Sea Level Data Research Articles

Relative sea-level data preclude major late Holocene ice-mass change in Pine Island Bay

The rapidly retreating Thwaites and Pine Island glaciers together dominate present-day ice loss from the West Antarctic Ice Sheet and are implicated in runaway deglaciation scenarios. Knowledge of whether these glaciers were substantially smaller in the mid-Holocene and subsequently recovered to their present extents is important for assessing whether current ice recession is irreversible. Here we reconstruct relative sea-level change from radiocarbon-dated raised beaches at sites immediately seawards of these glaciers, allowing us to examine the response of the earth to loading and unloading of ice in the Amundsen Sea region. We find that relative sea level fell steadily over the past 5.5 kyr without rate changes that would characterize large-scale ice re-expansion. Moreover, current bedrock uplift rates are an order of magnitude greater than the rate of long-term relative sea-level fall, suggesting a change in regional crustal unloading and implying that the present deglaciation may be unprecedented in the past ~5.5 kyr. While we cannot preclude minor grounding-line fluctuations, our data are explained most easily by early Holocene deglaciation followed by relatively stable ice positions until recent times and imply that Thwaites and Pine Island glaciers have not been substantially smaller than present during the past 5.5 kyr.

Characteristics of Ocean Waves in the Southern Ocean and Seasonal Prediction of Difficulty for the Vessels Crossing the Westerlies

In this study, the European Centre for Medium-Range Weather Forecasts reanalysis v5 (ERA5) wave height reanalysis data and sea-level pressure data from two seasonal prediction systems were used to study the wave characteristics of the Southern Ocean and the seasonal prediction of difficulty for the vessels crossing the westerlies. The results show that significant wave height, extreme wave height, and extreme wave processes were all much stronger in austral winter than in austral summer, making it more difficult for vessels to cross the westerlies in winter. Furthermore, the difficulty of crossing the westerlies has increased over the last 40 years, except in areas east of South America. We found that the monthly frequency of crossing the westerlies between 100° E and 75° W could be accurately estimated point by point using the monthly mean sea-level pressure difference between 30° S and 65° S. With a 1-month lead, the multi-model forecasts gave a fairly accurate forecast of such sea-level pressure difference signal between 150° E to 60° W for target months from May to December. Based on these assessments, we could estimate the difficulty of crossing the westerlies in some specific months in advance using a seasonal prediction system. We also found that the seasonal prediction system produced inaccurate predictions of sea-level pressure at high latitudes, which is the main barrier to further accurately estimating the difficulty of crossing the westerlies. These findings may provide support for predicting difficulty for the vessels crossing the westerlies with a 1-month lead and can provide planning for the route and the allocation of material reserves.

Characterization of Internal Tide Incoherence: Eulerian versus Lagrangian Perspectives

AbstractThe Lagrangian and Eulerian surface current signatures of a low-mode internal tide propagating through a turbulent balanced flow are compared in idealized numerical simulations. Lagrangian and Eulerian total (i.e., coherent plus incoherent) tidal amplitudes are found to be similar. Compared to Eulerian diagnostics, the Lagrangian tidal signal is more incoherent with comparable or smaller incoherence time scales and larger incoherent amplitudes. The larger level of incoherence in Lagrangian data is proposed to result from the deformation of an Eulerian internal tide signal induced by drifter displacements. Based on the latter hypothesis, a theoretical model successfully predicts Lagrangian autocovariances by relating Lagrangian and Eulerian autocovariances and the properties of the internal tides and jet. These results have implications for the separation of balanced flow and internal tides signals in the sea level data collected by the future Surface Water and Ocean Topography (SWOT) satellite mission.

Rapid sea-level rise during the first phase of the Littorina transgression in the western Baltic Sea

Glacio-isostatic adjustment (GIA) corrected limiting non-marine and marine sea-level data from the western Baltic Sea indicate a rapid relative sea-level (RSL) rise of 18 m for the first phase of the Littorina transgression using a linear age-elevation model. This accelerated RSL rise occurred in the time period 8.57 to 8.0 ka before present (BP) with an RSL rise rate of 31.5 mm/year. RSL rose from 28 m to 10 m below the mean relative sea level (bmrsl) during the time period of less than 600 years. The first phase of Littorina transgression documents the last big meltwater pulse (MWP), which has been reported also from various other regions in the world as a consequence of the final decay of the Laurentide ice sheet and additional meltwater sources from Antarctica.

