Tide Gauge Stations Research Articles

Sea Level Variation and Trend Analysis by Comparing Mann–Kendall Test and Innovative Trend Analysis in Front of the Red River Delta, Vietnam (1961–2020)

In this study, we analyze sea surface height referenced against the WGS84 ellipsoid at the Hon Dau tidal gauge station (Hai Phong, Vietnam), in front of the Red River Delta, between 1961 and 2020. The annual sea level varied from 165.23 cm to 206.06 cm in this period (+20.28 cm over 60 years). The average water level was 190.87 cm for 60 years, with higher annual values in recent years, especially from 2016 to the present (above 201.5 cm). The Mann–Kendall (MK) test with Sen’s slope estimator and Şen’s innovative trend analysis (ITA) were applied and compared to estimate the sea level rise. These methods showed complete agreement among tests with significant rising trends of about 3.38 mm/year with the MK test and 3.08 mm/year with the ITA method for 1961–2020. During the last 20 years (2001–2020), the mean sea level increased about 7.16 mm/year (MK test and Sen’s slope), 7.38 mm/year (ITA method), and around twice higher than the rate of the region and globally. The MK test and ITA method provided similar results for periods: 1961–2020, 1961–1980, and 2001–2020, with relatively stable monotonic related trend conditions. For the period 1981–2000, with a more nonmonotonic trend, the MK test and ITA method provided different trends and allowed to illustrate the specificity of each method.

Carbon accumulation and storage in a temperate coastal lagoon under the influence of recent climate change (Northwestern Adriatic Sea)

Pialassa Baiona is a shallow temperate coastal lagoon influenced by a variety of factors, including regional climate change and local anthropogenic disturbances. To better understand how these factors influenced modern organic carbon (OC) sources and accumulation rates, we measured OC as well as stable carbon isotopes (δ13C) in 210Pb-dated sediments within a vegetated saltmarsh habitat and a human impacted habitat. Relative Sea Level (RSL) at the nearby tide gauge station data and four different Sea Surface Temperature (SST) data sets were analyzed starting from 1900 to assess the potential effect of sea ingression and warming on the coastal lagoon sedimentary processes. The source contribution calculated from the MixSIAR Bayesian model revealed a mixed composition of sedimentary OC, dominated by an increase in marine-derived OC after the 1950s, matching with a decrease from autochthonous saltmarsh vegetation (Juncus spp.) in the saltmarsh habitat, and from riverine/estuarine-derived OC in the impacted habitat. RSL rise in the area (8.7 ± 0.5 mm yr−1 in the period 1900–2014) has been mainly driven by the land subsidence, especially during the central decades of the last century, enhancing the sea ingression into the lagoon. RSL rise influenced changes in sedimentary OC sources and accumulation at different level within the two habitats from the 1950s onward; conversely, no direct effect of SST was detected.

Hourly sea level height forecast based on GNSS-IR by using ARIMA model

ABSTRACT Multi-satellite and Multi-Signal-to-Noise Ratio (SNR) types provide more basic data for the monitoring of sea level height by Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technology. Few studies predict sea level height with high temporal resolution. This study proposes a theory based on GNSS-IR technology and Auto Regressive Integrated Moving Average (ARIMA) model. Taking the MAYG station as an example, the process of sea level height prediction and the determination of the best prediction scheme are shown. First, the sea level height monitored by the GNSS-IR technology is averaged hour by hour as the sea level height at the instantaneous moment. A linear interpolation method is used to compensate for the missing sea level time series. Then, the number of days to participate in the prediction of GNSS-IR sea level height and its forecast are selected for the experiment of predicting tide level. In the tide level prediction study from DOY125 to DOY153, the results of predicting the future 24 h, 48 h, and 72 h from one tide level period (29 days) illustrate that the accuracy of predicting the sea level height at 24 h is the best (R: 0.967, RMSE: 0.270 m, ME: −0.151 m), and the predicted tide level is highly consistent with the tide level measured at the tide gauge station. In addition, experiments reveal that the prediction accuracy gradually decreases with the increase of prediction time. This study verifies the feasibility of the hour-by-hour sea level prediction theory combined with the GNSS-IR technology and the ARIMA model. It proves that the theory can carry out continuous prediction of sea level, further promoting the breakthrough and transformation of GNSS-IR technology to the application level.

