Robust Adaptation to Multiscale Climate Variability

The assessment and implementation of structural or financial instruments for climate risk mitigation requires projections of future climate risk over the operational life of each proposed instrument. A point often neglected in the climate adaptation literature is that the physical sources of predictability differ between projects with long and short planning periods: While historical and paleo climate records emphasize low‐frequency modes of variability, anthropogenic climate change is expected to alter their occurrence at longer time scales. In this paper we present a set of stylized experiments to assess the uncertainties and biases involved in estimating future climate risk over a finite future period, given a limited observational record. These experiments consider both quasi‐periodic and secular change for the underlying risk, as well as statistical models for estimating this risk from an N‐year historical record. The uncertainty of IPCC‐like future scenarios is considered through an equivalent sample size N. The relative importance of estimating short‐ or long‐term risk depends on the investment life M. Shorter design lives are preferred for situations where interannual to decadal variability can be successfully identified and predicted, highlighting the importance of sequential investment strategies for adaptation. Key Points Quasi‐periodic and secular climate signals, with different identifiability and predictability, control future uncertainty and risk Adaptation strategies must consider how uncertainties in risk projections influence success of decision pathways Stylized experiments reveal how bias and variance of climate risk projections influence risk mitigation over a finite planning period