首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Optimization of Background Information and Layer Thickness for Improved Accuracy of Water-Vapor Profile Retrieval from Ground-Based Microwave Radiometer Measurements at K-Band
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Optimization of Background Information and Layer Thickness for Improved Accuracy of Water-Vapor Profile Retrieval from Ground-Based Microwave Radiometer Measurements at K-Band

机译:优化背景信息和层厚度,以提高K波段地面微波辐射计测量水蒸气剖面的准确性

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摘要

Ground-based microwave radiometers operating at frequencies near the 22.235 GHz (K-band) water vapor absorption line have been used extensively for remote sensing of water vapor in the troposphere, both the integrated amount and its profile. This paper explores the potential to use ground-based, zenith-pointing K-band radiometer measurements along with optimized background data sets consisting of radiosonde profiles to detect dynamic changes and gradients in water vapor profiles. To explore this capability, the HUMidity EXperiment 2011 (HUMEX11) was conducted at the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Site near Lamont, OK, USA. This enables the choice of appropriate retrieval parameters to monitor temporal changes in atmospheric water vapor profiles. The results of this study illustrate that in a retrieval algorithm both the choice of the size of the background data set measured near the radiometer measurement time and the choice of atmospheric layer thickness affect the ability to remotely sense dynamic changes in water vapor. In general, it is found that background data sets of larger size provide better accuracy in a statistical sense but inhibit the ability to detect gradients.
机译:在22.235 GHz(K波段)水蒸气吸收线附近工作的地基微波辐射计已广泛用于对流层中水蒸气的遥感,无论是其总量还是其分布。本文探讨了使用地面,天顶指向的K波段辐射计测量值以及由探空仪剖面组成的优化背景数据集来检测水蒸气剖面中动态变化和梯度的潜力。为了探索这一功能,我们在美国能源部(DOE)的美国大俄克拉荷马州南部大平原(SGP)大气辐射测量(ARM)站点进行了2011年HUMidity试验(HUMEX11)。这使得可以选择适当的检索参数来监视大气水蒸气剖面的时间变化。这项研究的结果说明,在检索算法中,对辐射计测量时间附近测量的背景数据集大小的选择以及大气层厚度的选择均会影响遥感水蒸气动态变化的能力。通常,发现较大的背景数据集在统计意义上提供了更好的准确性,但抑制了检测梯度的能力。

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