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Verification of an algorithm correcting SeaWinds measurements for rain effects.

机译：验证用于校正SeaWinds测量以防雨影响的算法。

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Moderate to heavy rain over the oceans corrupts the normalized radar cross-section measurements (NRCS) given by a space-borne scatterometer. The rain-affected NRCS is currently flagged and excluded from the wind vector calculations over the ocean. RSL at Kansas has developed an algorithm to correct and utilize the rain flagged NRCS data. We test effectiveness of the algorithm and verify the extent to which the rain flagged data could be corrected and re-flag otherwise.; This thesis discusses in detail the problems encountered with the monthly-regression model, the switch over to the instantaneous-regression model, the apparent shift in the slices projected on the earth depending on the NEXRAD location from the footprints, selection of Z-R and k-R relations in calculating the volume scatter and attenuation caused by the rain, and the threshold for the correction. In essence, it describes the procedure for verifying the algorithm (developed earlier) correcting scatterometer measurements for the effects of rain and some results of the verification. (Abstract shortened by UMI.)
机译：海洋上的中到大雨会破坏星载散射仪给出的归一化雷达横截面测量值（NRCS）。目前，受雨水影响的NRCS被标记出来，并从海洋的风向矢量计算中排除。堪萨斯州的RSL开发了一种算法来校正和利用带有雨水标记的NRCS数据。我们测试了该算法的有效性，并验证了可以更正多雨标记数据的范围，否则将其重新标记。本文详细讨论了月回归模型遇到的问题，切换到瞬时回归模型，投影到地球上的切片的表观位移取决于足迹中的NEXRAD位置，ZR和kR关系的选择计算雨水引起的体积散布和衰减，以及校正的阈值。本质上，它描述了验证算法（较早开发）的过程，该算法针对雨水和一些验证结果校正了散射计测量值。 （摘要由UMI缩短。）

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