Collaborative Research: Predictability of the Physical Climate System

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。海洋-陆地-大气研究中心的研究将继续并扩大对变化气候中季节到年际可预测性的调查，重点是当前气候的可实现可预测性，包括全球变化-不断变化的温室气体浓度、气溶胶和土地利用-对相互作用的海洋-大气-陆地冰冻圈系统的影响。将进一步发展一个以信息论为基础的综合可预测性框架，以了解初始状态、高频和低频大气瞬变、气候系统组成部分的耦合和全球变化对可预测性的贡献。陆地表面的作用及其与大气和海洋的耦合、厄尔尼诺和南方涛动的可预测性以及对厄尔尼诺和南方涛动的反应、大西洋和印度洋的内在变化与外部强迫变化、全球水文循环、季风和北美干旱，和极端天气气候统计的可预报性，工作范围将扩大到年代际的可预报性研究。变化，以确定（1）是否在ENSO的概率分布的变化，或一般的季节性异常，是可预测的，在十年的提前时间，（2）的十年可预测性的限制，和（3）全球变化的影响。自然变率模式的可预测性如何随着全球变化而变化，这一问题对于提供关于未来气候的区域具体信息特别重要，而且在很大程度上取决于气候模型的模拟能力。长期目标是帮助建立动态年代际气候预测的科学基础，这项工作将利用由NSF、NOAA和NASA支持的国家气候模式，包括社区气候系统模式（CCSM）、气候预报系统（CFS）、戈达德地球观测系统（GEOS）模式和GFDL模式，努力确定各个模型的优点和缺点，并将它们最佳地结合起来（先验和后验）。在这些全球模型中，更高分辨率的前景至关重要。这项研究还将包括与CMMAP合作进行气候预测的过程分辨模式的初步努力，既为了可预测性/预测研究的目的，也为了评估全球气候模式中分辨云与参数化云的功效。模型的缺陷限制了量化可预测性和实现熟练的气候预测的能力。将最大限度地利用每个模型的个别优势和独特性，包括其在国家气候模拟议程中的利基，并在科学和操作层面上向每个模拟小组提供反馈。更广泛的影响虽然COLA的主要重点是基础研究，但它作为一个国家中心的建立，其战略伙伴关系和开放政策使COLA成为一个国家资源。美国国家科学基金会支持大气科学战略指导委员会（2007年）发现，COLA努力了解气候可预测性，在气候研究中发挥国家领导作用，并提供信息技术基础设施，是国家多机构全球气候可变性和变化目标以及更好的气候预报服务的重要贡献者。COLA活动通过出版物、教育、研讨会和讲习班、咨询和审查小组以及软件和信息服务在几个关键领域产生了更广泛的影响，包括：o对政府间气候变化计划第四次评估报告的贡献o通过与乔治梅森大学建立战略伙伴关系的博士课程以及高中实习计划教育下一代气候科学家o华盛顿参加的杰出科学讲座计划，哥伦比亚特区地区的科学家和学生，以及COLA-CPC联合“气候试验台（CPC）研讨会系列“o现场和外部研讨会，包括为斯隆基金会和国际理论物理中心举办的讲习班以及2008年5月世界气候预测模拟峰会o气候研究计划（WCRP），NSF，AGU，美国气候变化和可预测性计划（CLIIVAR），全球能量和水循环实验（GEWEX），NOAA应用研究中心（ARC）和气候试验台（CTB），CCSM，NSF STC大气过程多尺度模拟（CMMAP），国际理论物理中心（ICTP），分发天气和气候软件和信息，包括GrADS和GDS -由COLA完全支持的免费开源软件（www.iges.org/grads/grads.html）

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Research by the Center for Ocean-Land-Atmosphere Studies (COLA) will continue andexpand the investigation of seasonal-to-interannual predictability in a changing climate, focusing on realizable predictability of the current climate, including the influence of global change - changing greenhouse gas concentrations, aerosols and land use - on the interactive ocean-atmosphere-landcryosphere system. A comprehensive predictability framework, grounded in information theory, will be further developed to understand the contributions to predictability from the initial state, the high and low frequency atmospheric transients, the coupling of climate system components, and global change. The role of the land surface and its couplings to the atmosphere and oceans, the predictability of El Niño and the Southern Oscillation (ENSO) and the ENSO response, intrinsic vs. externally-forced variations in the Atlantic and Indian Oceans, the global hydrologic cycle, monsoons and North American drought, and the predictability of the statistics of weather and climate extremes will be specifically addressed.The scope of work will be extended to investigate the predictability of decadal variations to determine (1) whether or not shifts in the probability distribution of ENSO, or of seasonal anomalies in general, are predictable at decadal lead times, (2) the limits of decadal predictability, and (3) the effects of global change. The question of how the predictability of the natural modes of variability may change in conjunction with the global change is particularly relevant for providing regionally specific informationon future climate and depends critically on the simulation capabilities of climate models. The long-term goal will be to help establish the scientific foundations for dynamic decadal climate prediction.This work will employ the national climate models supported by NSF, NOAA, and NASA, including the Community Climate System Model (CCSM), the Climate Forecast System (CFS), the Goddard Earth Observing System (GEOS) model and the GFDL models, with efforts to identify the strengths and weaknesses of individual models and to optimally combine them (both a priori and a posteriori). The prospect of much higher resolutions in these global models is of critical importance. The research will also include initial efforts directed toward process-resolving models for climate prediction incollaboration with CMMAP, both for the purposes of predictability/prediction studies and to evaluate the efficacy of resolved vs. parameterized clouds in global climate models. The ways in which model deficiencies are limiting the ability to both quantify predictability and realize skillful climate predictions will be examined. Maximum advantage will be taken of each model's individual strengths and uniqueness, including its niche in the nation's climate modeling agenda, and feedback at scientific andoperational levels will be provided to each of the modeling groups.BROADER IMPACTWhile COLA's primary focus is basic research, its establishment as a national center, its strategic partnerships and its open policies make COLA a national resource. The Committee on Strategic Guidance for NSF's Support of the Atmospheric Sciences (2007) found that COLA's efforts to understand climate predictability, to provide national leadership in climate research, and to provide information technology infrastructure are important contributors to the nation's multi-agency goals for global climate variabilityand change and better climate forecast services. COLA activities have broader impacts beyond basic Research via publications, education, seminars and workshops, advisory and review panels, and software and information services making a difference in several key areas, including:o Contributions to the Intergovernmental Program on Climate Change Fourth Assessment Reporto Educating the next generation of climate scientists through a PhD program in strategic partnership with George Mason University as well as a high school internship programo The distinguished scientific lectures program that is well attended by Washington, DC-area scientists and students, and the joint COLA-CPC "Climate Test Bed (CPC) Seminar Series"o On-site and external workshops, including workshops organized for the Sloan Foundation and the International Centre for Theoretical Physics and the May 2008 World Modeling Summit for Climate Predictiono Active membership and leadership of national and international panels of the World Climate Research Program (WCRP), NSF, AGU, US CLImate VARiability and predictability program (CLIIVAR), the Global Energy and Water cycle EXperiment (GEWEX), NOAA Applied Research Centers (ARCs) and Climate Test Bed (CTB), the CCSM, the NSF STC Multi Scale Modeling of Atmospheric Processes (CMMAP), that International Center for Theoretical Physics (ICTP), and the national TeraGrido Distributing weather and climate software and information, including GrADS and GDS - free, open-source software that is fully supported by COLA (www.iges.org/grads/grads.html)