Mean Sea Level Change Research Articles

Downscaling Future Longshore Sediment Transport in South Eastern Australia

Modelling investigations into the local changes in the shoreline resulting from enhanced atmospheric greenhouse gas concentrations and global climate change are important for supporting the planning of coastal mitigation measures. Analysis of Global Climate Model (GCM) and Regional Climate Model (RCM) simulations has shown that Lakes Entrance, a township located at the northern end of Ninety Mile Beach in south-eastern Australia, is situated in a region that may experience noticeable future changes in longshore winds, waves and coastal currents, which could alter the supply of sediments to the shoreline. This paper will demonstrate a downscaling procedure for using the data from GCM and RCM simulations to force a local climate model (LCM) at the beach scale to simulate additional nearshore wind-wave, hydrodynamic and sediment transport processes to estimate future changes. Two types of sediment transport models were used in this study, the simple empirical coastline-type model (CERC equation), and a detailed numerical coastal area-type model (TELEMAC). The two models resolved transport in very different ways, but nevertheless came to similar conclusions on the annual net longshore sediment transport rate. The TELEMAC model, with the Soulsby-Van Rijn formulation, showed the importance of the contribution of storm events to transport. The CERC equation estimates more transport during the period between storms than TELEMAC. The TELEMAC modelled waves, hydrodynamics and bed-evolutions are shown to agree well with the available observations. A new method is introduced to downscale GCM longshore sediment transport projections using wave-transport-directional change parameter to modify directional wave spectra. We developed a semi-empirical equation (NMB-LM) to extrapolate the ~3.7-year TELEMAC, storm dominated transport estimates, to the longer ~30-year hindcast climate. It shows that the shorter TELEMAC modelled period had twice as large annual net longshore sediment transport of the ~30 year hindcast. The CERC equation does not pick up this difference for the two climate periods. Modelled changes to the wave transport are shown to be an order of magnitude larger than changes from storm-tide current and mean sea level changes (0.1 to 0.2 m). Discussion is provided on the limitations of the models and how the projected changes could indicate sediment transport changes in the nearshore zone, which could impact the coastline position.

Uncertainty in satellite estimates of global mean sea-level changes, trend and acceleration

Abstract. Satellite altimetry missions now provide more than 25 years of accurate, continuous and quasi-global measurements of sea level along the reference ground track of TOPEX/Poseidon. These measurements are used by different groups to build the Global Mean Sea Level (GMSL) record, an essential climate change indicator. Estimating a realistic uncertainty in the GMSL record is of crucial importance for climate studies, such as assessing precisely the current rate and acceleration of sea level, analysing the closure of the sea-level budget, understanding the causes of sea-level rise, detecting and attributing the response of sea level to anthropogenic activity, or calculating the Earth's energy imbalance. Previous authors have estimated the uncertainty in the GMSL trend over the period 1993–2014 by thoroughly analysing the error budget of the satellite altimeters and have shown that it amounts to ±0.5 mm yr−1 (90 % confidence level). In this study, we extend our previous results, providing a comprehensive description of the uncertainties in the satellite GMSL record. We analysed 25 years of satellite altimetry data and provided for the first time the error variance–covariance matrix for the GMSL record with a time resolution of 10 days. Three types of errors have been modelled (drifts, biases, noises) and combined together to derive a realistic estimate of the GMSL error variance–covariance matrix. From the latter, we derived a 90 % confidence envelope of the GMSL record on a 10 d basis. Then we used a least squared approach and the error variance–covariance matrix to assess the GMSL trend and acceleration uncertainties over any 5-year time periods and longer in between October 1992 and December 2017. Over 1993–2017, we have found a GMSL trend of 3.35±0.4 mm yr−1 within a 90 % confidence level (CL) and a GMSL acceleration of 0.12±0.07 mm yr−2 (90 % CL). This is in agreement (within error bars) with previous studies. The full GMSL error variance–covariance matrix is freely available online: https://doi.org/10.17882/58344 (Ablain et al., 2018).

