The core of the problem lies in how scientists reconstruct sea level before the satellite era. Direct global measurements from satellite altimetry only began in late 1992, so everything we know about earlier decades comes from tide gauges, instruments that are fixed to the coast and measure the sea right at the shoreline. The most widely used reconstruction technique, known as reduced space optimal interpolation, infers empirical orthogonal functions, or EOFs, from satellite data and then fits a subset of these spatial patterns to tide gauge records to estimate how each pattern waxed and waned through time. Because long-term trends are otherwise poorly captured, a spatially uniform pattern, often called EOF0, is added to the mix, following an approach first proposed by John Church and colleagues in 2004.

That addition comes at a steep price. Previous work has shown that while EOF0 dramatically improves the estimate of the underlying long-term trend, it cripples the reconstruction’s ability to capture interannual to decadal variability. The scale of the failure is striking. When the researchers compared the detrended, de-seasoned global mean sea level from the gridded CMEMS altimetry product with the widely used Church and White 2011 reconstruction over the period 1994 to 2013, the two series showed almost no resemblance, with a correlation of minus 0.19. Worse, the reconstruction overestimated the variability by more than a factor of two, with a standard deviation of 0.45 centimeters against just 0.21 centimeters for the observed altimetry average.

Getting this variability right matters far more than academic tidiness. The year-to-year ups and downs of global sea level carry information about the global hydrological cycle, revealing how much water temporarily shifts between the ocean and the land. They also influence estimates of the long-term trend and its acceleration, the numbers that matter most for climate policy. Earlier studies found that both the warming-driven expansion of seawater and the addition of meltwater from land ice contribute roughly equally to this variability, and both are strongly tied to the El Niño-Southern Oscillation. Sea level variability is also increasingly significant in its own right, contributing to coastal flooding and erosion as the ocean warms.

The key clue came from earlier numerical experiments by Calafat and colleagues, who showed that the low skill of EOF reconstructions is largely due to differences between tide gauge records and the altimetry data at the nearest offshore points. Satellite altimetry degrades within roughly 10 to 20 kilometers of the coast, and coastal waters host real physical signals that a nadir-looking radar struggles to resolve. When the researchers replaced tide gauges with these altimetry points, effectively using them as virtual tide gauges, the reconstruction captured global variability almost perfectly, achieving a correlation of 0.98 with the true altimetry average. The differences between the two instruments, which the team calls Signal Differences, were clearly the dominant source of error, not the sparseness of the tide gauge network.

Crucially, the new study shows that these Signal Differences are not random noise. Their standard deviations range from nearly zero to 4.5 centimeters, with clusters of high values along continental coastlines, and they display strong regional coherence. Sites along the west coast of North America, the Bay of Biscay and English Channel, northeast Australia and the Río de la Plata basin each correlate strongly with their regional averages, with mean correlations between 0.62 and 0.74. A control test in which the differences were replaced with random values and the analysis repeated 100,000 times yielded a mean correlation of only 0.37, far below what the real data show. The differences are geophysical, not instrumental.

When the researchers probed what these differences actually represent, a telling pattern emerged. At 146 of 229 analyzed locations, the Signal Differences correlated significantly with the tide gauge records themselves, but at only 45 locations did they correlate with altimetry. This means the discrepancies are mostly caused by real oceanographic signals that the tide gauges detect but the altimeter does not, rather than by errors in either instrument. The likely physical mechanism is wind-driven coastal trapped waves, which propagate sea level signals over long distances along continental shelves around the world, from Europe and Australia to the United States. These waves have cross-shelf scales comparable to the shelf width, so their effects are confined to the coastal zone and may not be fully captured by altimetry.

Because the differences have a geophysical origin, they can be modeled. The team correlated the Signal Differences with the zonal and meridional components of 10-meter winds from the ERA5 reanalysis and with the Southern Oscillation Index, a normalized pressure difference between Tahiti and Darwin that tracks the El Niño-Southern Oscillation. Strong, coherent correlation patterns emerged along the Pacific coast of the United States, Australia, the United Kingdom and Japan, with absolute correlations of 0.5 or more at many sites. Building on this, the researchers constructed three multiple linear regression models at each tide gauge, progressively adding wind components, the Southern Oscillation Index and the tide gauge record itself as predictors. The full model achieved a globally averaged correlation of 0.67 with the Signal Differences and explained 49 percent of their variance, with wind alone accounting for 26 percent.

