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IAP/LASG全球海-陆-气耦合系统模式的纬向平均大气气候态分析(英文)
引用本文:Zhang Tao,Guo Yufu,Wu Guoxiong. IAP/LASG全球海-陆-气耦合系统模式的纬向平均大气气候态分析(英文)[J]. 大气科学进展, 2002, 19(6): 1091-1102
作者姓名:Zhang Tao  Guo Yufu  Wu Guoxiong
作者单位:Zhang Tao Guo Yufu and Wu GuoxiongState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029
基金项目:This study was supported by the National Natural Science Foundation of China under Grant No. 49875012.
摘    要:分海洋和陆地两种情况来讨论IAP/LASG全球海-陆-气耦合系统模式(GOAL)四个版本的结果,并与观测资料进行对比分析。一些重要的大气变量包括表面空气温度,海平面气压和降水率用来评估GOALS模式模拟当代气候和气候变率的能力。总的来说,GOALS模式的四个版本都能够合理地再现观测到的平均气候态和季节变化的主要特征。同时评估也揭示了模式的一些缺陷。可以清楚地看到模拟的全球平均海平面气压的主要误差是在陆地上。陆地上表面空气温度模拟偏高主要是由于陆面过程的影响。值得注意的是降水率模拟偏低主要是在海洋上,而中高纬的陆地降水在北半球冬天却比观测偏高。 通过模式不同版本之间的相互比较研究,可以发现模式中太阳辐射日变化物理过程的引入明显地改善了表面空气温度的模拟,尤其是在中低纬度的陆地上。太阳辐射日变化的引入对热带陆地的降水和中高纬度的冬季降水也有较大改进。而且,由于使用了逐日通量距平交换方案(DFA),GOALS模式新版本模拟的海洋上的温度变率在中低纬度有了改善。 比较观测和模拟的年平均表面空气温度的标准差,可以发现GOALS模式四个版本都低估了海洋和陆地上的温度变率,文中还对影响观测和模拟温度变率差异的可能原因进行了探讨。

关 键 词:纬向平均气候态  温度变率  海气耦合

Analysis of the Zonal Mean Atmospheric Climate State in IAP/ LASG GOALS Model Simulations
Zhang Tao,Guo Yufu and Wu Guoxiong. Analysis of the Zonal Mean Atmospheric Climate State in IAP/ LASG GOALS Model Simulations[J]. Advances in Atmospheric Sciences, 2002, 19(6): 1091-1102
Authors:Zhang Tao  Guo Yufu  Wu Guoxiong
Affiliation:State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
Abstract:The results of four versions of IAP/LASG Global Ocean-Atmosphere-Land System Model (GOALS) are analyzed separately over the oceans and over continents, and compared with observed data.Some fundamental atmospheric variables including surface air temperature (SAT), sea level pressure (SLP) and precipitation are examined to evaluate the ability of the GOALS model to simulate the contemporary climate and climate variability. In general, all four versions of the GOALS model are capable of reproducing the main features of the mean state and seasonal variation of the observed climate with reasonable accuracy.The evaluation also reveals some weakness of the model. According to this study, we can clearly see that the essential discrepancy of global averaged SLP lies over the continents in boreal summer. The simulated higher SAT over land versus the observed is mainly due to the effect of the land surface process. It is worth noting the underestimation by simulated precipitation rates mostly appears over the oceans, yet over-land precipitation is higher in high and middle latitudes than the observed for the boreal winter.Through intercomparisons among different versions of the model, it can be clearly seen that the incorporation of the diurnal cycle of solar radiation apparently improves the simulation of SAT, especially in the low and middle latitudes over land. Also, the introduction of the diurnal cycle shows a great improvement in precipitation in tropical continents and wintertime precipitation in high and middle latitudes. Furthermore,based on the daily flux anomaly exchange scheme (DFA), the latest version of GOALS model simulated over-ocean temperature variability is improved in the low and middle latitudes.Having compared the standard deviation of the annual mean surface air temperature (SAT) simulated by the GOALS model to observation, it is found that all four versions of the GOALS model underestimate surface air temperature variability over both oceans and land relative to observations. Several factors that may contribute to these differences between simulated and observed temperature variability are identified.
Keywords:zonal mean climate state   temperature variability   air-sea coupling
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