Glacial Ice Sheet Extent Effects on Modeled Tidal Mixing and the Global Overturning Circulation

AbstractAt present, tides supply approximately half (1 TW) of the energy necessary to sustain the global deep meridional overturning circulation (MOC) through diapycnal mixing. During the Last Glacial Maximum (LGM; 19,000–26,500 years BP), tidal dissipation in the open ocean may have strongly increased due to the 120‐ to 130‐m global mean sea level drop and changes in ocean basin shape. However, few investigations into LGM climate and ocean circulation consider LGM tidal mixing changes. Here, using an intermediate complexity climate model, we present a detailed investigation on how changes in tidal dissipation would affect the global MOC. Present‐day and LGM tidal constituents M2, S2, K1, and O1 are simulated using a tide model and accounting for LGM bathymetric changes. The tide model results suggest that the LGM energy supply to the internal wave field was 1.8–3 times larger than at present and highly sensitive to Antarctic and Laurentide ice sheet extent. Including realistic LGM tide forcing in the LGM climate simulations leads to large increases in Atlantic diapycnal diffusivities and strengthens (by 14–64% at 32°S) and deepens the Atlantic MOC. Increased input of tidal energy leads to a greater drawdown of North Atlantic Deep Water and mixing with Antarctic Bottom Water altering Atlantic temperature and salinity distributions. Our results imply that changes in tidal dissipation need be accounted for in paleoclimate simulation setup as they can lead to large differences in ocean mixing, the global MOC, and presumably also ocean carbon and other biogeochemical cycles.

The role of climate services in handling climate change risks: contributions of UKCP18

The role of climate services in handling climate change risks: contributions of UKCP18

Long-term regional trend and variability of mean sea level during the satellite altimetry era

The rise and fall of mean sea level are non-uniform around the global oceans. Their long-term regional trend and variability are intimately linked to the fluctuations and changes in the climate system. In this study, geographical patterns of sea level change derived from altimetric data over the period 1993-2015 were partitioned into large-scale oscillations allied with prevailing climatic factors after an empirical orthogonal function analysis. Taking into account the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillations (PDO), the sea level change deduced from the multiple regression showed a better estimate than the simple linear regression thanks to significantly larger coefficients of determination and narrower confidence intervals. Regional patterns associated with climatic factors varied greatly in different basins, notably in the eastern and western regions of the Pacific Ocean. The PDO exhibited a stronger impact on long-term spatial change in mean sea level than the ENSO in various parts of the Indian and Pacific Oceans, as well as of the subtropics and along the equator. Further improvements in the signal decomposition technique and physical understanding of the climate system are needed to better attain the signature of climatic factors on regional mean sea level.

Sea State Bias Variability in Satellite Altimetry Data

Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and spatial variability of the SSB correction in TOPEX, Jason-1, Jason-2 and Jason-3 missions, separately, as well as in the combined missions over the period 1993–2017. The long-term trend in global mean operational 2D non-parametric SSB correction is about −0.03 ± 0.03 mm/yr, which accounts for 1% of current global mean sea level change rate during 1993–2016. This correction contributes to sea level change rates of −1.27 ± 0.21 mm/yr and −0.26 ± 0.13 mm/yr in TOPEX-A and Jason-2 missions, respectively. The global mean SSB varies up to 7–10 mm during the very strong ENSO events in 1997–1998 and 2015–2016. Furthermore, the TOPEX SSB trend, which is consistent with recently reported sea level trend drift during 1993–1998, may leak into the determined global sea level trend in the period. Moreover, the Jason-1/2 zonal SSB variability is highly correlated with the significant wave height (SWH). On zonal average, SSB correction causes about 1% uncertainty in mean sea level trend. At high SWH regions, the uncertainties grow to 2–4% near the 50°N and 60°S bands. This should be considered in the study of regional sea level variability.

