Dynamic Sea Level Changes Research Articles

Regional Sea Level Response to External Forcings from the Twentieth to the Twenty-First Century

Abstract Using a range of Detection and Attribution Model Intercomparison Project (DAMIP) simulations from phase 6 of Coupled Model Intercomparison Project (CMIP6), we study the response of dynamic sea level (DSL) to external anthropogenic climate forcing [greenhouse gases (GHGs), aerosols, and stratospheric ozone] with a focus on the differences over the twentieth and twenty-first century. In the second half of the twentieth century, the DSL nonuniformity in the Northern Hemisphere (NH) was relatively small due to a cancellation between the effects of increasing GHGs and aerosols. In contrast, the DSL signal in the Southern Hemisphere (SH) over this period was large because stratospheric ozone depletion reinforced the effects of increasing GHGs. In the twenty-first century, the DSL response has been intensified in the NH because the warming effects of diminishing aerosols have acted to reinforce the effects of increasing GHGs. Meanwhile, the distribution of SH DSL has also become uneven although stratospheric ozone recovery has partially offset the effects of rising GHGs. Using a global ocean circulation model, we decompose the changes in the twenty-first century DSL into distinct responses to surface forcings including sea surface temperature, salinity, and wind stress. Our results show that the dipole-like pattern of DSL in the North Pacific can be attributed largely to sea surface warming, while the dipole-like pattern in the North Atlantic is attributed to subpolar surface salinity freshening. The belted pattern of DSL changes in the Southern Ocean is induced by both surface warming and intensifying/poleward-shifting westerly winds.

Improving statistical projections of ocean dynamic sea-level change using pattern recognition techniques

Abstract. Regional emulation tools based on statistical relationships, such as pattern scaling, provide a computationally inexpensive way of projecting ocean dynamic sea-level change for a broad range of climate change scenarios. Such approaches usually require a careful selection of one or more predictor variables of climate change so that the statistical model is properly optimized. Even when appropriate predictors have been selected, spatiotemporal oscillations driven by internal climate variability can be a large source of statistical model error. Using pattern recognition techniques that exploit spatial covariance information can effectively reduce internal variability in simulations of ocean dynamic sea level, significantly reducing random errors in regional emulation tools. Here, we test two pattern recognition methods based on empirical orthogonal functions (EOFs), namely signal-to-noise maximizing EOF pattern filtering and low-frequency component analysis, for their ability to reduce errors in pattern scaling of ocean dynamic sea-level change. We use the Max Planck Institute Grand Ensemble (MPI-GE) as a test bed for both methods, as it is a type of initial-condition large ensemble designed for an optimal characterization of the externally forced response. We show that the two methods tested here more efficiently reduce errors than conventional approaches such as a simple ensemble average. For instance, filtering only two realizations by characterizing their common response to external forcing reduces the random error by almost 60 %, a reduction that is only achieved by averaging at least 12 realizations. We further investigate the applicability of both methods to single-realization modeling experiments, including four CMIP5 simulations for comparison with previous regional emulation analyses. Pattern filtering leads to a varying degree of error reduction depending on the model and scenario, ranging from more than 20 % to about 70 % reduction in global-mean root mean squared error compared with unfiltered simulations. Our results highlight the relevance of pattern recognition methods as a tool to reduce errors in regional emulation tools of ocean dynamic sea-level change, especially when one or only a few realizations are available. Removing internal variability prior to tuning regional emulation tools can optimize the performance of the statistical model, leading to substantial differences in emulated dynamic sea level compared to unfiltered simulations.

