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首页> 外文期刊>Atmospheric Measurement Techniques >A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer
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A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

机译:一种使用地面微波辐射计的红外高温计测量的下降流红外辐射的云检测算法

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For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperature and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloudfree data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8 %, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.
机译:为了更好地利用地面微波辐射计,检测测量数据中的云存在很重要。在此,我们利用红外大气窗口区域中云的光学特性,介绍了一种简单而快速的云检测算法。新算法利用安装在微波辐射计顶部的红外辐射计测量的亮度温度(Tb)。两步算法由频谱测试和时间测试组成。首先将测得的Tb与通过经验公式获得的预测晴空Tb进行比较,该Tb是地面空气温度和水蒸气压力的函数。对于时间测试,在一分钟内测得的Tb的时间变化与动态阈值进行比较,该动态阈值代表晴空条件的变化。仅当光谱和时间测试均确认无云数据时,才将其指定为无云数据。总体而言,通过频谱测试可以成功检测到大多数厚而均匀的云,而通过时间测试可以检测到破碎和快速变化的云。通过与并置的云高仪数据(从2013年1月至2013年6月)进行比较,验证了该算法的正确性。总正确率约为88.3%,检测概率为90.8%,与以前的同类产品相当或更好方法。当新算法检测到云而云高仪未检测到云时,会出现三分之二的差异,从而导致不同的云基准高度的检测概率值不同,低,中和高云分别为93.8、90.3和82.8%。 。最后,由于光谱范围的特性,发现新算法对反演层的存在不敏感。

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