Evidence for a more extensive Greenland Ice Sheet in southwestern Greenland during the Last Glacial Maximum

Abstract The maximum extent and elevation of the Greenland Ice Sheet in southwestern Greenland during the Last Glacial Maximum (LGM, 26–19.5 ka) is poorly constrained. Yet, the size of the Greenland Ice Sheet during the LGM helps to inform estimates of past ice-sheet sensitivity to climate change and provides benchmarks for ice-sheet modeling. Reconstructions of LGM ice extents vary between an inner continental shelf minimum, a mid-shelf position, and a maximum extent at the shelf break. We use three approaches to resolve LGM ice extent in the Sisimiut sector of southwestern Greenland. First, we explore the likelihood of minimum versus maximum Greenland Ice Sheet reconstructions using existing relative sea-level data. We use an empirical relationship between marine limit elevation and distance to LGM terminus established from other Northern Hemisphere Pleistocene ice sheets as context for interpreting marine limit data in southwestern Greenland. Our analysis supports a maximum regional Greenland Ice Sheet extent to the shelf break during the LGM. Second, we apply a simple 1-D crustal rebound model to simulate relative sea-level curves for contrasting ice-sheet sizes and compare these simulated curves with existing relative sea-level data. The only realistic ice-sheet configuration resulting in relative sea-level model-data fit suggests that the Greenland Ice Sheet terminated at the shelf break during the LGM. Lastly, we constrain the LGM ice-sheet thickness using cosmogenic 10Be, 26Al, and 14C exposure dating from two summit areas, one at 381 m above sea level at the coast, and another at 798 m asl 32 km inland. Twenty-four cosmogenic radionuclide measurements, combined with results of our first two approaches, reveal that our targeted summits were likely ice-covered during the LGM and became deglaciated at ca. 11.6 ka. Inventories of in situ 14C in bedrock at one summit point to a small degree of inherited 14C and suggest that the Greenland Ice Sheet advanced to its maximum late Pleistocene extent at 17.1 ± 2.5 ka. Our results point to a configuration where the southwestern part of the Greenland Ice Sheet reached its maximum LGM extent at the continental shelf break.

Application of RNN on GNSS Reflectometry Sea level monitoring

ABSTRACT Global Navigation Satellite System reflectometry (GNSS-R) can be used to monitor the sea level with the signal-to-noise ratio (SNR) using the spectral analysis approach where the additional frequencies in SNR lead to small errors. This study is the first attempt to apply the Recurrent Neural Networks (RNN) approach to reduce the effect of additional frequencies in SNR. The output from the RNN approach is processed by the spectral analysis to estimate the frequency. To analyse the number of effective results, all results are processed by the outlier removal method which removes the outliers only depending on the results under low elevation angles. The data set used in the experiment is sampled from the SC02 GPS station. The experiment is set up by using abnormal elevation angle ranges to observe the performance. The results from the RNN-based method, detrend SNR method and EMD-based method are compared to the reference sea level data. RNN models are trained differently in three experiments based on 7-day historical sea level data, 7-day tide prediction data and 1-month tide prediction data. The results show that the RNN increases the temporal resolutions for all experiments and provides sufficient accuracy as compared to the detrend SNR method and EMD-based method. Using tide prediction data instead of sea level data as the training data improves temporal resolutions and correlations. RNN can be applied as the data preparation and denoising method for SNR spectral analysis sea level monitoring. Compared to the EMD-based method, the RNN-based denoising method is more suitable for short SNR data records.

Sea level along the world’s coastlines can be measured by a network of virtual altimetry stations

For nearly 30 years, space-based radar altimetry has been routinely measuring changes in sea level at global and regional scales. But this technique designed for the open ocean does not provide reliable sea level data within 20 km to the coast, mostly due to land contamination within the radar echo in the vicinity of the coast. This problem can now be overcome through dedicated reprocessing, allowing the retrieval of valid sea level data in the 0-20 km band from the coast, and then the access to novel information on sea level change in the world coastal zones. Here we present sea level anomalies and associated coastal sea level trends at 756 altimetry-based virtual coastal stations located along the coasts of North and South America, Northeast Atlantic, Mediterranean Sea, Africa, North Indian Ocean, Asia and Australia. This new dataset, derived from the reprocessing of high-resolution (300 m) along-track altimetry data from the Jason-1, 2 and 3 missions from January 2002 to December 2019, allows the analysis of the decadal evolution of coastal sea level and fills the coastal gap where sparse sea level information is currently available.

