Model Jobs in Glonn
- Gesponsert
){kind=logo}
Deep-convective wind gust forecasting and implications for wind energy applications
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)Baiern, Bavaria, Germany
German Speaking Marketing & Sales Consultant in Barcelona!
Cross Border TalentsBavaria, Germany
DO-254 FPGA Developer - (m / f / d)
Technology & StrategyBayernGermany, Bavaria
Change Manager (f / m / d)
W. L. Gore & AssociatesGermany, Bavaria, Putzbrunn- Gesponsert
GRC / ISMS (Senior) Consultant (m / w / d)
difesa GmbH & Co. KGGrafing bei München, Germany
Senior Director, Enterprise
DatabricksBavaria, Germany
Senior Electrical Enigneer - High Voltage
TE ConnectivityOTTOBRUNN, BY, DE
Sr. Field Service Technician
AmazonValley City
Senior Flight Control System Engineer
Maple AviationOttobrunn, Bavaria, Germany
Foster Care In Home Case Manager
State of North DakotaValley City- Gesponsert
Leitender Servicetechniker im Außendienst
ABBHolzkirchen, DE
HR Shared Service Center Professional Solutions DACH Manager (f / m / d)
EssilorLuxottica GroupGrasbrunn, DEDeep-convective wind gust forecasting and implications for wind energy applications
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)Baiern, Bavaria, GermanyDLR.de / jobs
PhD position
Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 11,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!
For our Institute of Atmospheric Physics in Oberpfaffenhofen near Munich we are looking for a
Meteorologist, Physicist or similar (f / m / x)
Deep-convective wind gust forecasting and implications for wind energy applications
What to expect :
Deep convective clouds (or thunderstorms) are associated with extreme weather events, including lightning, abrupt darkening, heavy precipitation, and strong wind ramps. The convectively-induced wind ramps, also known as "gust fronts", play a critical role in wind-energy applications, particularly in the context of wind turbine performance and longevity. Convective cold pools, which form when cold, denser air produced within thunderstorms spreads out near the surface, can produce strong, local changes in wind speed and direction (the gust front) over short time scales, presenting both opportunities and challenges for turbines and the energy sector. From a power output perspective, gust fronts are associated initially with temporarily increased wind speeds, affecting turbine power generation impacted by these weather events.
Therefore, the ability to accurately predict gust fronts is vital for maximizing the efficiency and safety of wind energy production. However, the short-term prediction of small-scale convective gusts is difficult for operational numerical weather models which have coarse spatiotemporal resolution. Nowcasting, which provides short-term, localized weather predictions from remote-sensing observations, can help wind farm operators anticipate the onset of gust fronts and adjust turbine operations accordingly.
The objective of this PhD thesis is the development of an accurate, robust and physically consistent short-term forecasting tool for boundary-layer gust front events induced by deep moist convection. The focus will be on the recently built state-of-the-art research wind park located in Krummendeich, northern Germany (windenergy-researchfarm.com). The extensive observational network at the wind park provides an excellent opportunity for testing and validating nowcasting models. The project will build on existing tools and longstanding experience at DLR. The model building will benefit from related concepts investigated in ongoing and parallel PhD projects and will exploit synergies. In addition to thorough validation of the model, case studies in wind energy demonstrators are an integral part of this project.
What we expect from you :
- completed university degree in physics or meteorology (diploma / Master) or comparable subject
- good knowledge in atmospheric physics and / or statistical physics
- good knowledge in programming, ideally in Python
- initial experience with machine learning and numerical modelling is a bonus
- knowledge in (passive) remote sensing and statistical data analyses are a plus
- very good spoken and written English
- high level of independence and team spirit
What we offer :
DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.
Further information :
Starting date : immediately
Duration of contract : 3 years
Type of employment : Part-time
Remuneration : up to German TVöD 13
Vacancy-ID : 98728
Contact :
Dr. Gerard Kilroy, Institut für Physik der Atmosphäre
Tel. : +49-8153-28-4780
Dr. Tobias Bölle, Institut für Physik der Atmosphäre
Tel. : +49-8153-28-1815