中国及其周边地区多种水凝物资料的气候态特征比较

对云的水凝物含量进行研究有利于认识云的辐射性质和强迫效应,以及改善模式的预报性能。利用目前几种较为常用的卫星观测资料（ISCCP、MODIS和CloudSat）和再分析资料（CFSR和ERA-Interim）,对中国及其周边地区的多种水凝物变量,包括积分的云水路径、液水路径和冰水路径,以及分层的液态水含量和冰水含量的气候态水平及垂直分布特征进行了比较研究。结果表明,在总的水凝物含量方面,无论是描述整个中国及其周边地区的水平分布特征和主要变化模态,还是不同海陆区域的月变化特点,MODIS、ERA和CFSR三种资料都显示出较高的一致性,而ISCCP的绝对数值和变化幅度与它们均存在一定差异。在液态水含量方面,无论是水平还是垂直分布,ERA-Interim都有最高的数值,作为观测数据的MODIS和ISCCP则显著偏低。对于冰水含量,不同资料间无论是水平和垂直分布形式还是具体数值都存在明显差异。通过分析不同水凝物资料间气候态分布的差异性特征,有利于认识目前常用的几种水凝物资料的“不确定性”程度,从而更好地估计云的辐射效应,以及理解其在气候变化中所扮演的角色。 

Comparison of climatological characteristics of several hydrometeors in China and the surrounding region

Hydrometeors and their characteristics, including cloud water path (CWP), liquid water path (LWP), ice water path (IWP), liquid water content (LWC), and ice water content (IWC), are important cloud physics parameters. Investigation of spatial-temporal variations of these hydrometeors is conducive to better understanding of the radiative property and forcing effects of clouds, which will be helpful for improvements of numerical prediction models. In this paper, the climatological characteristics of horizontal and vertical distributions of hydrometeors over China and its surrounding region are analyzed based on several popular satellite observation datasets from ISCCP, MODIS, CloudSat and two reanalysis datasets from CFSR and ERA-Interim. The results indicate that the spatial distribution, the first leading mode of the EOF and monthly average time series of CWP derived from MODIS, ERA and CFSR datasets are relatively consistent in different regions, but they are distinctly inconsistent with those from ISCCP regarding to both absolute value and amplitude variation. The LWP in ERA-Interim is the highest while that from satellite datasets of ISCCP and MODIS are much lower. In terms of IWP, the differences among various datasets are remarkable in horizontal and vertical distributions as well as absolute values. These results provide information about the "uncertainty" of these hydrometeors products, which in turn will be helpful for better estimation of cloud radiation effects and its importance in climate change study.