Uncertainty in GRACE/GRACE-follow on global ocean mass change estimates due to mis-modeled glacial isostatic adjustment and geocenter motion

Global mean sea level has increased about 3 mm/yr over several decades due to increases in ocean mass and changes in sea water density. Ocean mass, accounting for about two-thirds of the increase, can be directly measured by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) satellites. An independent measure is obtained by combining satellite altimetry (measuring total sea level change) and Argo float data (measuring steric changes associated with sea water density). Many previous studies have reported that the two estimates of global mean ocean mass (GMOM) change are in good agreement within stated confidence intervals. Recently, particularly since 2016, estimates by the two methods have diverged. A partial explanation appears to be a spurious variation in steric sea level data. An additional contributor may be deficiencies in Glacial Isostatic Adjustment (GIA) corrections and degree-1 spherical harmonic (SH) coefficients. We found that erroneous corrections for GIA contaminate GRACE/GFO estimates as time goes forward. Errors in GIA corrections affect degree-1 SH coefficients, and degree-1 errors may also be associated with ocean dynamics. Poor estimates of degree-1 SH coefficients are likely an important source of discrepancies in the two methods of estimating GMOM change.

Constraining rapid sea level change through radiometric dating of corals growing over a range in paleowater depths

Corals do not all grow near the sea surface. Different species favour different ranges in depth and can survive at different depths from 0 to 5 m to over 0–100 m. Fossil corals, as markers of sea level, are the preferred choice in radiometric dating. Timing and magnitude of sea-level variations are determined from the location and age of a set of in-situ coral samples, and mark the lower bound in sea level. In addition, they have to be assigned an uncertainty to define the upper bound in sea level. This is referred to as the paleowater depth (PWD) and creates a major ambiguity in estimating the appropriate span of habitable depth in sea level. This uncertainty also has an impact on constraining the timing and magnitude of rapid changes in sea level. However, there are approaches that may minimize PWD uncertainties. These include assessing sea level data for groups of coral, during relatively stable sea levels, rather than individually. If samples were recovered in multiple drill-cores, along a sea-bed transect, tighter PWD constraints may apply for samples, in each core, depending on the magnitude of the slope of the sea bed. This method is particularly useful in cases of rapid sea level change over shallow continental shelves when the shift in the shoreline, with sea level change, is large. In these circumstances, the presence of a shallow-water reef established up or down-slope is indicative of a rapid change in sea level.

Time Trends and Persistence in US Sea Level Data: An Investigation Using Fractional Integration Methods

This paper analyses US sea level data using long memory and fractional integration methods. Specifically, monthly data for 41 US stations covering the period from January 1950 to December 2018 are examined. Fractional integration methods suggest that all series exhibit orders of integration in the interval (0, 1), which implies long-range dependence with positive values of the differencing parameter; further, significant positive time trends are found in the case of 29 stations located on the East Coast and the Gulf of Mexico, and negative ones in the case of four stations on the North West Coast, but none for the remaining 8 on the West Coast. The highest degree of persistence is found for the West Coast stations and the lowest for the East Coast ones. Thus, in the event of shocks, more decisive action is required in the case of West Coast stations for the series to revert to their original trend.

What are the drivers of Caspian Sea level variation during the late Quaternary?

Quaternary Caspian Sea level variations depended on geophysical processes (affecting the opening and closing of gateways and basin size/shape) and hydro-climatological processes (affecting water balance). Disentangling the drivers of past Caspian Sea level variation, as well as the mechanisms by which they impacted the Caspian Sea level variation, is much debated. In this study we examine the relative impacts of hydroclimatic change, ice-sheet accumulation and melt, and isostatic adjustment on Caspian Sea level change. We performed model analysis of ice-sheet and hydroclimate impacts on Caspian Sea level and compared these with newly collated published palaeo-Caspian sea level data for the last glacial cycle. We used palaeoclimate model simulations from a global coupled ocean-atmosphere-vegetation climate model, HadCM3, and ice-sheet data from the ICE-6G_C glacial isostatic adjustment model. Our results show that ice-sheet meltwater during the last glacial cycle played a vital role in Caspian Sea level variations, which is in agreement with hypotheses based on palaeo-Caspian Sea level information. The effect was directly linked to the reorganization and expansion of the Caspian Sea palaeo-drainage system resulting from topographic change. The combined contributions from meltwater and runoff from the expanded basin area were primary factors in the Caspian Sea transgression during the deglaciation period between 20 and 15 kyr BP. Their impact on the evolution of Caspian Sea level lasted until around 13 kyr BP. Millennial scale events (Heinrich events and the Younger Dryas) negatively impacted the surface water budget of the Caspian Sea but their influence on Caspian Sea level variation was short-lived and was outweighed by the massive combined meltwater and runoff contribution over the expanded basin.

