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Macrophysical properties of continental cumulus clouds from active and passive remote sensing

机译:基于主动和被动遥感的大陆积云的宏观物理性质

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Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOV ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that the root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.
机译:云量是积云不可或缺的,广泛使用的宏观物理参数。通常将其定义为来自天顶指向的基于地面的主动和被动遥感的云量(CF)。但是,从具有非常窄的视场(FOV)的遥感数据中检索CF的常规方法可能无法代表周围区域。在这里,我们使用美国能源部(DOE)大气辐射测量(ARM)计划位于美国俄克拉荷马州南部大平原(SGP)站点收集的综合数据集来评估其代表性。对于我们的评估,重点是单层积云(2005-2016)的选定日期,我们包括窄FOV ARM活动遥感云位置(ARSCL)和大型FOV全天成像仪(TSI)云产品915 -MHz雷达风廓线仪(RWP)的风速和风向测量,以及Landsat和中分辨率成像光谱仪(MODIS)的高分辨率卫星图像。我们证明了15分钟的平均ARSCL云分数(CF)和15分钟的平均TSI分数天空覆盖(FSC)之间的均方根差(RMSD)很大(高达0.3)。我们还将讨论云的水平分布如何使用新的均匀性度量来修改获得的大RMSD。后者利用以高时间分辨率(30秒采样)获得的100°FOV TSI图像上FSC的空间分布。我们证明了FSC空间分布更均匀的情况表明,窄FOV CF和大FOV FSC之间具有更好的一致性,从而将RMSD降低了2倍。

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