Sea Level Dataset Research Articles

Comprehensive comparative analysis of reconstructed sea level datasets in the China Seas: insights from tide gauge and satellite altimetry

At present, there are many reconstructed datasets at the global scale. To test the applicability of these datasets in the China seas, the study comprehensively analyzes the reliability and accuracy of reconstructed sea level datasets in capturing nuanced temporal patterns of sea level changes in the China Seas. This study applied analysis methods or indicators such as time series, Taylor plots, correlation coefficients, growth rates, and standard deviations. Ocean Data Assimilations (ODAs) outperform Tide Gauge Reconstructions (TGRs) in terms of correlation with measured data in the nearshore, while TGRs exhibit superior capability in capturing oceanic sea level variability. Although the ODAs and TGRs both suffer from the underestimation of sea level variability in China as well as in neighboring seas, the TGRs perform better than the former. ODAs show inconsistency in reflecting the rate of sea level rise, but they, particularly the China Ocean Reanalysis (CORA), demonstrate a better correlation with satellite altimetry datasets. Meanwhile, both of them can reflect the Pacific Decadal Oscillation (PDO) well. TGRs, relying on oceanic tide gauge stations, suffer from poor correlation with tide gauge stations due to limited coverage. Reconstruction discrepancies are attributed to methodological differences and data assimilation techniques. Future studies should explore alternative variables like sea surface temperature and so on to enhance sea-level reconstruction, especially in regions with sparse tide gauge coverage.

Waiting Times for Sea Level Variations in the Port of Trieste: A Computational Data-Driven Study

We report here a series of detailed statistical analyses on the sea level variations in the Port of Trieste using one of the largest existing data catalogues that covers more than a century of measurements. We show that the distribution of waiting times, which are defined here akin to econophysics, namely the series of shortest time spans between a given sea level L and the next sea level of at least L + δ in the catalogue, exhibits a distinct scale-free character for small values of δ. For large values of δ, the shape of the distribution depends largely on how one treats the periodic components embedded in the sea level dataset. We show that direct analyses of the raw dataset yield distributions similar to the exponential distribution, while pre-processing the sea level data by means of a local averaging numerical recipe leads to Pareto-Tsallis distributions.

Sea Level Tidal Attributes in Port Said Harbor, Eastern Egyptian Mediterranean Coast

Observed sea level data attained from a pressure sensor tide gauge, installed inside Port Said harbor in Egypt, was utilized to modernize tidal characteristics and surges in the study area. Five years of hourly sea level dataset (June 2010 to June 2015) were analyzed using the harmonic analysis approach of Delft-3D Tide suit. The results of the analysis revealed that the semi-diurnal constituents (M2, S2), together with the solar annual (Sa) dominate tide behavior in the area. Furthermore, a semidiurnal tidal regime by a ratio of 0.21 is based on the form factor (FF) equation. Moreover, tidal asymmetry (Ar.) shows a flood tide with a short period of a value equal to 0.01068 > 0.01, which reflects a tide wave distortion. From power spectral analysis, the sea-level change is controlled by both the significant tidal and non-tidal (storm surge) components by almost an equal percentage of 50.63 % and 49.37 % respectively. Additionally, the residual from sea level harmonic analysis was annually correlated with the meteorological parameters of wind, temperature, and atmospheric pressure to estimate their effect on Sea-Level Rise (SLR). A small positive trend line of SL was distinguished in the years from 2011 to 2015 by approximately (2 mm/yr.) due to the weak correlation of meteorological parameters, in conjunction with a conventional relationship with atmospheric pressure and temperature. In 2010, a slight negative linear tendency was noticed of 0.3 mm/yr., which can be related to the direct proportional relation of atmospheric pressure and surge component, besides an inversely proportional relation of air temperature and residual component, regardless of the weak correlation with wind vector. Overall, the research provides insights into the tidal characteristics, surges, and sea-level rise in Port Said Harbor. Understanding these attributes serves the objective of this paper to assess the impact of sea-level rise and develop appropriate adaptation strategies in coastal areas

Long-Term and Decadal Sea-Level Trends of the Baltic Sea Using Along-Track Satellite Altimetry

