Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

Numerical Analysis of Storm Surges on Canada’s Western Arctic Coastline

A numerical study was conducted to characterize the probability and intensity of storm surge hazards in Canada’s western Arctic. The utility of the European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5) dataset to force numerical simulations of storm surges was explored. Fifty historical storm surge events that were captured on a tide gauge near Tuktoyaktuk, Northwest Territories, were simulated using a two-dimensional (depth-averaged) hydrodynamic model accounting for the influence of sea ice on air-sea momentum transfer. The extent of sea ice and the duration of the ice season has been reducing in the Arctic region, which may contribute to increasing risk from storm surge-driven hazards. Comparisons between winter storm events under present-day ice concentrations and future open-water scenarios revealed that the decline in ice cover has potential to result in storm surges that are up to three times higher. The numerical model was also used to hindcast a significant surge event that was not recorded by the tide gauge, but for which driftwood lines along the coast provided insights to the high-water marks. Compared to measurements at proximate meteorological stations, the ERA5 reanalysis dataset provided reasonable estimates of atmospheric pressure but did not accurately capture peak wind speeds during storm surge events. By adjusting the wind drag coefficients to compensate, reasonably accurate predictions of storm surges were attained for most of the simulated events. The extreme value probability distributions (i.e., return periods and values) of the storm surges were significantly altered when events absent from the tide gauge record were included in the frequency analysis, demonstrating the value of non-conventional data sources, such as driftwood line surveys, in supporting coastal hazard assessments in remote regions.

The ambiguous sea level rise at Brest’s 212 yearlong record elucidated

The tide gauge record at Brest, France, along Eastern part of Atlantic coast is one of the longest records in Europe spanning 212 years (1807–2019). Analyzing these records has important ramifications in assessing anthropogenic impact of climate change at local and regional scales during this period. All the previous studies that analyzed Brest’s tide gauge record have used vaguely defined quadratics models and did not incorporate the effect of sea level variations at various frequencies, which confounded the presence or absence of a plausible uniform acceleration. Here, we entertained two competing kinematic models; one with a uniform acceleration representing 212 years of monthly averaged tide gauge data, the other is a two-phase trend model (Phase I is 93 years long and Phase II is 119 years long). Both models include statistically significant (α = 0.05) common periodic effects, and sub and super harmonics of luni-solar origin for representing monthly averaged sea level anomalies observed at Brest. The least squares statistics for both models’ solutions cannot distinguish one model over the other, like earlier studies. However, the assessment of Phase I segment of the records disclosed the absence of a statistically significant trend and a uniform acceleration during this period. This outcome eliminates conclusively the occurrence of a uniform acceleration during the entire 212-year data span of the tide gauge record at Brest, favoring the two-phase trend model as a sound alternative.

Review and Assessment of gap-filling methods from tide-gauges: Maxima missing at the Esbjerg, Denmark station, before 1910.

<p>Information on extremes of the sea-level is obtained from tide-gauge<br>records.  Such records may have gaps.</p><p>Estimates of potential changes in the size and/or frequency of sea-level<br>extremes are hampered by long gaps, or when just the high extremes are<br>missing due, e.g. to equipment failure.</p><p>Methods used for filling such gaps can be based on having multiple<br>records from gauges near each other; but what to do if there is<br>only one record? This problem can typically occur when old tide-gauge<br>records are used -- the use of multiple recorders at the same place is<br>more wide-spread today. However, especially older and therefore longer<br>records hold the key to obtaining long-baseline insights into the temporal<br>evolution of extreme tides and thus impacts of e.g. climate change.</p><p>In this work, we review and assess methods for gap filling. We asses using<br>the 'known truth' method, i.e. by applying realistic gaps to complete<br>gauge records and reconstructing and then comparing errors calculated as<br>the diffrence between modelled and actual values.  We compare a simple<br>harmonic model fit method to various spline methods as well as Neural<br>network and deep learning approches.  We also test a hybrid method<br>which uses not just tide-gauge data but also air pressure readings<br>from a meteorological station near the tide-gauge.</p><p>We then attempt to fill in the missing maxima of the Esbjerg, Denmark<br>hourly tide-gauge record since 1889. Particularly, before 1910 the maxima<br>above 300 cm are missing (Bijl, et al., 1999), and we try to fill these in.</p>

