Predictability of Short Term Climate Variations

短期气候变化的可预测性

• 批准号: 9528183
• 负责人: Jagadish Shukla
• 金额: --
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-01 至 2000-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9528183&HistoricalAwards=false
• 关键词: Predictability; Short; Term; Climate; Variations

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.

ATM-9321354舒克拉，贾加迪什·施奈德，埃德温·K·金特，詹姆斯·L·施特劳斯，大卫·M·乔治·梅森大学标题：当前气候的可预测性和可变性这项研究包括一些密切相关的项目，目的是了解由大气、水圈、陆地生物系统、海洋和冰组成的耦合气候系统的低频(按月到年代际)变化，主要是在目前的气候制度下。目标既包括用单个系统和耦合系统的复杂数值模型模拟这些低频变化的能力，也包括估计这些变化可预测的程度。将使用的方法将涉及对现有数值模式和将它们结合起来的方案进行广泛的试验，以及对现有记录和世界主要业务中心计划在不久的将来计划的大气数据的回溯同化的观测数据进行广泛的诊断和分析。除了了解和预测气候系统的低频可变性的内在重要性外，这项工作还将有助于确定当前和未来气候观测系统的精度和覆盖范围要求，以便充分监测气候系统的当前行为。1.海-陆-气耦合系统的可预测性。系统地探索该系统在季节和年际时间尺度上的可预报性，前者通过大量的季节大气模拟，后者通过全耦合系统的积分。2.陆面气候相互作用。将探讨植被变化、反照率反馈和全球边界条件在萨赫勒干旱中的重要性。将讨论人类活动通过(假设)世界沙漠翻倍、全球森林退化和咸海地区干旱对气候的潜在影响。3.气候诊断。大气数据再利用计划的诊断包括详细检查水文循环、全球能量循环和关键的热带-温带相互作用。这些努力将得到对发散、特定湿度和糖尿病发热细微数量的一致估计。4.当前气候的模拟。为了测试数值模式模拟观测到的低频异常的能力，PI计划利用观测到的边界条件对大气模式进行大约100年的积分。同样，他们将在几百年内整合耦合气候系统模型，以测试其总体统计行为的真实性。5.气候观测系统仿真。指数将估计大气环流对边界条件多种类型变化的敏感度。他们将使用类似于当前(和未来)真实气候观测系统的方法来“观察”数值模拟的气候系统，以系统地探索其采样和精度特征。这项研究之所以重要，是因为它寻求加强对气候过程的了解，并改进对气候变异和变化的预测。这项研究的一部分是由USGCRP CMAP项目资助的。