Muography for a dense tide monitoring network

Sub-hourly to seasonal and interannual oceanographic phenomena can be better understood with high special resolution and high frequency tidal observations. However, while current tidal measurements can provide sufficiently high observational density in terms of time, the observational density in terms of space is low mainly due to the high expense of constructing tide gauge stations. In this work, we designed a novel tide monitoring technique with muography that could be operated in near-shore basements (or similar structures on land below sea level) and found that more practical, stable, robust and cost-effective high-spatiotemporal-density tide measurements are possible. Although the time resolution, sensitivity, and the distance between the detectors and the shorelines are tradeoffs, hourly and annual sensitivity (ability to detect the tide height variations) of less than 10 cm and 1 mm can be statistically attained, respectively. It is anticipated that the current muographic technique could be applied as an alternative, cost-effective and convenient dense tidal monitor network strategy in coastal areas worldwide.

Minimum record length for detecting a prospective uniform sea level acceleration at a tide gauge station

Minimum record length for detecting a prospective uniform sea level acceleration at a tide gauge station

Tsunami Effects on the Coast of Mexico by the Hunga Tonga-Hunga Ha'apai Volcano Eruption, Tonga.

The massive explosion by the January 15, 2022 Hunga Tonga-Hunga Ha’apai volcano in Tonga triggered a trans-oceanic tsunami generated by coupled ocean and atmospheric shock waves during the explosion. The tsunami reached first the coast of Tonga, and later many coasts around the world. The shock wave went around the globe, causing sea perturbations as far as the Caribbean and the Mediterranean seas. We present the effects of the January 15, 2022 Tonga tsunami on the Mexican Pacific Coast, Gulf of Mexico, and Mexican Caribbean coast, and discuss the underrated hazard caused by great volcanic explosions, and the role of early tsunami warning systems, in particular in Mexico. The shock wave took about 7.5 h to reach the coast of Mexico, located about 9000 km away from the volcano, and the signal lasted several hours, about 133 h (5.13 days). The shock wave was the only cause for sea alterations on the Gulf of Mexico and Caribbean Sea, while at the Mexican Pacific coast both shock wave and the triggered tsunami by the volcano eruption and collapse affected this coast. The first tsunami waves recorded on the Mexican Pacific coast arrived around 12:35 on January 15, at the Lázaro Cárdenas, Michoacán tide gauge station. The maximum tsunami height exceeded 2 m at the Ensenada, Baja California, and Manzanillo, Colima, tide gauge stations. Most tsunami warning advisories, with two exceptions, reached communities via social media (Twitter and Facebook), but did not clearly state that people must stay away from the shore. We suggest that, although no casualties were reported in Mexico, tsunami warning advisories of far-field tsunamis and those triggered non-seismic sources, such as landslides and volcanic eruptions, should be included and improved to reach coastal communities timely, explaining the associated hazards on the coast.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00024-022-03017-9.

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.

Evidence for Increasing Frequency of Extreme Coastal Sea Levels

Projections of extreme sea levels (ESLs) are critical for managing coastal risks, but are made complicated by deep uncertainties. One key uncertainty is the choice of model structure used to estimate coastal hazards. Differences in model structural choices contribute to uncertainty in estimated coastal hazard, so it is important to characterize how model structural choice affects estimates of ESL. Here, we present a collection of 36 ESL data sets, from tide gauge stations along the United States East and Gulf Coasts. The data are processed using both annual block maxima and peaks-over-thresholds approaches for modeling distributions of extremes. We use these data sets to fit a suite of potentially non-stationary generalized extreme value distributions and generalized Pareto distributions by covarying the ESL statistics with multiple climate variables. For all of the sites and statistical model structures for tide surge considered here, we find that accounting for changes in the frequency of coastal extreme sea levels provides a better fit to data than using a stationary extreme value model. Further, when maximizing the a posteriori probability of the model parameters, given the available tide gauge data, generalized extreme value distribution structures with non-stationary scale parameter are preferred over non-stationary location parameter. These results have implications for how deep uncertainties in coastal flood hazards are characterized, particularly in how studies incorporate potential non-stationarity in storm surge statistics.