One of the main effects of climate change is rising sea levels, which presents challenges due to its geographically heterogenous nature. Often, contradictory results arise from examining different sources of measurement and time spans. This study addresses these issues by analysing both long-term (1995–2022) and decadal (2000–2009 and 2010–2019) sea-level trends in the Baltic Sea. Two independent sources of data, which consist of 13 tide gauge (TG) stations and multi-mission along-track satellite altimetry (SA), are utilized to calculate sea-level trends using the ordinary least-squares method. Given that the Baltic Sea is influenced by geographically varying vertical land motion (VLM), both relative sea level (RSL) and absolute sea level (ASL) trends were examined for the long-term assessment. The results for the long-term ASL show estimates for TG and SA to be 3.3 mm/yr and 3.9 mm/yr, respectively, indicating agreement between sources. Additionally, the comparison of long-term RSL ranges from −2 to 4.5 mm/yr, while ASL varies between 2 and 5.4 mm/yr, as expected due to the VLM. Spatial variation in long-term ASL trends is observed, with higher rates in the northern and eastern regions. Decadal sea-level trends show higher rates, particularly the decade 2000–2009. Comparison with other available sea-level datasets (gridded models) yields comparable results. Therefore, this study evaluates the ability of SA as a reliable source for determining reginal sea-level trends in comparison with TG data.

Variance in the accuracy of tidal levels with increasing data length

The Highest Astronomical Tide level (HAT) is derived from sea level datasets of sufficient length to encapsulate the lunar nodal cycle. HAT based on datasets of 35, 90, 180 and 400 days was determined for 14 sites. The difference between HAT based on short datasets and on 20-year datasets indicate that short datasets gave an average difference of 0.22 to 0.24 m. Increasing the length to 400 days decreased the difference to 0.06 m. Sites with diurnal form gave a larger difference of 0.4 to 0.9 metres. Inferring shallow water tidal constituents from the nearest long-term site reduced the difference to 0.15 to 0.19 m.

A newly reconciled dataset for identifying sea level rise and variability in Dublin Bay

Abstract. We provide an updated sea level dataset for Dublin for the period 1938–2016 at yearly resolution. Using a newly collated sea level record for Dublin Port, as well as two nearby tide gauges at Arklow and Howth Harbour, we perform data quality checks and calibration of the Dublin Port record by adjusting the biased high water level measurements that affect the overall calculation of mean sea level (MSL). To correct these MSL values, we use a novel Bayesian linear regression that includes the mean low water values as a predictor in the model. We validate the re-created MSL dataset and show its consistency with other nearby tide gauge datasets. Using our new corrected dataset, we estimate a rate of sea level rise of 1.1 mm yr−1 during 1953–2016 (95 % credible interval from 0.6 to 1.6 mm yr−1), and a rate of 7 mm yr−1 during 1997–2016 (95 % credible interval from 5 to 8.8 mm yr−1). The overall sea level rise is in line with expected trends, but large multidecadal variability has led to higher rates of rise in recent years.

Digitising historical sea level records in the Thames Estuary, UK

London is one of the world’s most important coastal cities and is located around the Thames Estuary, United Kingdom (UK). Quantifying changes in sea levels in the Thames Estuary over the 20th century and early part of the 21st century is vital to inform future management of flood risk in London. However, there are currently relatively few long, digital records of sea level available in the Thames. Here we present a new extensive sea level dataset that we have digitised from historical hand-written tabulated ledgers of high and low water, from the Port of London Authority (PLA). We captured 463 years of data, from across 15 tide gauge sites, for the period 1911 to 1995. When these historical datasets are combined with digital records available from the PLA since 1995, the sea level time-series span the 111-year period from 1911 to 2021. This new dataset will be of great importance for ongoing monitoring of mean sea-level rise, and changes in tidal range and extreme sea levels in the Thames Estuary.

