Long-term Tide Research Articles

Machine learning models applied to altimetry era tide gauge and grid altimetry data for comparative long-term trend estimation: A study from Shikoku Island, Japan

Estimation of sea level trends is essential for understanding sea level rise dynamics. In this study, the performance of traditional Ordinary Least Squares (OLS) linear trend forecasting is compared with modern machine learning techniques, specifically Random Forests (RF) and Least Squares Support Vector Machines (LS-SVM).These methods are applied to 50 years of long-term tide gauge (TG) data from six tide gauge stations off the coast of Shikoku Island, Japan, and CMEMS Grid Altimetry data from 1993 to the present. The analysis uses OLS, RF, and LS-SVM to estimate trends from both data sets and compares the results. The objective is to determine the consistency and accuracy of RF and LS-SVM methods compared to the OLS method. The results indicate that machine learning algorithms (LS-SVM) effectively estimate sea level trends, offering potential improvements in precision for both long-term and medium-term analyses. Shikoku Island's coastal sea level trend is determined as 2.91±1.44 mm/yr using TG data and 3.00±1.52 mm/yr using CMEMS Grid Altimeter data with the OLS approach. Using the LS-SVM approach, the trend is found as 2.96±1.58 mm/yr with TG data and 3.02±1.60 mm/yr with CMEMS Grid Altimetry data. The novelty of this study lies in its thorough comparison of traditional and machine learning approaches for sea level trend estimation, providing valuable insights for future predictions of the sea level rise.

Underestimation of extremes in sea level surge reconstruction

Statistical models are an alternative to numerical models for reconstructing storm surges at a low computational cost. These models directly link surges to metocean variables, i.e., predictors such as atmospheric pressure, wind and waves. Such reconstructions usually underestimate extreme surges. Here, we explore how to reduce biases on extremes using two methods—multiple linear regressions and neural networks—for surge reconstructions. Models with different configurations are tested at 14 long-term tide gauges in the North-East Atlantic. We found that (1) using the wind stress rather than the wind speed as predictor reduces the bias on extremes. (2) Adding the significant wave height as a predictor can reduce biases on extremes at a few locations tested. (3) Building on these statistical models, we show that atmospheric reanalyses likely underestimate extremes over the 19th century. Finally, it is demonstrated that neural networks can effectively predict extreme surges without wind information, but considering the atmospheric pressure input extracted over a sufficiently large area around a given station. This last point may offer new insights into air-sea interaction studies and wind stress parametrization.

Improved tidal estimates from short water level records via the modified harmonic analysis model

To fully resolve eight major tides from short-term records, classical harmonic analysis model usually infers unresolved constituents with the help of inference relationships from nearby long-term tide gauges. Our previous study developed a modified harmonic analysis model using the credo of smoothness (i.e., MHACS) which can achieve this without inference relationships. Via introducing the inherent natural links between major tides, MHACS breaks the restrictions of the Rayleigh criterion and requires only ∼9-day hourly records to resolve eight major tides. However, when data length is shorter than 9 days, the results of MHACS become problematic due to over-fitting. In this study, we introduce ridge regression to replace ordinary least squares (OLS) in the MHACS. Practical experiments on short-term hourly tide gauge records and satellite altimeter observations indicate that ridge regression can effectively eliminate meaningless mathematical artifacts obtained by OLS. The minimum length of records for MHACS to resolve eight major tides dramatically decreases from ∼210 h to ∼75 h as a result of using ridge regression. It is also found that ridge regression can notably reduce the uncertainties of tidal estimates from MHACS. Moreover, other modified harmonic analysis models such as NS_TIDE designed for river tides also suffer from over-fitting which can be solved by ridge regression in a similar way.

Long-term variation in volume transport of the Tsushima warm current estimated from ADCP current measurement and sea level differences in the Korea/Tsushima Strait

