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Content archived on 2024-05-24

Mechanisms and predictability of decadal fluctuations in atlantic-european climate


Problems to be solved
There is a need of climate-sensitive business and governmental bodies for improved understanding and prediction of fluctuations over decades of Atlantic-European climate. Also, better quantification of "natural" climate variability over decades is needed in detection and attribution of anthropogenic climate change.
Scientific objectives and approach
The project aims to improve understanding, simulation and prediction of the decadal fluctuations that result from interactions between the ocean and atmosphere. These aims will be achieved through a coordinated programme of numerical experimentation, evaluation against observations, and development of prediction systems. The predictability of decade time scale fluctuations in climate will be quantified and work will be done with targeted user groups in the insurance, utilities and fisheries sectors to assess the potential benefits of decadal forecasts. Output from a series of multi-decadal ensemble integrations from four atmospheric GCM's forced with observed twentieth century Sea Surface Temperature (SST) and Sea Ice Extent (SIE) will be used to assess the potential predictability of decadal fluctuations in the North Atlantic Oscillation (NAO) and other facets of Atlantic-European climate. It will be investigated how the predictability of the atmospheric response to SST anomalies varies with season, atmospheric state and model and how the atmospheric response could feed back to force the ocean. Five ocean GCM's will be used for multidecadal ocean modelling. The models will be forced with observed atmospheric data (NCEP reanalyses), and the skill of the models to simulate major observed dynamic and thermodynamic decadal scale anomalies will be assessed in a common diagnostic framework. Particular emphasis will be given to oceanic regions that have been found in the atmospheric modelling above to significantly influence the atmosphere. The results of the various model runs will be used to assess sensitivity to model formulation and resolution. Based on the above results and by the analysis of multi-century control simulations with four coupled atmosphere-ocean GCM's mechanisms responsible for decadal fluctuations in climate will be clarified. Particular emphasis will be given to the role of tropical/extra-tropical interactions in the atmosphere and ocean, the role of Gulf Stream variability and the role of air-sea fluxes in the amplification or damping of SST anomalies. The coupled models will be used to perform ensembles of decadal predictions and model predictability will be evaluated using the spread of the trajectories of the ensemble members.
Expected impacts
The project will improve the European capability in decadal climate prediction and will furthermore link directly to potential users (e.g. from utilities, insurance, tourism and fisheries industries). Future decadal predictions could significantly benefit these economic sectors.
The main outcome of D-LAB is a software platform to implement the concept of "Virtual Laboratory" in any pre-existing technical/clinical environment. The main components of the platform are:
a - PROCESS EDITOR and WORKFLOW ENGINE, to create definitions of workflows/processes and to execute and process them
b - WEB SERVICES, to support the "workflow client" environment
c - ADMINISTRATION MODULE, to monitor processes running on a specific server
d - CENTRAL QUEUE MANAGER, to handle the exchange of messages between the D-LAB Server, the POCT's and the Information Systems
e - D-LAB BRIDGE, linking the Virtual Laboratory Information System of D-LAB to the other IS's installed in the HC Organisation
f - POCT MANAGER, for the management of the distributed testing equipments
g - D-LAB DATABASE, containing information on Patients/Contacts, Analysers, Panels and Tests, Maintenance, Quality Control

Call for proposal

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EU contribution
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Earley Gate 2, Whiteknights, Palmer Building
United Kingdom

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Total cost
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Participants (6)