Australian Coastal Flooding Trends and Forcing Factors

AbstractUsing the new Australian National Collection of Homogenized Observations of Relative Sea Level (ANCHORS) dataset, we assess trends in Australian relative sea levels over recent decades and subsequent coastal flooding impacts. We estimate a gauge average rate of mean sea level rise over the 1966–2019 period of 1.94 mm/yr with local variations around the Australian continent. Simultaneously, the frequency of coastal flooding impacts has increased at many major Australian cities including Sydney, Melbourne, Brisbane, Adelaide, and Perth. We find that this increase is not because storm surges are getting larger or more frequent, but because tides are reaching higher levels as they rise and fall about higher mean sea levels. This demonstrates that a major shift in the processes that lead to coastal flooding is underway, arising directly from global mean sea level rise, and is consistent with findings from the United States. This suggests that new perspectives on extreme sea levels are required, so research can be more impact‐based and meet the needs of policymakers planning for these impacts. Considering extreme sea levels more broadly, we show that the seasonality of extreme sea levels is closely linked to the monthly variability in the heights of the highest tides. This framework provides a holistic assessment of coastal flood risk in Australia, based on established impact‐based methodologies.

ANCHORS: A multi‐decadal tide gauge dataset to monitor Australian relative sea level changes

AbstractHere, we describe a new national tide gauge‐based sea level dataset for monitoring sea level changes around Australia, and the novel homogenization methodology used to develop it. Homogenization is a two‐step process that involves the detection of jumps or steps in the data (inhomogeneities) followed by a correction applied to remove the change. This new dataset is called the Australian National Collection of Homogenized Observations of Relative Sea Level (ANCHORS). ANCHORS provides coastal sea levels at hourly resolution with homogenization performed on annual means. ANCHORS is intended to be a national tide gauge‐based sea level dataset to monitor changes in mean sea level and resultant coastal flood frequency changes around Australia. Whilst sea levels are rising around Australia in response to global mean sea level changes, coastal water levels represent a notable gap in the suite of in situ high‐quality datasets available for researchers, governments and industry. Tide gauge datasets are well suited to impact‐based assessments of changes in flood frequency, duration and risk. In this regard, ANCHORS will sit alongside existing satellite‐ and numerical modelling‐based sea level datasets to provide enhanced insights into the physical impacts of sea level rise on Australian coastlines. We have adapted established homogenization techniques to develop a national collection of homogenous long tide gauge records. The dataset comprises 38 tide gauge records from around Australia, varying in length from 34 to 123 years, with an average of 57 years. Finally, we discuss limitations and potential applications for ANCHORS and how these have informed the design of this coastal sea level dataset.

Copernicus Sea Level Space Observations: A Basis for Assessing Mitigation and Developing Adaptation Strategies to Sea Level Rise

It is essential to monitor accurately current sea level changes to better understand and project future sea level rise (SLR). This is the basis to support the design of adaptation strategies to climate change. Altimeter sea level products are operationally produced and distributed by the E.U. Copernicus services dedicated to the marine environment (CMEMS) and climate change (C3S). The present article is a review paper that intends to explain why and to which extent the sea level monitoring indicators derived from these products are appropriate to develop adaptation strategies to SLR. We first present the main key scientific questions and challenges related to SLR monitoring. The different processing steps of the altimeter production system are presented including those ensuring the quality and the stability of the sea level record (starting in 1993). Due to the numerous altimeter algorithms required for the production, it is complex to ensure both the retrieval of high-resolution mesoscale signals and the stability of the large-scale wavelengths. This has led to the operational production of two different sea level datasets whose specificities are characterized. We present the corresponding indicators: the global mean sea level (GMSL) evolution and the regional map of sea level trends, with their respective uncertainties. We discuss how these products and associated indicators support adaptation to SLR, and we illustrate with an example of downstream application. The remaining gaps are analyzed and recommendations for the future are provided.

Minute Sea-Level Analysis (MISELA): a high-frequency sea-level analysis global dataset

Abstract. Sea-level observations provide information on a variety of processes occurring over different temporal and spatial scales that may contribute to coastal flooding and hazards. However, global research on sea-level extremes is restricted to hourly datasets, which prevent the quantification and analyses of processes occurring at timescales between a few minutes and a few hours. These shorter-period processes, like seiches, meteotsunamis, infragravity and coastal waves, may even dominate in low tidal basins. Therefore, a new global 1 min sea-level dataset – MISELA (Minute Sea-Level Analysis) – has been developed, encompassing quality-checked records of nonseismic sea-level oscillations at tsunami timescales (T<2 h) obtained from 331 tide-gauge sites (https://doi.org/10.14284/456, Zemunik et al., 2021b). This paper describes data quality control procedures applied to the MISELA dataset, world and regional coverage of tide-gauge sites, and lengths of time series. The dataset is appropriate for global, regional or local research of atmospherically induced high-frequency sea-level oscillations, which should be included in the overall sea-level extremes assessments.

