Collaborative Research: Understanding Climate Feedbacks and 3-D Global Warming Patterns in Global General Circulation Climate Models

合作研究：了解全球环流气候模型中的气候反馈和 3-D 全球变暖模式

• 批准号: 0832915
• 负责人: Guang Zhang
• 金额: $ 23.15万
• 依托单位: University of California-San Diego Scripps Inst of Oceanography
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-11-01 至 2012-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0832915&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Climate; Feedbacks

The lead Principal Investigator (PI) has successfully developed a new analysis framework to diagnose climate feedbacks for global warming studies. The new framework, referred to as the climate feedback response analysis method (CFRAM), differs from existing approaches in that it allows one to determine linearly the partial temperature changes due to external forcing and due to individual feedback processes or agents such as clouds, water vapor, and vertical and horizontal energy transport. These partial temperature changes are addable and their sum gives the total temperature change. The PIs will apply the CFRAM for analyzing and understanding spatial warming patterns of the surface and the atmospheric temperatures in response to anthropogenic greenhouse gases using outputs from an idealized global climate model (GCM) and the fully coupled National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) climate simulations, as well as the existing Intergovernmental Panel on Climate Change (IPCC)-Assessment Report 4 (AR4) GCM climate simulations. The PIs will also compare the new feedback analysis with an existing technique. This will help to shed light on the sources of the large inter-model spread of climate sensitivity derived from IPCC-AR4 climate simulations. Coupled model integrations using CCSM3 with an improved convective parameterization will also be analyzed to explore the dependency of climate feedbacks and sensitivities to model physical parameterizations. The main objectives of the research are: 1) To explore the feasibility of applying the CFRAM to isolating individual contributions to the total temperature change from the external forcing and various physical feedback processes in the context of coupled GCMs with full physical parameterizations. 2) To shed light on the dynamical/thermodynamic origins of the warming pattern asymmetries between (a) surface and atmospheric temperatures, (b) low and high latitudes, and (c) land and ocean. 3) To identify the contributions to the inter-model spread of the global warming and its spatial pattern due to the inter-model spreads of the 3-D structure of the external forcing, water vapor feedback, cloud feedback, surface albedo feedback, and surface turbulent sensible and latent heat flux feedbacks using the outputs from IPCC-AR4 climate simulations. The research aims to understand fundamental issues in global climate warming due to increases in anthropogenic greenhouse gases and feedback processes in the climate system. Broader impacts of this research include better quantification of the role of each feedback process in climate change and a more quantitative understanding of global warming spatial patterns. Graduate students and postdoctoral researchers will also be educated and trained in climate change science.

首席研究员 (PI) 成功开发了一个新的分析框架来诊断全球变暖研究的气候反馈。新框架被称为气候反馈响应分析方法（CFRAM），与现有方法的不同之处在于，它允许人们线性地确定由于外部强迫以及由于云、水等个体反馈过程或因素引起的部分温度变化。蒸气、垂直和水平能量传输。这些部分温度变化是可相加的，它们的总和给出了总温度变化。 PI 将利用理想化全球气候模型 (GCM) 和完全耦合的国家大气研究中心 (NCAR) 社区的输出，应用 CFRAM 来分析和理解地表空间变暖模式和大气温度对人为温室气体的响应气候系统模型 3 (CCSM3) 气候模拟，以及现有的政府间气候变化专门委员会 (IPCC)-评估报告 4 (AR4) GCM 气候模拟。 PI 还将新的反馈分析与现有技术进行比较。这将有助于揭示IPCC-AR4气候模拟得出的气候敏感性模型间大范围传播的根源。还将分析使用 CCSM3 和改进的对流参数化的耦合模型集成，以探索气候反馈和敏感性对模型物理参数化的依赖性。研究的主要目标是： 1) 探索在具有完整物理参数化的耦合 GCM 的背景下，应用 CFRAM 来隔离外部强迫和各种物理反馈过程对总温度变化的个体贡献的可行性。 2）阐明（a）地表温度和大气温度、（b）低纬度和高纬度以及（c）陆地和海洋之间变暖模式不对称的动力/热力学起源。 3) 确定由于外部强迫、水汽反馈、云反馈、表面反照率反馈和3D结构的模型间扩散对全球变暖及其空间格局的模型间扩散的贡献使用 IPCC-AR4 气候模拟的输出进行表面湍流感热和潜热通量反馈。该研究旨在了解由于人为温室气体增加和气候系统反馈过程导致的全球气候变暖的基本问题。这项研究的更广泛影响包括更好地量化每个反馈过程在气候变化中的作用以及更定量地了解全球变暖的空间模式。研究生和博士后研究人员也将接受气候变化科学方面的教育和培训。