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Reference : UMR3589-JEAMAH1-002
Workplace : TOULOUSE
Date of publication : Thursday, March 26, 2020
Type of Contract : FTC Scientist
Contract Period : 8 months
Expected date of employment : 1 June 2020
Proportion of work : Full time
Remuneration : Between 2,648 and 3,938 € gross monthly salary according to experience
Desired level of education : PhD
Experience required : Indifferent
Use of wind radar (SCAT) and wave radar (SWIM) data from the CFOSAT mission for assimilation into the global numerical weather prediction model ARPEGE
The proposed activities will concern the following themes:
1) Comparison of the performance of wind data produced by the NSOAS with those produced by the Dutch meteorological service KNMI within the framework of the activities of the SAF (Satellite Application Facility) OSI (Ocean and Sea Ice) of the European space agency EUMETSAT (secondary task)
2) The analysis and the design of a synergy between the data from the wave radar SWIM characterizing the sea states (wave spectra) and the wind scatterometer SCAT. This activity could lead to a possible correction of measurement bias with possible impacts (by ocean basins) on their assimilation in the ARPEGE numerical forecasting model and on its forecasts (main task)
3) The drafting of a technical report describing the conclusions of the study, namely the contribution of data from the CFOSAT mission for numerical weather forecasting (main task)
The candidate must have a very good knowledge of advanced programming languages (FORTRAN, PYTHON, C ++) and of the Linux environment. He must have worked on the exploitation of large datasets. Previous background in one of the following fields: space remote sensing (notably of ocean surfaces), numerical modeling and data assimilation, would be an additional asset. The candidate must have a good knowledge of French and / or English both orally and in writing to communicate his results in the form of reports and presentations.
The activities will take place in the context of the use of the observations for improving the initial conditions of the global numerical weather prediction model of Météo-France (ARPEGE). The first wind dataset from the SCAT scatterometer of the CFOSAT mission have been recently acquired and compared with those from short-term forecasts of the ARPEGE model to improve their quality. Experiments with data assimilation in the ARPEGE model can this be implemented and exploited.
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