Effects of Offsets and Outliers on the Sea Level Trend at Antalya 2 Tide Gauge within the Eastern Mediterranean Sea

Antalya 2 tide gauge (TG) station is located on the coast of Turkey within the Eastern Mediterranean Sea. Relative sea level trends 6.0 ± 1.5 and 6.44 ± 0.45 mm/year over 1985–2009 at Antalya 2 TG are different from the trend (1.6 ± 1.5 mm/year over 1935–1977) at Antalya TG within 10 km. In order to investigate this trend discrepancy, the monthly mean series at Antalya 2 TG is re-analyzed for offsets, outliers and trend estimation. The Zivot-Andrews method and the outlier test result in one offset at 1994.0417 year with magnitude of 71.24 ± 13.48 mm and nine outliers. The series, corrected for the offset and outliers, de-seasonalized and filled for missed points, is identified as trend-stationary process and analyzed for trend estimation by various models. The optimal model providing the lowest Akaike Information Criteria is polynomial linear trend with multiplicative seasonal Autoregressive Moving Average (ARMA(2,0)x(1,0)12). The estimated relative sea level trend by the optimal model is 1.77 ± 0.65 mm/year. The large trend discrepancy at Antalya 2 TG is accounted for by one offset primarily (∼71%) and nine outliers (∼3%).

Tidal Constants Derivation for Imo River

Tides play critical role in coastal processes, marine operations and navigation. Determination of tidal characteristics and prediction of water levels require knowledge of tide harmonic constants (amplitudes and phase lags) of all relevant tidal constituents. 37 days hourly water level observation was taken at established tide gauge station along Imo River and analysis of observed data using harmonic method implemented with T_Tide. 35 tidal constituents were generated and used for water level prediction. Tidal constants of four principal tidal constituents (K1, O1, M2 and S2) were used to compute tidal form factor and water level datum for the river. The analyses revealed that M2 constituent was the most dominant tidal constituent with amplitude of 0.7375. Computed form factor (0.2076) revealed Imo River to have a semidiurnal tidal regime which is the characteristics of Nigerian coastal waters. The river has a tidal range of 2.231m and mean water level of 1.660m. Comparison of predicted and observed tide gave root mean square error of 0.0177 and correlation coefficient of 0.9943. Results obtained from the study indicated that derived tidal constants are reliable for prediction of Imo River water levels and tide.

Accuracy Assessment of Recent Global Ocean Tide Models Using Tide Gauge Measurements from the East Sea of Korea

Lee, J.-C. and Lee, D-H., 2023. Accuracy assessment of recent global ocean tide models using tide gauge measurements from the East Sea of Korea. Journal of Coastal Research, 39(2), 354–359. Charlotte (North Carolina), ISSN 0749-0208. The continued rise in average sea level owing to climate change has intensified coastal damage worldwide. Therefore, various studies in the field of oceanography and hydrography including the development of ocean tidal prediction models are in progress. In this study, the accuracy of the recent ocean tide models using the long and short-term tide gauge measurements from seven tidal gauging stations and 10 tidal benchmarks at the coastal area in the East Sea of Korea was assessed. For this purpose, a total of five ocean tide models, DTU10, FES2014, OSU12, NAO99, and TPXO9 were used. The accuracy of the four major tidal components (M2, S2, K1, and O1) were assessed based on the same components determined from direct tide gauge measurements in east coastal area of Korea. The tide gauge measurements used in this study consisted of long-term observation data of over 1.7 years on average from seven permanent tide gauge stations and short-term observation data of about 6.6 months on average from 10 tidal benchmarks. Observation and determination of tidal components were performed by the Korea Hydrographic and Oceanographic Agency. The accuracy of each ocean tide model was assessed by comparing the amplitude of four major components with those from tide gauge measurements for each location of tide gauge. The lowest accuracy of modelled component values was detected in the M2, S2, K1, and O1 tidal components of NAO99 model. On the contrary, FES2014 was the most accurate in M2, S2 tidal components and TPXO9 was most accurate in the K1, O1 tidal components in the East Sea of Korea.

