Collaborative Research: EaSM 2: Stochastic Simulation and Decadal Prediction of Large-Scale Climate

在这一项目下，将在观测和模拟地球气候的最新大气环流模型中研究大尺度低频模式。该项目将建立在以前的NSF和DOE资助的LFM工作的基础上，这些LFM是由大西洋和太平洋地区的海洋风驱动和翻转环流以及它们与大气和热带气候变化的相互作用引起的。该项目将侧重于：（a）增进目前对低尺度模式及其相互作用的了解;（B）发展、修订和检验基于这些模式的概率性十年期预测的统计方法;（c）利用这些十年期预测与观测和大气环流模式模拟相结合，深入了解十年期和更长时间尺度上气候变化和气候变率的动力学原因。该项目将继续利用先进的数据自适应谱方法，从最近两个国际气候相互比较模拟项目的观测和模拟中确定大西洋和太平洋的十年模态。这些方法将包括多通道奇异谱分析（MSSA），以及谐波Koopman分析（HKA），沿着基于经验模型简化（EMR）的随机建模。研究人员将进一步应用新方法研究加州大学洛杉矶分校和西弗吉尼亚大学开发的同步混沌振荡器，以进一步了解太平洋内以及大西洋和太平洋之间的十年尺度遥相关，以及它们与厄尔尼诺-南方涛动（ENSO）的关系。使用在项目的第一部分中研究的LFM，研究人员将检查它们的年代际可预测性，并评估我们基于EMR，MSSA和HKA的新的经验预测模型所做的回顾性年代际预测的技巧。这些经验预测将与IPCC第五次评估报告中的初始气候预测进行比较。这种比较将有助于量化潜在的技能，由于内在的十年模态及其与ENSO的相互作用，以及与气候变化。这些活动的结合将产生先进的随机模拟工具，用于根据观测数据和近期气候变化和气候变异性中最可靠和最可预测的要素，该项目的智力价值在于开发用于气候预测和动力气候验证的通用统计工具和方法模型该项目还将推进我们对突出的大尺度低频模式之间的全球耦合的理解。该项目的一个预期成果是改进对气候预测可靠性的估计，方法是开发和测试新的度量标准--与地球仪之间的耦合和同步有关--以验证气候模式的预测。该项目更广泛的影响在于解决一个对社会至关重要的问题，即，了解气候的变化和变化。该项目的研究人员致力于使他们的随机模拟容易地提供给气候社区。这项工作将促进加州大学洛杉矶分校和西弗吉尼亚大学之间的科学伙伴关系，并进一步在两个机构的气候动力学研究生课程的发展。主要调查员将通过专门的网站、参考出版物、研讨会和在国家和国际会议上的发言，广泛传播调查结果。

Under this project, large-scale, low-frequency modes (LFMs) will be studied in observations and simulations of state-of-the-art general circulation models (GCMs) of Earth's climate. This project will build on previous NSF- and DOE-funded work on LFMs arising from the ocean's wind-driven and overturning circulations in the Atlantic and Pacific sectors, as well as from their interactions with the atmosphere and tropical climate variability. This project will focus on: (a) improving current understanding of LFMs and interactions between them; (b) developing, revising and testing statistical methods for probabilistic decadal prediction based on these modes; and (c) using these decadal predictions in conjunction with observations and GCM simulations to gain insight into the dynamical causes of climate change and climate variability at decadal and longer time scales. This project will continue the identification of decadal modes in the Atlantic and Pacific, from both observations and the simulations from the two most recent international climate intercomparison modeling projects, using advanced, data-adaptive spectral methods. These methods will include multi-channel singular spectrum analysis (MSSA), as well as harmonic Koopman analysis (HKA), along with stochastic modeling based on empirical model reduction (EMR). The investigators will further apply novel methods for the study of synchronized chaotic oscillators developed at UCLA and UWM, to gain additional understanding of decadal-scale teleconnections within the Pacific and between the Atlantic and the Pacific, as well as their relationships with the El Nino-Southern Oscillation (ENSO). Using the LFMs studied in the first part of the project, the investigators will examine their decadal predictability and assess the skill of retrospective decadal forecasts made with our new empirical forecast models based on EMR, MSSA and HKA. These empirical forecasts will be compared against the initialized climate predictions being made as part of the IPCC's 5th Assessment Report. This comparison will help quantify potential skill due to intrinsic decadal modes and their interactions with ENSO, as well as with climate change. The combination of these activities will lead to advanced stochastic simulation tools for creating benchmark scenarios of future climate, based on a combination of observed data and the most robust and predictable elements of near-term climate change and climate variability, out to about 2050.The intellectual merit of this project is in developing versatile statistical tools and methodologies for climate prediction and the validation of dynamical climate models. The project will also advance our understanding of global coupling between prominent large-scale low-frequency modes. An expected outcome of the project is improved estimates of reliability of climate projections, by developing and testing novel metrics - associated with coupling and synchronization between multiple LFMs across the globe - for validating climate model predictions.The project's broader impacts lie in addressing a problem of utmost societal importance, i.e., understanding climate variability and change. The project's investigators are committed to making their stochastic simulations easily available to the climate community. This work will foster scientific partnerships between UCLA and UWM, and further the development of graduate curricula in climate dynamics at both institutions. The principal investigators will broadly disseminate the results by means of a dedicated web site, refereed publications, seminars and presentations at national and international meetings.