Modelling the ocean circulation with random numbers
Lead Research Organisation:
University of Oxford
Department Name: Oxford Physics
Abstract
The ocean contains a vigorous geostrophic mesoscale eddy field with spatial scales of approximately 100km at mid-latitudes, evolving over time scales from weeks to months. These eddies are important in establishing the ocean's circulation and tracer distributions in the ocean' interior. In the vicinity of the Gulf Stream and the Kuroshio's extensions and in the Antarctic Circumpolar Current (ACC), eddies are the primary means by which heat is transported poleward. However, to adequately simulate the mesoscale eddy field and associated turbulent cascades of tracers in numerical models, horizontal resolution of at least 10 km is necessary. It is therefore unlikely that climate models will systematically resolve ocean eddies and their effect needs to be parametrized. Large improvements have been made in the implementation of deterministic parameterizations of mesoscale eddies. Despite such improvements, the major source of model error remains the imperfect or missing closure of these subgrid scale processes.
In the current proposal, we aim to improve our knowledge of how ocean eddy variability influences the large-scale climate. We also aim to develop a novel stochastic closure as an alternative approach to the current deterministic parameterization. Such stochastic closure offers the advantage of an explicit representation of the inherent uncertainty associated the parametrized processes. The new stochastic parameterization of eddies will be tested on a state-of-the-art climate model and the impact on the mean climate, its variability and predictability will be investigated.
In the current proposal, we aim to improve our knowledge of how ocean eddy variability influences the large-scale climate. We also aim to develop a novel stochastic closure as an alternative approach to the current deterministic parameterization. Such stochastic closure offers the advantage of an explicit representation of the inherent uncertainty associated the parametrized processes. The new stochastic parameterization of eddies will be tested on a state-of-the-art climate model and the impact on the mean climate, its variability and predictability will be investigated.
Planned Impact
The proposed research forms a blue skies project, focussed on delivering an improvement of the representation of ocean mesoscale eddies in ocean climate models, by means of a stochastic parameterization. The proposal seeks to improve our knowledge and physical understanding of the dynamics of ocean eddies and how they feed back into the large-scale ocean circulation. The immediate end users engaged in ocean climate model development that would directly benefit from the project results are primarily within the academic community. Within the UK, this includes research groups investigating such processes at the University of Reading and Imperial. However, the results of the project are likely to have down-the-line benefits for non-academic users involved in the application of oceanic circulation modelling in climate prediction and operational weather forecasting. For example, the UK Met Office and ECMWF are naturally engaged in efforts to improve and integrate ocean mesoscale eddies into their forecasting systems. The outcomes of this research will provide indirect benefits to such groups, by guiding model development within the academic community that is later incorporated into forecasting models.
The PI, and the host department (Oxford's AOPP) for this proposal, are in an excellent position to deliver impact to operational end users. AOPP is at the core of the University's existing formal links to the European Centre for Medium Range Weather Forecasting, and also manages many strong collaborative links with the UK Met Office, which have recently been strengthened by the University's inclusion in the Met Office's Academic Partnership scheme. As a result of this formalisation of the University's existing relationship with the Met Office, the PI will able to better develop interaction with the Met Office's ocean modelling team, a key end-user of the research. To this end, I propose a deliver a workshop on stochastic parametrisation in climate models at Oxford during the 2nd year of the project, and will interact with ECMWF and the Met Office's ocean modelling teams throughout the project.
I also intend to deliver wider impact by utilizing Oxford's established media resources such as the Oxford Science Blog, Twitter, Facebook, i-Tunes U, and the Department of Physics' co-ordinated system of outreach activities, which provides the ideal mechanism for engagement of the general public with the scientific topics of the proposed project.
The PI, and the host department (Oxford's AOPP) for this proposal, are in an excellent position to deliver impact to operational end users. AOPP is at the core of the University's existing formal links to the European Centre for Medium Range Weather Forecasting, and also manages many strong collaborative links with the UK Met Office, which have recently been strengthened by the University's inclusion in the Met Office's Academic Partnership scheme. As a result of this formalisation of the University's existing relationship with the Met Office, the PI will able to better develop interaction with the Met Office's ocean modelling team, a key end-user of the research. To this end, I propose a deliver a workshop on stochastic parametrisation in climate models at Oxford during the 2nd year of the project, and will interact with ECMWF and the Met Office's ocean modelling teams throughout the project.
I also intend to deliver wider impact by utilizing Oxford's established media resources such as the Oxford Science Blog, Twitter, Facebook, i-Tunes U, and the Department of Physics' co-ordinated system of outreach activities, which provides the ideal mechanism for engagement of the general public with the scientific topics of the proposed project.
People |
ORCID iD |
Laure Zanna (Principal Investigator) | |
Miroslaw Andrejczuk (Researcher) |
Publications
Andrejczuk M
(2016)
Oceanic Stochastic Parameterizations in a Seasonal Forecast System
in Monthly Weather Review
Anstey J
(2017)
A deformation-based parametrization of ocean mesoscale eddy reynolds stresses
in Ocean Modelling
Bachman S
(2018)
The relationship between a deformation-based eddy parameterization and the LANS-a turbulence model
in Ocean Modelling
Grooms I
(2017)
A note on 'Toward a stochastic parameterization of ocean mesoscale eddies'
in Ocean Modelling
Huddart B
(2016)
Seasonal and decadal forecasts of Atlantic Sea surface temperatures using a linear inverse model
in Climate Dynamics
Juricke S
(2018)
Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty.
in Quarterly journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain)
Juricke S
(2017)
Stochastic Subgrid-Scale Ocean Mixing: Impacts on Low-Frequency Variability
in Journal of Climate
Kjellsson J
(2017)
The Impact of Horizontal Resolution on Energy Transfers in Global Ocean Models
in Fluids
Van Sebille E
(2018)
Lagrangian ocean analysis: Fundamentals and practices
in Ocean Modelling
Zanna L
(2018)
Uncertainty and scale interactions in ocean ensembles: From seasonal forecasts to multidecadal climate predictions
in Quarterly Journal of the Royal Meteorological Society
Description | A new way to interpret, describe and represent ocean turbulence in climate models |
Exploitation Route | The findings can improve climate models. The findings are now in testing phase of 2 ocean climate models. |
Sectors | Energy Environment |
URL | https://www2.physics.ox.ac.uk/research/climate-and-ocean-physics/research |
Description | EC-Earth Consortium |
Organisation | EC-Earth |
Country | Global |
Sector | Charity/Non Profit |
PI Contribution | I am officially part of the EC-Earth Consortium and we are developing a new suite of stochastic parametrizations. |
Collaborator Contribution | They provided the European Climate model used for IPCC. |
Impact | N/A |
Start Year | 2015 |
Description | NCAR |
Organisation | NCAR National Center for Atmospheric Research |
Country | United States |
Sector | Academic/University |
PI Contribution | Providing help and guidance to the project for implementing our results in a different model. |
Collaborator Contribution | Our partners are helping import our results to one of their ocean models. |
Impact | n/a |
Start Year | 2017 |