North SEAL: a new dataset of sea level changes in the North Sea from satellite altimetry

Abstract. Information on sea level and its temporal and spatial variability is of great importance for various scientific, societal, and economic issues. This article reports about a new sea level dataset for the North Sea (named North SEAL) of monthly sea level anomalies (SLAs), absolute sea level trends, and amplitudes of the mean annual sea level cycle over the period 1995–2019. Uncertainties and quality flags are provided together with the data. The dataset has been created from multi-mission cross-calibrated altimetry data preprocessed with coastal dedicated approaches and gridded with an innovative least-squares procedure including an advanced outlier detection to a 6–8 km wide triangular mesh. The comparison of SLAs and tide gauge time series shows good consistency, with average correlations of 0.85 and maximum correlations of 0.93. The improvement with respect to existing global gridded altimetry solutions amounts to 8 %–10 %, and it is most pronounced in complicated coastal environments such as river mouths or regions sheltered by islands. The differences in trends at tide gauge locations depend on the vertical land motion model used to correct relative sea level trends. The best consistency with a median difference of 0.04±1.15 mm yr−1 is reached by applying a recent glacial isostatic adjustment (GIA) model. With the presented sea level dataset, for the first time, a regionally optimized product for the entire North Sea is made available. It will enable further investigations of ocean processes, sea level projections, and studies on coastal adaptation measures. The North SEAL data are available at https://doi.org/10.17882/79673 (Müller et al., 2021).

The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast

In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2–4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.

Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002\u20132018

Climate-related sea level changes in the world coastal zones result from the superposition of the global mean rise due to ocean warming and land ice melt, regional changes caused by non-uniform ocean thermal expansion and salinity changes, and by the solid Earth response to current water mass redistribution and associated gravity change, plus small-scale coastal processes (e.g., shelf currents, wind & waves changes, fresh water input from rivers, etc.). So far, satellite altimetry has provided global gridded sea level time series up to 10–15 km to the coast only, preventing estimation of sea level changes very close to the coast. Here we present a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset at monthly interval, together with associated sea level trends, at 429 coastal sites in six regions (Northeast Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, Southeast Asia and Australia). This new coastal sea level product is based on complete reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 missions.

Uncertainty in temperature and sea level datasets for the Pleistocene glacial cycles: Implications for thermal state of the subsea sediments

Abstract Temperature and sea level changes in the Pleistocene are uncertain. This leads to uncertainty in the associated response of the thermal state of the subsea sediments. We quantified the upper bound of the latter uncertainty in idealised simulations with a model for thermophysical processes in the sediments. At the coast and at the shallow and intermediate–depth shelves and except during relatively isolated time intervals, this bound for permafrost base depth and for the methane hydrate stability zone (MHSZ) characteristics (depth of its bottom boundary and its thickness) is ≤45% provided that the geothermal heat flux (GHF) is not larger than 80 mW m−2. These values are much smaller than the uncertainty metrics for the forcing data, which are typically ≥65%. However, for the intermediate shelf with a larger geothermal heat flux and for the deep shelf irrespective of GHF, different forcing time series may even lead to qualitatively different behaviour of the sediment thermophysical characteristics. We found that prescription of sea level changes plays a crucial role in uncertainty of the simulated subsea permafrost and MHSZ in the deep shelf sediments. In addition, we also quantified uncertainty for estimated apparent response time scales. The relative uncertainty for permafrost base depth and hydrate stability zone thickness time scales is ≤20% for most cases. We found no systematic dependence of our results on accounting for millennium–scale temperature variability provided that timescales of the order of 104 yr are resolved by forcing datasets.

