Absolute Sea Level Research Articles

Sea level patterns around Korea and Japan

The relative sea levels are the sum of one sea and one land component. Similar to the sea component, which is characterized by an accelerating pattern because of the thermostatic effect, the land component is characterized by an accelerating pattern because of growing subsidence. This work discusses the relative sea level patterns of Korea and Japan since the end of the 1800s. Korea has no long-term trend tide gauge of sufficient quality and length to evaluate a reliable velocity and acceleration of the sea level. On the contrary, in Japan, there are many long-term trend tide gauges recording the sea levels since 1894. The tide gauges of Hosojima, Wajima, Tonoura, and Oshoro, not suffering from subsidence or isostasy, show multi-decadal fluctuations of periodicity quasi-20 and quasi-60 years, but not rising, nor accelerating, relative sea levels. From the similarity of the patterns in the relative sea levels measured by tide gauges in Korea and the west coast of Japan since the 1960s and the similar pattern for the absolute sea levels from satellite altimetry since 1993, very likely Korea has growing relative sea levels since the 1960s only because of subsidence and short term time window.

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.

Higher quantiles of sea levels rise faster in Baltic Sea Climate projections

Absolute sea levels in the Baltic Sea will rise under the influence of climate warming, similar to those in the world ocean. For extreme sea levels, there are indications that they will rise even faster than mean sea levels, but that topic is still controversially discussed and existing studies point into different directions. We analyzed a regional climate model ensemble for the Baltic Sea for future sea level changes. We find that the rate of change differs between high sea levels and the average: In the eastern part of the Baltic Sea, the 99th percentile of sea level was predicted to rise faster than the median. In the south-western part, the relation was opposite. Thus, our simulations predict a change not only in the sea level mean, but also in its distribution. This pattern was almost consistent between the individual ensemble members. We investigated the 99th percentile as a proxy for extreme sea levels, since their partially stochastic nature limits the predictive skill of our 20-member ensemble. Our findings imply that adapting coastal protection to mean sea level change only may be regionally insufficient.

Regional variations in relative sea-level changes influenced by nonlinear vertical land motion

Vertical land movements can cause regional relative sea-level changes to differ substantially from climate-driven absolute sea-level changes. Whereas absolute sea level has been accurately monitored by satellite altimetry since 1992, there are limited observations of vertical land motion. Vertical land motion is generally modelled as a linear process, despite some evidence of nonlinear motion associated with tectonic activity, changes in surface loading or groundwater extraction. As a result, the temporal evolution of vertical land motion, and its contribution to projected sea-level rise and its uncertainty, remains unresolved. Here we generate a probabilistic vertical land motion reconstruction from 1995 to 2020 to determine the impact of regional-scale and nonlinear vertical land motion on relative sea-level projections up to 2150. We show that regional variations in projected coastal sea-level changes are equally influenced by vertical land motion and climate-driven processes, with vertical land motion driving relative sea-level changes of up to 50 cm by 2150. Accounting for nonlinear vertical land motion increases the uncertainty in projections by up to 1 m on a regional scale. Our results highlight the uncertainty in future coastal impacts and demonstrate the importance of including nonlinear vertical land motions in sea-level change projections.

Milankovitch cycles recorded by the Late Permian volcanic ash layers in southwestern China

The volcanic activity during the Cenozoic is thought to be forced by Earth's orbit, as it exhibits the Milankovitch cycle. However, the pattern of volcanic activity before the Cenozoic is still unclear. In this study, we studied the volcanic ash-bearing layers preserved in Upper Permian in Southwestern China and analyzed the cycle of volcanic activity from Emeishan Large Igneous Province (ELIP) during the waning stage of Emeishan mantle plume activity. Mineralogy, geochemistry, and gamma-ray (GR) data were used for high-resolution identification of volcanic ash-bearing layers. Al2O3/TiO2, aluminum normalized Th and Sn, and positive anomalies GR data can reflect volcanic ash input. The 206Pb/238U weighted age of zircon ranges from 256.00 ± 2.00 Ma to 251.47 ± 1.29 Ma, indicating synsedimentary volcanic ash. We apply cyclostratigraphic analysis to convert data from the depth domain to the time domain, and then utilize the multitaper method to analyze the cycle of volcanic activity of ELIP. Spectral analysis results reveal that the volcanic activity has long eccentricity (405-kyr), obliquity (∼33-kyr), and precession (∼20-kyr) periods. We propose the astronomical orbital forcing in volcanic activity during the Late Permian, and we have discovered volcanic activity cycles on a larger timescale of astronomical orbital periods (405-kyr long eccentricity). Volcanic activity was significantly correlated with sea level and climate change. During periods of low sea levels, the hot climate causes rapid sea level change, leading to rapid changes in crustal stress and strong volcanic activity. The absolute sea level controls volcanic activity, and the high sea levels suppress volcanic activity.

