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一种新的利用散射计(ERS1/2)数据反演有效波高和平均周期的模式被提出。通过俄罗斯学者利用浮标数据建立完全成长风浪条件下有效波高与风速之间的关系,与匹配浮标观测的有效波高数据对比,区分完全成长风浪、成长风浪和涌浪3种海况下的匹配数据;利用BP神经网络建立模式反演3种海况下的有效波高,均方根误差分别为0.53、0.57和0.86m,反演平均周期均方根误差分别为0.69、1.04和1.36s。这种反演方法在完全成长风浪海况下最好,依次是成长风浪和涌浪海况。该研究为散射计数据反演波浪参数提供了依据,使大面积反演波浪参数成为可能。
A new model of using ERS1 / 2 data to invert effective wave height and average period is proposed. By using the buoy data, Russian scholar established the relationship between effective wave height and wind speed under the condition of complete growth and the comparison of wind speed with the effective wave height data of the matched buoy observation to distinguish the matching data under the condition of complete growth, storm surge and surge. BP neural network model was used to validate the effective wave height under three sea states, with root mean square errors of 0.53, 0.57 and 0.86 m respectively. The root mean square error of the average period of inversion was 0.69, 1.04 and 1.36 s respectively. This inversion method is the best in the condition of complete growth of storms, followed by growth of storms and surging sea conditions. This study provides a basis for the inversion of wave parameters by scatterometer data and makes it possible to invert wave parameters over large areas.