Probabilistic reanalysis of storm surge extremes in Europe

<p>Extreme sea levels are a significant threat to life, property, and the environment. These threats are managed by coastal planers through the implementation of risk mitigation strategies. Central to such strategies is knowledge of extreme event probabilities. Typically, these probabilities are estimated by fitting a suitable distribution to the observed extreme data. Estimates, however, are often uncertain due to the small number of extreme events in the tide gauge record and are only available at gauged locations. This restricts our ability to implement cost-effective mitigation. A remarkable fact about sea-level extremes is the existence of spatial dependences, yet the vast majority of studies to date have analyzed extremes on a site-by-site basis. Here we demonstrate that spatial dependences can be exploited to address the limitations posed by the spatiotemporal sparseness of the observational record. We achieve this by pooling all the tide gauge data together through a Bayesian hierarchical model that describes how the distribution of surge extremes varies in time and space. Our new approach has two highly desirable advantages: 1) it enables sharing of information across data sites, with a consequent drastic reduction in estimation uncertainty; 2) it permits interpolation of both the extreme values and the extreme distribution parameters at any arbitrary ungauged location. Using our model, we produce the first, to our knowledge, observation-based probabilistic reanalysis of surge extremes covering the entire Atlantic and North Sea coasts of Europe for the period 1960-2013.</p>

Automating Tide Gauge Quality Control

<p>Tide gauges provide a vital component in coastal flooding alert systems, and as a record of past events. They are used to record short duration extremes such as tsunamis, storm surges lasting a few hours, regular tides, and long term changes in relative sea-level. Globally, there is far more tide gauge data in existence than is available in the public domain for research. A significant factor obstructing the release of data is that quality control of tide-gauge records is still carried out with a great deal of manual inspection, and is therefore labour-intensive. Automated systems must carefully distinguish between spikes due to instrumental error and genuine rare extreme events; and between damaged instruments and still water. The National Oceanography Centre automatic quality control software aims to enable analysis of any high-frequency tide-gauge record around the world with minimal manual intervention or parameter selection. We demonstrate the implementation in Matlab and discuss the successes and challenges of the software.</p><p> </p>

Probabilistic reanalysis of storm surge extremes in Europe

Extreme sea levels are a significant threat to life, property, and the environment. These threats are managed by coastal planers through the implementation of risk mitigation strategies. Central to such strategies is knowledge of extreme event probabilities. Typically, these probabilities are estimated by fitting a suitable distribution to the observed extreme data. Estimates, however, are often uncertain due to the small number of extreme events in the tide gauge record and are only available at gauged locations. This restricts our ability to implement cost-effective mitigation. A remarkable fact about sea-level extremes is the existence of spatial dependences, yet the vast majority of studies to date have analyzed extremes on a site-by-site basis. Here we demonstrate that spatial dependences can be exploited to address the limitations posed by the spatiotemporal sparseness of the observational record. We achieve this by pooling all of the tide gauge data together through a Bayesian hierarchical model that describes how the distribution of surge extremes varies in time and space. Our approach has two highly desirable advantages: 1) it enables sharing of information across data sites, with a consequent drastic reduction in estimation uncertainty; 2) it permits interpolation of both the extreme values and the extreme distribution parameters at any arbitrary ungauged location. Using our model, we produce an observation-based probabilistic reanalysis of surge extremes covering the entire Atlantic and North Sea coasts of Europe for the period 1960–2013.

