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首页> 外文期刊>Journal of Climate >Statistical Analyses of Satellite Cloud Object Data from CERES. PartI: Methodology and Preliminary Results of the 1998 El Nino/2000 LaNina
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Statistical Analyses of Satellite Cloud Object Data from CERES. PartI: Methodology and Preliminary Results of the 1998 El Nino/2000 LaNina

机译:CERES的卫星云目标数据的统计分析。第一部分:1998年El Nino / 2000 LaNina的方法论和初步结果

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This study presents an objective classification methodology that uses Earth Observing System (EOS) satellite data to classify distinct 'cloud objects' defined by cloud-system types, sizes, geographic locations, and matched large-scale environments. This analysis method identifies a cloud object as a contiguous region of the earth with a single dominant cloud-system type. It determines the shape and size of the cloud object from the satellite data and the cloud-system selection criteria. The statistical properties of the identified cloud objects are analyzed in terms of probability density functions (PDFs) based upon the Clouds and the Earth's Radiant Energy System (CERES) Single Satellite Footprint (SSF) data. Four distinct types of oceanic cloud objects-tropical deep convection, boundary layer cumulus, transition stratocumulus, and solid stratus-are initially identified from the CERES data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite for this study. Preliminary results are presented from the analysis of the grand-mean PDFs of these four distinct types of cloud objects associated with the strong 1997/98 El Nino in March 1998 and the very weak 2000 La Nina in March 2000. A majority of the CERES footprint statistical characteristics of observed tropical deep convection are similar between the two periods in spite of the climatological contrast. There are, however, statistically significant differences in some cloud macrophysical properties such as the cloud-top height and cloud-top pressure and moderately significant differences in outgoing longwave radiation (OLR), cloud-top temperature, and ice diameter. The footprint statistical characteristics of the three observed boundary layer cloud-system types are distinctly different from one another in all cloud microphysical, macrophysical, optical properties, and radiative fluxes. The differences between the two periods are not significant for most cloud microphysical and optical properties and the top-of-the-atmosphere albedo, but are statistically significant for some cloud macrophysical properties and OLR. These characteristics of the grand-mean PDFs of cloud microphysical, macrophysical, and optical properties and radiative fluxes can be usefully compared with cloud model simulations. Furthermore, the proportion of different boundary layer cloud types is changed between the two periods in spite of small differences in their grand-mean statistical properties. An increase of the stratus population and a decrease of the cumulus population are evident in the El Nino period compared to the very weak La Nina period. The number of the largest tropical convective cloud objects is larger during the El Nino period, but the total number of tropical convective cloud objects is approximately the same in the two periods.
机译:这项研究提出了一种客观的分类方法,该方法使用地球观测系统(EOS)卫星数据对由云系统类型,大小,地理位置和匹配的大规模环境定义的不同“云对象”进行分类。这种分析方法将云对象标识为具有单一优势云系统类型的地球连续区域。它根据卫星数据和云系统选择标准确定云对象的形状和大小。根据基于云和地球辐射能系统(CERES)单卫星足迹(SSF)数据的概率密度函数(PDF),对识别出的云对象的统计属性进行分析。最初从热带雨量测量任务(TRMM)卫星收集的CERES数据中初步识别出四种不同类型的海洋云物体:热带深对流,边界层积云,过渡层积云和固体层。通过对这四种不同类型的云对象的均值PDF进行分析,得出了初步结果,这些云对象与1998年3月的强1997/98 El Nino和2000年3月的非常弱的2000 La Nina相关。大部分CERES足迹尽管有气候对比,但在两个时期之间观察到的热带深对流的统计特征相似。但是,某些云的宏观物理特性(如云顶高度和云顶压力)在统计上存在显着差异,而出射长波辐射(OLR),云顶温度和冰径也有中等显着差异。在所有云的微观物理,宏观物理,光学特性和辐射通量方面,三种观察到的边界层云系统类型的足迹统计特征彼此明显不同。这两个时期之间的差异对于大多数云的微观物理和光学特性以及大气顶反照率而言并不显着,但对某些云的宏观物理特性和OLR具有统计学意义。云微观物理,宏观物理,光学特性和辐射通量的平均数PDF的这些特征可以与云模型模拟进行比较。此外,尽管两个边界层云类型的均值统计特性差异很小,但它们在两个周期之间的比例却发生了变化。与极弱的拉尼娜时期相比,在厄尔尼诺时期明显增加了层数,而积云减少了。在厄尔尼诺时期,最大的热带对流云物体数量较大,但在两个时期内热带对流云物体的总数大致相同。

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