Research Scientist

vor 4 Wochen

Offenbach, Hessen, Deutschland EUMETSAT Vollzeit

EUMETSAT seeks a highly motivated Research Fellow to contribute to cutting-edge advancements in satellite data assimilation within our Numerical Weather Prediction (NWP) department.

As part of the Observation Modelling and Verification Section, you will collaborate with leading DWD scientists specializing in the integration of satellite data into operational NWP systems. Your research will focus on a critical aspect of data assimilation: addressing the impact of model field inhomogeneities within satellite footprints.

Your Mission:

  • Develop and refine a radiative transfer framework utilizing existing software (RTTOV, Radsim) and DWD operational and experimental NWP model fields. This will enable you to evaluate the influence of inhomogeneities on simulated radiances.
  • Generate comprehensive datasets of simulated radiances and related model parameters across diverse scenarios, including various frequencies (visible, infrared, microwave), satellite footprint sizes, and model resolutions.
  • Conduct rigorous statistical analyses to quantify the effects of scene inhomogeneity on radiances, as characterized by key model parameters.
  • Identify the most influential parameters for developing an AI-based parameterization suitable for integration into data assimilation systems.
  • Disseminate your findings through presentations at conferences, publications in scientific journals, and internal reports.

Your Profile:

We are seeking a talented individual with a strong academic background in Meteorology, Physics, Remote Sensing, or Mathematics. Prior research experience, ideally at the PhD level, is highly desirable.

A deep understanding of radiative transfer modeling, numerics and statistics, data assimilation, and numerical weather forecasting would be a significant advantage. Experience working with large datasets, processing meteorological satellite observations, and applying AI methods is also valuable.

Proficiency in scientific programming languages (Fortran, C/C++, Python) on Unix/Linux systems is essential. Excellent communication, teamwork, and analytical skills are crucial for success in this role.

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