Supporting European coastal sectors to adapt to changes in extreme sea levels with climate change

2020 ◽  
Author(s):  
Sanne Muis ◽  
Maialen Irazoqui Apecechea ◽  
Job Dullaart ◽  
Joao de Lima Rego ◽  
Kristine S. Madsen ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Storm Surges ◽  
Climate Impact ◽  
Climate Impacts ◽  
Water Levels ◽  
Climate Data ◽  
Local Climate ◽  
Sea Levels ◽  
Extreme Sea Levels

<p>Climate change will lead to increases in the flood risk in low-lying coastal areas. Understanding the magnitude and impact of such changes is vital to design adaptive strategies and create awareness. In  the  context  of  the  CoDEC  project  (Coastal  Dataset  for  Evaluation  of  Climate  impact),  we  developed a consistent European dataset of extreme sea levels, including climatic changes from 1979 to 2100. To simulate extreme sea levels, we apply the Global Tide and Surge Model v3.0 (GTSMv3.0), a 2D hydrodynamic model with global coverage. GTSM has a coastal resolution of 2.5 km globally and 1.25 km in Europe, and incorporates dynamic interactions between sea-level  rise,  tides  and  storm surges. Validation of the dataset shows a good performance with a mean bias of 0-.04 m for the 1 in 10-year water levels. When analyzing changes in extreme sea levels for the future climate scenarios, it is projected that by the end of the century the 1 in 10-year water levels are likely to increase up to 0.5 m. This change is largely driven by the increase in mean sea levels, although locally changes in storms surge and interaction with tides can amplify the impacts of sea-level rise with changes up to 0.2 m in the 1 in 10-year water level.</p><p>The CoDEC dataset will be made accessible through a web portal on Copernicus Climate Data Store (C3S). The dataset includes a set of Climate Impact Indicators (CII’s) and new tools designed to evaluate the impacts of climate change on different sectors and industries. This data service will support European coastal sectors to adapt to changes in sea levels associated with climate change. In this presentation we will also demonstrate how the C3S coastal service can be used to enhance the understanding of local climate impacts.</p>

scholarly journals BENEFITS AND LIMITATIONS OF A COUPLED WAVE-SURGE MODEL FOR AUSTRALIAN EXTREMES

2020 ◽  
pp. 49
Author(s):  
Yasha Hetzel ◽  
Ivica Janekovic ◽  
Charitha Pattiaratchi
Keyword(s):  
Sea Level ◽  
Surface Wind ◽  
Circulation Model ◽  
Storm Surges ◽  
Breaking Waves ◽  
Water Levels ◽  
Storm Events ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Coupled Wave

Extreme sea levels result from a combination of a range of factors that include long term mean sea level variability, astronomical tides, storm surges due to atmospheric pressure and wind, wave breaking, and other regional dynamics. Numerical circulation/storm-surge models are frequently used to predict water levels over broad areas with the outputs used for planning or emergency management applications. Recently, coupled wave-circulation models have been shown to improve extreme sea level predictions through the inclusion of wave setup that results from the transfer of momentum of breaking waves into sea level at the shoreline. Other studies have shown that the representations of surface wind drag can be improved when the sea state is considered, and this can directly influence the amplitude of storm surges at the coast. However, most coupled wave-circulation model studies have been undertaken for relatively small computational domains and for a limited range of coastal morphologies and storm types. In this paper we assess the benefits and limitations of using a coupled wave-circulation model to predict extreme sea levels and determine wave effects for a broad range of coastal morphologies and extreme storm events all around Australia. Simulated events occurred in three oceans and considered tropical cyclones, a cyclone undergoing extratropical transition, and a large mid-latitude extratropical low-pressure system.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/UfyWHI4OHBA

scholarly journals Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Benjamin H. Strauss ◽  
Philip M. Orton ◽  
Klaus Bittermann ◽  
Maya K. Buchanan ◽  
Daniel M. Gilford ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
East Coast ◽  
The United States ◽  
Hurricane Sandy ◽  
Water Levels ◽  
Anthropogenic Climate Change ◽  
Economic Damage ◽  
Sea Levels