Determination of Long-Term (1993–2019) Sea Level Rise Trends Around the Korean Peninsula Using Ocean Tide-Corrected, Multi-Mission Satellite Altimetry Data

It is vital to improve estimations of long-term trends in global and regional sea level rise to help mitigate and adapt to climate change. Satellite altimetry data have been widely used for this purpose; however, data collected in regions with strong tidalmotions often suffer from significant aliasing effects unless they are sufficiently corrected using accurate ocean tide models.Long-term trends estimated from altimetry data are often also considerably affected by regional circulation changes, and by artificial effects arising from inconsistencies between different satellite missions. Here, we focused on two regions with high (>5 mm⋅yr–1) rates of long-term linear trend in sea level rise (LTSLR) around the Korean Peninsula (KP). We addressed the impacts of tidal correction and mission inconsistency in satellite altimetry data, and discussed the potential impacts of circulation changes on LTSLR. Because the LTSLR estimation is affected by the aliasing effects of altimetry data when the tidal motions are not corrected sufficiently, yet the correction depends on the performance of ocean tide models, we employed eight ocean tide models to correct altimetry data for comparison and validated the results against observations from 13 tide gauge (TG) stations around the KP. We also estimated LTSLR from 1993 to 2019 using annual mean sea level anomalies (SLAs) from two satellite (two-sat) and all 21 satellite (all-sat) missions, with corrections for ocean tides. The TPXO9 model showed the most reasonable spatial LTSLR rate pattern (∼3 mm⋅yr–1), with the smallest difference from TG observations. It performed best near the west coast where the tidal range was the largest and when using two-sat data, because of inconsistencies in all-sat altimetry data. In contrast, off the east coast, where the impact of tidal correction is negligible, the high (∼7 mm⋅yr–1) LTSLR rates were robust regardless of ocean tide models and altimetry missions, potentially driven by long-term changes in regional circulation. Our results highlight the importance of tidal correction and mission inconsistency for improving LTSLR estimations around the KP. They also have significant implications for determining regional sea level rise under changing circulation patterns, within and beyond the region.

Impact of highest maximum sustained wind speed and its duration on storm surges and hydrodynamics along Krishna–Godavari coast

The storm surge and hydrodynamics along the Krishna–Godavari (K–G) basin are examined based on numerical experiments designed from assessing the landfalling cyclones in Bay of Bengal (BoB) over the past 38 years with respect to its highest maximum sustained wind speed and its duration. The model is validated with the observed water levels at the tide gauge stations at Visakhapatnam during 2013 Helen and 2014 Hudhud. Effect of gradual and rapid intensification of cyclones on the peak water levels and depth average currents are examined and the vulnerable locations are identified. The duration of intensification of a rapidly intensifying cyclone over the continental shelf contributed to about 10–18% increase in the peak water levels, whereas for the gradually intensifying cyclone the effect is trivial. The inclusion of the wave-setup increased the peak water levels up to 39% compared to those without wave-setup. In the deep water region, only rapidly intensifying cyclones affected the peak MWEs. Intensification over the continental slope region significantly increases the currents along the shelf region and coast. The effect on peak maximum depth averaged current extends up to 400 km from the landfall location. Thus, it is necessary to consider the effect of various combinations of the highest cyclone intensity and duration of intensification for identifying the worst scenarios for impact assessment of coastal processes and sediment transport. The study is quite useful in improving the storm surge prediction, in preparedness, risk evaluation, and vulnerability assessment of the coastal regions in the present changing climate.

Assessing Numerical Model Skill at Simulating Coastal Flooding Using Field Observations of Deposited Debris and Photographic Evidence

Despite the growing range and availability of resources to support coastal flood hazard model development, there is often a scarcity of data to support critical assessment of the performance of community-scale coastal inundation models. Even where long-term tide gauge measurements are available in close proximity to the study area, the records provide little insight into the spatial distribution and limits of overland flooding, or the influence of topographic features and structures on flooding pathways. We present methods to support the assessment of model performance using field observations in lieu of, or supplementary to, conventional water-level records. A high-resolution, numerical coastal flood hazard model was developed to simulate storm surge-driven flooding in the Acadian Peninsula region of New Brunswick, Canada. Owing to the remoteness of the study area from tide gauge stations, model performance was assessed based on a comparison with field measurements of deposited wrack and debris, as well as photographic and video evidence of coastal flooding, for two significant storm surge events in recent history. Our research findings illustrate the value of observational and qualitative data for characterizing coastal flood hazards, lending gravity to the importance of non-conventional data sources, particularly in data-scarce regions.

