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Evaluating the quality of ground-based microwave radiometer measurements and retrievals using detrended fluctuation and spectral analysis methods

机译:使用去趋势波动和频谱分析方法评估地面微波辐射计的测量和检索质量

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摘要

Time series both of microwave radiometer brightness temperature measurements at 23.8 and 31.4 GHz and of retrievals of water vapor and liquid water path from these brightness temperatures are evaluated using the detrended fluctuation analysis method. As quantified by the parameter $\alpha$, this method (i) enables identification of the time scales over which noise dominates the time series and (ii) characterizes the temporal range of correlations in the time series. The more common spectral analysis method is also used to assess the data and its results are compared with those from detrended fluctuation analysis method. The assumption that measurements should have certain scaling properties allows the quality of the measurements to be characterized. The additional assumption that the scaling properties of the measurements of an atmospheric quantity are preserved in a useful retrieval provides a means for evaluating the retrieval itself. Applying these two assumptions to microwave radiometer measurements and retrievals demonstrates three points. First, the retrieved water vapor path during cloudy-sky periods can be dominated by noise on shorter than ~30~min time scales ($\alpha$-exponent = 0.1) and exhibits no scaling behavior at longer time scales. However, correlations in the brightness temperatures and liquid water path retrievals are found to be consistent with a power-law behavior for time scales up to 3 hr with an $\alpha$-exponent equal to approximately 0.3, as in other geophysical phenomena. Second, clear-sky, moist atmospheres show the expected scaling for both measurements and retrievals of the water vapor path. Third, during clear-sky, dry atmospheric days, instrument noise from the 31.4 GHz channel compromises the quality of the water vapor path retrieval.
机译:使用去趋势波动分析方法评估了微波辐射计在23.8 GHz和31.4 GHz的亮度温度测量的时间序列以及从这些亮度温度获取水蒸气和液体水路径的时间序列。如参数$ \ alpha $所量化的,此方法(i)能够识别噪声在时间序列中占主导地位的时间尺度,并且(ii)表征时间序列中相关性的时间范围。更常用的光谱分析方法还用于评估数据,并将其结果与去趋势波动分析方法的结果进行比较。测量应该具有一定的缩放属性的假设可以使测量的质量得到表征。在有用的检索中保留大气量测量的缩放比例属性的其他假设为评估检索本身提供了一种手段。将这两个假设应用到微波辐射计的测量和检索中,可以证明三点。首先,在多云的天空时期内,在短于约30分钟的时间尺度($α-指数= 0.1)上,噪声主导了水汽路径,而在较长的时间尺度上则没有尺度变化行为。但是,与其他地球物理现象一样,发现亮度温度和液态水路径反演的相关性与时间定律长达3小时且幂指数约为0.3的幂律行为一致。其次,天空晴朗,潮湿的大气层显示了水蒸气路径的测量和获取的预期比例。第三,在晴空干燥的日子里,来自31.4 GHz通道的仪器噪声会损害水蒸气路径检索的质量。

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