AbstractIn 2012, Hurricane Sandy hit the East Coast of the United States, creating widespread coastal flooding and over $60 billion in reported economic damage. The potential influence of climate change on the storm itself has been debated, but sea level rise driven by anthropogenic climate change more clearly contributed to damages. To quantify this effect, here we simulate water levels and damage both as they occurred and as they would have occurred across a range of lower sea levels corresponding to different estimates of attributable sea level rise. We find that approximately $8.1B ($4.7B–$14.0B, 5th–95th percentiles) of Sandy’s damages are attributable to climate-mediated anthropogenic sea level rise, as is extension of the flood area to affect 71 (40–131) thousand additional people. The same general approach demonstrated here may be applied to impact assessments for other past and future coastal storms.

scholarly journals Flooding Conditions at Aveiro Port (Portugal) within the Framework of Projected Climate Change

2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Américo Soares Ribeiro ◽  
Carina Lurdes Lopes ◽  
Magda Catarina Sousa ◽  
Moncho Gomez-Gesteira ◽  
João Miguel Dias
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Climate Change Impacts ◽  
Storm Surges ◽  
Historical Period ◽  
Return Periods ◽  
Wave Regime ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Far Future

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures' resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.

scholarly journals Modelling the increased frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta due to sea level rise and other effects of climate change

2015 ◽  
Vol 17 (7) ◽  
pp. 1311-1322 ◽  
Author(s):  
S. Kay ◽  
J. Caesar ◽  
J. Wolf ◽  
L. Bricheno ◽  
R. J. Nicholls ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
21St Century ◽  
Bay Of Bengal ◽  
Hydrodynamic Model ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
The Ganges

A hydrodynamic model of the Bay of Bengal has been used to explore increasing frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta over the 21st century.

scholarly journals ATTRICI v1.1 – counterfactual climate for impact attribution

2021 ◽  
Vol 14 (8) ◽  
pp. 5269-5284
Author(s):  
Matthias Mengel ◽  
Simon Treu ◽  
Stefan Lange ◽  
Katja Frieler
Keyword(s):  
Climate Change ◽  
Climate Impact ◽  
Climate Impacts ◽  
General Definition ◽  
Impact Model ◽  
Climate Data ◽  
Climate Trends ◽  
Long Term Changes ◽  
The Impact

Abstract. Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC Working Group II (WGII) a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system's behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause” (IPCC, 2014). Impact attribution following this definition remains a challenge because the counterfactual baseline, which characterizes the system behavior in the hypothetical absence of climate change, cannot be observed. Process-based and empirical impact models can fill this gap as they allow us to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.

scholarly journals PREDICTING EXTREME WATER LEVELS AROUND AUSTRALIA

2020 ◽  
pp. 7
Author(s):  
Charitha Pattiaratchi ◽  
Yasha Hetzel ◽  
Ivica Janekovic
Keyword(s):  
Sea Level ◽  
Land Use Planning ◽  
Wind Waves ◽  
Storm Surges ◽  
Flood Management ◽  
Water Levels ◽  
Coastal Development ◽  
Sea Levels ◽  
Extreme Water Levels ◽  
Rising Sea Levels

Throughout history, coastal settlers have had to adapt to periodic coastal flooding. However, as a society we have become increasingly vulnerable to extreme water level events as our cities and our patterns of coastal development become more intricate, populated and interdependent. In addition to this, there is now a real and growing concern about rising sea levels. Accurate estimates of extreme water levels are therefore critical for coastal planning and emergency planning and response. The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore, it is vitally important that the exceedance probabilities of extreme water levels be accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This objectives of this study was to estimate present day extreme sea level exceedance probabilities due to combination of storm surges, tides and mean sea level (including wind-waves) around the coastline of Australia.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/vGaB85VRujs

scholarly journals Insuring property under climate change

2017 ◽  
Vol 13 (4) ◽  
Author(s):  
Belinda Storey ◽  
Ilan Noy
Keyword(s):  
Climate Change ◽  
New Zealand ◽  
Sea Level ◽  
Housing Stock ◽  
High Tide ◽  
Storm Surges ◽  
Intergovernmental Panel ◽  
Sea Levels ◽  
The Antarctic ◽  
Emissions Scenario

