Re-assessing extreme sea level events through interplay of tides and storm surges

2020 ◽  
Author(s):  
Stephen Outten ◽  
Tobias Wolf ◽  
Fabio Mangini ◽  
Linling Chen ◽  
Jan Even Nilsen
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Critical Infrastructure ◽  
Tide Gauge ◽  
Storm Surges ◽  
Return Level ◽  
National Standard ◽  
Moderate Intensity ◽  
Extreme Storm ◽  
Warming World

<p>Flooding events pose an ever increasing threat in a warming world. Safety standards for buildings and infrastructure are often based on past observations of local sea level, as measured by tide gauges and remote sensing systems. However, sea level at a given location is not an isolated property and is determined by a combination of factors. For extreme sea level events, there are two factors that of particular importance: the astronomical tide, and storm surges. In this work, we analysed measurements from 21 stations in the Norwegian tide gauge network, disentangling the factors contributing to the previously observed extreme events.</p><p>By separating the observed sea level into a tidal component and a storm surge component, we found that in many cases the observed extreme sea level events were caused by an extreme storm surge coinciding with only a moderate tide, or an extreme tide coinciding with only a moderate storm surge. This raises the possibility of a ‘super-flooding’ event, where an extreme storm surge may occur with an extreme tide. Even in the short records examined in this study (less than 40 years), the combination of the highest observed tide with the highest observed storm surge would greatly exceed in the 1000-year return level event at many locations. This is often used as a national standard for critical infrastructure.  </p><p>We further complement the work by analysing the storm tracks close to Norway. By relating the storm surges with the individual storms giving rise to them, we found that many storm surges during extreme sea level events were related to cyclones of only moderate intensity. Combined with the previous findings, this work suggests the need to assess extreme sea level return values for future construction and infrastructure planning as the result of a multi-variable system. This is in contrast to basing such assessments on the single variable of observed sea level as it is done today.</p>

scholarly journals “Grey swan” storm surges pose a greater coastal flood hazard than climate change

2021 ◽  
Author(s):  
Kevin Horsburgh ◽  
Ivan D. Haigh ◽  
Jane Williams ◽  
Michela De Dominicis ◽  
Judith Wolf ◽  
...  
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Storm Surges ◽  
Natural Variability ◽  
Major Incident ◽  
Dynamical Response ◽  
Mean Sea Level ◽  
Coastal Flood ◽  
Extreme Storm ◽  
Observational Record

AbstractIn this paper, we show that over the next few decades, the natural variability of mid-latitude storm systems is likely to be a more important driver of coastal extreme sea levels than either mean sea level rise or climatically induced changes to storminess. Due to their episodic nature, the variability of local sea level response, and our short observational record, understanding the natural variability of storm surges is at least as important as understanding projected long-term mean sea level changes due to global warming. Using the December 2013 North Atlantic Storm Xaver as a baseline, we used a meteorological forecast modification tool to create “grey swan” events, whilst maintaining key physical properties of the storm system. Here we define “grey swan” to mean an event which is expected on the grounds of natural variability but is not within the observational record. For each of these synthesised storm events, we simulated storm tides and waves in the North Sea using hydrodynamic models that are routinely used in operational forecasting systems. The grey swan storms produced storm surges that were consistently higher than those experienced during the December 2013 event at all analysed tide gauge locations along the UK east coast. The additional storm surge elevations obtained in our simulations are comparable to high-end projected mean sea level rises for the year 2100 for the European coastline. Our results indicate strongly that mid-latitude storms, capable of generating more extreme storm surges and waves than ever observed, are likely due to natural variability. We confirmed previous observations that more extreme storm surges in semi-enclosed basins can be caused by slowing down the speed of movement of the storm, and we provide a novel explanation in terms of slower storm propagation allowing the dynamical response to approach equilibrium. We did not find any significant changes to maximum wave heights at the coast, with changes largely confined to deeper water. Many other regions of the world experience storm surges driven by mid-latitude weather systems. Our approach could therefore be adopted more widely to identify physically plausible, low probability, potentially catastrophic coastal flood events and to assist with major incident planning.

