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1. Coevolution of Extreme Sea Levels and Sea‐Level Rise Under Global Warming

   https://doi.org/10.1029/2023EF003649  

   Boumis, Georgios; Moftakhari, Hamed R.; Moradkhani, Hamid (July 2023, Earth's Future)

   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. 

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2. Communicating future sea-level rise uncertainty and ambiguity to assessment users

   https://doi.org/10.1038/s41558-023-01691-8  

   Kopp, Robert E.; Oppenheimer, Michael; O’Reilly, Jessica L.; Drijfhout, Sybren S.; Edwards, Tamsin L.; Fox-Kemper, Baylor; Garner, Gregory G.; Golledge, Nicholas R.; Hermans, Tim H.; Hewitt, Helene T.; et al (June 2023, Nature Climate Change)

   Future sea-level change is characterized by both quantifiable and unquantifiable uncertainties. Effective communication of both types of uncertainty is a key challenge in translating sea-level science to inform long-term coastal planning. Scientific assessments play a key role in the translation process and have taken diverse approaches to communicating sea-level projection uncertainty. Here we review how past IPCC and regional assessments have presented sea-level projection uncertainty, how IPCC presentations have been interpreted by regional assessments and how regional assessments and policy guidance simplify projections for practical use. This information influenced the IPCC Sixth Assessment Report presentation of quantifiable and unquantifiable uncertainty, with the goal of preserving both elements as projections are adapted for regional application. 

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3. Sea Level and Socioeconomic Uncertainty Drives High‐End Coastal Adaptation Costs

   https://doi.org/10.1029/2022EF003061  

   Wong, T. E.; Ledna, C.; Rennels, L.; Sheets, H.; Errickson, F. C.; Diaz, D.; Anthoff, D. (December 2022, Earth's Future)

   Abstract 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. 

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4. Spatial and temporal variability of 21st century sea level changes

   https://doi.org/10.1093/gji/ggad170  

   Roffman, Jeremy; Gomez, Natalya; Yousefi, Maryam; Han, Holly_Kyeore; Nowicki, Sophie (June 2023, Geophysical Journal International)

   SUMMARY Mass loss from polar ice sheets is becoming the dominant contributor to current sea level changes, as well as one of the largest sources of uncertainty in sea level projections. The spatial pattern of sea level change is sensitive to the geometry of ice sheet mass changes, and local sea level changes can deviate from the global mean sea level change due to gravitational, Earth rotational and deformational (GRD) effects. The pattern of GRD sea level change associated with the melting of an ice sheet is often considered to remain relatively constant in time outside the vicinity of the ice sheet. For example, in the sea level projections from the most recent IPCC sixth assessment report (AR6), the geometry of ice sheet mass loss was treated as constant during the 21st century. However, ice sheet simulations predict that the geometry of ice mass changes across a given ice sheet and the relative mass loss from each ice sheet will vary during the coming century, producing patters of global sea level changes that are spatiotemporally variable. We adopt a sea level model that includes GRD effects and shoreline migration to calculate time-varying sea level patterns associated with projections of the Greenland and Antarctic Ice Sheets during the coming century. We find that in some cases, sea level changes can be substantially amplified above the global mean early in the century, with this amplification diminishing by 2100. We explain these differences by calculating the contributions of Earth rotation as well as gravitational and deformational effects to the projected sea level changes separately. We find in one case, for example, that ice gain on the Antarctic Peninsula can cause an amplification of up to 2.9 times the global mean sea level equivalent along South American coastlines due to positive interference of GRD effects. To explore the uncertainty introduced by differences in predicted ice mass geometry, we predict the sea level changes following end-member mass loss scenarios for various regions of the Antarctic Ice Sheet from the ISMIP6 model ensemblely, and find that sea level amplification above the global mean sea level equivalent differ by up to 1.9 times between different ice mass projections along global coastlines outside of Greenland and Antarctica. This work suggests that assessments of future sea level hazard should consider not only the integrated mass changes of ice sheets, but also temporal variations in the geometry of the ice mass changes across the ice sheets. As well, this study highlights the importance of constraining the relative timing of ice mass changes between the Greenland and Antarctic Ice Sheets. 

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5. Emulating Ocean Dynamic Sea Level by Two‐Layer Pattern Scaling

   https://doi.org/10.1029/2020MS002323  

   Yuan, Jiacan; Kopp, Robert E. (March 2021, Journal of Advances in Modeling Earth Systems)

   Abstract Ocean dynamic sea level (DSL) change is a key driver of relative sea level (RSL) change. Projections of DSL change are generally obtained from simulations using atmosphere‐ocean general circulation models (GCMs). Here, we develop a two‐layer climate emulator to interpolate between emission scenarios simulated with GCMs and extend projections beyond the time horizon of available simulations. This emulator captures the evolution of DSL changes in corresponding GCMs, especially over middle and low latitudes. Compared with an emulator using univariate pattern scaling, the two‐layer emulator more accurately reflects GCM behavior and captures non‐linearities and non‐stationarity in the relationship between DSL and global‐mean warming, with a reduction in global‐averaged error during 2271–2290 of 36%, 24%, and 34% in RCP2.6, RCP4.5, and RCP8.5, respectively. Using the emulator, we develop a probabilistic ensemble of DSL projections through 2300 for four scenarios: Representative Concentration Pathway (RCP) 2.6, RCP 4.5, RCP 8.5, and Shared Socioeconomic Pathway (SSP) 3–7.0. The magnitude and uncertainty of projected DSL changes decrease from the high‐to the low‐emission scenarios, indicating a reduced DSL rise hazard in low‐ and moderate‐emission scenarios (RCP2.6 and RCP4.5) compared to the high‐emission scenarios (SSP3‐7.0 and RCP8.5). 

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