Research Projects
We are or have been involved in the following projects:
Climate, Climate Change, and Society (CLICCS)
Website: https://www.cliccs.uni-hamburg.de/
Type: Cluster of Excellence
HCDS involvement: Subproject "High-Perfomance Computing and Data-Intensive Science"
Period: 2019-2025
Description: Within the Cluster of Excellence “Climate, Climatic Change, and Society” (CLICCS), which explores climate change with broad expertise, the research area "High-Perfomance Computing and Data-Intensive Science" focuses on research and development to meeting the challenges arising from increasing computational requirements of climate research on the one hand, and bottlenecks limiting the efficiently scalable exploitation of progress made in in high-performance computing on the other hand. In the HCDS-VDA group, we investigate novel visual data analysis methods for climate research.
Waves to Weather
Website: https://www.wavestoweather.de/
Type: DFG-funded Collaborative Research Centre (Sonderforschungsbereich)
HCDS involvement: Subprojects C9 and Z2b
Period: 2019-2024
Description: Our ability to predict the weather up to a week or more ahead saves our societies billions of Euros annually and protects human life and property. Exponentially increasing computing power and new observations have led to continuous improvements in forecast quality over many years, but nonetheless forecasts are sometimes strikingly poor. Increasing evidence suggests that this is not merely due to defects in our forecasting methods, because in a chaotic atmosphere, some weather situations are intrinsically hard to predict. The great challenge today is to identify the limits of predictability in different situations and produce the best forecasts that are physically possible. The Collaborative Research Center "Waves to Weather" (CRC/Transregio 165; W2W) is conceived to meet this challenge and to deliver the underpinning science urgently needed to pave the way towards a new generation of weather forecasting systems. In the HCDS-VDA group, we investigate novel visual data analysis methods to support meteorological research projects in W2W, using our visualization framework Met.3D.