Computational modeling for climate-resilient planning and design
This course is held in English
Computational models are an essential tool to understand, analyze and predict the local and regional climate and to facilitate climate change adaptation and climate-resilient planning and design. This seminar provides an overview of a variety of different models that are used to analyze the past, current and future state of the near-surface atmospheric conditions.
Teaching staff
The seminar will consider regional climate (RCM), urban canopy (UCM), building energy models (BEM), and cover approaches such as multi-scale and integrated models and tools, but focus on outdoor thermal comfort (OTC) modelling. One or two selected user-friendly models will be studied more intensively and will be applied for a test case.
After successfully participating in the course, the students will be able to describe different types of models ranging from micro- to regional scale and from statistical to numerical for various applied research questions. Furthermore, they will be able to apply and run a selected user-friendly outdoor thermal comfort model for a test case and will be able to use the programming language Python for the analyses of model output data. The students will also be able to understand the changes and limitations of model-based methods and acquire skills in the scientific data processing.
Prior knowledge of environmental meteorology, urban climatology and/or data processing is preferable but not necessary.
Further information (HisPos).