The payoff came when the best-performing model was used to correct the tide gauge data before running the reconstruction. The team derived the regression parameters over the satellite era from 1994 to 2020, then extrapolated the corrections back to 1941, extending the improvement deep into the pre-altimetry past. The corrected reconstruction’s standard deviation of variability dropped from 0.30 to 0.25 centimeters for the satellite period, matching the true altimetry value exactly, and its correlation with the observed record doubled from 0.20 to 0.40. The difference between reconstruction and truth shrank by 23 percent. Importantly, the long-term trends were statistically unchanged, at around 2.0 millimeters per year for the full corrected record, confirming that the correction refines the variability without distorting the trend.

The improvement was most visible during the strongest El Niño events. Uncertainties in the corrected reconstruction shrank during the very strong El Niños of 1997-1998 and 2015-2016, and the corrected curve tracked the true altimetry record more closely through both episodes, evidence that uncorrected reconstructions had systematically mishandled the ENSO signature. The authors caution that some Signal Differences may still reflect poor-quality altimetry or tide gauge data rather than genuine ocean physics, and they note that non-linear vertical land motion at some sites remains a stubborn complication; correcting for it using contemporary gravitational, rotational and deformation data did not further improve the result. Future refinements may incorporate river discharge effects, the angle of wind approach to the coastline, and targeted testing of which low-difference sites actually need correction. For now, the study offers something the sea level community has lacked: a physically grounded way to make the pre-satellite record of our planet’s rising oceans finally tell the whole story.

Subject of Research: Improving short-term variability in Global Mean Sea Level reconstructions by correcting wind-driven tide gauge and altimetry differences

Article Title: An improvement to short term variability in Global Mean Sea Level reconstruction

Article References: Shaw, A. G. P., Jevrejeva, S., & Calafat, F. M. (2026). An improvement to short term variability in Global Mean Sea Level reconstruction. Ocean Science, 22(5), 2673-2689. https://doi.org/10.5194/os-22-2673-2026

Image Credits: AI Generated

DOI: 10.5194/os-22-2673-2026

Keywords: global mean sea level, sea level reconstruction, tide gauges, satellite altimetry, empirical orthogonal functions, coastal trapped winds, ENSO, Southern Oscillation Index, coastal trapped waves, sea level budget, climate variability, Ocean Science

The oldest of the three records came from Mossel Bay, on the north coast of the largest island of Spitsbergen, during the Swedish polar expedition led by the celebrated explorer Adolf Erik Nordenskiöld. In October and November 1872, the crew of the brig Gladan cut a small square hole in the sea ice and passed a graduated pole through it, fixed at one end in the seabed and standing four or five feet above the ice at the other. A wooden float slid up and down the pole with the tide, and sailors recorded readings every half hour at the changing of the guard. In spring 1873, personnel at the Polhem base repeated the exercise in shallower water, taking hourly measurements from mid-February to late April. The measurements were made in Swedish feet and decimal inches, units slightly smaller than their British equivalents, and the analysis was eventually published by August Wijkander in 1889, years after the expedition returned.

The second record is tied to one of the most haunting episodes in polar history. In June and July 1897, officers and sailors of the gunboat Svensksund read a simple tide board on the shore of Île des Danois at Port Virgo, on the northwest coast of Spitsbergen, during the second Svalbard expedition of Salomon August Andrée, the engineer who later that same year vanished while attempting to reach the North Pole by balloon. A book of the tabulated observations was handed to the physicist Vilhelm Carlheim-Gyllensköld by a sailor named Dahlgren, and the hourly values found their way into his 1905 report. The record spans just over a month, with several gaps filled by graphical interpolation, and the researchers note some confusion in the original documents over whether the times were recorded in local apparent or mean time, an ambiguity they show to be of little practical consequence.

The third and technically most extraordinary record was made at Sorgfjord, on the north coast of Spitsbergen, during the Swedish-Russian Arc-of-Meridian expedition of 1899 to 1902. That campaign, one of the largest geodetic projects of its kind ever attempted, stretched a chain of triangulation points across mountain tops spanning more than four degrees of latitude, in order to measure the length of a meridian arc and determine how much the spherical Earth is flattened at the poles. The Swedish wintering party at Sorgfjord was led by the geodesist Edvard Jäderin, who built much of the expedition’s equipment himself. Because the height of every point in a triangulation network depends on knowing the height of a baseline above mean sea level, a tide gauge was essential, and Jäderin installed one on 26 March 1900 after the expedition’s intended modern gauge, designed by the Finnish geodesist Alfred Petrelius, failed to arrive in time.