ADCP current data and sea level data from tide gauges and satellite altimetry were used in order to analyze long-term variation of the Tsushima Warm Current (TWC) volume transport passing through the Korea/Tsushima Strait. The annual mean transport of the TWC estimated from ADCP current measurement for about 17 years (1997–2013) is 2.64 ± 0.41 Sv (Sv = 106 m3s−1) in the Korea/Tsushima Strait, 1.53 ± 0.36 Sv (about 58% of the total transport) in the western channel, and 1.11 ± 0.14 Sv (about 42%) in the eastern channel. The TWC shows the minimum transport (1.74 Sv) in January and the maximum transport (3.10 Sv) in October, with seasonal variation of up to 1.36 Sv (51.5% of the annual mean transport). The seasonal variation of the total TWC transport in the Korea/Tsushima Strait is mainly similar to that in the western channel. The annual mean transport of the TWC and its seasonal variation in the Korea/Tsushima Strait, the western and eastern channels are all similar in three datasets (ADCP, tide gauge, satellite altimetry). The annual mean volume transport of the TWC estimated from long-term tide gauge data was 2.57 ± 0.37 Sv (total volume transport) for 44 years (1975–2018) in the Korea/Tsushima Strait, 1.51 ± 0.32 Sv in the western channel and 1.06 ± 0.14 Sv in the eastern channel. Long-term variation of the TWC transport shows a decreasing trend for 1975 to 1988, and an increasing trend from 1989 to 2018. For the latter period (1989 to 2018), monthly transport tends to increase in all months throughout the years, showing a greater increase, especially in spring and summer months. The increase of the transport in the eastern channel was about 2.8 times larger than that in the western channel. It is suggested that the increasing trend of the TWC transport since 1989 is related to the Pacific Decadal Oscillation (PDO), which has been changed to negative direction since mid-1980s. During the period when the negative PDO index is strong, the negative wind stress curl weakens in the mid-latitudes of the North Pacific, and the Kuroshio in the East China Sea also weakens. As a result, the flow is strengthened toward the Korea/Tsushima Strait, increasing the TWC transport.

Continuous measurement of sea ice freeboard with tide gauges and GNSS interferometric reflectometry

Sea ice thickness is an important climate indicator and is often monitored in the form of freeboard or total freeboard (with snow cover) using satellite altimetry. However, satellites often have a long revisit interval and freeboard measurements in coastal areas can be challenged by land, deformed ice and limited leads. Using a combination of tide gauge for sea level measurements and a coastal GNSS station for sea ice or snow surface height measurements based on GNSS interferometric reflectometry (GNSS-IR), I demonstrate freeboard measurements with high temporal resolution (hourly). In a 4.5-year period from late 2016 to middle 2021, freeboards measured with this method at Cape Roberts, western Ross Sea in Antarctica exhibit a clear annual cycle of ice growth and ablation in the range of ~0–40 cm, and a rapid decrease occurring in Antarctic summer when ocean water temperature increases abruptly. For places where the amplitudes of long-term tides are significantly smaller than the range of annual freeboard variation, GNSS-IR can independently measure both tides and freeboards. Compared to conventional sea ice thickness or freeboard measurements, the tide gauge and GNSS-IR combination method is safe, inexpensive, can distinguish spatial variation of freeboard over a distance of tens to hundreds of meters, and allows continuous monitoring of an area of a few square kilometers.

Shift of the storm surge season in Europe due to climate variability

Along the European coasts, changes in the timing of the storm surge season are analyzed. Using 10 long-term tide gauges located in western Europe, a consistent spatio-temporal shift emerged in the storm surge season between 1950 and 2000. Temporal shifts are positive (later events) in the North, negative (earlier events) in the South. Extreme surge events occurred about 4 days/decade later in northern Europe, and 5 days/decade earlier in southern Europe. Such a tendency is similar to the one already reported for European river floods between 1960 and 2010. In northern Europe, extreme surges are known to occur during the positive North Atlantic Oscillation phase (NAO+). Identified spatio-temporal shifts likely trace that NAO+ storms tend to occur later between 1950 and 2000. A new index measuring the timing of the NAO+ and NAO− persistent situations is shown to help capture this spatial distribution in the timing of the storm surge seasons.

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.

Establishing a long-term Tidal Water Elevation for Thane City, India

Future extreme tide levels and flood risk along the coastal region will be impacted strongly by climate change. Flooding in urban areas is a big challenge affecting coastal cities worldwide due to heavy rainfall coupled with high tides. The key factor in the design and planning of coastal town drainage systems is the selection of appropriate tide levels at drainage outfall location. The present study aims to define the long-term tidal water level for Thane city, India and this level will perform effectively under current and future tidal water conditions. The present study uses the observed tidal data from 2009 to 2018 about Thane Salt Bundar tide gauge station and Kasheli Bridge tide gauge station. Initially, the tidal levels are defined for various tidal phases using the fundamental statistical analysis method, the trend of tide level analysed by the linear regression model and then Gumbel's extreme value type I (EV-I) distribution method used to define the long-term tide levels for different return periods. The obtained results indicate that the tidal level may rise by 300 mm at Thane salt bundar and 270 mm at Kasheli bridge. The long-term tidal level at Thane salt Bundar may increase 3.3m and 2.3 m at Kasheli bridge. Established long-term tidal levels give good results under climate change conditions and can be safer for avoiding flood risk and improving the drainage outfall design for Thane city.

