摘要:采用20世纪再分析版本2c数据集的云水量逐月再分析数据，通过数理统计方法，分析了1960～2014年全球、海洋和陆地上空云水量的分布和变化特征及其与水汽通量的关系。结果表明：1）全球云水量空间分布不均，海洋高于陆地且比例约为4﹕3，中低纬海洋、陆地上空云水量变化趋势分别为0.07 g m?2 (10 a)?1和?0.04 g m?2 (10 a)?1，季节性差异主要体现于夏季在热带辐合带和南半球海洋高，冬季在北半球海洋和南半球陆地高。2）对比六大洲发现，云水量最高的南美洲有最快增加趋势，为0.46 g m?2 (10 a)?1，同时云水量最低的非洲有最快降低趋势，为?0.59 g m?2 (10 a)?1。3）中低层整层水汽通量散度场的辐合、辐散区和云水量的高、低值区相对应，云水量与水汽通量散度变化呈负相关（相关系数为?0.44），负相关关系在赤道附近的低纬地区显著。本文揭示了在全球变暖背景下，大气中云水量分布和变化的时空格局，为模式参数化和未来气候预估提供参考。
关键词:云水量/
水汽通量/
水汽通量散度/
分布特征/
变化趋势
Abstract:Based on the monthly cloud water content of the 20th-century reanalysis version 2c dataset, mathematical-statistical methods are employed to analyze the distribution and variation characteristics of the global cloud water content, including oceans and land from 1960 to 2014, and their relationships with water vapor flux. Results show that: 1) The global cloud water content is unevenly distributed spatially, with the oceans having a higher content than the land at a ratio of approximately 4﹕3. Variations in the trend of cloud water content over the middle and low latitude oceans and land are approximately 0.07 g m?2 (10 a)?1 and ?0.04 g m?2 (10 a)?1, respectively. Seasonal differences are reflected mainly as high cloud water content in the Tropical Convergence Zone and the Southern Hemisphere oceans in summer, and the Northern Hemisphere oceans and the Southern Hemisphere land in winter. 2) South America, with the highest cloud water content, has the fastest increasing trend of 0.46 g m?2 (10 a)?1 whereas Africa, with the lowest cloud water content, has the fastest decreasing trend of ?0.59 g m?2 (10 a)?1, as shown by a comparison of six continents. 3) The convergence and divergence zones of the water vapor flux divergence field in the middle and lower layers correspond to the high and low-value zones of cloud water content. The variation in the cloud water content and water vapor flux divergence presents a negative correlation, with a correlation coefficient of ?0.44. The negative correlation is significant at low latitudes near the equator. Herein, the temporal and spatial patterns of the distribution and change in the cloud water content under the background of global warming are revealed, providing a reference for model parameterization and future climate prediction.
Key words:Cloud water content/
Water vapor flux/
Divergence of water vapor flux/
Distribution characteristic/
Trend
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