What Jäderin improvised has no known precedent or successor. A strong wire, roughly 2.25 millimetres in diameter, was anchored at the foot of a post on land, passed through a hasp on a second weighted post, ran above the recording apparatus, and extended out to a pulley on a tripod frozen into the floating bay ice some 80 to 85 metres from shore. A stone weighing 75 to 100 kilograms hung from the wire below the pulley. Because the ratio of distances along the wire was fixed at one to 17.22, the vertical motion of the ice as the tide rose and fell was reproduced on a chart recorder, traced by a crayon on a thin red copper wire, at 17.22 times magnification. The clock-driven cylinder turned at just 2.3 millimetres per hour, and charts were replaced every Monday at ten in the morning. Datum control came from levelling sights on the ice and from dipping measurements through a hole near the tripod, tied back to benchmarks on land.

Against all expectations, the contraption worked. It produced hourly sea level values spanning 105 consecutive days, from late March to mid-July 1900, with only occasional interruptions of a few hours to several days, during which interpolated values were printed in italics in the original report. Woodworth and Aarup subjected the digitised record to modern harmonic analysis using software that fits 27 independent tidal constituents, appropriate for short records. The resulting amplitudes and phase lags for the two main semidiurnal constituents, M2 and S2, and the two main diurnal ones, K1 and O1, agree closely both with Carlheim-Gyllensköld’s own hand calculations and with the values long listed in the Admiralty Tide Tables. The residuals of the analysis show remarkably little non-tidal variability, as expected for the calm spring and summer months, with only a couple of short suspicious episodes that appear to stem from chart recording or digitisation errors.

The study also untangles a century of confusion in the official tidal literature. The Admiralty Tide Tables values for Sorgfjord, long assumed to derive from a 1930s reanalysis, were in fact computed far earlier by the United States Coast and Geodetic Survey for Robert Harris’s 1911 monograph on Arctic tides. Harris, comparing his values with Carlheim-Gyllensköld’s, mistakenly declared the latter evidently erroneous, apparently failing to realise that the Swedish phase lags were referred to Greenwich while the American ones were local values. A similar mix-up affected the Port Virgo constants, which passed through Harris and later through the Norwegian oceanographers Kjær and Fjeldstad into the modern tables, carrying with them an erroneous S2 phase lag. For Mossel Bay, the researchers identified a 180-degree error in the diurnal phase lags of Wijkander’s original analysis, a mistake noted by George Darwin as early as 1889, and conclude that the original values, once corrected, are the more reliable.

To place the historic measurements in context, the authors compared their computed constants with FES2022b, a leading global ocean tide model built on more than three decades of precise satellite altimetry and advanced hydrodynamic modelling. The agreement is excellent for the semidiurnal tides at all three sites, and good for most of the diurnal components, with the largest discrepancy a difference of about 20 degrees in the O1 phase lag at Mossel Bay for a constituent only centimetres in amplitude. The model also reveals the physics of the region: the M2 tidal wave rotates clockwise around the archipelago, its amplitude falling and its phase lag increasing as one travels east along the north coast of Spitsbergen, while the diurnal tides are comparatively uniform, apart from an amphidromic feature near the southern tip of Spitsbergen. Crucially, the match between the 1872, 1897 and 1900 observations and the modern model suggests there have been no large changes in the tide in this part of the Arctic over the past century and a half.

The researchers are careful to note that the records carry scientific value precisely because tide gauge coverage of the high Arctic remains sparse even today. Shorter modern recordings exist at Sorgfjord, one week in 1938 and three weeks in 2014, and at Port Virgo in 2008 and 2009, but none approaches the length of the historic series. The paper also points to other lost opportunities, including an Italian Hydrographic Institute gauge established in 1928 at Kings Bay in support of Umberto Nobile’s airship flights, whose benchmarks might still survive and could, with new measurements, allow long-term sea level change to be investigated. Above all, the authors pay tribute to the dedicated and often highly qualified participants who took such care with the most basic equipment in brutal conditions, from Jäderin’s wire-and-crayon machine to the sailors reading floats through holes in the ice. Their rescued data, now freely available in digital form, demonstrate that the patient recovery of historical measurements can still pay real dividends for present-day ocean science.