El Niño driven extreme sea levels in an Eastern Pacific tropical river delta: Landward amplification and shift from oceanic to fluvial forcing

As greenhouse warming is predicted to intensify the El Niño–Southern Oscillation (ENSO), it is key to understand relationships between the magnitudes and spatial distribution of ENSO events and associated extreme sea levels (ESLs). Current understanding is lacking for river deltas, where human societies and ecosystems are particularly vulnerable to coastal hazards. Using long-term tide gauge records, we report on ESLs during historical ENSO events of different magnitudes, spatial distribution and temporal evolution in the Guayas delta–Gulf of Guayaquil (Ecuador), the largest estuarine system on the Pacific coast of South America and a relevant hotspot for coastal hazards. Here, we found a landward amplification of sea level anomalies during Eastern Pacific El Niño events, with monthly mean values peaking from +43 cm at the open coast to +75 cm in the inner delta, producing among the highest ENSO driven ESLs ever documented. This landward amplification is shown to coincide with a sea-to-land gradient from a predominantly oceanic (thermosteric) to meteorological (fluvial) El Niño contribution to these ESLs, demonstrating the strong coupling between these two forcings of El Niño. Our findings highlight the strong exposure of coastal societies and ecosystems to ENSO driven ESLs and the pressing need for adaptation measures in face of continued global warming.

Is there a quasi 60-year oscillation in global tides?

We analyze long-term tide gauge records to examine whether there is a quasi 60-year oscillation in global tides. We find that there is a significant 55-year cycle at more than half of the tide gauges analyzed. For M2 tide, the amplitudes of the 55-year cycle range from 1.82 ± 0.80 mm (Los Angles) to 26.34 ± 6.75 mm (Cuxhaven), while for S2 tide, the amplitudes of the 55-year cycle range from 1.02 ± 0.48 mm (San Francisco) to 8.61 ± 2.25 mm (Cuxhaven). At Cuxhaven, shallow water constituents M4, MS4 and M6 tides which obtain energy from M2 and S2 tides also show significant 55-year cycles. It is found that the 55-year cycle significantly influences the estimation of the long-term trend of tidal amplitudes at Newlyn, Cuxhaven, Eastport and Victoria. The influence of the 55-year cycle on long-term trends of tidal amplitudes at Cuxhaven is the strongest among these stations. At Cuxhaven, the long-term trend of M2 (S2) amplitudes sharply increases from 0.68 ± 0.10 (0.22 ± 0.03) mm/yr to 0.93 ± 0.06 (0.31 ± 0.03) mm/yr when the 55-year cycle is removed. It is also found that the 55-year cycle in tides can partly explain the rapid change in M2 and S2 tides since 1980s in the North Atlantic. Quasi-60 year variations in sea levels and sea water temperature may be responsible for the 55-year cycle in tides while the detailed mechanisms still need further research.

Annual Sea Level Amplitude Analysis over the North Pacific Ocean Coast by Ensemble Empirical Mode Decomposition Method