Offsets in tide-gauge reference levels detected by satellite altimetry: ten case studies

Comparing measurements of absolute sea level by satellite altimetry and relative sea level by a tide gauge can reveal errors in either measurement system. Combining the measurements can determine vertical land motion (VLM) at the tide gauge. We here discuss ten case studies in which a tide gauge has likely experienced a small (≤10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\le 10$$\\end{document} cm), discontinuous offset in the vertical, suggesting inadvertent loss of reference-level stability. Proper interpretation of offsets is helped if independent VLM measurements from nearby geodetic stations are available. In two cases, earthquake-induced VLM cannot be ruled out, although it appears unlikely. Offsets as small as 1–2 cm can be detected when both altimeter and tide gauge successfully observe the same ocean signal. This is most likely to occur for tide gauges located on small, open-ocean islands. Tide gauges near large land masses are typically more challenging owing to inadequacies of satellite altimetry near land and to differences between coastal and open-ocean sea levels. The case studies highlight the utility of satellite altimetry for tide-gauge quality control.

Time Series Modeling of Global Average Absolute Sea Level Change

This study aimed to demonstrate the effectiveness of time series models in modeling long-term records of global average absolute sea level changes from 1880 to 2014. Following the Box–Jenkins methodology, the ARIMA(0,1,2) model with drift was identified as the best-fit model for the time series due to its lowest AIC value. Using the LM algorithm, the results revealed that the NARNN model with 7 neurons in the hidden layer and 7 time delays exhibited the best performance among the nonlinear autoregressive neural network models, as indicated by its lower MSE. While ARIMA models excel in modeling linear problems within time series data, NARNN models are better suited for nonlinear patterns. However, a HYBRID model was explored, which combines the strengths of both ARIMA and NARNN models, offering the capability to address both linear and nonlinear aspects of time series data. The comparative analysis of this study demonstrated that the HYBRID model, with 6 neurons in the hidden layer and 7 time delays, outperformed the NARNN model with 7 neurons in the hidden layer and 7 time delays, as well as the ARIMA(0,1,2) model, with the lowest MSE in this study. These findings represent a significant step in time series forecasting by leveraging the strengths of both statistical and machine learning methods.

Sea Level Rise and Future Projections in the Baltic Sea

This article aimed to provide an overview of relative and absolute sea level rise in the Baltic Sea based on different studies, where researchers have used data from tide gauges, satellite altimetry, sea level rise, and land uplift models. These results provide an opportunity to get an overview of the sea level rise in the Baltic Sea. However, to better understand the impact of sea level rise on the coastal area of the Baltic Sea, and especially in Estonia, two post-glacial land uplift models, the latest land uplift model NKG2016LU of the Nordic Commission of Geodesy (NKG) and Estonian land uplift model EST2020VEL, were used. These models enabled to eliminate post-glacial land uplift from absolute sea level rise. To determine the relative sea level rise in the coastal area of the Baltic Sea, the rates from land uplift models were compared to ESA’s BalticSEAL absolute sea level rise model. It was found that the relative sea level rise between 1995–2019 was −5 to 4.5 mm/yr (based on NKG2016LU) in the Baltic Sea. In addition, the southern area is more affected by relative sea level rise than the northern part. During the research, it was also found that the IPCC AR5 sea level projections predict a maximum relative sea level rise in the Baltic Sea by the year 2100 of between 0.3 to 0.7 m. As coastal areas in the southern part of the Baltic Sea are predominantly flat, the sea level may reach the real estate properties by the end of the 21st century. In the coastal area of Estonia, the relative sea level rise in the period 1995–2019 was −1.1 to 3.1 mm/yr (based on NKG2016LU) and −0.3 to 3.4 mm/yr (based on EST2020VEL), the difference between the land uplift models is −0.9 to 0.1 mm/y. In Estonia, the west and southwest area are most threatened by sea level rise, where the coast is quite flat. One of the largest cities in Estonia, Pärnu, is also located there. Using the ESA’s sea level and EST2020VEL land uplift models, it was found that the relative sea level rise will be 0.28 m by the year 2100. Based on the large spatial resolution IPCC AR5 sea level projections, the relative sea level rise will be on the same scale: 0.2–0.4 m.

