Comparison of microwave satellite humidity data and radiosonde profiles : a case study

Comparison of microwave satellite humidity data and radiosonde profiles : a case study
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微波卫星湿度数据与无线电探空仪剖面的比较:案例研究

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发表时间:
2004
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通讯作者:
H. Dier
H. Dier
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作者:
S. Buehler;M. Kuvatov;V. John;U. Leiterer;H. Dier

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[1]本文记录了一个比较无线电探空仪湿度数据和先进微波探测仪(AMSU)卫星湿度数据的案例研究。这项研究有两个目标:第一,开发一种稳健的方法进行这种比较,第二,检查无线电探空仪数据、辐射传输模型和AMSU数据的质量和相互一致性。所使用的无线电探空仪数据是来自德国气象局林登贝格站的Vaisala Rs80数据,与标准数据处理相比,这些数据经过了几次修正。辐射传输模式是大气辐射传输模拟器(ARTS),AMSU的数据是2001年和2002年期间NOAA 15和16卫星的数据。比较是在辐射空间进行的,使用辐射传输模式从探空仪数据模拟AMSU辐射。总体上符合得很好,辐射偏差在1.5K以下,标准偏差在2K以下。比较中“噪声”的主要来源是10公里尺度上的大气不均匀。虽然在林登堡进行的无线电探空仪校正显著减少了模拟和测量的AMSU辐射之间的偏差,但辐射差异仍然存在斜率。调查了造成这种情况的可能原因。最有可能的是,无线电探空仪低估了极端干燥条件下的相对湿度,当真实值为2-4%RH时,显示为0%RH。
[1] This article documents a case study comparing radiosonde humidity data to Advanced Microwave Sounding Unit (AMSU) satellite humidity data. The study had two goals: first, to develop a robust method for such a comparison, and second, to check the quality and mutual consistency of radiosonde data, radiative transfer model, and AMSU data. The radiosonde data used are Vaisala RS80 data from the station Lindenberg of the German Weather Service (DWD), which have been subject to several corrections compared to the standard data processing. The radiative transfer model is the Atmospheric Radiative Transfer Simulator (ARTS), and the AMSU data are those of the satellites NOAA 15 and 16 for the time periods 2001 and 2002. The comparison was done in radiance space, using a radiative transfer model to simulate AMSU radiances from the radiosonde data. The overall agreement is very good, with radiance biases below 1.5 K and standard deviations below 2 K. The main source of “noise” in the comparison is atmospheric inhomogeneity on the 10-km scale. While the radiosonde correction performed at Lindenberg significantly reduces the bias between simulated and measured AMSU radiance, there still remains a slope in the radiance difference. Possible reasons for this were investigated. Most likely, the radiosondes underestimate the relative humidity under extremely dry conditions, showing 0 %RH when the true value is 2–4 %RH.