Alongshore Propagation of Subtidal Sea Level Fluctuations Around the Korean Peninsula Over Varying Stratification and Shelf Topography

Understanding subtidal (a period band of 3–20 days) coastal sea level fluctuations is of increasing importance for the sustainable use of coastal areas under challenging conditions resulting from regional and global sea-level rise. The wind-forced coastal-trapped waves (CTW) theory often accounts for subtidal sea level fluctuations observed off global coasts with a considerable range of propagation speeds. Here, the propagation speeds of subtidal sea level fluctuations observed at seven coastal tide-gauge stations around the Korean Peninsula (KP) from 1997 to 2017 were compared with phase speeds modeled for 10 segments of realistic bottom topography around the KP and four seasons of density stratification using a wind-forced CTW model. Alongshore variations in the modeled phase speed (2.0–10.0 m s–1, increasing with the bottom depth, shelf width, and vertical density difference) were consistent with those of the observed propagation speed (4.7–18.9 m s–1), despite systematic underestimation by 50%, i.e., the mean speed of 6.0 vs. 11.8 m s–1. This underestimation is discussed considering subtidal sea level fluctuations of non-CTW origin that were not incorporated into the CTW model, such as (1) Barometric sea level response to atmospheric pressure disturbances, and (2) Upwelling/downwelling response to local alongshore wind stress. This study suggests that subtidal coastal sea level fluctuates around the KP within and beyond CTW dynamics.

Time difference between the 1854 CE Ansei\u2013Tokai and Ansei\u2013Nankai earthquakes estimated from distant tsunami waveforms on the west coast of North America

We estimated the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai earthquakes from tidal records of two tide gauge stations (San Francisco and San Diego) on the west coast of North America. The first signals of the Ansei–Tokai tsunami were apparent, whereas those of the Ansei–Nankai tsunami were obscured by the later waves of the Ansei–Tokai tsunami. Waveforms of the Ansei–Nankai tsunami simulated with nonlinear dispersive wave theory by assuming an origin time of 07:00 GMT on 24 December arrived earlier than in the observations. The normalized root mean square and the misfit between the simulated and observed waveforms of the Ansei–Nankai tsunami showed a time difference between them of approximately 0.4 h. This finding suggests that the actual origin time of the Ansei–Nankai tsunami was approximately 07:24 GMT on 24 December. A previous study estimated the origin time of the Ansei–Tokai tsunami to be about 00:30 GMT on 23 December. Thus, we concluded that the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai tsunamis was 30.9 h. Despite the significant difference in the time resolution between the seasonal timekeeping system used in Japan in 1854 and waveform digitization, our result is roughly in agreement with historical descriptions of the tsunamis, suggesting that such information can be effectively used to determine the origin times of historical earthquakes.

Validation of Recent Altimeter Missions at Non-Dedicated Tide Gauge Stations in the Southeastern North Sea

Consistent calibration and monitoring is a basic prerequisite for providing a reliable time series of global and regional sea-level variations from altimetry. The precisions of sea-level measurements and regional biases for six altimeter missions (Jason-1/2/3, Envisat, Saral, Sentinel-3A) are assessed in this study at 11 GNSS-controlled tide gauge stations in the German Bight (SE North Sea) for the period 2002 to 2019. The gauges are partly located at the open water, and partly at the coast close to mudflats. The altimetry is extracted at virtual stations with distances from 2 to 24 km from the gauges. The processing is optimized for the region and adjusted for the comparison with instantaneous tide gauge readings. An empirical correction is developed to account for mean height gradients and slight differences of the tidal dynamics between the gauge and altimetry, which improves the agreement between the two data sets by 15–75%. The precision of the altimeters depends on the location and mission and ranges from 1.8 to 3.7 cm if the precision of the gauges is 2 cm. The accuracy of the regional mission biases is strongly dependent on the mean sea surface heights near the stations. The most consistent biases are obtained based on the CLS2011 model with mission-dependent accuracies from 1.3 to 3.4 cm. Hence, the GNSS-controlled tide gauges operated operationally by the German Waterway and Shipping Administration (WSV) might complement the calibration and monitoring activities at dedicated CalVal stations.