Decomposing Mean Sea Level Rise in a Semi-Enclosed Basin, the Baltic Sea

AbstractWe analyzed changes in mean sea level (MSL) for the period 1950–2015 using a regional ocean model for the Baltic Sea. Sensitivity experiments allowed us to separate external from local drivers and to investigate individual forcing agents triggering basin-internal spatial variations. The model reveals a basin-average MSL rise (MSLR) of 2.08 ± 0.49 mm yr−1, a value that is slightly larger than the simultaneous global average of 1.63 ± 0.32 mm yr−1. This MSLR is, however, spatially highly nonuniform with lower than average increases in the southwestern part (1.71 ± 0.51 mm yr−1) and higher than average rates in the northeastern parts (2.34 ± 1.05 mm yr−1). While 75% of the basin-average MSL externally enters the Baltic basin as a mass signal from the adjacent North Sea, intensified westerly winds and a poleward shift of low pressure systems explain the majority of the spatial variations in the rates. Minor contributions stem from local changes in baroclinicity leading to a basin-internal redistribution of water masses. An observed increase in local ocean temperature further adds to the total basinwide MSLR through thermal expansion but has little effect on the spatial pattern. To test the robustness of these results, we further assessed the sensitivity to six different atmospheric surface forcing reanalysis products over their common period from 1980 to 2005. The ensemble runs indicated that there are significant differences between individual ensemble members increasing the total trend uncertainty for the basin average by 0.22 mm yr−1 (95% confidence intervals). Locally the uncertainty varies from 0.05 mm yr−1 in the central part to up to 0.4 mm yr−1 along the coasts.

The Ability of Barotropic Models to Simulate Historical Mean Sea Level Changes from Coastal Tide Gauge Data

The nature of mean sea level variation over the global coastal ocean is considered based on 219 historical tide gauge records and three barotropic ocean circulation models forced by reanalysis surface air pressure and wind stress. The consistency of the models and their ability to reproduce the data are considered on nonseasonal timescales (seasonal cycles and linear trends removed) from bimonthly to multidecadal over 1900–2010. Models consistently simulate stronger sea level variability at higher latitude, higher frequency, between winters, and over broad shallow shelves and semi-enclosed marginal seas; standard deviations in modeled monthly sea level grow from 1–2 cm on average at low latitude (0°–30°) to 5–10 cm at high latitude (60°–90°), with larger values simulated over some shelf areas (e.g., North Sea). Models are more consistent over narrow shelf regions adjacent to deep basins and less consistent along the broad shallow continental shelf. On monthly timescales, discrepancies between models arise mostly from differences in model configuration (e.g., fine vs. coarse horizontal resolution), whereas model configuration and surface forcing (i.e., choice of atmospheric reanalysis) contribute comparably to model differences on annual timescales. Model solutions become more uncertain at earlier times (e.g., prior to 1950). The models show more skill explaining variance in tide gauge data at higher latitude, higher frequency, between winters, and over broad shallow shelves and within semi-enclosed marginal seas; at middle and high latitudes (poleward of 45°), model sea level solutions on average explain 30–50% of the monthly variance and 35–70% of the variance from one winter to the next in the tide gauge data records. Statistically significant relationships between the model solutions and observational data persist on long decadal periods. The relative skill of individual models is sensitive to region and timescale, such that no one model considered here consistently performs better than the others in all cases. Results suggest that barotropic models are useful for reducing noise in tide gauge records for studies of sea level rise and motivate additional model comparison studies in the context of sea level extremes.