Dynamic sea-level changes and potential implications for storm surges in the UK: a storylines perspective

Global sea-level rise caused by a warming climate increases flood risk from storm surge events for those who live in coastal and low-lying areas. Estimates of global thermosteric sea-level rises are well constrained by model projections, but local variability in dynamic sea-level arising from seasonal and interannual changes is less well characterised. In this paper we use satellite altimetry observations coupled with CMIP6 model projections to understand drivers of change in dynamic sea-level over the UK shelf seas. We find a northward shift in the atmospheric jet stream and a weakening of the Atlantic meridional overturning circulation to be the key drivers of local dynamic sea-level variability. Using a storyline approach to constrain climate system responses to changes in atmospheric greenhouse gas concentrations, we find that dynamic sea-level is predicted to rise between 15–39 cm by 2080–2099 along the east coast of England (ECE). Under a worst-case scenario, assuming maximum variability as seen in the CMIP6 projections, ECE dynamic sea-level rise could reach 58 cm by 2100. We illustrate the impact of this dynamic sea-level rise in addition to non-dynamic components on the risks posed by storm surge events in ECE using an idealised example. If a storm surge event of the magnitude of the one experienced in ECE on the 5th of December 2013 was to occur in 2100, an additional 1414 km2 of land would potentially be affected in our worst-case idealised example, 22.4% of which can be attributed to dynamic sea-level rise.

Sensitivity of MPI-ESM Sea Level Projections to Its Ocean Spatial Resolution

Abstract The dependence of future regional sea level changes on ocean model resolution is investigated based on Max Planck Institute Earth System Model (MPI-ESM) simulations with varying spatial resolution, ranging from low resolution (LR), high resolution (HR), to eddy-rich (ER) resolution. Each run was driven by the shared socioeconomic pathway (SSP) 5-8.5 (fossil-fueled development) forcing. For each run the dynamic sea level (DSL) changes are evaluated by comparing the time mean of the SSP5-8.5 climate change scenario for the years 2080–99 to the time mean of the historical simulation for the years 1995–2014. Respective results indicate that each run reproduces previously identified large-scale DSL change patterns. However, substantial sensitivity of the projected DSL changes can be found on a regional to local scale with respect to model resolution. In comparison to models with parameterized eddies (HR and LR), enhanced sea level changes are found in the North Atlantic subtropical region, the Kuroshio region, and the Arctic Ocean in the model version capturing mesoscale processes (ER). Smaller yet still significant sea level changes can be found in the Southern Ocean and the North Atlantic subpolar region. These sea level changes are associated with changes in the regional circulation. Our study suggests that low-resolution sea level projections should be interpreted with care in regions where major differences are revealed here, particularly in eddy active regions such as the Kuroshio, Antarctic Circumpolar Current, Gulf Stream, and East Australian Current. Significance Statement Sea level change is expected to be more realistic when mesoscale processes are explicitly resolved in climate models. However, century-long simulations with eddy-resolving models are computationally expensive. Therefore, current sea level projections are based on climate models in which ocean eddies are parameterized. The representation of sea level by these models considerably differs from actual observations, particularly in the eddy-rich regions such as the Southern Ocean and the western boundary currents, implying erroneous ocean circulation that affects the sea level projections. Taking this into account, we review the sea level change pattern in a climate model with featuring an eddy-rich ocean model and compare the results to state-of-the-art coarser-resolution versions of the same model. We found substantial DSL differences in the global ocean between the different resolutions. Relatively small-scale ocean eddies can hence have profound large-scale effects on the projected sea level which may affect our understanding of future sea level change as well as the planning of future investments to adapt to climate change around the world.

The Impact of Horizontal Resolution on Projected Sea-Level Rise Along US East Continental Shelf With the Community Earth System Model.

The Intergovernmental Panel on Climate Change Fifth Assessment Report lists sea‐level rise as one of the major future climate challenges. Based on pre‐industrial and historical‐and‐future climate simulations with the Community Earth System Model, we analyze the projected sea‐level rise in the Northwest Atlantic Ocean with two sets of simulations at different horizontal resolutions. Compared with observations, the low resolution (LR) model simulated Gulf Stream does not separate from the shore but flows northward along the entire coast, causing large biases in regional dynamic sea level (DSL). The high resolution (HR) model improves the Gulf Stream representation and reduces biases in regional DSL. Under the RCP8.5 future climate scenario, LR projects a DSL trend of 1.5–2 mm/yr along the northeast continental shelf (north of 40° N), which is 2–3 times the trend projected by HR. Along the southeast shelf (south of 35° N), HR projects a DSL trend of 0.5–1 mm/yr while the DSL trend in LR is statistically insignificant. The different spatial patterns of DSL changes are attributable to the different Gulf Stream reductions in response to a weakening Atlantic Meridional Overturning Circulation. Due to its poor representation of the Gulf Stream, LR projects larger (smaller) current decreases along the north (south) east continental slope compared to HR. This leads to larger (smaller) trends of DSL rise along the north (south) east shelf in LR than in HR. The results of this study suggest that the better resolved ocean circulations in HR can have significant impacts on regional DSL simulations and projections.

