EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

AI for Climate Adaptation?

Tina-Simone Neset1, Katerina Vrotsou2, Carlo Navarra1, Fredrik Schück3, Clara Greve Villaro3, Magnus Mateo Edström4, and Caroline Rydholm4
Tina-Simone Neset et al.
  • 1Department of Thematic Studies–Environmental Change, Centre for Climate Science and Policy Research, Linköping University, Linköping, Sweden
  • 2Department of Science and Technology, Division for Media and Information Technology, Linköping University, Linköping, Sweden
  • 3Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden
  • 4County Administrative Board Östergötland, Linköping, Sweden

In October 2021, the Swedish Meteorological and Hydrological Institute launched a novel national system for impact-based weather warnings, moving from the traditional format for meteorological, hydrological, and oceanographic warnings towards an assessment process that includes collaboration and consultation with regional stakeholders on the impacts that certain weather events would have for a specific geographic area and time frame. As part of this new system, local and regional administrative efforts are made to create assessment-support documentation drawing on local knowledge and providing support ahead of and during extreme weather events.

We present initial results from the ongoing research project ‘AI4ClimateAdaptation’ (, which explores the potential of employing AI-based image and text analysis to support the process and evaluate the precision of impact-based weather warnings. The project collects image and text data appropriate for subsequent use in AI-based analysis from citizen science campaigns and social media. The presentation focuses on the concept of integrating AI-based text and image analysis with the processes of the warning system, as well as the barriers and enablers that are identified by local, regional, and national stakeholders related to the role of AI in weather warning systems. We further discuss to what extent data and knowledge on historical extreme weather events can be integrated with local and regional climate adaptation efforts, and whether these efforts could bridge the divide between long-term adaptation strategies and short-term response measures related to extreme weather events. The results of this study are expected to contribute to the national system for impact-based weather warnings and to increase resilience to extreme climate-related weather events.

How to cite: Neset, T.-S., Vrotsou, K., Navarra, C., Schück, F., Greve Villaro, C., Mateo Edström, M., and Rydholm, C.: AI for Climate Adaptation?, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11023,, 2023.