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Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

机译:比较卫星对地面的自动和手动云覆盖观测结果–案例研究

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摘要

In this case study we compare cloud fractionalcover measured by radiometers on polar satellites (AVHRR)and on one geostationary satellite (SEVIRI) to ground-basedmanual (SYNOP) and automated observations by a cloudcamera (Hemispherical Sky Imager, HSI). These observationstook place in Hannover, Germany, and in Lauder, NewZealand, over time frames of 3 and 2 months, respectively.Daily mean comparisons between satellite derivations andthe ground-based HSI found the deviation to be 6 14%for AVHRR and 8 16% for SEVIRI, which can be consideredsatisfactory. AVHRR’s instantaneous differences aresmaller (2 22 %) than instantaneous SEVIRI cloud fractionestimates (8 29 %) when compared to HSI due to resolutionand scenery effect issues. All spaceborne observationsshow a very good skill in detecting completely overcast skies(cloud cover 6 oktas) with probabilities between 92 and94% and false alarm rates between 21 and 29% for AVHRRand SEVIRI in Hannover, Germany. In the case of a clearsky (cloud cover lower than 3 oktas) we find good skill withdetection probabilities between 72 and 76 %. We find poorskill, however, whenever broken clouds occur (probability ofdetection is 32% for AVHRR and 12% for SEVIRI in Hannover,Germany).In order to better understand these discrepancies we analyzethe influence of algorithm features on the satellite-baseddata. We find that the differences between SEVIRI and HSIcloud fractional cover (CFC) decrease (from a bias of 8 toalmost 0 %) with decreasing number of spatially averagedpixels and decreasing index which determines the cloud coveragein each “cloud-contaminated” pixel of the binary map.We conclude that window size and index need to be adjustedin order to improve instantaneous SEVIRI and AVHRR estimates.Due to its automated operation and its spatial, temporaland spectral resolution, we recommend as well that moreautomated ground-based instruments in the form of cloudcameras should be installed as they cover larger areas of thesky than other automated ground-based instruments. Thesecameras could be an essential supplement to SYNOP observationas they cover the same spectral wavelengths as thehuman eye.
机译:在本案例研究中,我们将通过辐射计在极地卫星(AVHRR)和对地静止卫星(SEVIRI)上测量的云分数覆盖与基于地面的手动云台(SYNOP)以及由云照相机(半球天空成像仪,HSI)进行的自动观测进行比较。这些观测值分别在3个月和2个月的时间范围内分别在德国汉诺威和新西兰劳德市进行。卫星衍生与地面HSI的日均比较发现,AVHRR的偏差为6 14%,地面HSI的偏差为8 16%对于SEVIRI,可以认为是令人满意的。与HSI相比,由于分辨率和景观效果问题,AVHRR的瞬时差异小于瞬时SEVIRI云分数估计值(8 29%)(2 22%)。所有太空观测都显示出一种非常好的技巧,可以检测德国汉诺威的AVHRR和SEVIRI,其完全阴暗的天空(云层6 oktas)的概率在92%至94%之间,错误警报率在21%至29%之间。在晴空条件下(云量低于3 oktas),我们发现其检测概率在72%到76%之间的良好技能。但是,每当出现碎云时,我们就会发现技能很差(在德国汉诺威,AVHRR的检测概率为32%,对于SEVIRI的检测概率为12%)。为了更好地理解这些差异,我们分析了算法功能对基于卫星的数据的影响。我们发现SEVIRI和HSIcloud分数覆盖率(CFC)之间的差异随着空间平均像素数量的减少和指数的降低而减小(从8到几乎0%的偏差),这决定了二元地图中每个“被云污染”像素的云覆盖率我们得出结论,为了改善SEVIRI和AVHRR的瞬时估计,需要调整窗口的大小和索引。由于其自动操作以及其空间,时间和光谱分辨率,我们还建议采用云相机形式的更自动化的地面仪器可以安装,因为它们比其他自动地面仪器覆盖更大的天空区域。这些相机可能是SYNOP观测的重要补充,因为它们涵盖了与人眼相同的光谱波长。

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