Understanding spatial and temporal changes of seasonal sea level cycles is important because of direct influence on coastal systems. The annual sea level cycle is substantially larger than semi-annual cycle in most parts of the ocean. Ensemble empirical mode decomposition (EEMD) method has been widely used to study tidal component, long-term sea level rise, and decadal sea level variation. In this work, EEMD is used to analyze the observed monthly sea level anomalies and detect annual cycle characteristics. Considering that the variations of the annual sea level variation in the Northeast Pacific Ocean are poorly studied, the trend and characteristics of annual sea level amplitudes and related mechanisms in the North Pacific Ocean are investigated using long-term tide gauge records covering 1950–2016. The average annual amplitude of coastal sea level exhibits interannual-to-decadal variability within the range of 14–220 mm. The largest value of ~174 mm is observed in the west coast of South China Sea. In the other coastal regions of North Pacific Ocean, the mean annual amplitude is relatively low between 77 and 124 mm for the western coast and 84 and 87 mm for the eastern coast. The estimated trend values for annual sea level amplitudes in the western coastal areas of South China Sea and Northeast Pacific Ocean have statistically decreased over 1952–2014 with a range of −0.77 mm·yr−1 to −0.11 mm·yr−1. Our results suggested that the decreasing annual amplitude in the west coast of South China Sea is in good agreement with the annual mean wind stress associated with the Pacific Decadal Oscillation (PDO). This wind phenomenon also explains the temporal variations of annual sea level amplitude in Northeast Pacific Ocean, especially the high correlations since 1980 (R = 0.61−0.72).

The decadal sea level variability observed in the Indian Ocean tide gauge records and its association with global climate modes

Decadal sea level variability of the Indian Ocean is studied using long-term tide gauge observations of 17 stations. The existence of close association between Indian Ocean sea level and the global decadal climate modes, such as Pacific Decadal Oscillation (PDO) and/or Atlantic Multidecadal Oscillation (AMO) is revealed in most of the tide gauge data sets. An anti-phase sea level evolution with PDO index is identified in the regions such as west coast of India, east coast of India and the western coast of Australia. Moreover, the PDO related sea level variability is found to be stronger at the tide gauge stations along the west coast of India compared to that along the east coast of India, ruling out the remote forcing from the equatorial Indian Ocean. On the other hand, the tide gauge station at Mumbai with more than 100 years of data shows an in-phase relationship with AMO index on the decadal timescales, whereas such relationship is very weak at the tide gauge station Fremantle where similar long-term data is available. The analysis of sea level pressure (SLP), rainfall and winds over the tropical Indian Ocean indicates existence of strong relationship with AMO especially over the Arabian Sea region, strongly suggesting that the variability observed at the tide gauge station Mumbai may have larger spatial signatures. During the positive phase of AMO, the Arabian Sea region is characterized by large fall in SLP and a strong cross equatorial flow towards the Indian land mass, which are primarily responsible for the positive sea level anomalies (SLAs) at the Mumbai tide gauge station and the adjacent regions and positive rainfall over India.

A 3-D MODEL USING REPRESENTATIVE WAVES METHOD FOR SHORELINE MORPHODYNAMICS AROUND COASTAL STRUCTURES

The Fort Pierce Shore Protection Project nourishes a 2.1-km Atlantic Ocean shoreline south of Fort Pierce Inlet in St. Lucie County, Florida. The beach fill erodes nonuniformly with a hotspot along the northernmost 0.7 km requiring nourishment after about two years of normal wave regime. This study validated and applied to beach stabilization a shoreline morphology model to evaluate designs and combinations of coastal structures to increase the nourishment interval. Simulations of long-term normal tides, waves, and storm conditions show (a) shoreline movement pattern similar to the general historical pattern observed in the project area, including accurately indicating the largest erosion rate and shoreline retreat along the first 0.7 km south of the jetty; (b) the coastal structures retain beach fill longer, resulting in lower erosion rates from 0.8 to 6.4 km south of the jetty; and (c) the coastal structures alternative extends the normal beach nourishment interval from the current two years to four years. Application of representative waves allows accurate and efficient modeling of long-term 3-D beach and shoreline deformation.

Coastal Dam Inundation Assessment for the Yellow River Delta: Measurements, Analysis and Scenario

Coastal dams along the Yellow River Delta are built to prevent seawater intrusion. However, land subsidence caused by significant oil, gas and brine extraction, as well as sediment compaction, could exacerbate the flooding effects of sea-level rise and storm surge. In order to evaluate the coastal dam vulnerability, we combined unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR) with small baseline subsets (SBAS) interferometric synthetic aperture radar (InSAR) results to generate an accurate coastal dam digital elevation model (DEM) over the next 10, 30 and 80 years. Sea-level simulation was derived from the relative sea-level rise scenarios published by the Intergovernmental Panel on Climate Change (IPCC) and local long-term tide gauge records. Assuming that the current rate of dam vertical deformation and sea-level rise are linear, we then generated different inundation scenarios by the superposition of DEMs and sea-levels at different periods by way of a bathtub model. We found that the overtopping event would likely occur around Year 2050, and the northern part of the dam would lose its protective capability almost entirely by the end of this century. This article provides an alternative cost-effective method for the detection, extraction and monitoring of coastal artificial infrastructure.

