Change in the Atlantic Atmosphere Ocean System: ChAAOS

Lead Research Organisation: University of Oxford
Department Name: Oxford Physics


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.
Description Developing methods for constraining climate models using recent climate observations
Exploitation Route Now contributing to other RCUK funded projects
Sectors Environment

Description Research still in progress -- no tangible impact as yet
First Year Of Impact 2014
Sector Environment
Description Allen, M. R, Chapter 1 Framing and Context, SPECIAL REPORT: GLOBAL WARMING OF 1.5 ºC
Geographic Reach Multiple continents/international 
Policy Influence Type Membership of a guideline committee