Changes in mean sea level on the coast of Baltic Sea on tide gouge data from years 1811_2015

Changes in mean sea level on the coast of Baltic Sea on tide gouge data from years 1811_2015

Co-seismic change in ocean bottom topography: Implication to absolute global mean sea level change

Earthquakes perturb both the ocean bottom topography due to displacements of sea floor and the geoid due to mass redistribution, which induces the relative sea level (RSL) change. However, the relative global mean sea level (GMSL) change is zero in that sea water mass is conserved. But the absolute GMSL change is not zero because earthquakes displace total ocean mass with respect to the Earth's center of mass (CM) which remains unchanged after an earthquake. This displacement, i.e. the absolute GMSL change, may be detectable by altimetry since the satellites are orbiting around CM. In this paper, we proposed a method to estimate co-seismic absolute GMSL change caused by earthquakes based on the point dislocation theory for a spherically symmetric, non-rotating, elastic and isotropic (SNREI) Earth. This change can be directly connected to the perturbation of ocean bottom topography. We first computed co-seismic displacements as well as the change in geo-potential and solved the sea level equation to validate the insignificance of the oceans' feedback, i.e. the loading effect due to RSL change, to co-seismic displacements. The results imply that the loading effect due to RSL change is negligible on displacements while is considerable on geoid. We then computed the absolute GMSL change caused by co-seismic vertical and horizontal displacements by making use of the integrated Green's function method. The numerical results show that a large earthquake may raise the absolute GMSL by magnitude of sub-millimeter and the recent three large events cause GMSL to rise about one millimeter, in which the contribution from horizontal displacement is non-negligible.

Spatiotemporal variations of extreme sea levels around the South China Sea: assessing the influence of tropical cyclones, monsoons and major climate modes

With sea levels projected to rise as a result of climate change, it is imperative to understand not only long-term average trends, but also the spatial and temporal patterns of extreme sea level. In this study, we use a comprehensive set of 30 tide gauges spanning 1954–2014 to characterize the spatial and temporal variations of extreme sea level around the low-lying and densely populated margins of the South China Sea. We also explore the long-term evolution of extreme sea level by applying a dynamic linear model for the generalized extreme value distribution (DLM-GEV), which can be used for assessing the changes in extreme sea levels with time. Our results show that the sea-level maxima distributions range from ~ 90 to 400 cm and occur seasonally across the South China Sea. In general, the sea-level maxima at northern tide gauges are approximately 25–30% higher than those in the south and are highest in summer as tropical cyclone-induced surges dominate the northern signal. In contrast, the smaller signal in the south is dominated by monsoonal winds in the winter. The trends of extreme high percentiles of sea-level values are broadly consistent with the changes in mean sea level. The DLM-GEV model characterizes the interannual variability of extreme sea level, and hence, the 50-year return levels at most tide gauges. We find small but statistically significant correlations between extreme sea level and both the Pacific Decadal Oscillation and El Nino/Southern Oscillation. Our study provides new insight into the dynamic relationships between extreme sea level, mean sea level and the tidal cycle in the South China Sea, which can contribute to preparing for coastal risks at multi-decadal timescales.

Quantifying the impacts of human interventions on relative mean sea level change in the Pearl River Delta, China

Due to the impact of both natural and human-induced changes, the hydrological regimes of many river deltas worldwide have been experienced either gradual or abrupt shifts. However, little work has explored the relative impacts of natural and human-induced changes on the natural balance of these delta systems. This study explores the overall influences of intensive human interventions (e.g., dam constructions, sand excavations, and land reclamations) on the relative mean sea level (RMSL) changes in the Pearl River Delta (PRD) in China. The analysis uses long-term measurements based on monthly averaged RMSL in 26 stations and reproduces the RMSL that would have occurred in the absence of large-scale human interventions by means of a simple bivariate linear regression model. Generally, we observe that the RMSL dynamics can be categorized into three distinct types, descending, ascending and fluctuant, according to the Mann-Kendall trend test. The analysis shows that the RMSL in the upper and central parts of the PRD displays a significant descending tendency owing to the deepening of the channels, which is primarily attributed to large-scale sand excavation. In contrast, for stations near the outlets, we observed an ascending tendency in RMSL that can be attributed to the combined effects of both the rise in global sea level and channel extension due to large-scale land reclamations. The regression model confirms that the human interventions have greater impacts in the upper and central parts of the PRD that feature river-dominated dynamics, compared with the lower parts of the PRD that are characterized by tide-dominated dynamics. In addition, the simulated results display a marked seasonal alteration in the RMSL: the alteration induced by human interventions is apparently greater during the flood season than it is during the dry season. The proposed method used here to quantify the impacts of both natural and human-induced interventions on the RMSL is particularly useful for setting scientific guidelines for water managements (e.g., flood control and salt intrusion prevention) and regulation projects (e.g., dam constructions and land reclamations) in river deltas.

