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An Algorithm for Retrieving Vertical Wind Profiles from Satellite-Observed Winds over the Indian Ocean Using Complex EOF Analysis

机译:复杂EOF分析的印度洋卫星观测风垂直风廓线反演算法

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摘要

With an aim to exploit current satellite observations for determining vertical wind profiles, the authors have carried out a complex empirical orthogonal function (CEOF) analysis of a large number of radiosonde observations of wind fields over the Indian Ocean. This analysis suggests that the first two CEOFs explain more than 80% of the total variance. While the first principal component is highly correlated with the upper-ievel winds at 250 mb (r - 0.95), the second one is well correlated widi the 800-rnb winds (r = 0.82). This analysis leads to a retrieval algorithm that ensures the retrieval of vertical profiles of winds, using satellite-tracked cloud motion vector winds. Assuming that accurate measurements of wind are available at the above-mentioned levels, the rms error of retrieval for each component of wind is estimated to range between 2 and 6.5 m s~(-1) at different levels, which is much lower than the natural variance of wind at these levels. To construct a better visualization of retrieval, the authors have provided retrieved and true wind profiles side by side for three typical synoptic conditions.
机译:为了利用当前的卫星观测来确定垂直风廓线,作者对印度洋上风场的大量无线电探空仪观测进行了复杂的经验正交函数(CEOF)分析。该分析表明,前两个CEOF解释了总方差的80%以上。第一个主成分与上层风在250 mb(r-0.95)高度相关,而第二个主要成分与800 rnb风(r = 0.82)高度相关。该分析导致了一种检索算法,该算法使用卫星跟踪的云运动矢量风确保了风的垂直剖面的检索。假设可以在上述级别上获得准确的风速测量值,则在不同级别上风的每个分量的均方根估计误差估计在2到6.5 ms〜(-1)之间,这比自然值低得多。在这些水平上风的变化。为了构建更好的可视化可视化效果,作者针对三种典型的天气条件并排提供了真实风廓线。

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