EGU22-13542
https://doi.org/10.5194/egusphere-egu22-13542
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Climate change adaptation digital twin to support decision making

Jenni Kontkanen1, Pekka Manninen1, Francisco Doblas-Reyes2, Sami Niemelä3, and Bjorn Stevens4
Jenni Kontkanen et al.
  • 1CSC – IT Center for Science, Espoo, Finland
  • 2Barcelona Supercomputing Center (BSC), Barcelona, Spain
  • 3Finnish Meteorological Institute, Helsinki, Finland
  • 4Max Planck Institute for Meteorology, Hamburg, Germany

Climate change will have far reaching impacts on human and natural systems during the 21st century. To increase the understanding of the present and future climate impacts and build resilience, improved Earth system modelling is required. The European Commission Destination Earth (DestinE) initiative aims to contribute to this by developing high precision digital twins (DTs) of the Earth. We present our solution to a climate-change adaptation DT, which is one of the two DTs developed during the first phase of DestinE. The objective of the climate change adaptation DT is to improve the assessment of the impacts of climate change and different adaptation actions at regional and national levels over multi-decadal timescales. This will be achieved by using two storm- and eddy-resolving global climate models, ICON (Icosahedral Nonhydrostatic Weather and Climate Model) and IFS (Integrated Forecasting System). The models will be run at a resolution of a few km on pre-exascale LUMI and MareNostrum5 supercomputers, which are flagship systems of the European High Performance Computing Joint Undertaking (EuroHPC JU) network. Following a radically different approach, climate simulations will be combined with a set of impact models, which enables assessing impacts on different sectors and topics, such as forestry, hydrology, cryosphere, energy, and urban areas. The end goal is to create a new type of climate simulations, in which user requirements are an integral part of the workflow, and thus adaptation solutions can be effectively deployed.

How to cite: Kontkanen, J., Manninen, P., Doblas-Reyes, F., Niemelä, S., and Stevens, B.: Climate change adaptation digital twin to support decision making, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13542, https://doi.org/10.5194/egusphere-egu22-13542, 2022.