Feedback-based sea level rise impact modelling for integrated assessment models with FRISIAv1.0

The socio-economic costs of sea level rise (SLR) are an important component of climate impact representations in integrated assessment models (IAMs). However, the representation of global or regional mean SLR and its impacts varies substantially between different IAMs; from no representation at all to the use of regionally resolved coastal impact models with more than 10,000 individual coastal segments. Current SLR impact models thereby often follow a cost-benefit analysis approach, might not represent diverse pathways of SLR impacts, or miss coastal adaptation. Especially, there is a lack of process-based models of SLR impacts with a focus on global, time-varying dynamics.

Here, we present a new modelling framework, the Feedback-based knowledge Repository for Integrated assessments of Sea level rise Impacts and Adaptation version 1.0 (FRISIAv1.0), a model designed for process-based, non-equilibrium IAMs. Its formulation for the calculation of global mean sea level rise is based on existing models, while its impact and adaptation component is a substantially modified derivation of the Coastal Impact and Adaptation Model (CIAM) for use in globally or regionally aggregated models. FRISIA follows a system dynamics approach, focusing on interconnectedness and feedback between components that is often missing in existing models. Examples of such additional connections included in FRISIA are: a reduction of local asset values and GDP per capita through the increasing storm surge damages, reduced investment in coastal zones under expected increases in exposure, and a limitation to the amount of money that can annually be spent on flood protection.

A version of FRISIA without these feedbacks approximately reproduces CIAM's results, while their integration leads to emerging new behaviour, such as a potential peak and decline in SLR-driven storm surge damages in the early 22^nd century, due to economic feedbacks in the coastal zone. When coupling FRISIA to an IAM, global GDP is reduced by 1.5 - 6.2 % (17^th - 83^rd percentile range) under the mean SSP5-8.5 global-mean sea level rise from the IPCC's AR6 report (0.77 m by 2100) and no coastal adaptation, which is within the range reported in previous studies. We further show that the coupling of a diverse set of SLR impact streams into a process-based IAM allows the representation of a wide range of socio-economic consequences, such as effects on GDP, inflation, mortality or public debt.

As an outlook, we explore different adaptation strategies in a set of sensitivity simulations with FRISIA, focusing on the effect of delays and interruptions in flood protection investments on optimal SLR adaptation strategies. We find that both aspects can reduce the likelihood that a protect strategy (such as building a sea wall) is the optimal strategy, and we highlight the risk of a positive feedback loop of increasing SLR damage, reduced economic growth and reduced protection investments that might be triggered in some regions.