Simulated sea levels during 1948–2009 in a global ocean-sea ice model for OMIP

This paper assesses the ability of the State Key Laboratory of Atmospheric Science and Geophysical Fluid Dynamics of the Institute of Atmospheric Physics (LASG/IAP) Climate System Ocean Model version 3 (LICOM3) to simulate sea levels. For the time series of global changes, most of the global mean steric sea level (SSL) changes were dominated by thermosteric sea level (TSSL) changes in the upper 700 m, with a relatively small contribution from halosteric sea level (HSSL). LICOM3 can reproduce the observed dynamic sea level (DSL) in most regions to reflect the spatial patterns of regional changes. Deviations between LICOM3 and observations were mainly concentrated in the western boundary current and the tropical eastern Pacific. The departure in the western boundary current was primarily related to the model resolution. LICOM3 could not depict DSL changes in the high latitudes where the mesoscale eddies were active. The excessive negative trend in the tropical eastern Pacific was mainly caused by the trend error in the CORE-II forcing products. For the sea level variability, the analysis results of different DSL periods showed that the LICOM3 model could simulate interannual and decadal variability and the satellite altimeter period trend. At least 50 years of data were used to separate the decadal variability and long-term trend. The decadal variability had no significant effect on the 50-year long-term trend change in the DSL in the tropical western Pacific.Analysis of sea level component contributions showed that the changes in global time series, spatial patterns, and sea level variability mainly resulted from the change in TSSL. The TSSL changes in the upper 700 m could roughly reflect the TSSL changes for the whole depth, except for the North Atlantic and the Southern Ocean. In the Atlantic, the contribution of HSSL was comparable to and compensated by TSSL. When compared with reanalysis, the simulation generated differences in the Southern Ocean and North Atlantic. The linear trend of TSSL simulated by LICOM3 was much stronger than that simulated by reanalysis. The deviation of the Southern Ocean may be related to the CORE-II forcing product. The lack of observations in the Southern Ocean led to the uncertainty of the CORE-II forcing product.

The Effect of Wind Stress on Seasonal Sea-Level Change on the Northwestern European Shelf

Abstract Projections of relative sea level change (RSLC) are commonly reported at an annual mean basis. The seasonality of RSLC is often not considered, even though it may modulate the impacts of annual mean RSLC. Here, we study seasonal differences in twenty-first-century ocean dynamic sea level change (DSLC; 2081–2100 minus 1995–2014) on the Northwestern European Shelf (NWES) and their drivers, using an ensemble of 33 CMIP6 models complemented with experiments performed with a regional ocean model. For the high-end emissions scenario SSP5–8.5, we find substantial seasonal differences in ensemble mean DSLC, especially in the southeastern North Sea. For example, at Esbjerg (Denmark), winter mean DSLC is on average 8.4 cm higher than summer mean DSLC. Along all coasts on the NWES, DSLC is higher in winter and spring than in summer and autumn. For the low-end emissions scenario SSP1–2.6, these seasonal differences are smaller. Our experiments indicate that the changes in winter and summer sea level anomalies are mainly driven by regional changes in wind stress anomalies, which are generally southwesterly and east-northeasterly over the NWES, respectively. In spring and autumn, regional wind stress changes play a smaller role. We also show that CMIP6 models not resolving currents through the English Channel cannot accurately simulate the effect of seasonal wind stress changes on the NWES. Our results imply that using projections of annual mean RSLC may underestimate the projected changes in extreme coastal sea levels in spring and winter. Additionally, changes in the seasonal sea level cycle may affect groundwater dynamics and the inundation characteristics of intertidal ecosystems.

