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ECMWF - European Centre for Medium-Range Weather Forecasts | Bonn, Nordrhein Westfalen | Germany | 29 days ago
28 Mar 2024 Job Information Organisation/Company ECMWF - European Centre for Medium-Range Weather Forecasts Research Field Computer science Environmental science Environmental science Mathematics
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this project we apply a promising new automatic tuning algorithm to the parameters of the world-leading weather forecasting system, the IFS model of the European Centre for Medium Range Weather Forecasts (ECMWF
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About ECMWF The European Centre for Medium-Range Weather Forecasts (ECMWF) is a world-leader in weather and environmental forecasting. As an international organisation we serve our members and the
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Who can apply Applicants are invited to complete the online application form by clicking on the apply button above. At ECMWF, we consider an inclusive environment as key for our success. We
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institutions: ECMWF , Argonne National Laboratory (USA), CNRS (France), and University of Cambridge (United Kingdom). The primary objective of the project is to provide a fast computational framework for
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of improving weather forecasts via data assimilation. The project will be done in close collaboration with the European Centre for Medium-Range Forecasts (ECMWF) and the Met Office, applying the concepts in a
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scale-aware surface flux parameterizations through connections to ESA, KNMI and ECMWF. Requirements Specific Requirements Master's degree in Earth sciences, physics, applied mathematics, engineering
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-leading weather forecasting system, the IFS model of the European Centre for Medium Range Weather Forecasts (ECMWF). This model is part of the global climate model EC-Earth that we co-develop and use in our
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retrievals and boundary layer processes. Your research will aid the development of space-borne wind stress retrievals and scale-aware surface flux parameterizations through connections to ESA, KNMI and ECMWF
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current analyzes from the European center. This will involve adjusting the altitude domains and the intensity of the restoring force between the model itself, the ECMWF analysis data and the MSIS