Multi-sectoral evaluation of climate change risks and adaptation urgency using a response surface approach

This paper presents a new approach to climate change impact and adaptation analysis within a risk framework. We test the feasibility of applying impact models for representing three aspects of potential relevance for policy: (i) sensitivity –  examining the sensitivity of the sectors to changing climate for readily observable indicators; (ii) urgency – estimating risks of approaching or exceeding critical thresholds of impact under alternative scenarios as a basis for determining urgency of response; and (iii) response –  determining the effectiveness of potential adaptation and mitigation responses. By working with observable indicators, the approach is also amenable to long-term monitoring as well as evaluation of the success of adaptation, where this too can be simulated.

 

The approach involves the construction of impact response surfaces (IRSs) based on impact model simulations, using sectoral impact models that are also capable of simulating some adaptation measures. An IRS is constructed from an analysis of the modelled sensitivity of an impact indicator of interest to systematic changes in key drivers (e.g. temperature and precipitation) and the resulting impact variable is plotted as a surface comprising contour lines of equal response over a wide range of perturbations. This facilitates analysis of model behaviour across many possible future conditions. IRSs can also be combined with probabilistic projections of climate change to estimate the likelihood of exceeding certain critical thresholds of impact. An important step here is the identification of such critical thresholds, which are meaningful limits of tolerance for the functioning of the system and typically requiring expert advice from key stakeholders.

 

Two examples are shown that illustrate the types of analyses to be undertaken and their potential outputs: risks of crop yield shortfall in Finland (Pirttioja et al. 2019) and impact risks for water management in a Portuguese reservoir (Fronzek et al., in prep.). Three challenges require special attention in this new modelling exercise: (a) ensuring the salience and credibility of the modelling conducted, through engagement with relevant stakeholders, (b) co-exploration of the capabilities of current impact models and the need for improved representation of adaptation and (c) co-identification of critical thresholds for key impact indicators and effective representation of uncertainties.

 

The approach is currently being tested at national scale in Finland in the Adapt-FIRST project (https://www.syke.fi/projects/adapt-first), using models of water resources, agriculture, forest productivity, nature recreation and human health to address multiple climate-related hazards such as droughts, floods, heat and forest fires and their interaction with mean changes in climate. Impact likelihoods will be estimated for regions in Finland, contributing to a national risk assessment to support adaptation policies. This approach could be a useful device for indicating the level of urgency for action, whether by adaptation to ameliorate the risk or mitigation to avert the hazard.

 

 

References

Fronzek et al. (in prep.) Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces.

Pirttioja et al. (2019) Using impact response surfaces to analyse the likelihood of impacts on crop yield under probabilistic climate change. Agr Forest Meteorol 264:213-224.