一次长江流域梅雨降水中三种云量计算方案的对比研究  

Comparison of the performance of three schemes in calculating the cloudiness during a Mei-yu rainfall process over the Yangtze River Basin

作　　者：崔文君[1,2] 智协飞[1] 朱寿鹏 周志敏[3] 王晓芳[3] 李红莉[3] 

机构地区：[1]南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心/东亚季风与区域气候变化科技创新团队,江苏南京210044 [2]美国北达科他大学大气科学系,北达科他州大福克斯市58202 [3]中国气象局武汉暴雨研究所,湖北武汉430205

出　　处：《大气科学学报》2016年第2期209-220,共12页Transactions of Atmospheric Sciences

基　　金：国家自然科学基金资助项目(41575104);国家重大基础科学研究计划(2012CB955200)项目;江苏高校优势学科建设工程资助项目(PAPD);江苏省“青蓝工程”

摘　　要：采用NCEP分析场,选取2010年梅雨期长江流域的一次降水过程,分别基于Slingo方案、NCAR方案和钱氏方案,利用相对湿度计算云量,并以LAPS(Local Analysis and Prediction System)系统输出的云量分析场作为观测值,分别在高层(400 h Pa)与低层(850 h Pa),从宏观比较与统计分析的角度,与计算结果进行云量大小与区域分布的对比分析。结果表明,三个云量计算方案对云量中心位置的把握均较为准确,但对云量值的计算存在大小不等的误差。NCAR方案计算结果和LAPS输出场最为吻合,能够体现出云量大值区,但区域一般偏大;Slingo方案相较NCAR方案来说略差,但也能较好地描述云带分布;此外,钱氏方案计算出的云量值始终偏小,但其能够较好地描述云带轮廓与云量的分布特征。综合对比结果,NCAR云量计算方案比其余两者更优,且在低层(850 h Pa)表现尤为明显。Cloud is an important internal factor of the climate system,especially in the earth—atmosphere system. The formation of clouds and their characteristics mainly result from both dynamic and thermodynamic processes of the surface and the atmosphere. An accurate grasp of the distribution of cloud and its variability can contribute greatly when attempting to assess the role of cloud in climate change. And related to this,a calculation scheme that is effective at describing cloudiness is a key part of improving the ability to simulate cloud in numerical models. In order to identify a satisfactory cloudiness calculation scheme,the present study employed NCEP reanalysis data to calculate cloudiness and relative humidity,based on three schemes（ Slingo,NCAR,and Qian）,during a Mei-yu rainfall process in the Yangtze River basin in 2010. Comparative analysis between the calculation results and Local Analysis and Prediction System（ LAPS） reanalysis data,considered as the cloud observation,was conducted in terms of cloud distribution and cloudiness values at upper and lower levels,represented by 400 h Pa and 850 h Pa,respectively. Based on the comparison results,as well as statistical analysis involving anomaly correlation coefficients（ ACCs） and RMSE,it was found that the three cloudiness calculation schemes all managed to successfully simulate the cloud central positions,but each had their own advantages and particular characteristics when it came to cloudiness values. The results calculated using the NCAR scheme matched the LAPS outputs very well at largevalue centers of cloud,but the regions containing these values were always too large. To a certain extent,although it was found that the Slingo scheme could also describe the cloud well,it showed a slightly lower capacity than the NCAR scheme in terms of its cloudiness calculation. Additionally,the Qian scheme demonstrated fairly limited ability to calculate the cloudiness values,but always presented the cloud profile and its distribution accurately.Based on t

关 键 词：相对湿度 云量计算 Slingo方案 NCAR方案 钱氏方案 

分 类 号：P426.5[天文地球—大气科学及气象学]