skip to main content


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

 
more » « less
Award ID(s):
2223893
NSF-PAR ID:
10442140
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Earth's Future
Volume:
11
Issue:
7
ISSN:
2328-4277
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Sea‐level rise (SLR) increasingly threatens coastal communities around the world. However, not all coastal communities are equally threatened, and realistic estimation of hazard is difficult. Understanding SLR impacts on extreme sea level is challenging due to interactions between multiple tidal and non‐tidal flood drivers. We here use global hourly tidal data to show how and why tides and surges interact with mean sea level (MSL) fluctuations. At most locations around the world, the amplitude of at least one tidal constituent and/or amplitude of non‐tidal residual have changed in response to MSL variation over the past few decades. In 37% of studied locations, “Potential Maximum Storm Tide” (PMST), a proxy for extreme sea level dynamics, co‐varies with MSL variations. Over all stations, the median PMST will be 20% larger by the mid‐century, and conventional approaches that simply shift the current storm tide regime up at the rate of projected SLR may underestimate the flooding hazard at these locations by up to a factor of four. Micro‐ and meso‐tidal systems and those with diurnal tidal regime are generally more susceptible to altered MSL than other categories. The nonlinear interactions of MSL and storm tide captured in PMST statistics contribute, along with projected SLR, to the estimated increase in flood hazard at three‐fourth of studied locations by mid‐21st century. PMST is a threshold that captures nonlinear interactions between extreme sea level components and their co‐evolution over time. Thus, use of this statistic can help direct assessment and design of critical coastal infrastructure.

     
    more » « less
  2. Abstract

    Flood exposure is increasing in coastal communities due to rising sea levels. Understanding the effects of sea level rise (SLR) on frequency and consequences of coastal flooding and subsequent social and economic impacts is of utmost importance for policymakers to implement effective adaptation strategies. Effective strategies may consider impacts from cumulative losses from minor flooding as well as acute losses from major events. In the present study, a statistically coherent Mixture Normal‐Generalized Pareto Distribution model was developed, which reconciles the probabilistic characteristics of the upper tail as well as the bulk of the sea level data. The nonstationary sea level condition was incorporated in the mixture model using Quantile Regression method to characterize variable Generalized Pareto Distribution thresholds as a function of SLR. The performance validity of the mixture model was corroborated for 68 tidal stations along the Contiguous United States (CONUS) coast with long‐term observed data. The method was subsequently employed to assess existing and future coastal minor and major flood frequencies. The results indicate that the frequency of minor and major flooding will increase along all CONUS coastal regions in response to SLR. By the end of the century, under the “Intermediate” SLR scenario, major flooding is anticipated to occur with return period less than a year throughout the coastal CONUS. However, these changes vary geographically and temporally. The mixture model was reconciled with the property exposure curve to characterize how SLR might influence Average Annual Exposure to coastal flooding in 20 major CONUS coastal cities.

     
    more » « less
  3. Abstract

    Climate change is raising sea levels across the globe. On river deltas, sea‐level rise (SLR) may result in land loss, saline intrusion into groundwater aquifers, and other problems that adversely impact coastal communities. There is significant uncertainty surrounding future SLR trajectories and magnitudes, even over decadal timescales. Given this uncertainty, numerical modeling is needed to explore how different SLR projections may impact river delta evolution. In this work, we apply the pyDeltaRCM numerical model to simulate 350 years of deltaic evolution under three different SLR trajectories: steady rise, an abrupt change in SLR rate, and a gradual acceleration of SLR. For each SLR trajectory, we test a set of six final SLR magnitudes between 5 and 40 mm/yr, in addition to control runs with no SLR. We find that both surface channel dynamics as well as aspects of the subsurface change in response to higher rates of SLR, even over centennial timescales. In particular, increased channel mobility due to SLR corresponds to higher sand connectivity in the subsurface. Both the trajectory and magnitude of SLR change influence the evolution of the delta surface, which in turn modifies the structure of the subsurface. We identify correlations between surface and subsurface properties, and find that inferences of subsurface structure from the current surface configuration should be limited to time spans over which the sea level forcing is approximately steady. As a result, this work improves our ability to predict future delta evolution and subsurface connectivity as sea levels continue to rise.

     
    more » « less
  4. Abstract

    The artificial impoundment of water behind dams causes global mean sea level (GMSL) to fall as reservoirs fill but also generates a local rise in sea level due to the increased mass in the reservoir and the crustal deformation this mass induces. To estimate spatiotemporal fluctuations in sea level due to water impoundment, we use a historical data set that includes 6,329 reservoirs completed between 1900 and 2011, as well as projections of 3,565 reservoirs that are expected to be completed by 2040. The GMSL change associated with the historical data (−0.2 mm yr−1from 1900–2011) is consistent with previous studies, but the temporal and spatial resolution allows for local studies that were not previously possible, revealing that some locations experience a sea level rise of as much as 40 mm over less than a decade. Future construction of reservoirs through ~2040 is projected to cause a GMSL fall whose rate is comparable to that of the last century (−0.3 mm yr−1) but with a geographic distribution that will be distinct from the last century, including a rise in sea level in more coastal areas. The analysis of expected construction shows that significant impoundment near coastal communities in the coming decades could enhance the flooding risk already heightened by global sea level rise.

     
    more » « less
  5. 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).

     
    more » « less