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项目编号9528183
Predictability of Short Term Climate Variations
Jagadish Shukla
主持机构George Mason University
开始日期1995-09-01
结束日期2000-08-31
资助经费1088378(USD)
项目类别Continuing Grant
资助机构US-NSF(美国国家科学基金会)
项目所属计划CLIMATE & LARGE-SCALE DYNAMICS, ,
语种英语
国家美国
英文简介Abstract ATM-9321354 Shukla, Jagadish Schneider, Edwin K. Kinter, James L. Straus, David M. George Mason University Title: Predictability and Variability of the Present Climate This research encompasses a number of closely related projects which are aimed at understanding the low frequency (monthly to decadal) variations of the coupled climate system consisting of the atmosphere, hydrosphere, land biosystems, oceans and ice, primarily in the present climatic regime. Goals include both the ability to simulate these low frequency variations with complex numerical models of the individual and coupled systems, and to estimate the degree to which these variations are predictable. The methods to be used will involve extensive experimentation with existing numerical models and schemes to couple them, and extensive diagnosis and analysis of observational data from both existing records and from the retrospective assimilation of atmospheric data planned by the major operational centers of the world for the near future. In addition to the intrinsic importance of understanding and predicting the low frequency variability of the climate system, this work will help to define the accuracy and coverage requirements for current and future climate observing systems in order to adequately monitor the current behavior of the climate system. 1. Predictability of the coupled ocean-land-atmosphere system. The predictability of this system on both the seasonal and interannual time scales will be systematically explored, the former by a large number of seasonal atmospheric simulations, and the latter from integrations of the fully coupled system. 2. Land-surface-climate interactions. The importance of vegetation change, albedo feedback and the global boundary conditions in the Sahel drought will be explored. The potential impacts of man's activity on climate through the (hypothetical) doubling of the world's deserts, global de forestati on and the desiccation of the Aral Sea region will be addressed. 3. Climate diagnostics. Diagnostics of the planned reassimilation of atmospheric data includes a detailed examination of the hydrological cycle, and global energy cycle and the critical tropical-extratropical interactions. These efforts will be aided by the availability of consistent estimates of the subtle quantities of divergence, specific humidity and diabetic heating. 4. Simulation of the present climate. To test the ability of numerical models to simulate the observed low frequency anomalies, the PIs plan an integration of the atmospheric model dor about 100 years using observed boundary conditions. Similarly, they will integrate the coupled climate system model for several hundred years in order to test the realism of its overall statistical behavior. 5. Climate observing system simulation. The PIs will estimate the sensitivity of the atmospheric circulation to many types of changes in the boundary conditions. They will "observe" numerically modelled climate system using methods similar to the current (and future) observing systems for the real climate to explore their sampling and accuracy characteristics systematically. This research is important because it seeks to enhance knowledge about climate processes and improvements in predicting climate variation and change. Part of this research is funded under the USGCRP CMAP project.
来源学科分类Geosciences
URLhttps://www.nsf.gov/awardsearch/showAward?AWD_ID=9528183
资源类型项目
条目标识符http://119.78.100.177/qdio/handle/2XILL650/342114
推荐引用方式
GB/T 7714
Jagadish Shukla.Predictability of Short Term Climate Variations.1995.
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