Artificial intelligence in support of weather warnings and climate adaptation

Abstract

In October 2021, the Swedish Meteorological and Hydrological Institute (SMHI) 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. For certain types of warnings, joint assessments of the potential impacts of weather events for a specific geographic area and time frame are made in collaboration with local and regional actors. As part of this new system, local and regional administrative efforts are made to create assessment-support documentation which are collated by practitioners at the municipal or organizational level, drawing on local knowledge, and subsequently compiled by the County Administrative Board. This process aims to support the collaborative decision-making processes ahead of the publication and in the evaluation of issued weather warnings.

This paper explores the potential of integrating long- and short-term perspectives in societal response to climate change impacts with focus on extreme weather events. We present a case of AI-based technology to support processes linked to the national system for impact-based weather warnings and its integration with local and regional climate adaptation processes. We explore opportunities to integrate an AI-based pipeline, employing AI-based image and text analysis of crowdsourced data, in the processes of the warning system, and analyse barriers and enablers identified by local, regional, and national stakeholders. We further discuss to what extent data and knowledge of 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. Thus, this study unfolds the existing and perceived barriers to this integration and discusses possible synergies and ways forward in risk management and climate adaptation practice.