Thanks to the organizing committee of the 2019 IPSWD for putting together a fantastic event. It was a pleasure to speak about my ongoing work on how the identifiability and predictability of different climate signals map onto the success or failure of investments in climate adaptation with different planned project lifetimes. I also enjoyed learning about how students in other disciplines (economics was particularly well-represented) are tackling important environmental challenges. I hope that future years can see this workshop attract more scientists and engineers, since I know that many of us are keenly interested in sustainable development and I think that the earlier we are able to learn the language and culture of other disciplines, the easier it will be for us to work together in the future.
If you're interested, please find my slides here.
We've also submitted a paper which gives this work in greater detail. Please find the abstract below and feel free to contact me if you would like a draft of the manuscript.
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 interannual to multidecadal 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 the short- or long-term risk extremes depends on the investment life \(M\). Shorter design lives are preferred c6for situations where inter-annual to decadal variability can be successfully identified and predicted, suggesting the importance of sequential investment strategies for adaptation.
- Quasi-periodic and secular climate signals, with different identifiability and predictability, control future uncertainty and risk
- Adaptation strategies need to 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