SeeLevelViz: A simple data science tool for dynamic visualization of shoreline displacement caused by sea-level change

We present SeeLevelViz, a free, open-source program written in Python for making interactive visualizations of relative sea-level change in landscapes and shorelines. The accurate reconstruction of shoreline positions is a crucial factor in coastal palaeolandscape studies, particularly in areas where the coast is fronted by islands, since the separation of islands from the mainland drives important ecological and sociocultural outcomes. This program creates accurate time-slice reconstructions of shoreline positions and palaeolandscapes when the user provides two components: 1) a digital elevation model of the target region (including currently submerged areas), and 2) a simple spreadsheet of relative sea-level elevations at different dates derived either from a glacio isostatic adjustment model of relative sea-level change, or from observed past sea-level data points. The tool is presented using the eastern coast of the Adriatic Sea in the Mediterranean as a test case, since this region has a complex coastline articulation due to combined geological and geomorphological factors. In this area, like in many other Mediterranean coastal areas, the separation of islands from the mainland following the last glacial maximum and throughout the Holocene has occurred in connection with important phases of the development, particularly of Mesolithic and Neolithic cultures, influencing human migrations and the spread of seafaring techniques. Reliable palaeolandscape reconstructions at different time slices are thus crucial for supporting archaeological interpretation. Flexibile and user-friendly, SeeLevelViz can compliment reconstructions of coastal landscape changes either based on glacial isostatic adjustment models or on relative palaeo-sea- level evidence, since simple, interactive visualizations are a powerful technique for understanding spatial time-series data, both for the interpretation phase of research, and for presentation to colleagues and the public. The program can be modified or used freely for papers, presentations, etc. By crediting and citing this article.

Correlation of wind waves and sea level variations on the coast of the seasonally ice-covered Gulf of Finland

Abstract. Both sea level variations and wind-generated waves affect coastal flooding risks. The correlation of these two phenomena complicates the estimates of their joint effect on the exceedance levels for the continuous water mass. In the northern Baltic Sea the seasonal occurrence of sea ice further influences the situation. We analysed this correlation with 28 years (1992–2019) of sea level data, and 4 years (2016–2019) of wave buoy measurements from a coastal location outside the City of Helsinki, Gulf of Finland in the Baltic Sea. The wave observations were complemented by 28 years of simulations with a parametric wave model. The sea levels and significant wave heights at this location show the strongest positive correlation (τ=0.5) for southwesterly winds, while for northeasterly winds the correlation is negative (−0.3). The results were qualitatively similar when only the open water period was considered, or when the ice season was included either with zero wave heights or hypothetical no-ice wave heights. We calculated the observed probability distribution of the sum of the sea level and the highest individual wave crest from the simultaneous time series. Compared to this, a probability distribution of the sum calculated by assuming that the two variables are independent underestimates the exceedance frequencies of high total water levels. We tested nine different copulas for their ability to account for the mutual dependence between the two variables.

Characteristics of seasonal changes of the Baltic Sea extreme sea levels

This work analyses the monthly spatial distribution of extreme sea levels in the Baltic Sea as well as the relationship of these levels with the NAO and AO indicators. The research was based on hourly sea level data from the 45 tide gauge stations gathered in the years 1960 to 2020. The analysis shows that the duration of extreme sea levels tends to increase moving from along the line joining the open sea and the gulf end. This is associated with the narrowing of the gulf and the geomorphological and bathymetric configuration of the coastal zone. The duration of high and low sea levels in the Baltic Sea decreases from a maximum in January to a minimum in the months of May to August, then it increases again until the end of the year. This cycle corresponds well to the annual occurrence of storm surges, which are affected by the annual changes in atmospheric circulation. The impact of the variations of the circulation on extreme sea levels was confirmed by examining the relation between maximum, minimum and mean levels of the Baltic waters and the zone circulation indices NAO and AO for each month of the year and the seasons in the multiyear period 1960–2020. The results indicate that the strongest correlations exist between sea levels and NAO/AO in the winter months. There is a spatial differentiation of the correlation and its increase from the southwest to the northeast in Baltic Sea.

