Scientific Collaborator to improve the ICON data assimilation system for high-resolution forecasts in the Alpine region
ETH Zurich is one of the world’s leading universities specialising in science and technology. It is renowned for its excellent education, its cutting-edge fundamental research, and its efforts to put new knowledge and innovations into practice.
The Center for Climate Systems Modeling (C2SM) at ETH and the Federal Institute of Meteorology and Climatology MeteoSwiss jointly develop and deploy the weather and climate model ICON. The resulting model data is analysed to address research questions in the weather and climate domain. We are seeking a Scientific Collaborator to improve the data assimilation system of the ICON model at very high resolution (80-100%).
As a scientific collaborator, you contribute to the improvement of the Numerical Weather Prediction (NWP) forecasts based on ICON, particularly its ensemble data assimilation system (KENDA). Your main responsibility will be the improvement of the existing data assimilation system at 1000 m grid spacing for operational weather forecasting. Additionally, you will contribute to the preparation and support of the data assimilation system at 500 m grid spacing for two international research collaborations: the GLORI-A Digital Twin project as well as the experimental NWP forecast support for the TEAMx Observational Campaign.
- Assessment of the quality of the KENDA-ICON system and improvement at 1000 m grid spacing.
- Improve the impact of observations in the KENDA data assimilation system.
- Evaluate and improve the representation of uncertainty at the convective scale.
- Evaluate the quality of the system using ensemble verification.
- Work on data assimilation tasks for GLORI-A and TEAMx.
- Setup of KENDA-ICON system at 500 m grid spacing.
- Re-assess quality and configuration using learnings and tools from the 1000 m tasks above.
- Support experimental runs for GLORI-A and TEAMx from a data assimilation perspective.
- Publish the work in peer-reviewed journal articles.
- You have an MSc in natural sciences or a related field and a PhD in atmospheric science, or equivalent experience.
- You have proven expertise in numerical weather prediction, and a keen interest in the area of data assimilation.
- You have advanced programming skills in at least one programming or scripting language, preferably in Fortran and Python.
- You are an open-minded personality with an ability to learn new skills rapidly. You have the ability to analyse and visualise scientific data and to solve complex problems. You have a collaborative attitude and enjoy working in a small team.
At C2SM and MeteoSwiss, we are committed to promoting flexible and family-friendly working models, and a healthy work-life balance is important to us. The position offers interesting and challenging tasks. You will have the opportunity to work with a cutting-edge operational weather prediction system within a highly motivated team. Your work will directly impact the future operational weather forecasts for Switzerland and bring value to weather related decisions in all sectors.
The position is limited to 3 years. It is available immediately and will remain open until filled. The place of work is at MeteoSwiss at Zurich-Airport. Applications including a letter of interest, a CV, and the names and contact information of 2-3 references will be given full consideration. Please note that we exclusively accept applications submitted through our online application portal. Further information on this position can be obtained from Dr. Marco Arpagaus (firstname.lastname@example.org; no applications). For further information on C2SM and the collaboration between ETH and MeteoSwiss, please contact the executive director of C2SM, Dr. Christina Schnadt Poberaj (email@example.com).
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