Prediction of Mean Sea Level with GNSS-VLM Correction Using a Hybrid Deep Learning Model in Australia

The prediction of sea level rise is extremely important for improved future climate change mitigation and adaptation strategies. This study uses a hybrid convolutional neural Network (CNN) and a bidirectional long short-term (BiLSTM) model with successive variational mode decomposition (SVMD) to predict the absolute sea level for two study sites in Australia (Port Kembla and Milner Bay). More importantly, the sea level measurements using a tide gauge were corrected using Global Navigation Satellite System (GNSS) measurements of the vertical land movement (VLM). The SVMD-CNN-BiLSTM model was benchmarked by a multi-layer perceptron (MLP), support vector regression (SVR) and gradient boosting (GB). The SVMD-CNN-BiLSTM model outperformed all the comparative models with high correlation values of more than 0.95 for Port Kembla and Milner Bay. Similarly, the SVMD-CNN-BiLSTM model achieved the highest values for the Willmott index, the Nash–Sutcliffe index and the Legates and McCabe index for both study sites. The projected linear trend showed the expected annual mean sea rise for 2030. Using the current trend, Port Kembla was projected to have an MSL value of 1.03 m with a rate rise of approx. 4.5 mm/year. The rate of the MSL for Milner Bay was comparatively lower with a value of approx. 2.75 mm/year and an expected MSL value of 1.27 m for the year 2030.

Subinertial Sea Surface Heights Anomalies Estimated Using High Frequency Radar Surface Current Data in the Mississippi Bight

AbstractSea level studies in the Mississippi Bight (MSB) are less abundant than in other coastal waters of USA. This study investigates the subinertial (time scales >2 days) sea level anomalies in the MSB shelf. The diagnostics of the terms in the invariant form of the momentum equation were computed to determine which terms have the most influence on the anomalies in sea level. It was determined that at subinertial scales the geostrophic balance is the dominant balance in the MSB while the non‐linear and time derivative terms are insignificant relative to the Coriolis term. A Least Squares procedure was applied to the subinertial surface currents data from high frequency radar surface currents (filtered with a window of 2‐day Butterworth filter) to extract subinertial sea level anomalies in the MSB shelf using both geostrophic balance and the invariant form of Reynolds' averaged momentum equations. The resulting subinertial sea level anomalies were validated using sea level observations from an offshore buoy and Sentinel‐3 along‐track satellite altimeter data. The estimated sea level anomalies were reasonably close to observations (more than half had root mean square difference of <0.04 m) and mostly influenced by geostrophic balance. Analysis of the empirical orthogonal functions showed that the first two modes explained the majority (85%) of the variance in the sea level anomalies estimated using the geostrophic approximation. Absolute sea level could be estimated if Global Navigation Satellite System buoys are deployed in the radar footprint.

