Mean Sea Level Variations Research Articles

Establishing an Integrated Permanent Sea-Level Monitoring Infrastructure towards the Implementation of Maritime Spatial Planning in Cyprus

The Maritime Spatial Planning is a piece of legislation (2014/89/EU) of the European Union that must be implemented by all member countries to enable management of their waters in a more coherent way to reduce conflicts, encourage investments, increase cross-border cooperation and protect the environment. Cyprus and Greece are working together in the frame of the THALCHOR2 project to implement this directive. From the Cyprus point of view, this directive has been a unique opportunity to modernize its Hydrographic and Geodetic Infrastructure to enable and facilitate the generation of reliable marine geospatial information. Concordantly, a network of integrated state-of-the-art multi-sensor stations has been established along the shoreline of the government-controlled territories to seamlessly monitor sea level, vertical crustal motion and meteorological parameters. This research provides insight into the implementation of this infrastructure and the data processing workflow to determine tidal levels. Furthermore, the first results acquired after exploiting two years of observations are presented along with initial aspects concerning mean sea-level variability in the Southeastern Mediterranean region.

Drivers of Interannual Sea Level Variability on the Northwestern European Shelf

AbstractSea level on the northwestern European shelf (NWES) varies substantially from year to year. Removing explained parts of interannual sea level variability from observations helps to improve estimates of long‐term sea level trends. To this end, the contributions of different drivers to interannual sea level variability need to be understood and quantified. We quantified these contributions for the entire NWES by performing sensitivity experiments with a high‐resolution configuration of the Regional Ocean Modeling System (ROMS). The lateral and atmospheric boundary conditions were derived from reanalyses. We compared our model results with satellite altimetry data and used our sensitivity experiments to show that nonlinear feedbacks cause only minor interannual sea level variability on the shelf. This indicates that our experiments can be used to separate the effects of different drivers. We find that wind dominates the variability of annual mean sea level in the southern and eastern North Sea (up to 4.7‐cm standard deviation), whereas the inverse barometer effect dominates elsewhere on the NWES (up to 1.7‐cm standard deviation). In contrast, forcing at the lateral ocean boundaries results in small and coherent variability on the shelf (0.5‐cm standard deviation). Variability driven by buoyancy fluxes ranges from 0.5‐ to 1.3‐cm standard deviation. The results of our sensitivity experiments explain the (anti)correlation between interannual sea level variability at different locations on the NWES and can be used to estimate sea level rise from observations in this region with higher accuracy.

Origin of interannual variability in global mean sea level

The two dominant drivers of the global mean sea level (GMSL) variability at interannual timescales are steric changes due to changes in ocean heat content and barystatic changes due to the exchange of water mass between land and ocean. With Gravity Recovery and Climate Experiment (GRACE) satellites and Argo profiling floats, it has been possible to measure the relative steric and barystatic contributions to GMSL since 2004. While efforts to "close the GMSL budget" with satellite altimetry and other observing systems have been largely successful with regards to trends, the short time period covered by these records prohibits a full understanding of the drivers of interannual to decadal variability in GMSL. One particular area of focus is the link between variations in the El Niño-Southern Oscillation (ENSO) and GMSL. Recent literature disagrees on the relative importance of steric and barystatic contributions to interannual to decadal variability in GMSL. Here, we use a multivariate data analysis technique to estimate variability in barystatic and steric contributions to GMSL back to 1982. These independent estimates explain most of the observed interannual variability in satellite altimeter-measured GMSL. Both processes, which are highly correlated with ENSO variations, contribute about equally to observed interannual GMSL variability. A theoretical scaling analysis corroborates the observational results. The improved understanding of the origins of interannual variability in GMSL has important implications for our understanding of long-term trends in sea level, the hydrological cycle, and the planet's radiation imbalance.

On the need for a new generation of coastal change models for the 21st century

The combination of climate change impacts, declining fluvial sediment supply, and heavy human utilization of the coastal zone, arguably the most populated and developed land zone in the world, will very likely lead to massive socio-economic and environmental losses in the coming decades. Effective coastal planning/management strategies that can help circumvent such losses require reliable local scale (<~10 km) projections of coastal change resulting from the integrated effect of climate change driven variations in mean sea level, storm surge, waves, and riverflows. Presently available numerical models are unable to adequately fulfill this need. A new generation of multi-scale, probabilistic coastal change models is urgently needed to comprehensively assess and optimise coastal risk at local scale, enabling risk informed, climate proof adaptation measures that strike a good balance between risk and reward.