The Seasonal Cycle of Mean Sea Level in the North East Atlantic Ocean

Payo-Payo, M. and Bertin, X., 2020. The seasonal cycle of mean sea level in the North East Atlantic Ocean. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1515-1519. Coconut Creek (Florida), ISSN 0749-0208.The analysis of long-term tide gauge data collected in the Northeast Atlantic Ocean reveals that the seasonal cycle of mean sea level (hereafter MSL) exhibits amplitudes of up to 0.4 m. The position of MSL is of fundamental importance for many issues such as storm-induced flooding or the morphodynamics of shallow inlets, yet the underlying mechanisms are not fully understood. We characterize the seasonal cycle based on field observations complemented with a numerical hindcast. We analyzed long-term series (2000-2010) of in-situ tide gauge data along the coasts of Portugal, Spain and France. The combined analysis of field observation and model results revealed that atmospheric pressure, wind and steric effect are the main contributors to the seasonal cycle of MSL along North East Atlantic Ocean coastlines. We find a coherent signal over the region: the cycle peaks around November and has its minimum in February. Monthly mean sea level rises slowly and falls quickly. The different features between north and south mirror the different forcing mechanisms acting in each area. To the north, the seasonal cycle of MSL is more irregular and controlled by atmospheric forcing because this region is on the track of low-pressure storms, especially during winter. To the south, the steric effect plays an important role mostly due to the persistence of high pressure and a narrow continental shelf. Our results suggest that for a given storm, the water level and subsequent flooding damage will be higher if it occurs at the end of the autumn than at the end of the winter, which suggest that the seasonal cycle of MSL should be represented in flooding modeling systems.

An extreme sea level event along the northwest coast of the South China sea in 2011–2012

An extreme sea-level (ESL) event in 2011–2012 and its associated mechanisms are investigated using long-term tide gauge records and satellite altimeter data. The composite sea level anomaly (SLA) along the northwest coast of the SCS is up to 85.2 mm in 2012, reaching the highest since 1975. The ESL event in 2011–2012 is a combined effect of the mean sea-level rise, La Niña event and negative Pacific Decadal Oscillation (PDO) phase. The three factors work on different time scales. The long-term rising rate is 3.1 mm/yr from 1975 to 2015, the linear estimate of the mean sea level is 45.1 mm in 2012, accounting for about 52.9% of the total ESL (85.2 mm). After removing the linear trend, La Niña has a 28.2% contribution of the highest SLA, the negative PDO phase has a 51.3% contribution, and they jointly give rise to the ESL event on interannual to decadal time scales. The dynamic sea-level variation is the dominant contributor, explaining 72.8% of the observed sea-level differences between 2010 and 2012. The sea level pressure contributes 34.4%, and the steric effect contributes 7.7% of the observed results.

Characterisation of low-frequency sea level oscillations in the Mediterranean sea

Implementing adequate defences for low-lying coastal area against coastal flooding requires thorough knowledge of all potential influences leading to increased sea levels, including low-frequency sea level oscillations. We present and describe several methods applicable for the analysis of low-frequency sea level oscillations in the Mediterranean Sea: wavelet analysis, spectral analysis, moving-periodogram analysis, and rotary spectral analysis. These methods were applied for characterisation of subinertial sea level oscillations with periods greater of the period of inertial oscillation (18 hours in the Northern Adriatic Sea) on measured sea surface elevations and current velocities in the Mediterranean Sea. Preliminary analysis was performed on observations of a storm event in the Adriatic Sea at the end of January and the beginning of February 2014, revealing a peak in the frequency spectrum in the frequency band between 0.3−0.4 day−1. Further analysis was done on long-term tide gauge measurements available for 62 stations in the Mediterranean basin. The application of the selected methods provided a preliminary set of seasonal occurrences and durations of subinertial oscillation. This sets the ground for further investigation into the propagation of low-frequency sea level oscillations throughout the Mediterranean basin and for characterisation of the mechanisms triggering the process, including with regard to climate change.

