散射计资料的风场神经网络反演算法研究

NEURAL NETWORK WIND RETRIEVAL FROM SCATTEROMETER DATA

建立一种神经网络反演海面风场的算法。该算法以ERS_1/2散射计数据和欧洲中期预报分析风场(ECM-WF)的配准点数据作为神经网络训练和检验数据集。研究表明,该算法具有运行速度快和精度高等特点,反演的风速和风向与C波段第4模型(COMD 4)和ECMWF吻合较好。

This paper presents a neural network method for retrieving wind vectors from ERS - 1/2 scatterometer data, which resolves wind directional ambiguities for scatterometer derived winds by a circular median filter algo- rithm. Learning data set and test data set come from ERS - 1/2 scatterometer data collocated pairs with ECMWF vectors. A comparison with COMD4 and ECMWF wind vector shows that the result is good and the performance is quicker than any other methods. The good performance of the neural network method suggests the possibility of wind retrieval from ERS -1/2 scatterometer.