Investigation of Black Sea mean sea level variability by singular spectrum analysis

The mean sea level has been continuously increasing since the end of the 19th century and will continue to increase in the 21st century. The Intergovernmental Panel on Climate Change (IPCC) states that the sea level will rise by 40-60 cm until 2100. This situation will lead to social and economic problems, especially in coastal areas. For this reason, studies on sea level determination have great importance in our country. In this paper, we used the singular spectrum analysis (SSA) to investigate mean sea level variability along the coasts of the Black Sea, which is an intercontinental inland sea. This study aimed to determine the trend in sea level change along the coasts of the Black Sea over time. The mean sea level data from 10 tide gauge stations (Amasra, Batumi, Bourgas, Constantza, Igneada, Poti, Sevastapol, Trabzon II, Tuapse and Varna) are analyzed in this study. The mean sea level data were obtained from the Permanent Service for Mean Sea Level (PSMSL). SSA was applied to the mean sea level observations at tide gauges stations, and the results were interpreted. According to the analysis results, there are increasing trends at the Batumi, Poti, Tuapse, Constantza, Sevastopol and Varna stations. The obtained trend of Bourgas station is not significant. There is The results of the Amasra, Igneada and Trabzon II tide gauge stations were inadequate in interpreting any change. There were no trends at these stations. Close eigenvalues were computed from the mean sea level at the tide gauge stations. This situation shows that there is a dominant seasonal component in the time series.

The certitude of a global sea level acceleration during the satellite altimeter era

Abstract Recent studies reported a uniform global sea level acceleration during the satellite altimetry era (1993–2017) by analyzing globally averaged satellite altimetry measurements. Here, we discuss potential omission errors that were not thoroughly addressed in detecting and estimating the reported global sea level acceleration in these studies. Our analyses results demonstrate that the declared acceleration in recent studies can also be explained equally well by alternative kinematic models based on previously well-established multi-decadal global mean sea level variations of various origins, which suggests prudence before declaring the presence of an accelerating global mean sea level with confidence during the satellite altimetry era.

Partial mortality of intertidal corals due to seasonal daytime low water levels at the Houtman Abrolhos Islands

Extensive partial mortality of intertidal corals was observed at the Houtman Abrolhos Islands, Western Australia, associated with extended and recurrent daytime low water levels from September to November 2018. Branching Acropora corals on shallow leeward reef platforms were emersed during the middle of day during the Austral spring due to diurnal tidal influences, seasonal mean sea-level minima associated with the southward flowing Leeuwin Current and interannual variability related to the El Nino–Southern Oscillation. Pre-emersion total live coral cover was estimated to be ~ 35%, dominated by Acropora (~ 24%). Post-emersion, live Acropora cover decreased to 11.1% (± 1.5 SE) and total cover to 21.7% (± 0.8 SE). Mortality of non-acroporid corals which were lower in the water column was not observed. Partial coral mortality associated with seasonal low tides and interannual variability in mean sea level is a universal process and under-reported driver of temporal variability in coral cover on intertidal reef platforms.

An extreme sea level indicator for the contiguous United States coastline

We develop an aggregated extreme sea level (ESL) indicator for the contiguous United States coastline, which is comprised of separate indicators for mean sea level (MSL) and storm surge climatology (SSC). We use water level data from tide gauges to estimate interannual to multi-decadal variability of MSL and SSC and identify coastline stretches where the observed changes are coherent. Both the MSL and SSC indicators show significant fluctuations. Indicators of the individual components are combined with multi-year tidal contributions into aggregated ESL indicators. The relative contribution of the different components varies considerably in time and space. Our results highlight the important role of interannual to multi-decadal variability in different sea level components in exacerbating, or reducing, the impacts of long-term MSL rise over time scales relevant for coastal planning and management. Regularly updating the proposed indicator will allow tracking changes in ESL posing a threat to many coastal communities, including the identification of periods where the likelihood of flooding is particularly large or small.

Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms

The estimation of an increase in sea level with sufficient warning time is important in low-lying regions, especially in the east coast of Peninsular Malaysia (ECPM). This study primarily aims to investigate the validity and effectiveness of the support vector machine (SVM) and genetic programming (GP) models for predicting the monthly mean sea level variations and comparing their prediction accuracies in terms of the model performances. The input dataset was obtained from Kerteh, Tioman Island, and Tanjung Sedili in Malaysia from January 2007 to December 2017 to predict the sea levels for five different time periods (1, 5, 10, 20, and 40 years). Further, the SVM and GP models are subjected to preprocessing to obtain optimal performance. The tuning parameters are generalized for the optimal input designs (SVM2 and GP2), and the results denote that SVM2 outperforms GP with R of 0.81 and 0.86 during the training and testing periods, respectively, at the study locations. However, GP can provide values of 0.71 and 0.79 for training and testing, respectively, at the study locations. The results show precise predictions of the monthly mean sea level, denoting the promising potential of the used models for performing sea level data analysis.

West African sea level variability under a changing climate –what can we learn from the observational period?

This study focuses on mean sea-level variability at the West African coast in the observational period (1993–2013) and its offshore waters, investigating its decadal variability, long-term trends and the large-scale climate patterns that are connected to its variability. To achieve this objective, statistically analyses is performed on several available data sets: sea-level data from tide gauges (Takoradi, Tema and Forcados), satellite altimetry (combined TOPEX/Poseidon, Jason-1 and Jason-2/OSTM), gridded sea-level reconstruction (Church et al., J Clim 17(13):2609–2625, 2004), meteorological reanalysis (NCEP), a high-resolution ocean model simulation driven by this meteorological reanalysis, and, observational data sets (The Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST1), and the Atlantic Multi-decadal Oscillation (AMO) index). Ghana is the only country along the West African coast with two relatively long sea-level records available (Takoradi and Tema), but with data quality concerns (Woodworth et. al., Afr J Mar Sci 29(3):321–330, 2007). Attempts are made to combine these two records, which cover different but overlapping periods, to construct a regional sea-level curve for Ghana (1929–1981) that may be regionally representative. A physical connection is identified between the AMO, sea-surface temperature and sea level in the Gulf of Guinea and mean sea-level trends and variability of the West African coast. It has been found that a stronger AMO is connected with higher mean sea-level in the Tropical Atlantic and in particular also at the Gulf of Guinea sea-level. This connection may explain the multidecadal variability of sea-level there, and in particular the negative trends between 1955 and 1975 and the positive trends thereafter. In addition, warmer sea surface temperatures in the Gulf of Guinea are also connected with higher sea-level, although a simple estimation based on reasonable assumptions of the thermal expansion of the water column is not sufficient to explain the connection between sea-surface-temperature and sea-level. More detailed modelling studies will be needed to explain this link. Although this study provides useful information for adaption strategies in Ghana, the research is unable to provide sea-level information between the years 1981 and 1993 because of lack of data.

Tidal variability in the Hong Kong region

Abstract. Mean sea level (MSL) is rising worldwide, and correlated changes in ocean tides are also occurring. This combination may influence future extreme sea levels, possibly increasing coastal inundation and nuisance flooding events in sensitive regions. Analyses of a set of tide gauges in Hong Kong reveal complex tidal behavior. Most prominent in the results are strong correlations of MSL variability to tidal variability over the 31-year period of 1986–2016; these tidal anomaly correlations (TACs) express the sensitivity of tidal amplitudes and phases (M2, S2, K1, O1) to MSL fluctuations and are widely observed across the Hong Kong region. At a few important harbor locations, time series of approximations of the parameter δ-HAT, computed from combinations of the major tidal constituents, are found to be highly sensitive to MSL variability, which may further increase local flood levels under future MSL rise. Other open-water locations in Hong Kong only show TACs for some individual tidal constituents but not for combined tidal amplitudes, suggesting that the dynamics in enclosed harbor areas may be partially frequency dependent and related to resonance or frictional changes. We also observe positive correlations of the fluctuations of diurnal (D1) tides to semidiurnal (D2) tides at most locations in the region, which may lead to further amplified tidal ranges under MSL. It is demonstrated here that tidal changes in the Hong Kong coastal waters may be important in combination with MSL rise in impacting future total water levels.