Land Subsidence Estimation With Tide Gauge and Satellite Radar Altimetry Measurements Along the Texas Gulf Coast, USA

A double difference (DD) method was employed to estimate vertical land motion (VLM) at 26 tide gauge (TG) sites with record lengths of at least ten years across the Texas Gulf Coast, USA, between 1993 and 2020. In the method, the first difference was conducted by coupling nearby correlated TG stations to remove sea-level variability for both TG and satellite radar altimetry (SRA) data. Upon completion of the first difference, a second difference was performed by subtracting between TG and SRA data. Results obtained from the DD method were compared against that of: 1) a single difference (SD) method through subtraction between measurements from TG and SRA, and 2) a global navigation satellite system (GNSS) precise point positioning (PPP) method. Results showed that the DD method improved the performance of VLM estimation with an uncertainty below 1.0 mm/yr at most TG stations. Meanwhile, the estimated VLM trends acquired from the DD method correlated better to that of the ground-truth GNSS PPP solutions than the SD method. The DD method possesses great potential to discover VLM knowledge, particularly along coastal regions where other techniques such as GNSS and interferometric synthetic aperture radar (InSAR) are of impaired estimation capability.

Determination of vertical land movements through the integration of tide gauge observations and satellite altimetry data at the Brazilian Vertical Datum from 2002 to 2015

Satellite altimetry missions and tide gauges allow the monitoring of sea level variations over time. While tide gauges monitor sea level relative to a local reference, satellite altimetry missions do so in relation to the Earth’s geocenter. From the comparison between time series generated by these two methods, we observed differences that may be related to possible vertical land movement (VLM). Our objective in this study is to determine the linear trends of VLMs from the difference between the sea level trend found by the satellite altimetry missions TOPEX/Poseidon, JASON 1, 2 and 3 (v SA ) and the sea level trend found by the tide gauge of Imbituba in Santa Catarina (SC), Brazil (v TG ). For this, we demarcated cells along the satellite tracks at a radius of up to 500 km over the ocean from the location of the tide gauge station. The mean values for v SA (1992-2017) and v TG (2002-2015) were 2.5 mm/a ±1.2 mm/a and 5.4 mm/a ±1.9 mm/a, while the mean values for v SA (2007-2015) and v TG (2007-2015) were 7.1 mm/a ±4.6 mm/a and 13.0 mm/a ±4.2 mm/a, respectively. The comparison of VLM obtained between the combination of v SA and v TG and GNSS showed results with better consistency over longer time series.

Comparison of two data acquisition protocols for tide gauge sensors at Imbituba port – Santa Catarina State

The Santa Catarina Tide Gauge Network (SCTGN) is a continuous sea level monitoring system to support fishery, aquaculture, and navigation in general. Deployed in the state of Santa Catarina, Brazil, the initiative started in 2012 with one tide gauge at the Santa Catarina Island South Bay to support aquaculture research projects and hydrodynamic numerical modelling. By 2020, the SCTGN was fully operational, consisting of 11 tide gauge stations along the 450km of the Santa Catarina coastal line. The next step is standardizing these tide stations to international data collection protocols. Knowledge of the effects different programming protocols have on data collection are important since they may affect the results. Data from a radar gauge (RG) and a vented (or relative) pressure gauge (VPG) were obtained over six months. The difference between RG and VPG measurements showed a 5.07cm2 variance. Percentage of reading errors was 0.03% and 0.77% for RG and VPG, respectively. This study aims to evaluate the feasibility of the SCTGN data collection protocol in the RG to comply with the Intergovernmental Oceanographic Commission (IOC) recommendations for sea level monitoring. We find that an RG gauge using the SCTGN protocol is adequate to monitor sea levels and has an easier installation and maintenance, and more stable vertical datum control.