Pictures Matter: How Images of Projected Sea-Level Rise Shape Long-Term Sustainable Design Decisions for Infrastructure Systems

Community input matters in long-term decisions related to climate change, including the development of public infrastructure. In order to assess the effect of different ways of informing the public about infrastructure projects, a sample of people in the United States (n = 630) was provided with a case study concerning the redevelopment of the San Diego Airport. Participants received the same written information about the projected future condition of the airport. In addition, participants received images either portraying current conditions or portraying conditions in 2100 based on NOAA (National Oceanic and Atmospheric Administration) sea-level rise data. Participants were asked to choose 7 out of 21 design options to implement in the redevelopment project. The framework used for the design options stemmed from the Envision rating system. We analyzed the participants’ selection of the credits using generalized linear mixed models. Those that received the images portraying the future were significantly more likely to select design options that would reduce the risk of climate change and flooding. Images portraying sea-level rise had different effects depending on participant demographics. Such images increased the selection of design elements related to the climate and risk for participants identifying as female or as Democrat. For participants identifying as male or as Republican, the same images increased their selection of design elements to enhance community public space. The results demonstrate the positive effects of portraying the future in terms of encouraging focus on long-term sustainable design decisions for infrastructure systems.

Extension and application of an observation‐based local climate index aimed to anticipate the impact of El Niño–Southern Oscillation events on Colombia

AbstractThe Tumaco multivariate index (TMI) is a multidecadal monthly index constructed with unique time series of sea surface temperature, surface air temperature and rain measured at Tumaco bay, in the southern Pacific coast of Colombia, and available since 1961. In this work, this index is re‐evaluated after the addition of in situ sea level data, and its properties for different standardization periods are compared against oceanic El Niño–Southern Oscillation (ENSO) and other derived indices. In particular, we propose a modified TMI, hereinafter referred as TMI4, whose potential to identify the expected sign and the amount of future variations of rain induced by ENSO events in Colombia is analysed for selected extreme episodes. Results indicate that after the inclusion of sea level data, TMI4 can anticipate the development of El Niño events before the ENSO 3 and some other sea surface temperature‐based regional indices, although its predictability depends on the ENSO type (canonical or Modoki). The explanation is that sea level includes new information into TMI4 on the onset of El Niño events. In particular, the signal of intraseasonal sea level anomalies carried by downwelling Kelvin waves is detected at Tumaco tide‐gauge. Moreover, the analysis of the differences, both in magnitude and spatial distribution, of rainfall anomalies induced by positive (El Niño) and negative (La Niña) ENSO events characterized by TMI4 are regionally presented. As a result, we find that TMI4 is especially suited for extensive northern and western areas of mainland Colombia. For completeness, in the appendix we briefly introduce the semi‐automated implementation of TMI4, including a visual interface, which is currently being tested by personnel within the operational oceanography area at Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (Dimar‐CCCP).

Assessment and Prediction of Sea Level Trend in the South Pacific Region

Sea level rise is an important and topical issue in the South Pacific region and needs an urgent assessment of trends for informed decision making. This paper presents mean sea level trend assessment using harmonic analysis and a hybrid deep learning (DL) model based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique, Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Neighbourhood Component Analysis (NCA) to build a highly accurate sea level forecasting model for three small islands (Fiji, Marshall Island and Papua New Guinea (PNG)) in the South Pacific. For a 20-year period, the estimated mean sea level rise per year from the harmonic computation is obtained: 112 mm for PNG, 98 mm for Marshall Island and 52 mm for Fiji. The DL procedure uses climate and environment-based remote sensing satellite (MODIS, GLDAS-2.0, MODIS TERRA, MERRA-2) predictor variables with tide gauge base mean sea level (MSL) data for model training and development for forecasting. The developed CEEMDAN-CNN-GRU as the objective model is benchmarked by comparison to the hybrid model without data decomposition, CNN-GRU and standalone models, Decision Trees (DT) and Support Vector Regression (SVR). All model performances are evaluated using reliable statistical metrics. The CEEMDAN-CNN-GRU shows superior accuracy when compared with other standalone and hybrid models. It shows an accuracy of >96% for correlation coefficient and an error of <1% for all study sites.