scholarly journals Storm surges in the Western Black Sea. Operational forecasting

2000 ◽  
Vol 1 (1) ◽  
pp. 45 ◽  
Author(s):  
G. MUNGOV ◽  
P. DANIEL
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Black Sea ◽  
Tide Gauge ◽  
Coastal Zone Management ◽  
World Ocean ◽  
Storm Surges ◽  
Statistical Characteristics ◽  
The Black Sea ◽  
Operational Forecasting

The frequency of the storm surges in the Black Sea is lower than that in other regions of the World Ocean but they cause significant damages as the magnitude of the sea level set-up is up to 7-8 times greater than that of other sea level variations. New methods and systems for storm surge forecasting and studying their statistical characteristics are absolutely necessary for the purposes of the coastal zone management. The operational forecasting storm surge model of Meteo-France was adopted for the Black Sea in accordance with the bilateral agreement between Meteo-France and NINMH. The model was verified using tide-gauge observations for the strongest storms observed along the Bulgarian coast over the last 10 years.

NUMERICAL MODELING OF STORM SURGES, WIND WAVES AND FLOODING IN THE TAGANROG BAY

2017 ◽  
Author(s):  
Vladimir Fomin ◽  
Vladimir Fomin ◽  
Dmitrii Alekseev ◽  
Dmitrii Alekseev ◽  
Dmitrii Lazorenko ◽  
...  
Keyword(s):  
Sea Level ◽  
Wind Waves ◽  
Storm Surges ◽  
Atmospheric Model ◽  
Extreme Storm ◽  
Regional Atmospheric Model ◽  
Sea Level Oscillations ◽  
Flooding And Drying ◽  
Flooded Area ◽  
Taganrog Bay

Storm surges and wind waves are ones of the most important hydrological characteristics, which determine dynamics of the Sea of Azov. Extreme storm surges in Taganrog Bay and flooding in the Don Delta can be formed under the effect of strong western winds. In this work the sea level oscillations and wind waves in the Taganrog Bay were simulated by means of the coupled SWAN+ADCIRC numerical model, taking into account the flooding and drying mechanisms. The calculations were carried out on an unstructured mesh with high resolution. The wind and atmospheric pressure fields for the extreme storm from 20 to 28 of September, 2014 obtained from WRF regional atmospheric model were used as forcing. The analysis of simulation results showed the following. The western and northern parts of the Don Delta were the most flood-prone during the storm. The size of the flooded area of the Don Delta exceeded 50%. Interaction of storm surge and wind wave accelerated the flooding process, increased the size of the flooded area and led to the intensification of wind waves in the upper of Taganrog Bay due to the general rise of the sea level.

HIDRA 1.0: Deep-Learning-Based Ensemble Sea Level Forecasting in the Northern Adriatic 

2021 ◽  
Author(s):  
Lojze Žust ◽  
Matjaž Ličer ◽  
Anja Fettich ◽  
Matej Kristan
Keyword(s):  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Feature Learning ◽  
Circulation Model ◽  
Storm Surges ◽  
Building Blocks ◽  
Lead Times ◽  
Atmospheric Forcing ◽  
Northern Adriatic

<p>Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modeling in Adriatic a challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our setup of the general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2 × 10<sup>-6</sup>). HIDRA exhibits larger bias but lower RMSE than our setup of NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. HIDRA architecture building blocks are experimentally analyzed in detail and compared to alternative approaches. Results show the importance of sea level input for forecast lead times below 24 h and the importance of atmospheric input for longer lead times. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing while compensating for the errors in the tidal model. HIDRA is trained and analysed on a ten-year (2006-2016) timeseries of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a one-year (2019) hourly time series from tide gauge in Koper (Slovenia). Spectral and continuous wavelet analysis of the forecasts at the semi-diurnal frequency (12 h)<sup>-1</sup> and at the ground-state basin seiche frequency (21.5 h)<sup>-1</sup> is performed. The energy at the basin seiche in the HIDRA forecast is close to the observed, while our setup of NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic the timing and amplitude of basin seiches.</p>

scholarly journals Statistical Prediction of Extreme Storm Surges Based on a Fully Supervised Weather-Type Downscaling Model