Sedimentary processes, stratigraphic sequences and middens: the link between archaeology and geoheritage—a case study from the Quaternary of the Broome region, Western Australia

The cliffed and active dune coastal region of Broome provides an excellent record of Pleistocene and Holocene stratigraphy of desert environments interfacing with the Indian Ocean. The Mesozoic Broome Sandstone is the basal stratigraphic unit in the area and is overlain by Pleistocene red desert quartz sand (Mowanjum Sand). Modern coastal processes of waves, wind and tide have resulted in distinctive sedimentary bodies (stratigraphic units) clearly linked to the sedimentary environment. The Mowanjum Sand, reworked by coastal winds, generates the landward-ingressing orange quartzose Churchill Sand, or reworked by waves and abraded to white sand with the addition of carbonate grains that form the beaches (Cable Beach Sand) and with eolian action, coastal dunes or inland-ingressing white dunes (Shoonta Hill Sand). These sedimentary bodies and stratigraphic units form a template with which to locate and interpret archaeological middens and Indigenous occupation over the past 5000 years in a context of coastal occupation, coastal stability, mean sea-level changes, climate changes, and availability of marine food and freshwater. Shell middens and stone artefacts form definitive layers or horizons in relation to the stratigraphy, in places in situ, and elsewhere reworked as sheets and plumes; understanding their inter-relationships has enabled the unravelling of the archaeological history and relating Indigenous occupation to biofacies and lithofacies. The array of sedimentary, biofacies and stratigraphic units are of national geoheritage significance in their own right. The addition of archaeological deposits as stratigraphic units provides a link between geoheritage and archaeology, where the archaeological materials are viewed as part of the complex stratigraphic story, part of the coastal history, and part of the geoheritage story.

Impact of terrestrial reference frame realizations on altimetry satellite orbit quality and global and regional sea level trends: a switch from ITRF2008 to ITRF2014

Abstract. A terrestrial reference frame (TRF) is a basis for precise orbit determination of Earth-orbiting satellites, since it defines positions and velocities of stations, the tracking data of which are used to derive satellite positions. In this paper, we investigate the impact of the International Terrestrial Reference Frame realization ITRF2014, as compared to its predecessor ITRF2008, on the quality of orbits, namely, on root-mean-square (rms) fits of observations and orbital arc overlaps of three altimetry satellites (TOPEX/Poseidon, Jason-1, and Jason-2) in the time interval from August 1992 to April 2015 and on altimetry products computed using these orbits, such as single-satellite altimeter crossover differences, radial and geographically correlated mean sea surface height (SSH) errors and regional and global mean sea level trends. The satellite orbits are computed using satellite laser ranging (SLR) and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) observations of a global network of stations. We have found that using ITRF2014 generally improves the orbit quality as compared to using ITRF2008. Thus, the mean values of the rms fits of SLR observations decreased (improved) by 2.4 % and 8.8 % for Jason-1 and Jason-2, respectively, but are almost not impacted for TOPEX/Poseidon when using ITRF2014 instead of ITRF2008. The internal orbit consistency in the radial direction (as derived from arc overlaps) is reduced (improved) by 6.6 %, 2.3 %, and 5.9 % for TOPEX/Poseidon, Jason-1, and Jason-2, respectively. Single-satellite altimetry crossover analyses indicate reduction (improvement) in the absolute mean crossover differences by 0.2 mm (8.1 %) for TOPEX, 0.4 mm (17.7 %) for Jason-1, and 0.6 mm (30.9 %) for Jason-2 with ITRF2014 instead of ITRF2008. The major improvement of the mean values of the rms of crossover differences (0.13 mm; 0.3 %) has been found for Jason-2. Multi-mission crossover analysis shows slight improvements in the standard deviations of radial errors: 0.1 %, 0.2 %, and 1.6 % for TOPEX, Jason-1, and Jason-2, respectively. The standard deviations of geographically correlated mean SSH errors improved by 1.1 % for Jason-1 and 5.4 % for Jason-2 and degraded by 1.3 % for TOPEX. The change from ITRF2008 to ITRF2014 orbits only has minor effects on the estimation of regional and global sea level trends over the 22-year time series from 1993 to 2015. However, on interannual timescales (3–8 years) large-scale coherent trend patterns are observed that seem to be connected to drifts between the origins of the tracking station networks. This leads to the changes in interannual global mean sea level of up to 0.06 mm yr−1 for TOPEX, 0.05 mm yr−1 for Jason-1, and up to 0.12 mm yr−1 for Jason-2, i.e., up to 4 % of the corresponding sea level signal based on altimetry for timescales of 3 to 8 years. The respective changes in the regional sea level trend on these timescales are up to 0.4 mm yr−1 in the time span from April 1993 to July 2008 and up to 1.0 mm yr−1 in the time span from July 2008 to April 2015.