An approach for constraining mantle viscosities through assimilation of palaeo sea level data into a glacial isostatic adjustment model

Abstract. Glacial isostatic adjustment is largely governed by the rheological properties of the Earth's mantle. Large mass redistributions in the ocean–cryosphere system and the subsequent response of the viscoelastic Earth have led to dramatic sea level changes in the past. This process is ongoing, and in order to understand and predict current and future sea level changes, the knowledge of mantle properties such as viscosity is essential. In this study, we present a method to obtain estimates of mantle viscosities by the assimilation of relative sea level rates of change into a viscoelastic model of the lithosphere and mantle. We set up a particle filter with probabilistic resampling. In an identical twin experiment, we show that mantle viscosities can be recovered in a glacial isostatic adjustment model of a simple three-layer Earth structure consisting of an elastic lithosphere and two mantle layers of different viscosity. We investigate the ensemble behaviour on different parameters in the following three set-ups: (1) global observations data set since last glacial maximum with different ensemble initialisations and observation uncertainties, (2) regional observations from Fennoscandia or Laurentide/Greenland only, and (3) limiting the observation period to 10 ka until the present. We show that the recovery is successful in all cases if the target parameter values are properly sampled by the initial ensemble probability distribution. This even includes cases in which the target viscosity values are located far in the tail of the initial ensemble probability distribution. Experiments show that the method is successful if enough near-field observations are available. This makes it work best for a period after substantial deglaciation until the present when the number of sea level indicators is relatively high.

A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level

Abstract. Robust, proxy-based reconstructions of relative sea-level (RSL) change are critical to distinguishing the processes that drive spatial and temporal sea-level variability. The relationships between individual proxies and RSL can be complex and are often poorly represented by traditional methods that assume Gaussian likelihood distributions. We develop a new statistical framework to estimate past RSL change based on nonparametric, empirical modern distributions of proxies in relation to RSL, applying the framework to corals and mangroves as an illustrative example. We validate our model by comparing its skill in reconstructing RSL and rates of change to two previous RSL models using synthetic time-series datasets based on Holocene sea-level data from South Florida. The new framework results in lower bias, better model fit, and greater accuracy and precision than the two previous RSL models. We also perform sensitivity tests using sea-level scenarios based on two periods of interest – meltwater pulses (MWPs) and the Holocene – to analyze the sensitivity of the statistical reconstructions to the quantity and precision of proxy data; we define high-precision indicators, such as mangroves and the reef-crest coral Acropora palmata, with 2σ vertical uncertainties within ± 3 m and lower-precision indicators, such as Orbicella spp., with 2σ vertical uncertainties within ± 10 m. For reconstructing rapid rates of change in RSL of up to ∼ 40 m kyr−1, such as those that may have characterized MWPs during deglacial periods, we find that employing the nonparametric model with 5 to 10 high-precision data points per kiloyear enables us to constrain rates to within ± 3 m kyr−1 (1σ). For reconstructing RSL with rates of up to ∼ 15 m kyr−1, as observed during the Holocene, we conclude that employing the model with 5 to 10 high-precision (or a combination of high- and low-precision) data points per kiloyear enables precise estimates of RSL within ±∼ 2 m (2σ) and accurate RSL reconstructions with errors ≲ 0.7 m. Employing the nonparametric model with only lower-precision indicators also produces fairly accurate estimates of RSL with errors ≲1.50 m, although with less precision, only constraining RSL to ±∼ 3–4 m (2σ). Although the model performs better than previous models in terms of bias, model fit, accuracy, and precision, it is computationally expensive to run because it requires inverting large matrices for every sample. The new model also provides minimal gains over similar models when a large quantity of high-precision data are available. Therefore, we recommend incorporating the nonparametric likelihood distributions when no other information (e.g., reef facies or epibionts indicative of shallow-water environments to refine coral elevational uncertainties) or no high-precision data are available at a location or during a given time period of interest.

Climate Change Impacts of Sea Level Rise on the Saemangeum Sea Dike

The Saemangeum Sea Dike, completed in 2011 in South Korea, is the longest sea dike in the world. One of the most pressing issues of today, climate change leads to sea-level rise that could increase the risk of sea dike overflow. However, what impact climate change will have on the Saemangeum Sea Dike has not been verified yet. Here, we estimate the impacts of sea-level rise on the Saemangeum Sea Dike, using the Linear Regression Analysis method, the Continuous Wavelet Transform (CWT) method, and the Ensemble Empirical Mode Decomposition (EEMD) method. The sea level data of the Saemangeum area over the last 30 years were analyzed, and the results showed that the maximum rate of sea-level rise of the Saemangeum Sea Dike is at 2.51 mm/year when the EEMD method was applied. It means that the impact of sea-level rise on the Saemangeum sea dike is reasonably low because the sea level rise will exceed the freeboard after 366 years, so there is currently no clear sign that it poses a problem.