Change in the Atlantic Atmosphere Ocean System: ChAAOS

该项目使用两种新的投入，以解决在全球大气-海洋耦合系统的背景下了解大西洋观测到的变异和变化的基本问题。利用分布式计算和新的伴随估计最近的海洋状态以及其中的不确定性，我们的目标是确定大气-海洋环流模型的自由运行版本，第一次，实际上再现了过去15年来大尺度气候系统的完整演变。这些模型的集合将提供对海洋状态最近变化的起源、性质和可预测性的独特见解，以及评估未来可预测性和大西洋经向翻转环流长期大幅变化风险的宝贵工具。耦合模式目前用于十年预测和长期预测的响应不断变化的边界条件通常依赖于模式气候学的模式异常与观测异常的比较，从一些估计的“真实的世界”的气候学。这是一个基本的问题，当（a）外部强迫的响应是不确定的，并可比的任何可预测性，可能会出现从初始状态或（B）系统包含显着的非线性，可能会影响任何预测。我们将使用一种全新的方法，直接从最先进的海洋分析中初始化耦合模型，使用耦合模型参数的直接扰动来找到跟踪过去15年真实的世界的模型版本。这一非常具有挑战性的目标是可行的，前所未有的计算资源，允许数千名成员的合奏与一个完全耦合的大气-海洋环流模型，由分布式计算提供。我们的方法是从ECCOc海洋分析中初始化数万到数十万个扰动版本的两个AOGCM，扰动以考虑观测和结构不确定性，根据ECCOc和其他分析之间的差异进行估计。我们将使用似然分析和重要性抽样的统计技术来确定参数/分析组合，这些组合允许模型在最初的六个月内继续“跟踪”分析，随后，随着我们对有希望的扰动的关注，直到整整15年。所使用的模型将是HadCM 3，这是已经建立了分布式计算应用程序，和一个新的模型的基础上耦合的HadAM 3 P模型的MITgcm中使用的ECCOc分析，利用信息的参数敏感性的两个模型，已经从过去的合奏实验和（在MITgcm的情况下）从模型伴随。成功的模式版本将在整个世纪（HadCM 3）或从1975年起（HadAM 3 P/MITgcm）免费运行，以评估它们在过去二十年中响应总外部强迫和人为强迫而产生的AMOC趋势范围。它们还将为VALOR联合体进行的集合预报实验提供一系列初始条件。除了其科学效益外，该项目还将提供一个重要的公众宣传机会，使参与者能够看到RAPID数据被直接用于解决明确和直接关注的问题。

This project uses two novel inputs to address the fundamental problem of understanding observed variability and change in the Atlantic Ocean in the context of the global coupled atmosphere-ocean system. Using a combination of large-ensemble perturbed-physics experiments made possible with distributed computing and new adjoint-based estimates of the recent ocean state together with uncertainty therein, we aim to identify free-running versions of an atmosphere-ocean general circulation model that, for the first time, actually reproduce the full evolution of the large-scale climate system over the past 15 years. The ensemble of such models will provide unique insights into the origins, nature and predictability of recent changes in ocean state, together with a valuable tool for assessing future predictability and the risk of substantial Atlantic Meridional Overturning Circulation changes in the longer term. Coupled models currently used both for decadal prediction and longer-term projections of the response to changing boundary conditions typically rely on the comparison of model anomalies from the model climatology with observed anomalies from some estimate of the 'real world' climatology. This is a fundamental problem when either (a) the response to external forcing is uncertain and comparable to any predictability that may arise from the initial state or (b) the system contains significant non-linearities that are likely to impact on any forecast. We will use an entirely novel approach to initialising coupled models directly from a state-of-the-art ocean analysis, using direct perturbation of coupled model parameters to find model-versions that track the real world over the past 15 years. This very challenging objective is made feasible by the unprecedented computing resources, allowing multi-thousand-member ensembles with a fully coupled atmosphere-ocean general circulation model, provided by distributed computing. Our approach will be to initialize tens to hundreds of thousands of perturbed versions of two AOGCMs from the ECCOc ocean analysis, perturbed to allow for both observational and structural uncertainty, estimated from the discrepancies between ECCOc and other analyses. We will use the statistical techniques of likelihood profiling and importance sampling to identify parameter/analysis combinations that allow models to continue to 'shadow' the analysis initially for six months and subsequently, as we home in on promising perturbations, out to the full 15 years. The models used will be HadCM3, which is already set up for distributed computing applications, and a new model based on coupling the HadAM3P model to the MITgcm used in the ECCOc analysis, exploiting information on the parameter-sensitivities of both models that is already available from past ensemble experiments and (in the case of the MITgcm) from the model adjoint. Successful model-versions will then be run free over the full 20th century (for HadCM3) or from 1975 onward (for HadAM3P/MITgcm) to assess the range of AMOC trends they generate in response to total external forcing and anthropogenic forcing only over the past two decades. They will also provide an range of initial conditions for an ensemble prediction experiment to be performed by the VALOR consortium. In addition to its scientific benefits, this project will provide a significant public outreach opportunity, allowing participants to see RAPID data being used directly to address problems of clear and immediate concern.