Mapping Sea-Level Change in Time, Space, and Probability

Horton, Benjamin P.; Kopp, Robert; Garner, Andra J.; Hay, Carling C.; Khan, Nicole S.; Roy, Keven; Shaw, Timothy A.

doi:10.1146/annurev-environ-102017-025826

Cited by 149 publications

(87 citation statements)

References 204 publications

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“…Our expectation is that some worsening of total inundation levels during storms is occurring globally associated with the anthropogenic contributions to global and regional sea level rise (Bindoff et al 2013, Horton et al 2018, assuming all other factors equal (Woodruff et al 2013;Sweet et al 2013). However, a TC climate change signal has not yet been convincingly identified as a residual in sea level extremes data, after accounting for background sea level rise.…”

Section: Case Studies -Assessment Of De-tection and Attributionmentioning

confidence: 99%

Tropical Cyclones and Climate Change Assessment: Part I: Detection and Attribution

Knutson

Camargo

Chan

et al. 2019

Bulletin of the American Meteorological Society

426

305

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An assessment was made of whether detectable changes in tropical cyclone (TC) activity are identifiable in observations and whether any changes can be attributed to anthropogenic climate change. Overall, historical data suggest detectable TC activity changes in some regions associated with TC track changes, while data quality and quantity issues create greater challenges for analyses based on TC intensity and frequency. A number of specific published conclusions (case studies) about possible detectable anthropogenic influence on TCs were assessed using the conventional approach of preferentially avoiding type I errors (i.e., overstating anthropogenic influence or detection). We conclude there is at least low to medium confidence that the observed poleward migration of the latitude of maximum intensity in the western North Pacific is detectable, or highly unusual compared to expected natural variability. Opinion on the author team was divided on whether any observed TC changes demonstrate discernible anthropogenic influence, or whether any other observed changes represent detectable changes. The issue was then reframed by assessing evidence for detectable anthropogenic influence while seeking to reduce the chance of type II errors (i.e., missing or understating anthropogenic influence or detection). For this purpose, we used a much weaker “balance of evidence” criterion for assessment. This leads to a number of more speculative TC detection and/or attribution statements, which we recognize have substantial potential for being false alarms (i.e., overstating anthropogenic influence or detection) but which may be useful for risk assessment. Several examples of these alternative statements, derived using this approach, are presented in the report.

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Section: Case Studies -Assessment Of De-tection and Attributionmentioning

confidence: 99%

Tropical Cyclones and Climate Change Assessment: Part I: Detection and Attribution

Knutson

Camargo

Chan

et al. 2019

Bulletin of the American Meteorological Society

426

305

View full text Add to dashboard Cite

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“…Small enough in the context of expected utility approaches means that the results are insensitive to the choice of the scenario, because SLR projections do not significantly diverge between the lowest and highest emission/concentration scenarios. Until the middle of the century, differences between global mean SLR projections due to differences in scenarios are generally small (Garner et al, ; Horton et al, ), but the point in time when scenarios diverge differs across locations and depends on the metric applied for detecting divergence. As an illustration, we take the Fifth Assessment Report (AR5) SLR projections (Church et al, ) together with interannual sea level variability from global tide gauge stations from Woodworth et al (), to assess the year of scenario divergence, using a 10% threshold in the statistical distance between the distributions of RCP2.6 and RCP8.5 (Figure ).…”

Section: Meeting the Identified Needsmentioning

confidence: 99%

“…Regarding the vertical land movement component of local sea level change, paleo-records and geodetic measurements can provide useful information on long-term gradual vertical land movement (e.g., Horton et al, 2018;Wöppelmann & Marcos, 2016). However, future vertical land movements are especially difficult to quantify and can hardly be included in a probabilistic framework when the two following types of processes are involved.…”

Section: 1029/2018ef001071mentioning

confidence: 99%

Meeting User Needs for Sea Level Rise Information: A Decision Analysis Perspective

et al. 2019

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Despite widespread efforts to implement climate services, there is almost no literature that systematically analyzes users' needs. This paper addresses this gap by applying a decision analysis perspective to identify what kind of mean sea level rise (SLR) information is needed for local coastal adaptation decisions. We first characterize these decisions, then identify suitable decision analysis approaches and the sea level information required, and finally discuss if and how these information needs can be met given the state of the art of sea level science. We find that four types of information are needed: (i) probabilistic predictions for short‐term decisions when users are uncertainty tolerant; (ii) high‐end and low‐end SLR scenarios chosen for different levels of uncertainty tolerance; (iii) upper bounds of SLR for users with a low uncertainty tolerance; and (iv) learning scenarios derived from estimating what knowledge will plausibly emerge about SLR over time. Probabilistic predictions can only be attained for the near term (i.e., 2030–2050) before SLR significantly diverges between low and high emission scenarios, for locations for which modes of climate variability are well understood and the vertical land movement contribution to local sea levels is small. Meaningful SLR upper bounds cannot be defined unambiguously from a physical perspective. Low‐ to high‐end scenarios for different levels of uncertainty tolerance and learning scenarios can be produced, but this involves both expert and user judgments. The decision analysis procedure elaborated here can be applied to other types of climate information that are required for mitigation and adaptation purposes.

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“…The ARIM scenario offers an alternate plausible upper-end sea level rise projection for 21st century rise for New York City, based on recent advances in understanding of ice sheet behavior, particularly that of Antarctica, in order to prepare for possible high-impact situations. For the ARIM scenario, there are multiple plausible alternative distributions that exhibit limited convergence (Horton et al, 2018).…”

Section: Development Of Arim--a Newmentioning

confidence: 99%