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PhD position (A6a)

Big ensembles to represent the evolution of forecast uncertainty

This PhD position contributes to project A6 "Representing the evolution of forecast uncertainty".

Primary supervisor: Prof. Dr. George Craig
Other project leaders: Dr. Christian Keil

The Theoretical Meteorology group at the Meteorological Institute (MIM) at the LMU Munich, offers a PhD position within Phase 2 of the collaborative research center "Waves to Weather". The Theoretical Meteorology group at MIM has a strong focus on predictability of weather and has established a leading international reputation in atmospheric predictability, stochastic parameterization and data assimilation. As one of Europe’s leading research universities, Ludwig-Maximilians-Universität (LMU) in Munich is committed to the highest international standards of excellence in research and teaching. Building on its more than 500-year-long tradition, it offers a broad spectrum that covers all areas of knowledge within its 18 Faculties, ranging from the humanities, law, economics and social sciences, to medicine and the natural sciences.

Forecasting convective precipitation remains one of the key challenges in weather forecasting. In the first few minutes, radar observations can be used to give very accurate predictions of individual storms, but after a few hours only a vague probabilistic forecast is possible. The aim of project A6 of W2W is to understand how predictability of convective precipitation decays with forecast lead time, and how it should be represented in a prediction system at different stages of the evolution. We will use very large ensembles of forecasts from a simple, computationally efficient model of the atmosphere to fully represent the nonlinear evolution of the probability density. A second doctoral student, also in project A6 at LMU, will perform parallel experiments with the numerical weather prediction system of the DWD.

It is not known how large an ensemble of forecasts is needed to represent their complex nonlinear evolution. By using a simple model that represents the key dynamical processes, we will be able to run ensembles of 10.000 members or more and accurately define the forecast probability distribution. The model and analysis software will be implemented in Python and use a variety of dynamical and statistical methods. The project is organized so that results can be compared with the full weather prediction model and the two PhD students can collaborate on the design of experiments.

The ideal candidate holds a MSc in Meteorology, Physics, or Mathematics and has already some experience in numerical modelling and/or skills to evaluate huge data sets. Besides very good knowledge of English, experience with Python, Unix, or other scientific programming tools would be an advantage.

The position is initially funded for 3 years with possible extension until June 2023 and should start as soon as possible. It is remunerated according to TV-L E13 (75%). Applicants are asked to specify their desired starting date and to give the contact details of two academic referees.

W2W features an innovative program for the development of early career researchers based on self-government. In addition to self-organized activities such as workshops, trainings and a guest program, the successful candidate will have the opportunity, if desired, to pursue an international research visit of at least one week. The consortium conducts an ambitious program to gradually enhance gender equality on all career levels within the academic fields
combined in W2W.

LMU is an equal opportunity employer. Women are especially encouraged to apply. Applicants with disabilities will be preferentially considered if equally qualified. The successful candidate will work in the city center of Munich and will have access to extensive training and career development activities offered by the LMU.

If you are interested, please apply online here!


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