2020 ◽  
Vol 8 (12) ◽  
pp. 1028
Author(s):  
Wagner Costa ◽  
Déborah Idier ◽  
Jérémy Rohmer ◽  
Melisa Menendez ◽  
Paula Camus
Keyword(s):  
Storm Surge ◽  
Storm Surges ◽  
Absolute Error ◽  
Weather Type ◽  
Statistical Prediction ◽  
Daily Maximum ◽  
Maximum Absolute Error ◽  
Extreme Storm ◽  
Gauge Station ◽  
Data Driven Approach

Increasing our capacity to predict extreme storm surges is one of the key issues in terms of coastal flood risk prevention and adaptation. Dynamically forecasting storm surges is computationally expensive. Here, we focus on an alternative data-driven approach and set up a weather-type statistical downscaling for daily maximum storm surge (SS) prediction, using atmospheric hindcasts (CFSR and CFSv2) and 15 years of tidal gauge station measurements. We focus on predicting the storm surge at La Rochelle–La Pallice tidal gauge station. First, based on a sensitivity analysis to the various parameters of the weather-type approach, we find that the model configuration providing the best performance in SS prediction relies on a fully supervised classification using minimum daily sea level pressure (SLP) and maximum SLP gradient, with 1° resolution in the northeast Atlantic domain as the predictor. Second, we compare the resulting optimal model with the inverse barometer approach and other statistical models (multi-linear regression; semi-supervised and unsupervised weather-types based approaches). The optimal configuration provides more accurate predictions for extreme storm surges, but also the capacity to identify unusual atmospheric storm patterns that can lead to extreme storm surges, as the Xynthia storm for instance (a decrease in the maximum absolute error of 50%).

Storm Surge Impact to Subterranean Areas by Hurricane Sandy, and Lessons for Japan’s Storm Surge Countermeasures

2016 ◽  
Vol 11 (2) ◽  
pp. 274-284 ◽  
Author(s):  
Joel Challender ◽  
Keyword(s):  
New York ◽  
Storm Surge ◽  
Critical Infrastructure ◽  
Human Life ◽  
Public Information ◽  
Storm Surges ◽  
Recovery Phase ◽  
Hurricane Sandy ◽  
Coastal Communities ◽  
Eastern Seaboard

Hurricane Sandy caused critical damage to subterranean infrastructure in New York and also claimed 285 human lives across the Eastern Seaboard. The storm surge impact easily overwhelmed existing pumping systems, devastating power supply and paralyzing transport. Despite extensive preparations and pre-storm public information efforts, inundation and underground flooding caused causalities. The size of the disaster, sheer scope of damage and multifaceted response spanning the onset through to the recovery phase provides useful lessons for Japan, given its vulnerability to similar storm surges and flooding disasters, such as the Ise Bay Typhoon of 1959. Given this, a delegation composed of members of the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) and Researchers from Japan’s Universities and Academic Societies working in disaster prevention conducted two surveys in 2013 and 2014. This involved hearing from emergency management officers in New York, Washington D.C and coastal communities about their experiences evacuating vulnerable residents and protecting critical infrastructure. The author of this paper was a member of both delegations. Based on fieldwork from these joint surveys and other materials, this paper outlines the scope of the damage that a storm of Sandy’s size was capable of inflicting, and looks at lessons applicable to Japan for preventing similar damage to infrastructure and human life in future storm surge events, and discusses how New York is attempting to become a more resilient city in preparation for the next flooding or storm surge disaster.

scholarly journals Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the N orth S ea and B altic S ea

