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Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction

logo_demeter.png Project type: European project
Funding institution: European Union
Program: 5th European FP
Period: April 2000 - September 2003
Status: Finished
Web: http://www.ecmwf.int/research/demeter/

Seven comprehensive European global coupled atmosphere-ocean models will be run in a seasonal forecast experiment. The use of a multi-model ensemble system allows for uncertainties in model formulation to be included in the estimation of seasonal forecast probabilities. Based on evidence from the earlier Fourth Framework project PROVOST, it is believed that such a multi-model system will produce the most reliable seasonal climate forecasts possible. The DEMETER system will be fully tested on past cases using the ERA-40 database for initial and validation data.

An extensive set of 6-monthly hindcast ensemble integrations will be generated using the DEMETER system. These will be run four times a year over a period of about 40 years. Each model will produce nine members of the multi-model ensemble. Output from the individual members of the multi-model ensemble will be linked with tropical disease prediction models and European crop-yield models. Sensitivity and downscaling studies will also be undertaken.

In order to combine ensemble members from models with different systematic-error characteristics, it is desirable to apply a model correction technique to each individual-model ensemble. Datasets containing corrected multi-model ensembles will be produced. The sensitivity of the coupled-model simulations to the inclusion of satellite altimeter data, to changes in the model parametrizations, and to the use of persisted sea surface temperature anomalies will be investigated. The feasibility of applying the DEMETER output to scales smaller than can be resolved by the global models will also be assessed.

Selected variables from the project are available online in order to make them available to the world scientific community.