Projected sea-level changes in the marginal seas near China based on dynamical downscaling

AbstractProjections of future sea-level changes are usually based on global climate models (GCMs). However, the changes in shallow coastal regions, like the marginal seas near China, cannot be fully resolved in GCMs. To improve regional sea-level simulations, a high-resolution (~8 km) regional ocean model is set up for the marginal seas near China for both the historical (1994-2015) and future (2079-2100) periods under representative concentration pathways (RCPs) 4.5 and 8.5. The historical ocean simulations are evaluated at different spatiotemporal scales, and the model is then integrated for the future period, driven by projected monthly climatological climate change signals from 8 GCMs individually via both surface and open boundary conditions. The downscaled ocean changes derived by comparing historical and future experiments reveal greater spatial details than those from GCMs, e.g., a low dynamic sea level (DSL) centre of -0.15 m in the middle of the South China Sea (SCS). As a novel test, the downscaled results driven by the ensemble mean forcings are almost identical with the ensemble average results from individually downscaled cases. Forcing of the DSL change and increased cyclonic circulation in the SCS are dominated by the climate change signals from the Pacific, while the DSL change in the East China marginal seas is caused by both local atmosphere forcing and signals from the Pacific. The method of downscaling developed in this study is a useful modelling protocol for adaptation and mitigation planning for future oceanic climate changes.

Variability and upward trend in the kinetic energy of western boundary currents over the last century: impacts from barystatic and dynamic sea level change

Global sea level reconstruction (RecSL) for 1900–2015 was used to estimate the variations in oceanic kinetic energy (OKE) and compare OKE with changes in wind patterns and wind kinetic energy (WKE); the comparison was done for each latitude and for 5 western boundary currents (WBCs). Two contributors to variability in sea level were analyzed: gravitational, rotational and deformational effects (GRD) related to changes in water masses (barystatic sea level change), and changes in the sterodynamic sea level (SDSL), associated with changes in wind, steric sea level and ocean circulation. GRD changes were responsible for latitudinal multidecadal variations with time scale of ~ 60 to 80 years, while SDSL changes were responsible for interannual and decadal variability, and together with the Greenland ice melt, to sea level acceleration since the 1960s. Regional changes near WBCs show a coherent upward trend in OKE (+ 24% ± 3 increase per century), while trends in WKE over the same regions changed widely from -11% (decrease) over the Gulf Stream region to + 28% (increase) over the Brazil Current region. Low frequency oscillations of wind and oceanic kinetic energy are correlated in some WBCs (e.g., R = 0.5 in the Kuroshio region) but not in others (e.g., R = -0.05 in the Gulf Stream region). The study suggests that several forcing mechanisms contribute to the increased OKE, they include an increased wind-stress curl over subtropical gyres, local changes in wind patterns that impact some WBCs, and large uneven warming near WBCs that increased sea level gradients and thus intensified OKE.

Emulating Ocean Dynamic Sea Level by Two-Layer Pattern Scaling.

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).

Long-term Regional Dynamic Sea Level Changes from CMIP6 Projections

Anthropogenic climate forcing will cause the global mean sea level to rise over the 21st century. However, regional sea level is expected to vary across ocean basins, superimposed by the influence of natural internal climate variability. Here, we address the detection of dynamic sea level (DSL) changes by combining the perspectives of a single and a multi-model ensemble approach (the 50-member CanESM5 and a 27-model ensemble, respectively, all retrieved from the CMIP6 archive), under three CMIP6 projected scenarios: SSP1-2.6, SSP3-7.0 and SSP5-8.5. The ensemble analysis takes into account four key metrics: signal (S), noise (N), S/N ratio, and time of emergence (ToE). The results from both sets of ensembles agree in the fact that regions with higher S/N (associated with smaller uncertainties) also reflect earlier ToEs. The DSL signal is projected to emerge in the Southern Ocean, Southeast Pacific, Northwest Atlantic, and the Arctic. Results common for both sets of ensemble simulations show that while S progressively increases with increased projected emissions, N, in turn, does not vary substantially among the SSPs, suggesting that uncertainty arising from internal climate variability has little dependence on changes in the magnitude of external forcing. Projected changes are greater and quite similar for the scenarios SSP3-7.0 and SSP5-8.5 and considerably smaller for the SSP1-2.6, highlighting the importance of public policies towards lower emission scenarios and of keeping emissions below a certain threshold.