Imprints of wave climate and mean sea level variations in the dynamics of a coastal spit over the last 250 years: Cap Ferret, SW France

AbstractIn coastal areas, sea level rise (SLR) and changing wave climates are expected to be the main oceanic drivers of shoreline adjustments. These drivers have been shown to vary on a wide spectrum of spatial and temporal scales. Nonetheless, a general rule about how this variability impacts global shorelines remains to be articulated. Here, we discuss the impacts of wave climate changes and SLR on the evolution of a barrier spit–inlet system over the last 250 years. The distal end of the Cap Ferret barrier spit, SW France, has undergone large‐scale oscillations that were well correlated with variations of the decadal average of the winter North Atlantic Oscillation (NAO) index. The local wave climate hindcast supports that increased alongshore wave energy fluxes associated with the positive phase of the NAO were responsible for the updrift retreat of the spit. By opposition, the spit has elongated downdrift when waves were less energetic and more shore normal, as during the negative phase of the NAO. In addition, lower rates of SLR appeared to be necessary for the spit to develop, as higher rates of SLR very likely forced the adjacent inlet to enlarge, at the expense of the spit. These results should help to predict and detect coastal adjustments driven by climate change and by climate variability. © 2019 John Wiley &amp; Sons, Ltd.

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.

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.

Seasonal variations in global mean sea level and consequences on the excitation of length-of-day changes

Seasonal variations in global mean sea level and consequences on the excitation of length-of-day changes

THE DYNAMICS OF STORM SURGE AND MEAN SEA LEVEL VARIABILITY IN THE NORTHEASTERN CASPIAN SEA

Storm surge is a major natural hazard to the construction and operation of infrastructure projects in shallow and gently sloping coastal areas such as the northeastern part of the Caspian Sea. Up-surge events cause significant coastal flooding, while down-surge events disrupt marine transportation by constraining safe navigable water depths. Coastal developments therefore have to achieve a judicious balance of these conflicting constraints. Further, the unpredictability of long-term and intra-annual Mean Sea Level (MSL) variability as well as periodic freeze-up and break-up due to ice formation in this part of the Caspian Sea complicate a robust and unequivocal basis for defining storm surge hazards.

Multi-decadal variability in seasonal mean sea level along the North Sea coast

Abstract. Seasonal deviations from annual-mean sea level in the North Sea region show a large low-frequency component with substantial variability at decadal and multi-decadal timescales. In this study, we quantify low-frequency variability in seasonal deviations from annual-mean sea level and look for drivers of this variability. The amplitude, as well as the temporal evolution of this multi-decadal variability shows substantial variations over the North Sea region, and this spatial pattern is similar to the well-known pattern of the influence of winds and pressure changes on sea level at higher frequencies. The largest low-frequency signals are found in the German Bight and along the Norwegian coast. We find that the variability is much stronger in winter and autumn than in other seasons and that this winter and autumn variability is predominantly driven by wind and sea-level pressure anomalies which are related to large-scale atmospheric patterns. For the spring and summer seasons, this atmospheric forcing explains a smaller fraction of the observed variability. Large-scale atmospheric patterns have been derived from a principal component analysis of sea-level pressure. The first principal component of sea-level pressure over the North Atlantic Ocean, which is linked to the North Atlantic Oscillation (NAO), explains the largest fraction of winter-mean variability for most stations, while for some stations, the variability consists of a combination of multiple principal components. The low-frequency variability in season-mean sea level can manifest itself as trends in short records of seasonal sea level. For multiple stations around the North Sea, running-mean 40-year trends for autumn and winter sea level often exceed the long-term trends in annual mean sea level, while for spring and summer, the seasonal trends have a similar order of magnitude as the annual-mean trends. Removing the variability explained by atmospheric variability vastly reduces the seasonal trends, especially in winter and autumn.

Evaluation of sea level rise and associated responses in Hangzhou Bay from 1978 to 2017

The mean sea level, extreme sea level, and astronomical tide in Hangzhou Bay were analyzed using the tide gage data from 1978 to 2017 in Tanxu station, and the effects of rising sea levels on floods were estimated. The mean sea level in Hangzhou Bay showed a significant rising trend of 4.6 mm per year in 1978–2017. This rate was much higher than the mean sea level of the China seas, and the extreme sea level in Hangzhou Bay increased at the rate of 0.011 m per year. During 1978–2017, the mean tide range increased at the rate of 1.30 cm per year. The amplitude of M2 significantly increased at the rate of 0.57 cm per year, whereas the phase lag decreased at the rate of −0.21° per year. The amplitude and phase lag of the K1 tidal component slightly decreased at the rate of −0.03 cm per year and −0.07° per year, respectively. The changes in extreme sea level in Hangzhou Bay were mainly caused by variations in mean sea level. The coastal areas of Hangzhou Bay at risk from flooding due to the 100-year sea level return will increase by about 400 km2 by 2050.

Climate Change, Coasts and Coastal Risk

Projected climate change driven variations in mean sea level (i. [...]