Collaborative Research: Understanding Transient Behavior of Climate Feedbacks and Its Role in Decadal Climate Variability and Prediction

合作研究：了解气候反馈的瞬态行为及其在十年间气候变化和预测中的作用

• 批准号: 1354834
• 负责人: Kevin Speer
• 金额: $ 27.87万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1354834&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Transient; Behavior

Representation of climate feedbacks in a coupled-model remains the largest source of uncertainty in its projection of future climate change driven by increasing greenhouse gases. The sign and magnitude of a feedback, however, depends critically on the dynamical and thermodynamical properties of a background climate. Due to internal variability of the climate system and fluctuations in external forcing, climate models inevitably excite low frequency variability and generate a wide range of background climates. The drift of feedbacks with these background climates, hence the transient behavior of climate feedbacks, presents a major challenge in our assessment of the risk of climate change acceleration and abrupt climate change. Delineating the evolving nature of feedback processes in a model is of particular importance for understanding the source of both the skill and bias in decadal climate prediction. However, the lack of a local measure of feedback strength has greatly limited our ability to make connections between actual model predictions (e.g., local temperature change) and transient behavior of climate feedbacks.This project will use a newly-developed technique, the coupled atmosphere-surface climate feedback-response analysis method (CFRAM) to tackle this problem. The study will take advantage of modern reanalysis products and the multi-model ensemble products from the decadal prediction experiments of the Coupled Model Intercomparison Project (CMIP5) to explore CFRAM's full potential in quantifying local and transient behavior of climate feedbacks and understanding the skill and bias of a model's ability to simulate decadal climate prediction. Specific research tasks that will be undertaken are (i) to quantify the relative contributions of various feedbacks to the annual cycle and interannual to decadal variations in surface air temperature (SAT) using reanalyses data; (ii)to evaluate the fidelity of CMIP5 models in representing the SAT annual cycle and decadal prediction of SAT; and (iii) to examine the attribution of models skills and biases in the ability to simulate decadal climate predictions and identify feedback processes that have major contributions to both systematic errors in the SAT annual cycle and forecast errors in decadal prediction of SAT.

在一个耦合模式中对气候反馈的描述仍然是其对温室气体增加所驱动的未来气候变化预测的最大不确定性来源。然而，反馈的符号和大小主要取决于背景气候的动力学和热力学性质。由于气候系统的内部变率和外部强迫的波动，气候模式不可避免地激发低频变率并产生广泛的背景气候。这些背景气候的反馈漂移，因此气候反馈的瞬态行为，提出了一个重大挑战，在我们的气候变化加速和气候突变的风险评估。描述模式中反馈过程的演变性质对于理解十年气候预测中技巧和偏差的来源特别重要。然而，缺乏反馈强度的局部测量极大地限制了我们在实际模型预测之间建立联系的能力（例如，本项目将使用一种新开发的技术，即大气-地面气候反馈-响应耦合分析方法来解决这一问题。这项研究将利用现代再分析产品和耦合模式相互比较项目（CMIP 5）的年代际预测试验的多模式集合产品，探索CFRAM在量化气候反馈的局部和瞬态行为以及了解模式模拟年代际气候预测能力的技能和偏差方面的全部潜力。将进行的具体研究任务是：（一）利用再分析数据量化各种反馈对地面气温年周期和年际至十年变化的相对贡献;（二）评价CMIP 5模式在代表地面气温年周期和地面气温十年预测方面的保真度;以及（iii）研究模式模拟年代际气候预测能力的技能和偏差的归因，并确定对SAT年周期中的系统误差和年代际预测中的预测误差有主要贡献的反馈过程的SAT。