Future dynamic sea level change in the western subtropical North Pacific associated with ocean heat uptake and heat redistribution by ocean circulation under global warming

In the present study, the relative importance of ocean heat uptake and heat redistribution on future sea level changes in the western North Pacific has been reconciled based on a set of climate model experiments in which anomalous surface fluxes of wind stress, heat, and freshwater in a warmed climate are separately given to those fluxes in a pre-industrial control simulation. Our findings suggest that the basin-wide ocean heat uptake and resultant heat accumulation by the climatological-mean advection are required to explain the future dynamic sea level (DSL) rise in the western subtropical North Pacific caused by the thermal expansion of subtropical mode water (STMW). At the same time, it has been recognized that the localized heat uptake in association with the wintertime mixed-layer formation around the Kuroshio Extension can be solely attributed to the future STMW change. The thermally induced component is a dominant contribution to the future DSL rise in the western subtropical North Pacific compared to the contributions of wind-induced and halosteric components, which, especially the former, have been reported as a dominant factor resulting from a linear response of the ocean to the northward shift and strengthening of the mid-latitude westerly over the North Pacific in a warmed climate.

What causes the spread of model projections of ocean dynamic sea-level change in response to greenhouse gas forcing?

Sea levels of different atmosphere–ocean general circulation models (AOGCMs) respond to climate change forcing in different ways, representing a crucial uncertainty in climate change research. We isolate the role of the ocean dynamics in setting the spatial pattern of dynamic sea-level (ζ) change by forcing several AOGCMs with prescribed identical heat, momentum (wind) and freshwater flux perturbations. This method produces a ζ projection spread comparable in magnitude to the spread that results from greenhouse gas forcing, indicating that the differences in ocean model formulation are the cause, rather than diversity in surface flux change. The heat flux change drives most of the global pattern of ζ change, while the momentum and water flux changes cause locally confined features. North Atlantic heat uptake causes large temperature and salinity driven density changes, altering local ocean transport and ζ. The spread between AOGCMs here is caused largely by differences in their regional transport adjustment, which redistributes heat that was already in the ocean prior to perturbation. The geographic details of the ζ change in the North Atlantic are diverse across models, but the underlying dynamic change is similar. In contrast, the heat absorbed by the Southern Ocean does not strongly alter the vertically coherent circulation. The Arctic ζ change is dissimilar across models, owing to differences in passive heat uptake and circulation change. Only the Arctic is strongly affected by nonlinear interactions between the three air-sea flux changes, and these are model specific.

FGOALS-g3 Model Datasets for CMIP6 Flux-Anomaly-Forced Model Intercomparison Project

The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) is an endorsed Model Intercomparison Project in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The goal of FAFMIP is to investigate the spread in the atmosphere-ocean general circulation model projections of ocean climate change forced by increased CO2, including the uncertainties in the simulations of ocean heat uptake, global mean sea level rise due to ocean thermal expansion and dynamic sea level change due to ocean circulation and density changes. The FAFMIP experiments have already been conducted with the Flexible Global Ocean-Atmosphere-Land System Model, gridpoint version 3.0 (FGOALS-g3). The model datasets have been submitted to the Earth System Grid Federation (ESGF) node. Here, the details of the experiments, the output variables and some baseline results are presented. Compared with the preliminary results of other models, the evolutions of global mean variables can be reproduced well by FGOALS-g3. The simulations of spatial patterns are also consistent with those of other models in most regions except the North Atlantic and the Southern Ocean, indicating large uncertainties in the regional sea level projections of these two regions.