Subject of Research: Historical Arctic tide gauge records from Svalbard and their modern tidal analysis

Article Title: Three historic tide gauge records from Svalbard

Article References: Woodworth, P. L., & Aarup, T. (2026). Three historic tide gauge records from Svalbard. History of Geo- and Space Sciences, 17(1), 1-12. https://doi.org/10.5194/hgss-17-1-2026

Image Credits: AI Generated

DOI: 10.5194/hgss-17-1-2026

Keywords: tide gauges, Svalbard, Arctic, sea level, tidal analysis, harmonic constants, data archaeology, polar exploration, geodesy, FES2022b, ocean tides, history of science

The core insight of the study is deceptively simple. Tides are not random. They are governed by the gravitational interplay between the Earth, the Moon and the Sun, producing regular cycles of rising and falling water that can be calculated years in advance. In many coastal locations, the tide determines whether a given storm surge is sufficient to push water levels above established flood thresholds. When a moderate surge coincides with a high tide, flooding follows; when the same surge arrives at low tide, water levels may remain safely below the threshold. As Haigh explains, even storm-driven flooding often inherits the timing of the tides, because the tide acts as the gatekeeper that decides whether the surge crosses the critical line.

What makes the new work distinctive is its focus on the hour of the day rather than the season or the year. Previous research on flooding has concentrated heavily on seasonal patterns, examining, for example, why river floods cluster in certain months or why coastal floods are more frequent during particular times of the year. Haigh notes that surprisingly little attention has been paid to what hour of the day flooding actually occurs. Part of the reason, he argues, lies in how flooding is measured. Flood impacts are commonly summarized as the number of flood days per year, and once an event is compressed into a single day, the information about whether the flooding happened at 3 a.m., 8 a.m. or 3 p.m. simply disappears. By returning to the underlying records and preserving the temporal detail, the research team was able to recover patterns that conventional flood statistics had erased.

The regional results are striking in their specificity. In Boston, floods occur predominantly around noon and midnight, mirroring the timing of that harbor’s high tides. In Southern California, flooding is more common in the morning, again tracking the local tidal cycle. In Florida, the picture is more varied, because tidal behavior differs substantially from one stretch of coastline to another. Along the Atlantic Coast and down toward the Florida Keys, coastal flooding is moderately predictable in its timing, while along the Gulf Coast, where tidal ranges are smaller and more complex, flooding is less predictable. These differences matter, because they show that the daily fingerprint of flooding is not a universal pattern but a local one, shaped by the specific tidal regime of each coastline.

The study also establishes that the phenomenon is not confined to places with semidiurnal tides, the familiar pattern of two high tides and two low tides each day that characterizes much of the U.S. East Coast and the U.K. The researchers found that predictable daily timing also emerges in locations with diurnal tidal systems, which experience only one high tide and one low tide per day. The reason lies in the way different tidal signals interact. Tides are generated by multiple astronomical constituents, each with its own period, and their superposition produces the observed water-level cycle. Whether a coastline experiences two highs a day or one, the resulting pattern remains regular enough that flood events, which require water levels to cross a threshold, cluster around the recurring peaks of that cycle.

The technical implication is that flood risk is not evenly distributed across the hours of a day, even when the weather is. A storm system that lingers offshore for twelve hours does not pose a uniform threat throughout its passage. Its most dangerous moments are those that coincide with high tide, and in many locations those moments can be identified in advance with the same precision used to publish tide tables. This reframing has consequences for how flood forecasting is constructed. Traditional forecasts emphasize the magnitude of expected water levels, but the timing of when those levels are most likely to be exceeded is equally important for operational decisions, from closing roads to repositioning emergency assets.

Haigh argues that this matters because timing influences impacts. The same flood can have very different consequences depending on whether it occurs during the morning commute, during business hours or in the middle of the night. A flood that peaks at rush hour can strand commuters, snarl traffic and endanger drivers who attempt to cross inundated roadways. A flood of identical height at 3 a.m. may cause comparable physical damage but far fewer casualties and disruptions, simply because fewer people are exposed. Understanding these temporal patterns, the study suggests, could improve flood forecasting, emergency planning, infrastructure operations and long-term coastal adaptation. Utilities, hospitals, schools and transit agencies could all incorporate the known tidal windows into their contingency planning, aligning preparedness measures with the hours when flooding is statistically most likely.