Rising Sea Levels: Helping Decision-Makers Confront the Inevitable

Sea-level rise (SLR) is not just a future trend; it is occurring now in most coastal regions across the globe. It thus impacts not only long-range planning in coastal environments, but also emergency preparedness. Its inevitability and irreversibility on long time scales, in addition to its spatial non-uniformity, uncertain magnitude and timing, and capacity to drive non-stationarity in coastal flooding on planning and engineering timescales, create unique challenges for coastal risk-management decision processes. This review assesses past United States federal efforts to synthesize evolving SLR science in support of coastal risk management. In particular, it outlines the: (1) evolution in global SLR scenarios to those using a risk-based perspective that also considers low-probability but high-consequence outcomes, (2) regionalization of the global scenarios, and (3) use of probabilistic approaches. It also describes efforts to further contextualize regional scenarios by combining local mean sea-level changes with extreme water level projections. Finally, it offers perspectives on key issues relevant to the future uptake, interpretation, and application of sea-level change scenarios in decision-making. These perspectives have utility for efforts to craft standards and guidance for preparedness and resilience measures to reduce the risk of coastal flooding and other impacts related to SLR.

Uncertainty representations of mean sea-level change: a telephone game?

For the long-term management of coastal flood risks, investment and policy strategies need to be developed in light of the full range of uncertainties associated with mean sea-level rise (SLR). This, however, remains a challenge due to deep uncertainties involved in SLR assessments, many ways of representing uncertainties and a lack of common terminology for referring to these. To contribute to addressing these limitations, this paper first develops a typology of representations of SLR uncertainty by categorising these at three levels: (i) SLR scenarios versus SLR predictions, (ii) the type of variable that is used to represent SLR uncertainty, and (iii) partial versus complete uncertainty representations. Next, it is analysed how mean SLR uncertainty is represented and how representations are converted within the following three strands of literature: SLR assessments, impact assessments and decision analyses. We find that SLR assessments mostly produce partial or complete precise probabilistic scenarios. The likely ranges in the report of the Intergovernmental Panel on Climate Change are a noteworthy example of partial imprecise probabilistic scenarios. SLR impact assessments and decision analyses mostly use deterministic scenarios. In conversions of uncertainty representations, a range of arbitrary assumptions are made, for example on functional forms of probability distributions and relevant confidence levels. The loss of quality and the loss of information can be reduced by disregarding deterministic and complete precise probabilistic predictions for decisions with time horizons of several decades or centuries and by constructing imprecise probabilistic predictions and using these in approaches for robust decision-making.