2015 ◽  
Vol 120 (9) ◽  
pp. 6405-6418 ◽  
Author(s):  
Kristine S. Madsen ◽  
Jacob L. Høyer ◽  
Weiwei Fu ◽  
Craig Donlon
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Tide Gauge

scholarly journals A century of sea level data and the UK's 2013/14 storm surges: an assessment of extremes and clustering using the Newlyn tide gauge record

2014 ◽  
Vol 11 (4) ◽  
pp. 1995-2028 ◽  
Author(s):  
M. P. Wadey ◽  
I. D. Haigh ◽  
J. M. Brown
Keyword(s):  
Sea Level ◽  
Return Period ◽  
Tide Gauge ◽  
Storm Surges ◽  
High Water ◽  
Lower Probability ◽  
Tide Gauge Record ◽  
Storm Activity ◽  
Sea Levels ◽  
Level Data

Abstract. For the UK's longest and most complete sea level record (Newlyn), we assess extreme high water events and their temporal clustering; prompted by the 2013/2014 winter of flooding and storms. These are set into context against this almost 100 yr record. We define annual periods for which storm activity, tides and sea levels can be compared on a year-by-year basis. Amongst the storms and high tides which affected Newlyn the recent winter produced the largest recorded high water (3 February 2014) and five others above a 1 in 1 yr return period. The large magnitude of tide and mean sea level, and the close inter-event spacings (of large return period high waters), suggests that the 2013/2014 high water "season" may be considered the most extreme on record. However, storm and sea level events may be classified in different ways. For example in the context of sea level rise (which we calculate linearly as 1.81 ± 0.1 mm yr−1 from 1915 to 2014), a lower probability combination of surge and tide occurred on 29 January 1948, whilst 1995/1996 storm surge season saw the most high waters of ≥ 1 in 1 yr return period. We provide a basic categorisation of five types of high water cluster, ranging from consecutive tidal cycles to multiple years. The assessment is extended to other UK sites (with shorter sea level records and different tide-surge characteristics), which suggests 2013/2014 was extreme, although further work should assess clustering mechanisms and flood system "memory".

scholarly journals Coastal Floods Induced by Mean Sea Level Rise—Ecological and Socioeconomic Impacts on a Mesotidal Lagoon

2021 ◽  
Vol 9 (12) ◽  
pp. 1430
Author(s):  
Francisco Silveira ◽  
Carina Lurdes Lopes ◽  
João Pedro Pinheiro ◽  
Humberto Pereira ◽  
João Miguel Dias
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Storm Surges ◽  
Socioeconomic Impacts ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Ria De Aveiro ◽  
The Future ◽  
Coastal Floods ◽  
Agricultural Areas

Coastal floods are currently a strong threat to socioeconomic activities established on the margins of lagoons and estuaries, as well as to their ecological equilibrium, a situation that is expected to become even more worrying in the future in a climate change context. The Ria de Aveiro lagoon, located on the northwest coast of Portugal, is not an exception to these threats, especially considering the low topography of its margins which has led to several flood events in the past. The growing concerns with these regions stem from the mean sea level (MSL) rise induced by climate changes as well as the amplification of the impacts of storm surge events, which are predicted to increase in the future due to higher mean sea levels. Therefore, this study aims to evaluate the influence of MSL rise on the inundation of Ria de Aveiro habitats and to assess the changes in inundation patterns resulting from frequent storm surges (2-year return period) from the present to the future, assessing their ecological and socioeconomic impacts. For this, a numerical model (Delft3D), previously calibrated and validated, was used to simulate the lagoon hydrodynamics under different scenarios combining MSL rise and frequent storm surge events. The numerical results demonstrated that MSL rise can change the vertical zonation and threaten the local habitats. Many areas of the lagoon may change from supratidal/intertidal to intertidal/subtidal, with relevant consequences for local species. The increase in MSL expected for the end of the century could make the lagoon more vulnerable to the effect of frequent storm surges, harming mostly agricultural areas, causing great losses for this sector and for many communities who depend on it. These extreme events can also affect artificialized areas and, in some cases, endanger lives.

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