Spatial Correlation Analysis of the Mean Sea Level Data Sets in the Coastal Seas, Korea

Spatial Correlation Analysis of the Mean Sea Level Data Sets in the Coastal Seas, Korea

Satellite Altimetry and Tide Gauge Observed Teleconnections between Long-Term Sea Level Variability in the U.S. East Coast and the North Atlantic Ocean

Rising sea levels amplify the threat and magnitude of storm surges in coastal areas. The U.S. east coast region north of Cape Hatteras has shown a significant sea level rise acceleration and is believed to be a “hot-spot” for accelerating tidal flooding. To better understand the forcing mechanism of long-term regional sea level change, in order to more efficiently implement local sea level rise adaptation and mitigation measures, this work investigated the teleconnections between low-frequency sea level variability in the coastal region north of Cape Hatteras and the subpolar/tropical North Atlantic Ocean by using tide gauge measurements, satellite altimetry data and a sea level reconstruction dataset. The correlation analysis demonstrates that the tide-gauge measured sea level variability in the area north of Cape Hatteras is highly and positively correlated with that observed by satellite altimetry in the subpolar and tropical North Atlantic between 1993 and 2002. Over the following decade (2003–2012), the phase of the teleconnection in the subpolar region was reversed and the spatio-temporal correlation in the tropical North Atlantic was enhanced. Furthermore, the positive correlation in the region north of Cape Hatteras’s near shore area is strengthened, while the negative correlation in the Gulf Stream front region is weakened. The North Atlantic Oscillation and Atlantic Multidecadal Oscillation, which affect variations of the Atlantic Meridional Overturning Circulation and Gulf Stream, were shown to have significant impacts on the decadal changes of the teleconnections. Coherent with satellite altimetry data, the reconstructed sea level dataset in the 20th century exhibits similar spatial correlation patterns with the Atlantic Meridional Overturning Circulation, North Atlantic Oscillation and Atlantic Multidecadal Oscillation indices.

Satellite Altimetry Measurements of Sea Level in the Coastal Zone

Satellite radar altimetry provides a unique sea level data set that extends over more than 25 years back in time and that has an almost global coverage. However, when approaching the coasts, the extraction of correct sea level estimates is challenging due to corrupted waveforms and to errors in most of the corrections and in some auxiliary information used in the data processing. The development of methods dedicated to the improvement of altimeter data in the coastal zone dates back to the 1990s, but the major progress happened during the last decade thanks to progress in radar technology [e.g., synthetic aperture radar (SAR) mode and Ka-band frequency], improved waveform retracking algorithms, the availability of new/improved corrections (e.g., wet troposphere and tidal models) and processing workflows oriented to the coastal zone. Today, a set of techniques exists for the processing of coastal altimetry data, generally called “coastal altimetry.” They have been used to generate coastal altimetry products. Altimetry is now recognized as part of the integrated observing system devoted to coastal sea level monitoring. In this article, we review the recent technical advances in processing and the new technological capabilities of satellite radar altimetry in the coastal zone. We also illustrate the fast-growing use of coastal altimetry data sets in coastal sea level research and applications, as high-frequency (tides and storm surge) and long-term sea level change studies.

Forecasts of Wave-Induced Coastal Hazards in the United States Pacific Islands: Past, Present, and the Future

This paper summarizes the existing coastal hazard forecast methods of PacIOOS, such as wave-induced run-up, by focusing on the critical components that need to be addressed in order to improve these forecasts and make them more accurate and available to broader coastal communities. We then propose that a horizontally, two-dimensional numerical modeling approach method should be adopted for developing future wave-induced coastal forecasts. To reach a future in which real-time two-dimensional model-based forecasts are a reality, we identify existing technologies that could lead to improvements, such as: (i) more accurate, accessible and frequently updated bathymetry and topography datasets; (ii) increased computational and software capabilities; and, (iii) more accurate sea level datasets. These advances, combined with crowdsourced-based model-data validation, will result in faster and more accurate forecasting tools that could greatly benefit coastal communities in need of more efficient risk mitigation programs.

ESTIMATING GLOBAL SEA LEVEL VARIATIONS AND RESULTING INUNDATION EXPOSURE

Concerns about climate change highlights the needs to understand extreme sea levels and the resulting flood exposure in coastal areas on a global scale. The combined impacts of storm surge, tide, breaking wave setup and potential sea level rise will pose many economic, societal and engineering challenges in coming years. In order to predict the global coastal flood risk, a global sea level dataset of sufficiently long duration is required to undertake extreme value analysis. This presentation will outline the development and application of such a dataset.