Use of Oceanic Reanalysis to Improve Estimates of Extreme Storm Surge

AbstractA storm surge hindcast for the west coast of Canada was generated for the period 1980–2016 using a 2D nonlinear barotropic Princeton Ocean Model forced by hourly Climate Forecast System Reanalysis wind and sea level pressure. Validation of the modeled storm surges using tide gauge records has indicated that there are extensive areas of the British Columbia coast where the model does not capture the processes that determine the sea level variability on intraseasonal and interannual time scales. Some of the discrepancies are linked to large-scale fluctuations, such as those arising from major El Niño and La Niña events. By applying an adjustment to the hindcast using an ocean reanalysis product that incorporates large-scale sea level variability and steric effects, the variance of the error of the adjusted surges is significantly reduced (by up to 50%) compared to that of surges from the barotropic model. The importance of baroclinic dynamics and steric effects to accurate storm surge forecasting in this coastal region is demonstrated, as is the need to incorporate decadal-scale, basin-specific oceanic variability into the estimation of extreme coastal sea levels. The results improve long-term extreme water level estimates and allowances for the west coast of Canada in the absence of long-term tide gauge records data.

Contemporary monitoring of storm surge activity

There is growing interest in storm surge activity related to catastrophic events and their unintended consequences in terms of casualties and damage around the world and in increasing populations and issues along coastal areas in the context of global warming and rising sea levels. Accordingly, knowledge on storm surge monitoring has progressed significantly in recent years, and this review, focused on monitoring the spatial and temporal variability of storm surges, responds to the need for a synthesis. Three main components are presented in the review: (1) monitoring storm surges from the viewpoint of three effective approaches; (2) understanding the challenges faced by the three monitoring approaches to increase our awareness of monitoring storm surges; (3) identifying three research priorities and orientations to provide new ideas in future storm surge monitoring. From the perspective of monitoring approaches, recent progress was achieved with respect to tide gauges, satellite altimetry and numerical simulation. Storm surge events can nowadays be identified accurately, and the surge heights can be calculated based on long-term tide gauge observations. The changing frequency and intensity of storm surge activity, combined with statistical analysis and climatology, can be used to enable a better understanding of the possible regional or global long-term trends. Compared with tidal observation data, satellite altimetry has the advantage of providing offshore sea level information to an accuracy of 10 cm. In addition, satellite altimetry can provide more effective observations for studying storm surges, such as transient surge data of the deep ocean. Simultaneously, the study of storm surges via numerical simulation has been further developed, mainly reflected in the gradual improvement of simulation accuracy but also in the refinement of comprehensive factors affecting storm surge activity. However, from the above approaches, storm surge activity monitoring cannot fully reflect the spatial and temporal variability of storm surges, especially the spatial changes at a regional or global scale. In particular, compared to global storm surge, tide gauges and satellite altimeters are relatively sparse, and the spatial distribution is extremely uneven, which often seriously restricts the overall understanding of the spatial distribution features of storm surge activity. Numerical models can be used as a tool to overcome the above-mentioned shortcomings for storm surge monitoring, as they provide real-time spatiotemporal features of storm surge events. But long-term numerical hindcast of tides and surges requires an extremely high computational effort. Considering the shortcomings of the above approaches and the impact of climate change, there is no clear approach to remedy the framework for studying the spatial and temporal characteristics of global or regional storm surge activity at a climatic scale. Therefore, we show how new insights or techniques are useful for the monitoring of future crises. This work is especially important in planning efforts by policymakers, coastal managers, civil protection managers and the general public to adapt to climate change and rising sea levels.

THE VERTICAL LAND MOTION OF TIDE GAUGE AND ABSOLUTE SEA LEVEL RISE IN BOHAI SEA

Abstract. The ground vertical movement of the tide gauges around the Bohai sea was firstly analyzed by using the observation data from 2009 to 2017 of the nine co-located GNSS stations. It was found that the change rate of ground vertical motion of four stations was in the same order of magnitude as the sea level change. In particular, the land subsidence rate of BTGU station reaches 11.47 mm/yr, which should be paid special attention to in the analysis of sea level change. Then combined with long-term tide gauges and the satellite altimetry results, the sea level changes in the Bohai sea and adjacent waters from 1993 to 2012 were analyzed. The relative and absolute sea level rise rates of the sea area are 3.81 mm/yr and 3.61 mm/yr, respectively, both are higher than the global average rate of change. At the same time, it is found that the vertical land motion of tide gauge stations is the main factor causing regional differences in relative sea level changes.