Climate change will increasingly create severe risks for  New Zealand’s coastal housing stock. Even a small amount of sea level rise will substantially exacerbate the costs of flooding and storm surges (Parliamentary Commissioner for the Environment, 2015). Under the Intergovernmental Panel on Climate Change’s (IPCC) three mitigation scenarios, global average sea levels are likely to rise by between 28cm and 73cm by 2100 (above the 1986–2005 average). Under the IPCC’s high emissions scenario the sea level is likely to rise by between 52cm and 98cm by 2100 (IPCC, 2013). Only collapse of parts of the Antarctic ice sheet, if triggered, could cause the sea level to rise substantially above these ranges. Some regions in New Zealand (including the main urban centres) have high enough quality geographic data to infer the number of homes at risk. In those regions, there are over 43,000 homes within 1.5m of the present average spring high tide and over 8,000 within 50cm.

scholarly journals GESLA Version 3: A major update to the global higher-frequency sea-level dataset

2021 ◽  
Author(s):  
Ivan Haigh ◽  
Marta Marcos ◽  
Stefan Talke ◽  
Philip Woodworth ◽  
John Hunter ◽  
...  
Keyword(s):  
Sea Level ◽  
Storm Surges ◽  
Coastal Engineering ◽  
Multiple Sources ◽  
Sea Levels ◽  
The Third ◽  
Wide Range ◽  
The World ◽  
Extreme Sea Levels ◽  
Level Analysis

This paper describes a major update to the quasi-global, higher-frequency sea-level dataset known as GESLA (Global Extreme Sea Level Analysis). Versions 1 (released 2009) and 2 (released 2016) of the dataset have been used in many published studies, across a wide range of oceanographic and coastal engineering-related investigations concerned with evaluating tides, storm surges, extreme sea levels and other related processes. The third version of the dataset (released 2021), presented here, contains twice the number of years of data (91,021), and nearly four times the number of records (5,119), compared to version 2. The dataset consists of records obtained from multiple sources around the world. This paper describes the assembly of the dataset, its processing and its format, and outlines potential future improvements. The dataset is available from https://www.gesla.org.

Extreme sea levels in the context of climate change

2020 ◽  
Author(s):  
Lucia Pineau-Guillou ◽  
Pascal Lazure ◽  
Guy Wöppelmann
Keyword(s):  
Climate Change ◽  
North Atlantic ◽  
Tide Gauge ◽  
Storm Surges ◽  
Sea Levels ◽  
The North ◽  
Extreme Sea Levels ◽  
Centennial Time Scale ◽  
The North Atlantic ◽  
Phd Thesis

<p>The objective of this study is to investigate how extreme sea levels are changing, at a centennial time scale, in the context of climate change. We focus on Brest tide gauge (France), one of the longest time series in the world. First observations were recorded in 1701, and hourly data have been registered continuously since 1846 with little gaps. These data have been  carefully processed, in order to ensure good quality, especially regarding the datum continuity (Pouvreau, 2008) and stability (Poitevin, 2019).</p><p>Here, we investigate the evolution of the storm surges over the last 170 years. We focus on the skew surge, defined as the difference between the maximum observed water level and the maximum predicted tidal level (taking into account the mean sea level rise). This parameter is directly linked to the atmosphere variations, and may be correlated with regional climate parameters, such as the North Atlantic Oscillation (Menéndez and Woodworth, 2010). But it is also correlated with the evolution of the storminess in the North Atlantic. One of the challenges is to separate the natural interannual variability of the sea level from the long term trends at a centennial time scale.</p><p>We will discuss the variability of the storm surges, in terms of changes in the 99th percentile and the 5-year return period level. Statistical analysis will be based on extreme values theory (e.g. Generalized Extreme Value distribution, General Pareto Distribution). Correlation with other parameters such as the significant wave height (from buoys) and the wind and storm tracks (from global reanalysis, e.g. ERA5 from ECMWF) will also be investigated.</p><p>References<br>Menéndez M., Woodworth P. L. (2010). Changes in extreme high water levels based on a quasi-global tide-gauge dataset. J Geophys Res 115:C10011.<br>Poitevin (2019). Variabilité du niveau marin relatif le long du littoral de Brest (France) par combinaison de méthodes géodésiques spatiales (altimétrie radar, InSAR et GPS). PhD thesis, University of La Rochelle.<br>Pouvreau N. (2008). Trois cents ans de mesures marégraphiques en France : outils, méthodes et tendances des composantes du niveau de la mer au port de Brest. PhD thesis, University of La Rochelle.<br><br><br></p><p> </p>

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