2-year postdoc position on development and application of an atmospheric transport model for inverse modelling of greenhouse gas emissions in Dübendorf

Understanding and quantifying anthropogenic emissions of greenhouse gases (GHG) and their exchange with the biosphere is of great interest in the context of international climate treaties such as the Paris Agreement. Switzerland is one of only three countries worldwide that includes estimates of GHG emissions derived "top-down" from atmospheric measurements in its National Inventory Report complementing the officially reported numbers derived "bottom-up" from statistical data and emission factors. The quality of the top-down estimates critically depends on the atmospheric transport model that is needed to connect atmospheric observations with upstream sources. In a Swiss nationally funded project and in collaboration with the Goethe University of Frankfurt (GUF) and MeteoSwiss, Empa will further advance its modelling system taking advantage of the next-generation numerical weather prediction model ICON developed jointly by the German weather service and the Max Planck Institute for Meteorology in Hamburg.

Your tasks

• Contribute to the development of a new version of the Lagrangian atmospheric dispersion model FLEXPART coupled to ICON.
• Improve the representation of turbulent mixing in FLEXPART and enhance the consistency with turbulence as represented in ICON (in collaboration with GUF).
• Participate in an international model intercomparison exercise organized under the Integrated Global Greenhouse Gas Information Sytem (IG3IS) of the World Meteorological Organization.
• Participate in project meetings, manage Empa's tasks and deliverables in the project.

Required qualifications

• PhD degree in physics, atmospheric sciences, environmental engineering or a related discipline.
• A strong background in atmospheric modelling; experience in Lagrangian transport modelling is an advantage.
• Excellent programming skills (e.g., Fortran, Python); parallel programming skills (OpenMP, OpenACC) would be advantageous.
• Ability to communicate scientific results in peer-reviewed journals and conferences.
• Fluency in English is required; basic knowledge of German is desirable.