Quantifying uncertainties of sandy shoreline change projections as sea level rises

Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of future mean sea-level changes, of vertical ground motions, and of other natural and anthropogenic processes affecting shoreline change variability and trends. Furthermore, the erosive impact of sea-level rise itself can be quantified using two fundamentally different models. Here, we show that this latter source of uncertainty, which has been little quantified so far, can account for 20 to 40% of the variance of shoreline projections by 2100 and beyond. This is demonstrated for four contrasting sandy beaches that are relatively unaffected by human interventions in southwestern France, where a variance-based global sensitivity analysis of shoreline projection uncertainties can be performed owing to previous observations of beach profile and shoreline changes. This means that sustained coastal observations and efforts to develop sea-level rise impact models are needed to understand and eventually reduce uncertainties of shoreline change projections, in order to ultimately support coastal land-use planning and adaptation.

Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: a Bayesian statistical approach

Changes in mean sea level (MSL) are a major, but not the unique, cause of changes in high-percentile sea levels (HSL), e.g. the annual 99.9th quantile of sea level (among other factors, climate variability may also have huge influence). To unravel the respective influence of each contributor, we propose to use structural time series models considering six major climate indices (CI) (Artic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Southern Oscillation Index, Niño 1 + 2 and Niño 3.4) as well as a reconstruction of MSL. The method is applied to eight century-long tide gauges across the world (Brest (France), Newlyn (UK), Cuxhaven (Germany), Stockholm (Sweden), Gedser (Danemark), Halifax (Canada), San Francisco (US), and Honolulu (US)). The treatment within a Bayesian setting enables to derive an importance indicator, which measures how often the considered driver is included in the model. The application to the eight tide gauges outlines that MSL signal is a strong driver (except for Gedser), but is not unique. In particular, the influence of Artic Oscillation index at Cuxhaven, Stockholm and Halifax, and of Niño Sea Surface Temperature index 1 + 2 at San Francisco appear to be very strong as well. A similar analysis was conducted by restricting the time period of interest to the 1st part of the 20th century. Over this period, we show that the MSL dominance is lower, whereas an ensemble of CI contribute to a large part to HSL time evolution as well. The proposed setting is flexible and could be applied to incorporate any alternative predictive time series such as river discharge, tidal constituents or vertical ground motions where relevant.

Extended Spectral Analysis of Tidal Variability in the North Atlantic Ocean

AbstractOcean tides have experienced large‐scale changes over the past century, in concert with regionally variable global mean sea level (MSL) rise. Additionally, there can be coherencies between MSL and tidal fluctuations that are active at shorter time scales. This combination of water level variabilities may enhance the probabilities of exceeding flood levels under high‐tide events, leading to increased frequency of short‐term coastal inundation and nuisance flooding. Previous studies have established the tidal anomaly correlation (TAC) method to analyze covariability of individual tidal components and MSL in the Pacific Ocean, as well as their combination as a proxy for the change in the highest astronomical tide (δ‐HAT). Here we extend this methodology to new regions and perform analyses of 170 tide gauges in the North Atlantic Ocean, considering the eight largest gravitational tides and seven overtides. Results indicate that nearly all gauges (95%) exhibit strong individual TACs in one or more tidal constituents, and over half show significant δ‐HATs, with a near‐equal occurrence of positive and negative tendencies. The most coherent connections of tides and MSL were found on the U.S. East Coast and in the marginal waters of Europe. At some locations, all tidal variabilities act in the same direction, which may amplify possible flood level. At other locations major parts of the tidal spectrum may counteract the MSL rise and partially mitigate extreme water levels due to tidal evolution. In either case, an understanding of regional tidal changes correlated to MSL changes can be instructive in guiding future coastal development efforts.

Observations of the Rate and Acceleration of Global Mean Sea Level Change

Observations of the Rate and Acceleration of Global Mean Sea Level Change