Ocean‐Only FAFMIP: Understanding Regional Patterns of Ocean Heat Content and Dynamic Sea Level Change

AbstractThere is large uncertainty in the future regional sea level change under anthropogenic climate change. Our study presents and uses a novel design of ocean general circulation model (OGCM) experiments to investigate the ocean's response to surface buoyancy and momentum flux perturbations without atmosphere‐ocean feedbacks (e.g., without surface restoring or bulk formulae), as part of the Flux‐Anomaly‐Forced Model Intercomparison Project (FAFMIP). In an ensemble of OGCMs forced with identical surface flux perturbations, simulated dynamic sea level (DSL) and ocean heat content (OHC) change demonstrate considerable disagreement. In the North Atlantic, the disagreement in DSL and OHC change between models is mainly due to differences in the residual (resolved and eddy) circulation change, with a large spread in the Atlantic meridional overturning circulation (AMOC) weakening (20–50%). In the western North Pacific, OHC change is similar among the OGCM ensemble, but the contributing physical processes differ. For the Southern Ocean, isopycnal and diapycnal mixing change dominate the spread in OHC change. In addition, a component of the atmosphere‐ocean feedbacks are quantified by comparing coupled, atmosphere‐ocean GCM (AOGCM) and OGCM FAFMIP experiments with consistent ocean models. We find that there is 10% more AMOC weakening in AOGCMs relative to OGCMs, since the extratropical North Atlantic SST cooling due to heat redistribution amplifies the surface heat flux perturbation. This component of the atmosphere‐ocean feedbacks enhances the pattern of North Atlantic OHC and DSL change, with relatively stronger increases and decreases in the tropics and extratropics, respectively.

Regional Dynamic Sea Level Simulated in the CMIP5 and CMIP6 Models: Mean Biases, Future Projections, and Their Linkages

AbstractThe ocean dynamic sea level (DSL) is an important component of regional sea level projections. In this study, we analyze mean states and future projections of the DSL from the global coupled climate models participating in phase 5 and phase 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Despite persistent biases relative to observations, both CMIP5 and CMIP6 simulate the mean sea level reasonably well. The equatorward bias of the Southern Hemisphere westerly wind stress is reduced from CMIP5 to CMIP6, which improves the simulated mean sea level in the Southern Ocean. The CMIP5 and CMIP6 DSL projections exhibit very similar features and intermodel uncertainties. With several models having a notably high climate sensitivity, CMIP6 projects larger DSL changes in the North Atlantic and Arctic associated with a larger weakening of the Atlantic meridional overturning circulation (AMOC). We further identify linkages between model mean states and future projections by looking for their intermodel relationships. The common cold-tongue bias leads to an underestimation of DSL rise in the western tropical Pacific. Models with their simulated midlatitude westerly winds located more equatorward tend to project larger DSL changes in the Southern Ocean and North Pacific. In contrast, a more equatorward location of the North Atlantic westerly winds or a weaker AMOC under current climatology is associated with a smaller weakening of the AMOC and weaker DSL changes in the North Atlantic and coastal Arctic. Our study provides useful emergent constraints for DSL projections and highlights the importance of reducing model mean-state biases for future projections.

Improving sea-level projections on the Northwestern European shelf using dynamical downscaling

Changes in ocean properties and circulation lead to a spatially non-uniform pattern of ocean dynamic sea-level change (DSLC). The projections of ocean dynamic sea level presented in the IPCC AR5 were constructed with global climate models (GCMs) from the Coupled Model Intercomparison Project 5 (CMIP5). Since CMIP5 GCMs have a relatively coarse resolution and exclude tides and surges it is unclear whether they are suitable for providing DSLC projections in shallow coastal regions such as the Northwestern European Shelf (NWES). One approach to addressing these shortcomings is dynamical downscaling – i.e. using a high-resolution regional model forced with output from GCMs. Here we use the regional shelf seas model AMM7 to show that, depending on the driving CMIP5 GCM, dynamical downscaling can have a large impact on DSLC simulations in the NWES region. For a business-as-usual greenhouse gas concentration scenario, we find that downscaled simulations of twenty-first century DSLC can be up to 15.5 cm smaller than DSLC in the GCM simulations along the North Sea coastline owing to unresolved processes in the GCM. Furthermore, dynamical downscaling affects the simulated time of emergence of sea-level change (SLC) above sea-level variability, and can result in differences in the projected change of the amplitude of the seasonal cycle of sea level of over 0.3 mm/yr. We find that the difference between GCM and downscaled results is of similar magnitude to the uncertainty of CMIP5 ensembles used for previous DSLC projections. Our results support a role for dynamical downscaling in future regional sea-level projections to aid coastal decision makers.

