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: 1354402
• 负责人: Yi Deng
• 金额: $ 31.62万
• 依托单位: Georgia Tech Research Corporation
• 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 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1354402&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.

耦合模型中气候反馈的表示仍然是预测由温室气体增加驱动的未来气候变化的最大不确定性来源。然而，反馈的符号和幅度很大程度上取决于背景气候的动力学和热力学特性。由于气候系统的内部变率和外强迫的波动，气候模型不可避免地会激发低频变率并产生大范围的背景气候。这些背景气候的反馈漂移，因此气候反馈的瞬态行为，对我们评估气候变化加速和气候突变的风险提出了重大挑战。描述模型中反馈过程的演变性质对于理解十年间气候预测的技能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（例如局部温度变化）和气候反馈瞬态行为之间建立联系的能力。该项目将使用一种新开发的技术，即大气-地表气候反馈响应耦合分析方法（CFRAM）来解决这个问题。该研究将利用现代再分析产品和耦合模型比对项目 (CMIP5) 的年代际预测实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型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（i）使用再分析数据量化各种反馈对地表气温（SAT）的年周期和年际至年代际变化的相对贡献； (ii)评估CMIP5模型在代表SAT年度周期和SAT年代际预测方面的保真度； (iii) 检查模型技能和模拟年代际气候预测能力的偏差，并确定对 SAT 年度周期中的系统误差和 SAT 年代际预测中的预测误差有重大影响的反馈过程。