| 1月和7月月平均气候的模拟与IAP GCM模式效能检证 |
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| 引用本文： | 薛 峰,曾庆存.1月和7月月平均气候的模拟与IAP GCM模式效能检证[J].气候与环境研究,1997,2(2):115-133. |
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| 作者姓名： | 薛 峰 曾庆存 |
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| 作者单位： | 中国科学院大气物理研究所 |
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| 摘 要： | 利用ＩＡＰＧＣＭ２５年的积分结果，系统分析了模式的１、７月月平均气候，并与观测资料、ＯＳＵＧＣＭ和其它大气环流模式的模拟结果作了比较，所比较的变量包括大气基本变量即海平面气压、表面气温和降水以及与流场、加热场和水汽场有关的诸多变量。结果表明，模式成功地模拟出各种大气变量的分布特征，大多数变量的模拟结果要优于ＯＳＵＧＣＭ，从而证实模式对１、７月月平均气候有较好的模拟能力，特别是由于ＩＡＰＧＣＭ与ＯＳＵＧＣＭ两模式物理过程十分相似，这一结果还进一步证实了ＩＡＰＧＣＭ动力框架和计算方案的优良性能。模拟的主要误差包括南极槽偏浅、冰雪区表面气温偏高以及主要降雨区雨量偏大等，同时还分析了模拟误差的可能原因，提出了改进模式的一些设想。此外，计算并比较分析了模式中动量、感热和水汽的经向输送。
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| 关 键 词： | 大气环流模式 模拟 观测 |
Simulation of January and July Mean Climate and Validation of IAP GCM |
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| Xue Fang and Zeng Qingcun.Simulation of January and July Mean Climate and Validation of IAP GCM[J].Climatic and Environmental Research,1997,2(2):115-133. |
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| Authors: | Xue Fang and Zeng Qingcun |
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| Abstract: | The January and July monthly mean climate of 25 years simulation resucts by the IAP GCM are analysed and compared with the observational data and the simulation results by the OSU GCM and many other GCMs. The compared atmospheric variables include sea-level pressure, surface air temperature and precipitation and many other variables related to wind, heating and moisture fields. It is shown that the IAP GCM can simulate the most of features of the large-scale distributions more accurately than the OSU GCM, and therefore, the model has a good ability to simulate the January and July climate. Particularly, due to similarities of physical processes between the two models, the above result further demonstrates the superiority of dynamical frame and computational scheme of the IAP GCM to those of the OSU GCM. On the other hand, the model simulates a more shallow Antarctic trough, a higher temperature in the region covered by ices and snows and a higher precipitation rate in some regions with precipitation centers. Besides, some ideas about the simulation discrepancies and improvements of the model are also mentioned. Finally, the meridional transports of zonal momentum, heat and water vapor in the model are analysed. |
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| Keywords: | general circulation model simulation observation |
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