Relative Sea Level Trends for the Coastal Areas of Peninsular and East Malaysia Based on Remote and In Situ Observations

Absolute sea-level rise has become an important topic globally due to climate change. In addition, relative sea-level rise due to the vertical land motion in coastal areas can have a big societal impact. Vertical land motion (VLM) in Southeast Asia includes a tectonically induced component: uplift and subsidence in plate boundary zones where both Peninsular and East Malaysia are located. In this paper, the relative sea-level trends and (seismic cycle-induced) temporal changes across Malaysia were investigated. To do so, the data (1984–2019) from 21 tide gauges were analyzed, along with a subset (1994–2021) of nearby Malaysian GNSS stations. Changes in absolute sea level (ASL) at these locations (1992–2021) were also estimated from satellite altimetry data. As a first for Peninsular and East Malaysia, the combination ASL minus VLM was robustly used to validate relative sea-level rise from tide-gauge data and provide relative sea-level trend estimates based on a common data period of 25+ years. A good match between both the remote and in situ sea-level rise estimations was observed, especially for Peninsular Malaysia (differences < 1 mm/year), when split trends were estimated from the tide gauges and GNSS time series to distinguish between the different VLM regimes that exist due to the 2004 Sumatra–Andaman megathrust earthquake. As in the south of Thailand, post-seismic-induced negative VLM has increased relative sea-level rise by 2–3 mm/year along the Andaman Sea and Malacca Strait coastlines since 2005. For East Malaysia, the validation shows higher differences (bias of 2–3 mm/year), but this poorer match is significantly improved by either not including data after 1 January 2014 or applying a generic jump to all East Malay tide gauges from that date onwards. Overall, the present relative sea-level trends range from 4 to 6 mm/year for Malaysia with a few regions showing up to 9 mm/year due to human-induced land subsidence.

Shoreline change due to global climate change and human activity at the Shandong Peninsula from 2007 to 2020

In this study, how shoreline change responses to global climate change and human activity at the Shandong Peninsula was quantified by analyzing shoreline locations, inshore erosion/accretion rates, and sandy beach profiles for 2007–2020. During the study period, the total shoreline length decreased from 3345.55 km to 3310.18 km, whereas the natural shoreline decreased by 25.41%. As a dominant shore type, the artificial shoreline increased by 827.89 km. Human activities, such as land reclamation and harbor construction, have caused continuous shoreline advance, resulting in a net land increase of 672.40 km2. However, natural shores (e.g., sandy shore) receded at an average annual rate of −1.0 m due to ongoing erosion. The inshore waters of the Shandong Peninsula were largely sedimentary as erosion occurred only at a few hotspots. Therefore, seaward sediment deposition dominated the erosion/accretion trends of the inshore areas of the peninsula. However, global climate change and human activities have exacerbated the erosion caused by sea level rise. Specifically, the climate change caused absolute sea level rise and increasing frequency of extreme weather events, whereas the human activity dominated the transport and supply of sediment in the coastal zone. In the short term, the shoreline of the Shandong Peninsula continues to advance toward the sea due to the growing artificial shoreline. However, this disrupts the balance between sediment supply and marine energies in the coastal zone, and the system then rebalance itself by eroding unprotected natural shores. In the long term, main shoreline evolution trends depend on global climate change and sea level rise which plays a decisive role in shoreline retreat in the Shandong Peninsula.

New age constraints on the MIS 9 – MIS 5.3 marine terraces of the Pontine Plain (central Italy) and implications for global sea levels

New constraints were set on the age of marine deposits in the Pontine Plain and of the related sea level indicators on the Tyrrhenian Sea coast of central Italy by twelve new 40Ar/39Ar dates on detrital sanidine from these deposits. By combining a new geomorphologic analysis and previous morpho-pedo-stratigraphic studies with these geochronological constraints we reconstructed the geometry of four marine terraces and correlated these with the highstands during the marine isotopic stages (MIS) 9.3, 7.5, 5.5 and 5.3.Results point to a progressive tilting of the terraces, the elevation increasing from the SE to the NW due to differential tectonic uplift that occurred over the last 300 ka. We identified a MIS 9 sea level at 30 - 25 m asl in the northwestern sector, whereas the MIS 7.5 sea level reached a maximum of 24 m asl in the NW and descended to 18 m asl in the central sector. Moderate tilting affected the MIS 5.5 sea level, with an elevation of 12 to 9.5 m asl in between the Anzio and Circeo headlands. Finally, an undeformed MIS 5.3 sea level at ca. 3 m asl is indicated throughout this coastal reach, confirming previous data suggesting a much higher absolute sea level during this highstand with respect to the δ18O-derived predicted level.