The research arrives at a moment when the baseline for coastal flooding is shifting. As sea levels continue to rise, coastal flooding is increasingly occurring without storms to spur it on, a phenomenon often described as nuisance or sunny-day flooding, in which exceptionally high tides alone are enough to inundate low-lying streets. Haigh points out that higher mean sea levels mean it takes only a relatively small weather contribution, or sometimes simply a very high astronomical tide, to cross a flood threshold. In such conditions, the timing of the tides becomes even more decisive, and understanding exactly when those critical tidal windows occur could become an increasingly important component of coastal flood forecasting and preparedness.

The practical payoff of the work could be substantial. Haigh says the findings could make existing flood forecasts more predictable, providing more warning before disasters occur. That added lead time can help residents, businesses and emergency managers anticipate disruption and plan accordingly, whether that means scheduling deliveries around high-tide windows, warning drivers before morning inundations or pre-positioning pumps and barriers. Because the tidal component of flood timing is deterministic, it can be computed far in advance, offering a layer of foresight that weather-driven forecasting alone cannot match. The uncertainty in a flood forecast then narrows to the meteorological contribution, while the tidal contribution is already known.

The study, titled Coastal flooding at predictable hours and published in Nature Communications on 28 July 2026, represents a collaboration among international researchers and reflects Haigh’s long career in sea level and coastal impacts. A professor who joined the University of Central Florida in 2025 as director of the Center for Integrated Coastal Research, Haigh previously held the chair in sea level and coastal impacts at the University of Southampton and directed the Center for Doctoral Training for Resilient Flood Futures. His team’s work suggests a quiet but consequential shift in coastal science: the hazard that communities have treated as random now reveals a schedule, and learning to read that schedule may prove one of the most practical tools available as rising seas make the ocean’s high-water moments an ever more frequent visitor to the world’s coastlines.

Subject of Research: Predictable daily timing of coastal flooding driven by tidal cycles

Article Title: Study shows coastal flooding occurs at predictable times

Article References: Study shows coastal flooding occurs at predictable times. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: coastal flooding, tides, sea level rise, flood forecasting, storm surge, tidal cycles, Nature Communications, University of Central Florida, emergency planning, nuisance flooding, tide gauges, coastal adaptation

The study, led by Somayeh Abdollahi of Ghent University together with colleagues from Flanders Hydraulics, the National Geographic Institute, and the Agency for Maritime and Coastal Services, harnessed twenty-three years of high-resolution water-level observations recorded between 2001 and 2023. Four tide gauges anchored the analysis: Nieuwpoort and Oostende on the open coast, the harbour station at Zeebrugge, and the offshore Westhinder platform, designated MP7, which stands sentinel over the shipping approaches far from land. For the first time in Belgian waters, the team systematically compared multiple analysis windows, reconstruction strategies, and tidal-constituent selection procedures, all within the widely used UTide harmonic-analysis framework developed by David Codiga at the University of Rhode Island.

Harmonic analysis is the classical engine of tidal science, tracing its lineage back to Arthur Doodson’s landmark 1921 decomposition of the tide-generating potential. The idea is elegant: the tide at any location can be represented as the sum of dozens of sinusoidal constituents, each with a precisely known astronomical frequency but an amplitude and phase that must be estimated from observations. Once those amplitudes and phases are locked in, the tide can be predicted forward or backward in time indefinitely. LAT is then defined as the lowest water level the astronomical tide alone can produce, excluding the chaotic contributions of storm surges and weather. In practice, however, the answer depends heavily on which constituents are included, how long a record is analysed, and how the reconstruction is performed.

The researchers confronted this methodological fragility head-on. They tested four period-selection approaches, labelled M1 through M4: a single long-record harmonic analysis spanning 2001 to 2019 with annual reconstructions; separate year-by-year analyses; annual analyses used to predict the following nineteen years; and a sophisticated complex averaging of annual harmonic coefficients that preserves the vector nature of tidal amplitudes and phases. Each method was applied at all four stations, and the spread in the resulting LAT estimates turned out to be far from trivial, underscoring that a single ‘correct’ LAT value is an illusion unless the analytical recipe is specified precisely.

Equally consequential was the choice of tidal constituents. The team compared three selection strategies: the default constituent set offered by UTide, a fixed set traditionally used by the Dutch hydrographic service, and a novel iterative procedure guided by the spectrum of the analysis residuals. In the residual-spectrum-guided approach, the researchers analysed the tide, examined the frequency content of what remained unexplained, and added constituents corresponding to prominent residual peaks, repeating the process until the spectrum was clean. This data-driven strategy, implemented entirely with UTide routines, emerged as the preferred configuration, capable of capturing shallow-water constituents that generic or borrowed constituent sets overlook in the complicated hydrodynamics of the southern North Sea.