The long-term variability of extreme sea levels in the German Bight

Extreme high sea levels (ESLs) caused by storm floods constitute a major hazard for coastal regions. We here quantify their long-term variability in the southern German Bight using simulations covering the last 1000 years. To this end, global earth system model simulations from the PMIP3 past1000 project are dynamically scaled down with a regionally coupled climate system model focusing on the North Sea. This approach provides an unprecedented long high-resolution data record that can extend the knowledge of ESL variability based on observations, and allows for the identification of associated large-scale forcing mechanisms in the climate system. While the statistics of simulated ESLs compare well with observations from the tide gauge record at Cuxhaven, we find that simulated ESLs show large variations on interannual to centennial timescales without preferred oscillation periods. As a result of this high internal variability, ESL variations appear to a large extent decoupled from those of the background sea level, and mask any potential signals from solar or volcanic forcing. Comparison with large-scale climate variability shows that periods of high ESL are associated with a sea level pressure dipole between northeastern Scandinavia and the Gulf of Biscay. While this large-scale circulation regime applies to enhanced ESL in the wider region, it differs from the North Atlantic Oscillation pattern that has often been linked to periods of elevated background sea level. The high internal variability with large multidecadal to centennial variations emphasizes the inherent uncertainties related to traditional extreme value estimates based on short data subsets, which fail to account for such long-term variations. We conclude that ESL variations as well as existing estimates of future changes are likely to be dominated by internal variability rather than climate change signals. Thus, larger ensemble simulations will be required to assess future flood risks.

The long-term variability of extreme sea levels in the German Bight

We investigate the long-term variability of extreme high sea levels (ESL) in the southern German Bight and associated large-scale forcing mechanisms in the climate system using simulations covering the last 1000 years. To this end, global MPI-ESM simulations from the PMIP3 past1000 project are dynamically scaled-down with a regionally coupled climate system model focusing on the North Sea. We find that the statistics of simulated ESL compare well with observations from the tide gauge record at Cuxhaven but show large variations on interannual to centennial timescales. ESL arise independent of preferred systematic oscillations and are to a large extent decoupled from variations of the background sea level (BSL). Large scale circulation regimes associated with periods of high ESL are regionally consistent and similar to those associated with elevated BSL, but the location of the respective centers of action of the governing sea level pressure (SLP) dipole differs. While BSL variations correlate well with the wintertime North Atlantic Oscillation (NAO), ESL variations are rather associated with a dipole between northeastern Scandinavia and the Gulf of Biscay, leading to a stronger local north-westerly wind component in the North Sea. Potential links with solar or volcanic forcing are masked due to the high ESL variability. The high internal variability stresses the irreducible uncertainties related to traditional extreme value estimates based on shorter subsets which fail to account for long-term variations. Existing estimates of future changes in ESL may be dominated by natural variability rather than climate change signals, thus requiring larger ensemble simulations to assess future flood risks.

Sea Level Rise and Land Subsidence Contributions to the Signals from the Tide Gauges of China

The tide gauges measure the local oscillations of the sea level vs. the tide gauge instrument. The tide gauge instrument is generally subjected to the general subsidence or uplift of the nearby inland, plus some additional subsidence for land compaction and other localised phenomena. The paper proposes a non-linear model of the relative sea level oscillations including a long term trend for the absolute sea level rise, another term for the subsidence of the instrument, and finally a sinusoidal approximation for the cyclic oscillations of periodicities up to decades. This non-linear model is applied to the tide gauges of China. The paper shows that the limited information available for China does not permit to infer any proper trend for the relative rates of rise, as the tide gauge records are all short or incomplete and the vertical movement of the tide gauge instruments is unassessed. The only tide gauge record of sufficient length that may be assembled for China is obtained by combining the North Point and Quarry Bay tide gauges in Hong Kong (NPQB). This NQPB composite tide gauge record is shown to have similarities with the tide gauge records of Sydney, equally in the West pacific, and San Diego, in the east Pacific, oscillating about the longer term trend mostly determined by the local subsidence. As it is very well known that China generally suffers of land subsidence, and the tide gauge installations may suffer of additional subsidence vs. the inland, it may be concluded from the analysis of the other worldwide tide gauges that the sea levels of China are very likely rising about the same amount of the subsidence of the tide gauges, with the sea level acceleration component still negligible.