AN IMPROVED ALGORITHM FOR SEA SURFACE WIND SPEED RETRIEVAL OF A CLASSIFIED NEURAL NETWORK
一种改进海面风速反演的分类神经网络方法

A new neural network algorithm is developed to improve the retrieval precision of the global sea surface wind speed from the SSM/I brightness data. At first, the data in different conditions, such as high-speed and low-speed winds, and clear and cloudy weather, are used to train different neural networks. Then these neural networks are used independently to retrieve the sea surface wind speed. Compared with the buoy wind, the RMS (root mean square) error of the retrieving is about 1.60m/s. This method reduces the bias resulted from the lack of quality data in high-speed wind, and cloudy weather on the neural network algorithm.