The preferred configuration, based on the 2001–2019 input window, yielded deterministic LAT values of −0.648 metres at Nieuwpoort, −0.499 metres at Oostende, −0.251 metres at Zeebrugge, and −0.300 metres at the offshore Westhinder station, all expressed relative to the Belgian national height datum TAW/DNG. The pronounced spatial variation, with LAT nearly half a metre deeper at Nieuwpoort than at Zeebrugge, reflects the complex interplay of coastal geometry, bathymetry, and shallow-water tidal dynamics along the Belgian coast. No single conversion grid, the researchers caution, can faithfully represent such station-specific behaviour without careful local calibration.

To quantify how confident one can be in these numbers, the team propagated uncertainty in the harmonic parameters using 1000 Gaussian Monte Carlo realisations, perturbing the estimated amplitudes and phases according to their statistical uncertainties and recomputing the LAT minimum for each realisation. The resulting conditional standard deviations were remarkably tight, ranging from 0.0031 to 0.0034 metres, suggesting that once the harmonic model and constituent set are fixed, the LAT estimate is numerically robust. The authors are careful, however, to frame this spread as conditional on the chosen model rather than a complete uncertainty budget; it captures parameter uncertainty but not the full spectrum of errors that could affect an operational datum.

The Monte Carlo experiments also delivered a reassuring message about computational practicality. Comparing ensembles of 500 and 1000 realisations across the four period-selection methods produced maximum absolute differences of only 0.007 metres in the Monte Carlo mean, 0.009 metres in the conditional standard deviation, and 0.020 metres in one percentile-interval bound. For the preferred residual-spectrum-guided configuration, those differences shrank further to 0.003, 0.004, and 0.006 metres respectively. In other words, halving the ensemble size barely moves the answer, a finding that will ease the computational burden for hydrographic offices considering similar analyses elsewhere.

Throughout the study, the researchers treated existing operational products, including station values published by the Agency for Maritime and Coastal Services and the official LAT conversion grid, as consistency benchmarks rather than independent ground truth. This distinction matters: the operational values were not used to validate the new estimates in an absolute sense, but to check whether the updated analysis remains compatible with the datums that Belgian mariners and coastal engineers rely on today. The deterministic LAT, defined as the minimum of the unperturbed harmonic reconstruction, and the Monte Carlo mean, the average of minima across perturbed realisations, were deliberately reported separately, since the two quantities answer subtly different questions.

The broader significance of the work extends beyond Belgium’s short coastline. The 18.61-year nodal cycle, in which the lunar orbit’s precession modulates tidal amplitudes by up to tens of centimetres, means that short analysis windows can bias LAT estimates substantially, a phenomenon documented in tide-gauge records worldwide. By demonstrating the value of a nineteen-year input window, roughly one full nodal cycle, and by providing a reproducible framework for constituent selection and uncertainty propagation, the Belgian team has offered a template that other hydrographic services can adapt. As sea levels rise and extreme water levels evolve, the low end of the tidal envelope deserves the same scrutiny as the high end, and this study shows exactly how that scrutiny should be applied. The tide-gauge data underpinning the analysis remain freely available through the Meetnet Vlaamse Banken portal, inviting researchers everywhere to test, refine, and extend the approach.

Subject of Research: Assessment of Lowest Astronomical Tide at Belgian North Sea tide gauges using long-term harmonic analysis and residual-spectrum-guided constituent selection

Article Title: Assessment of lowest astronomical tide at belgian north sea tide gauges using long-term harmonic analysis and residual-spectrum-guided constituent selection

Article References: Abdollahi, S., Vanlede, J., Verbeurgt, J., Verstraeten, J., De Kuyper, A., Gurdebeke, P., & De Wulf, A. (2026). Assessment of lowest astronomical tide at belgian north sea tide gauges using long-term harmonic analysis and residual-spectrum-guided constituent selection. Ocean Dynamics, 76(9), Article 96. https://doi.org/10.1007/s10236-026-01850-3

Image Credits: AI Generated

DOI: 10.1007/s10236-026-01850-3

Keywords: Lowest Astronomical Tide, Belgian North Sea, harmonic analysis, tide gauges, tidal constituents, UTide, Monte Carlo uncertainty, vertical datum, ocean dynamics, hydrography, coastal sciences, residual spectrum