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Adjustment of visually observed ship winds (Beaufort winds) in ICOADS.

机译:调整ICOADS中肉眼观察到的船风(鲍福风)。

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摘要

The bias adjustment of visually estimated ship winds in the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is addressed through the comparison to the QuickSCAT scatterometer equivalent neutral winds. We assume that visually estimated winds and satellite scatterometer winds share similar characteristics, which are a function of stress rather than wind speed, and treat the estimated ship winds as equivalent neutral winds. Under such an assumption, we use statistical analyses to calculate the bias correction for estimated ship winds. Because observation practices vary by country and data provider, ICOADS identifies datasets by "deck" which is a number that allows for differentiating the source of the records (different deck numbers indicate different data collections provided to ICOADS, each which may contain one or more sources/countries). Three ICOADS decks 792, 926, and 992 contain the vast majority (∼90%) of collocated visually estimated ship winds covering the time period November 1999-October 2009. The Root-Mean-Square difference between these visually estimated ship winds and scatterometer winds are 3.0ms-1, 2.8ms-1 and 2.9ms-1 for each major deck respectively. Following the methodology of Freilich (1997) and Freilich and Dunbar (1999), we numerically show that for lower wind speeds (0ms-1-5ms-1 in this case) that the random error in the component of the visually estimated ship winds causes an artificial appearance of an overestimation relative to satellite scatterometer winds. We also extend this statistical artifact test to test higher wind speeds (12ms-1-18ms-1 in this case) through a Monte Carlo approach. An apparent slight drop of the conditional sample means relative to reference line is shown to be a statistical artifact. These artificial biases are properly accounted in this study. A new bias correction, LMS correction, is calculated and also compared to prior corrections such as Lindau (1995). This new bias correction is available for wind speeds ranging from 0ms-1 to 17ms-1, because there are too few spatial and temporal collocated matches at wind speed greater than 17ms-1. We are limited in our ability to perform the adjustments required for intercallibration because when comparing visual winds to scatterometer winds the necessary wind speed observations are rare and small in magnitude.
机译:通过与QuickSCAT散射仪等效中性风的比较,解决了国际海洋和大气综合数据集(ICOADS)中通过视觉估算的船舶风的偏差调整。我们假设视觉估计的风和卫星散射仪的风具有相似的特征,它们是应力而不是风速的函数,并将估计的船风视为等效的中性风。在这样的假设下,我们使用统计分析来计算估计的船风的偏差校正。由于观察方法因国家和数据提供者而异,因此ICOADS通过“ deck”来识别数据集,该数字允许区分记录的来源(不同的甲板编号表示提供给ICOADS的不同数据收集,每个数据收集可能包含一个或多个数据源/国家)。三个ICOADS甲板792、926和992包含大约1999年11月至2009年10月这段时间内并置的视觉估计船风的绝大部分(约90%)。这些视觉估计船风和散射仪风之间的均方根差每个主要平台分别为3.0ms-1、2.8ms-1和2.9ms-1。根据Freilich(1997)和Freilich and Dunbar(1999)的方法,我们通过数值方法表明,对于较低的风速(在这种情况下为0ms-1-5ms-1),视觉上估计的船舶风分量中的随机误差会导致相对于卫星散射仪风的高估的人为外观。我们还扩展了此统计伪像测试,以通过Monte Carlo方法测试更高的风速(在这种情况下为12ms-1-18ms-1)。条件样本均值相对于参考线的明显下降表明是统计伪像。这些人为偏差在本研究中得到了适当的解释。一个新的偏差校正,即LMS校正,被计算出来并与以前的校正如Lindau(1995)进行了比较。这种新的偏差校正可用于0ms-1至17ms-1的风速,因为风速大于17ms-1时空间和时间并置的匹配太少。我们进行嵌入校正所需的能力受到限制,因为在将可见风与散射仪风进行比较时,必要的风速观测值很少且幅度很小。

著录项

  • 作者

    Li, Keqiao.;

  • 作者单位

    The Florida State University.;

  • 授予单位 The Florida State University.;
  • 学科 Meteorology.;Physical oceanography.;Atmospheric sciences.
  • 学位 M.S.
  • 年度 2016
  • 页码 43 p.
  • 总页数 43
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:42:25

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