In 2012, Hurricane Sandy hit the East Coast of the United States, creating widespread coastal flooding and over $60 billion in reported economic damage. The potential influence of climate change on the storm itself has been debated, but sea level rise driven by anthropogenic climate change more clearly contributed to damages. To quantify this effect, here we simulate water levels and damage both as they occurred and as they would have occurred across a range of lower sea levels corresponding to different estimates of attributable sea level rise. We find that approximately $8.1B ($4.7B–$14.0B, 5th–95th percentiles) of Sandy’s damages are attributable to climate-mediated anthropogenic sea level rise, as is extension of the flood area to affect 71 (40–131) thousand additional people. The same general approach demonstrated here may be applied to impact assessments for other past and future coastal storms.
Sea‐level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing coastal adaptation and impacts are important tools to inform the design of strategies to manage these risks. Representing the often deep uncertainties influencing these risks poses nontrivial challenges. A common uncertainty characterization approach is to use a few benchmark cases to represent the range and relative probabilities of the set of possible outcomes. This has been done in coastal adaptation studies, for example, by using low, moderate, and high percentiles of an input of interest, like sea‐level changes. A key consideration is how this simplified characterization of uncertainty influences the distributions of estimated coastal impacts. Here, we show that using only a few benchmark percentiles to represent uncertainty in future sea‐level change can lead to overconfident projections and underestimate high‐end risks as compared to using full ensembles for sea‐level change and socioeconomic parametric uncertainties. When uncertainty in future sea level is characterized by low, moderate, and high percentiles of global mean sea‐level rise, estimates of high‐end (95th percentile) damages are underestimated by between 18% (SSP1‐2.6) and 46% (SSP5‐8.5). Additionally, using the 5th and 95th percentiles of sea‐level scenarios underestimates the 5%–95% width of the distribution of adaptation costs by a factor ranging from about two to four, depending on SSP‐RCP pathway. The resulting underestimation of the uncertainty range in adaptation costs can bias adaptation and mitigation decision‐making.
more » « less- Award ID(s):
- 2213432
- NSF-PAR ID:
- 10386712
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Earth's Future
- Volume:
- 10
- Issue:
- 12
- ISSN:
- 2328-4277
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Sea‐level rise sits at the frontier of usable climate climate change research, because it involves natural and human systems with long lags, irreversible losses, and deep uncertainty. For example, many of the measures to adapt to sea‐level rise involve infrastructure and land‐use decisions, which can have multigenerational lifetimes and will further influence responses in both natural and human systems. Thus, sea‐level science has increasingly grappled with the implications of (1) deep uncertainty in future climate system projections, particularly of human emissions and ice sheet dynamics; (2) the overlay of slow trends and high‐frequency variability (e.g., tides and storms) that give rise to many of the most relevant impacts; (3) the effects of changing sea level on the physical exposure and vulnerability of ecological and socioeconomic systems; and (4) the challenges of engaging stakeholder communities with the scientific process in a way that genuinely increases the utility of the science for adaptation decision making. Much fundamental climate system research remains to be done, but many of the most critical issues sit at the intersection of natural sciences, social sciences, engineering, decision science, and political economy. Addressing these issues demands a better understanding of the coupled interactions of mean and extreme sea levels, coastal geomorphology, economics, and migration; decision‐first approaches that identify and focus research upon those scientific uncertainties most relevant to concrete adaptation choices; and a political economy that allows usable science to become used science.
-
more » « less
Abstract Sea level rise (SLR) is a long‐lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process‐based models. However, risk‐averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high‐end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high‐end scenarios. High‐end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1‐2.6) relative to pre‐industrial values our high‐end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5‐8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long‐term benefits of mitigation. However, even a modest 2°C warming may cause multi‐meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high‐end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high‐end SLR.
-
more » « less
Abstract Design of coastal defense structures like seawalls and breakwaters can no longer be based on stationarity assumption. In many parts of the world, an anticipated sea‐level rise (SLR) due to climate change will constitute present‐day extreme sea levels inappropriate for future coastal flood risk assessments since it will significantly increase their probability of occurrence. Here, we first show that global annual maxima sea levels (AMSLs) have been increasing in magnitude over the last decades, primarily due to a positive shift in mean sea level (MSL). Then, we apply non‐stationary extreme value theory to model the extremal behavior of sea levels with MSL as a covariate and quantify the evolution of AMSLs in the following decades using revised probabilistic sea‐level rise projections. Our analysis reveals that non‐stationary distributions exhibit distinct differences compared to simply considering stationary conditions with a change in location parameter equal to the amount of MSL rise. With the use of non‐stationary distributions, we show that by the year 2050 many locations will experience their present‐day 100‐yr return level as an event with return period less than 15 and 9 years under the moderate (RCP4.5) and high (RCP8.5) representative concentration pathways. Also, we find that by the end of this century almost all locations examined will encounter their current 100‐yr return level on an annual basis, even if CO2concentration is kept at moderate levels (RCP4.5). Our assessment accounts for large uncertainty by incorporating ambiguities in both SLR projections and non‐stationary extreme value distribution parameters via a Monte Carlo simulation.
-
Integrating new sea‐level scenarios into coastal risk and adaptation assessments: An ongoing processmore » « less
Abstract The release of new and updated sea‐level rise (SLR) information, such as from the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports, needs to be better anticipated in coastal risk and adaptation assessments. This requires risk and adaptation assessments to be regularly reviewed and updated as needed, reflecting the new information but retaining useful information from earlier assessments. In this paper, updated guidance on the types of SLR information available is presented, including for sea‐level extremes. An intercomparison of the evolution of the headline projected ranges across all the IPCC reports show an increase from the fourth and fifth assessments to the most recent “
Special Report on the Ocean and Cryosphere in a Changing Climate ” assessment. IPCC reports have begun to highlight the importance of potential high‐end sea‐level response, mainly reflecting uncertainties in the Greenland/Antarctic ice sheet components, and how this might be considered in scenarios. The methods that are developed here are practical and consider coastal risk assessment, adaptation planning, and long‐term decision‐making to be an ongoing process and ensure that despite the large uncertainties, pragmatic adaptation decisions can be made. It is concluded that new sea‐level information should not be seen as an automatic reason for abandoning existing assessments, but as an opportunity to review (i) the assessment's robustness in the light of new science and (ii) the utility of proactive adaptation and planning strategies, especially over the more uncertain longer term.This article is categorized under:
Assessing Impacts of Climate Change > Scenario Development and Application
