B5: Urban Systems Test Bed Hamburg

Research Topic B-5: Urban Systems accentuates the research on the regional manifestations of climate impacts and the socio-cultural dimension of climate. UHH meteorologists, soil scientists, biologists and geographers closely collaborate with partners of the DWD, HCU, BSU and other stakeholders in Hamburg.

Objectives

The research in Urban Systems broadens the knowledge pool on the urban climate system, using the Metropolitan region of Hamburg as a test bed.

This research topic is a structural element of CliSAP to trigger coordinated and integrated research on urban systems. The foci lie on the following research topics, which are of fundamental interest for understanding climate changes in and their impacts on urban systems:

Scale attribution: Separate global and regional climate change signals from effects induced by urban development, which is also essential for understanding global processes in RA-A.

Urban climate risks: Relating potential risks of urban climate change to social areas and coping capacities of social groups in order to guide adaptation strategies, which are be analysed in cooperation with RA-C.

Local influences: Determining to what degree urban climate can be influenced and controlled by human actions.

Implications for urban planning: Deriving implications for future town planning, architectural design, urban safety, and urban governance.

Urban Systems serves as the focal point for research on urban climate systems at CliSAP and in the City of Hamburg.

Urban Climate is the local climate in urban areas. The urban climate is modified by the specific properties of the urban fabric and often features phenomena such as the urban heat island, where under certain conditions urban temperatures are increased compared to temperature in the surrounding rural areas.

Latest B5 Publications

  • Sismanidis, P., Keramitsoglou, I., Bechtel, B., & Kiranoudis, C. T. (2017). Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels. Remote Sensing, 9(1): 23. doi:10.3390/rs9010023.
  • Broussea, O., Martilli, A., Foley, M., Mills, G., & Bechtel, B. (2016). WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid. Urban Climate, 17, 116-134. doi:10.1016/j.uclim.2016.04.001.
  • Alexander, P., Bechtel, B., Chow, W., Fealy, R., & Mills, G. (2016). Linking urban climate classification with an urban energy and water budget model: Multi-site and multi-seasonal evaluation. Urban Climate, 17, 196-215. doi:10.1016/j.uclim.2016.08.003.
  • Sismanidis, P., Keramitsoglou, I., Kiranoudis, C. T., & Bechtel, B. (2016). Assessing the Capability of a Downscaled Urban Land Surface Temperature Time Series to Reproduce the Spatiotemporal Features of the Original Data. Remote Sensing, 8(4), 274. doi:10.3390/rs8040274.
  • Wiesner, S., Gröngröft, A., Ament, F., & Eschenbach, A. (2016). Spatial and temporal variability of urban soil water dynamics observed by a soil monitoring network. Journal of Soils and Sediments, 1-15. doi:10.1007/s11368-016-1385-6.