Identifying sites of high geoarchaeological potential using aerial LIDAR and GIS on Quadra Island, Canada

The dynamic environmental history and relative sea level (RSL) changes experienced on the Northwest Coast of North America during the early post-glacial period and the early Holocene resulted in significant archaeological visibility challenges for prospection of early coastal archaeological sites. This study offers an integrated methodological approach in support of locating palaeo-coastal sites by combining: (1) geomorphic interpretation of landscape attributes captured by LIDAR (Light Detection and Ranging) mapping; (2) GIS-based archaeological site potential mapping; and (3) local RSL history. The RSL history for the study site (Quadra Island, British Columbia, Canada) shows notable regression over the past 14,300 years from a highstand of at least 197 m resulting from post-glacial isostatic rebound. Late Pleistocene and early Holocene palaeo-shorelines are found inland from, and elevated above, modern sea level and represent key areas for archaeological prospecting. Bare-earth Digital Terrain Models (DTMs) derived from the LIDAR dataset were interpreted to identify palaeo-shorelines at 10 m and 30 m above mean sea level. A GIS-derived map was created to identify regions of high archaeological potential. Field validation suggests that this integrated methodology provides a promising approach for archaeological prospection that could be applied to other post-glacial coastal settings.

Climate Model Uncertainty and Trend Detection in Regional Sea Level Projections: A Review

Projections of future sterodynamic sea level change from global climate models are associated with different sources of uncertainty. From a scientific, societal and policy-making perspective, it is relevant to both understand and reduce uncertainty in projections of climate change. Here, we review recent findings which describe, and shed light on, climate model uncertainty focusing particularly on two types of model uncertainty that contribute to the currently large spread in dynamical sea level patterns (i.e., regional sea level relative to the global mean). These uncertainties are: (1) intermodel uncertainty due to differences in models’ responses in a warming climate and (2) internal model variability due to an individual model’s own climate variability. On timescales longer than about 50 years from now, anthropogenic sterodynamic (dynamic plus global mean) sea level trends from middle- and high-end forcing scenarios will be larger than internal model variability. By 2100, these anthropogenic trends will also be larger than intermodel uncertainty when global mean thermosteric sea level rise and/or melting contributions from land ice are considered along with dynamic sea level changes. Furthermore, we discuss projections of future coastal sea level from the perspective of global climate models as well as from downscaled efforts based on regional climate models. Much knowledge and understanding has been achieved in the last decade from intermodel experiments and studies of sea level process-based model; here, the prospects for improving coastal sea level and reducing sea level uncertainty are discussed.

Understanding the Uncertainty in the 21st Century Dynamic Sea Level Projections: The Role of the AMOC

AbstractClimate models show that the largest uncertainties in the 21st century dynamic sea level (DSL) projections are in the high latitudes of the North Atlantic and Southern Oceans. We conduct an intermodel singular value decomposition analysis and find that the DSL uncertainties in these two oceans are both intrinsically connected to the uncertainty in the change of the Atlantic meridional overturning circulation (AMOC). We further conduct a freshwater hosing experiment to show that the AMOC decline not only accounts for the dipole pattern in the DSL change in the North Atlantic but also remotely induces a poleward shift in the Southern Hemisphere westerlies that helps build a belted pattern of DSL change in the Southern Ocean. Our results suggest that reducing the intermodel spread in the change of the AMOC can greatly improve the consistency of DSL projection among models not only in individual basins but over the global ocean.