Coastal tides measurement in Indonesia using GNSS-Reflectometry

The important role of coastal areas in human life and their vulnerability to natural hazards such as sea level rise, make continuous monitoring of coastal ecosystem rehabilitation concerning the local sea level is urgently required. Conventional tide observation using a tide gauge sensor measures a local sea level relative to the land. Unfortunately, the effects of deformation and land subsidence around tidal stations make local tide observations irrelevant to measure absolute sea level rise. Currently, an alternative method is being developed accordingly. The method utilizes Global Navigation Satellite Systems (GNSS) signal, known as GNSS-Reflectometry (GNSS-R), to observe the tide. This research aimed to observe the sea level from the reflection of the GNSS signal. Tidal observation using GNSS-R was carried out in four Geospatial Information Agency’s tidal stations, i.e., Morotai, Piru, Tehoru, and Pasangkayu. The tide was determined based on the dominant frequency of a multipath signal, which is obtained by separating the composite signal from the direct one using 3rd order polynomial fitting. The combination of GPS and GLONASS at the L1 and L2 frequencies resulted in tide observations with an RMSE value of 18 cm. The result is 90% correlated with tidal observation using tide gauge sensor. The residual of main tidal constituent vector in both semidiurnal and diurnal components ranged from 0.01 to 0.02 m. This means that the tide prediction generated from the GNSS-R observation is statistically similar to the prediction generated from the tide gauge sensor.

Absolute Sea Level Changes Along the Coast of China From Tide Gauges, GNSS, and Satellite Altimetry

AbstractThis study quantifies the absolute sea level (ASL) change along the coast of China from 1993 to 2019 using tide gauge (TG) and Global Navigation Satellite System (GNSS) data. The sea level change at 12 collocated TG and GNSS stations along the Chinese coast are first analyzed by TG + GNSS data. Then the ASL rise and its spatial variation along the coast of China and that in surrounding oceans are studied using TG + GNSS data and satellite altimetry products. The results show that the relative sea level rise along the Chinese coast varied from 2.61 ± 0.76 to 5.56 ± 0.70 mm/yr, while the effect of vertical land motion (VLM) ranged from −1.46 ± 0.30 to 1.07 ± 0.38 mm/yr. After correcting the effect of the VLM, the ASL rise ranged from 2.51 ± 0.86 to 5.03 ± 0.60 mm/yr, with a mean rate of 3.94 ± 0.88 mm/yr, which was 0.7 mm/yr higher than the global average. It is found that ASL rise rate is significantly higher in Chinese seas and neighboring oceans, with a meridional distribution in the East China Sea and a zonal distribution in the South China Sea. This may be related to factors such as sea surface temperature rise, atmospheric pressure decrease, freshwater runoff, zonal wind stress anomaly, and alongshore currents in the area.

Estimation of vertical land motion along the south and west coast of Turkey from multi-sensor observations

This study aims to estimate Vertical Land Motion (VLM) using multi-sensor and in-situ data at the tide gauge stations (TG) located on the western and southern coasts of Turkey. The analysis of tide gauge data, used to determine sea level changes for centuries, was supported by modern global geodetic observations, and the effect of VLM on the sea level trend was determined. In this context, VLM was calculated from the relative sea level trends of eight TG's between 1998 and 2018 and the absolute sea level trends obtained from the CTOH Along-Track Sea Level Anomalies regional products (X-TRACK) and Copernicus Marine Environment Monitoring Service (CMEMS) improved altimetry data covering the same temporal period. GNSS (Global Navigation Satellite System) measurements give a solution of the point-wise information about VLM at TG's, whereas InSAR (Interferometric Synthetic Aperture Radar) solutions give spatial information about VLM that were calculated from Sentinel-1 data, which was put into service after 2014. The analyses carried out on Turkey's south and west coasts revealed an uplift trend at all TG's, whereas an insignificant subsidence trend was determined at the MNTS tide gauge station. When focusing on the MNTS station, in the period of 1998–2018 VLM from XTRACK minus TG and CMEMS minus TG were estimated as −0.7 ± 0.9 mm/yr and −0.5 ± 0.8 mm/yr, respectively and also during the period of 2014–2018 VLM from GNSS and InSAR were estimated as −0.6 ± 0.2 mm/yr and −0.3 ± 0.1 mm/yr, respectively.

