations of the two sensors onboard HY-2A satellite: radiometer (HRAD) and scatterometer (HSCAT) to achieve wind speed retrieving under typhoon conditions. The network was trained by GRAPS (global/regional assimilation and prediction system) data used as true values of wind speeds in typhoons. The established network was verified by data excluded from training data set. Results show that the wind speeds obtained from the network are better than the products of HY-2A compared to GRAPS data. The research of this paper has provided a clue of retrieving typhoon wind speeds for HY-2A products and for the data processing of coming HY satellite series, though further work on wind direction obtain, data comparison between different kinds of assimilation and perdition systems and the test of this method on other scatterometer and radiometer data are to be done in the near future." @default.
- W2772003292 created "2017-12-22" @default.
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- W2772003292 date "2017-07-01" @default.
- W2772003292 modified "2023-09-23" @default.
- W2772003292 title "Wind speed retrieving for combined observations of scatterometer and radiometer onboard HY-2A for typhoons using neural network" @default.
- W2772003292 cites W2034630107 @default.
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- W2772003292 doi "https://doi.org/10.1109/igarss.2017.8127415" @default.
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