Estimating global damages from sea level rise with the Coastal Impact and Adaptation Model (CIAM)

Coastal sector impacts from sea level rise (SLR) are a key component of the projected economic damages of climate change, a major input to decision-making and design of climate policy. Moreover, the ultimate global costs to coastal resources will depend strongly on adaptation, society's response to cope with the local impacts. This paper presents a new open-source optimization model to assess global coastal impacts from SLR from the perspective of economic efficiency. The Coastal Impact and Adaptation Model (CIAM) determines the optimal strategy for adaptation at the local level, evaluating over 12,000 coastal segments, as described in the DIVA database (Vafeidis et al. 2006), based on their socioeconomic characteristics and the potential impacts of relative sea level rise and uncertain sea level extremes. A deterministic application of CIAM demonstrates the model's ability to assess local impacts and direct costs, choose the least-cost adaptation, and estimate global net damages for several climate scenarios that account for both global and local components of SLR (Kopp et al. 2014). CIAM finds that there is large potential for coastal adaptation to reduce the expected impacts of SLR compared to the alternative of no adaptation, lowering global net present costs through 2100 by a factor of seven to less than $1.7 trillion, although this does not include initial transition costs to overcome an under-adapted current state. In addition to producing aggregate estimates, CIAM results can also be interpreted at the local level, where retreat (e.g., relocate inland) is often a more cost-effective adaptation strategy than protect (e.g., construct physical defenses).