Components of 21 years (1995–2015) of absolute sea level trends in the Arctic

Abstract. The Arctic Ocean is at the frontier of the fast-changing climate in the northern latitudes, and sea level trends are a bulk measure of ongoing processes related to climate change. Observations of sea level in the Arctic Ocean are nonetheless difficult to validate with independent measurements, and this is globally the region where the sea level trend (SLT) is most uncertain. The aim of this study is to create a satellite-independent reconstruction of Arctic SLT, as it is observed by altimetry and tide gauges (TGs). Previous studies use Gravity Recovery and Climate Experiment (GRACE) observations to estimate the manometric (mass component of) SLT. GRACE estimates, however, are challenged by large mass changes on land, which are difficult to separate from much smaller ocean mass changes. Furthermore, GRACE is not available before 2003, which significantly limits the period and makes the trend more vulnerable to short-term changes. As an alternative approach, this study estimates the climate-change-driven Arctic manometric SLT from the Arctic sea level fingerprints of glaciers, Greenland, Antarctica and glacial isostatic adjustment (GIA) with the addition of the long-term inverse barometer (IB) effect. The halosteric and thermosteric components complete the reconstructed Arctic SLT and are estimated by interpolating 300 000 temperature (T) and salinity (S) in situ observations. The SLT from 1995–2015 is compared to the observed SLT from altimetry and 12 selected tide gauges (TGs) corrected for vertical land movement (VLM). The reconstructed estimate manifests the salinity-driven halosteric component as dominating the spatial SLT pattern with variations between −7 and 10 mm yr−1. The manometric SLT in comparison is estimated to be 1–2 mm yr−1 for most of the Arctic Ocean. The reconstructed SLT shows a larger sea level rise in the Beaufort Sea compared to altimetry, an issue that is also identified by previous studies. There is a TG-observed sea level rise in the Siberian Arctic in contrast to the sea level fall from the reconstructed and altimetric estimate. From 1995–2015 the reconstructed SLT agrees within the 68 % confidence interval with the SLT from observed altimetry in 87 % of the Arctic between 65∘ N and 82∘ N (R=0.50) and with 5 of 12 TG-derived (VLM-corrected) SLT estimates. The residuals are seemingly smaller than results from previous studies using GRACE estimates and modeled T–S data. The spatial correlation of the reconstructed SLT to altimetric SLT during the GRACE period (2003–2015) is R=0.38 and R=0.34/R=0.37 if GRACE estimates are used instead of the constructed manometric component. Thus, the reconstructed manometric component is suggested as a legitimate alternative to GRACE that can be projected into the past and future.

Absolute sea level variability of Arctic Ocean in 1993–2018 from satellite altimetry and tide gauge observations

Absolute sea level variability of Arctic Ocean in 1993–2018 from satellite altimetry and tide gauge observations

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).

A deep-learning model for national scale modelling and mapping of sea level rise in Malaysia: the past, present, and future

In this study, we conducted a holistic evaluation of current and future trend in coastal sea level at the 21 stations along Malaysia’s coastline. For sea level prediction, univariate and 3 scenarios of multivariate Long Short Term Memory (LSTM) neural networks were trained with absolute sea level data and ocean-atmospheric variables. The result from the four scenario predictive models revealed that multivariate LSTM neural network trained with combined ocean-atmospheric variables performed best for modelling sea level variation, giving a mean RMSE and R accuracy of 0.060 and 0.861, respectively. The national sea level rise estimated from the average of sea level trend at all stations is 3.72 mm/yr for relative sea level and 3.68 mm/yr for absolute sea level. The 2050 and 2100 projections indicate that sea level will continue to rise but at a very slow rate with no acceleration.