Coastal extreme sea levels in the Caribbean Sea induced by tropical cyclones

2021 ◽  
Author(s):  
Ariadna Martín ◽  
Angel Amores ◽  
Alejandro Orfila ◽  
Marta Marcos
Keyword(s):  
Tropical Cyclones ◽  
Wind Waves ◽  
Storm Surges ◽  
Wave Model ◽  
Caribbean Sea ◽  
Sea Levels ◽  
Global Database ◽  
Extreme Sea Levels ◽  
The Caribbean ◽  
Hydrodynamic Wave

<p>Every year the Caribbean Sea faces the passage of powerful tropical cyclones that generate coastal extreme sea levels with potential strong and hazardous impacts. In this work we simulate the storm surges and wind-waves induced by a set of over 1000 tropical cyclones over the Caribbean Sea that are representative of the present-day climate and that have been extracted from a global database of synthetic hurricanes spanning a 10,000-year period. The atmospheric forcing fields, built from the synthetic tropical cyclones, are used to feed a fully coupled hydrodynamic-wave model with high resolution (~1 km) along the continental and island coasts. Given the large number of events modelled, the outputs allow detailed statistical analyses of the magnitude and mechanisms of coastal extreme sea levels as well as the identification of most exposed areas to both storm surges and large wind-waves.</p>

Creating a global database with return periods of extreme sea levels caused by tropical and extratropical cyclones

2020 ◽  
Author(s):  
Job Dullaart
Keyword(s):  
Storm Surges ◽  
Air Pressure ◽  
Synthetic Dataset ◽  
Economic Losses ◽  
Extreme Value Analysis ◽  
Extratropical Cyclones ◽  
Return Periods ◽  
Sea Levels ◽  
Global Database ◽  
Extreme Sea Levels

<p>Storm surges are driven by low air pressure and strong winds in tropical (TC) and extratropical cyclones (ETC). Coastal flooding is often caused by this type of extreme weather with large socio-economic impacts in densely populated and low-lying coastal areas. Recent examples of coastal disasters include typhoon Hagibis that made landfall in Japan, Hurricane Dorian which devastated the northwestern Bahamas, and extratropical cyclone Xaver that affected northern Europe. Each of these storms generated dangerous storm surges, reaching 6m in some parts of the Bahamas during Hurricane Dorian with approximately 100 fatalities as a result. Economic losses are estimated at 10 billion U.S. Dollars for both typhoon Hagibis and hurricane Dorian.</p><p>To inform flood risk management and develop effective adaptation strategies it is important to have accurate information on return periods of extreme sea levels. To date, there exists no global database with return periods of extreme sea levels that fully includes TCs. Global databases of extreme sea levels are typically based on historical climate simulations covering multiple decades. While this is sufficient for ETCs, TCs will be underestimated in such databases. This because TCs have generally low probabilities and affect only a small stretch of coastline, compared to ETCs. A climate reanalysis covering multiple decades includes too few TCs to perform an extreme value analysis. To resolve this, previous studies at local scale have used synthetic TC tracks generated by a statistical model to estimate the probabilities of extreme sea levels.</p><p>The aim of this research is to develop a global database of extreme sea levels that include both ETCs and TCs. For ETCs, we force the hydrodynamic Global Tide and Surge Model (GTSM) with ERA5 10-meter wind speed and air pressure data to calculate the return periods of extreme sea levels based on the period 1979-2017. Since ERA5 includes all storms, we filter out extreme sea levels caused by TCs. Preliminary results show that GTSM forced with ERA5 atmospheric data performs well for ETCs. For TCs, we force GTSM with synthetic TC tracks that correspond to 10.000 year of TC statistics. The synthetic tracks of TCs are obtained from the STORM model (Bloemendaal et al., in review) based on the International Best Track Archive for Climate Stewardship (IBTrACS) TC database. With STORM it is possible to statistically extend the ~38-year observed dataset to a 10.000-year synthetic dataset. The synthetic dataset preserves the climatological statistics as found in the original dataset. Finally, we will merge the TC and ETC related return periods to create a global extreme sea level database.</p>

Coastal risks induced by Mediterranean hurricanes

2021 ◽  
Author(s):  
Tim Toomey ◽  
Angel Amores ◽  
Marta Marcos ◽  
Alejandro Orfila ◽  
Romualdo Romero
Keyword(s):  
Mediterranean Sea ◽  
Climate Models ◽  
Global Climate ◽  
Wind Waves ◽  
Storm Surges ◽  
Wave Model ◽  
Global Climate Models ◽  
Coastal Risks ◽  
The Mediterranean ◽  
Hydrodynamic Wave

<p>Medicanes, for Mediterranean hurricanes, are mesoscale cyclones with morphological and physical characteristics similar to tropical cyclones. Although less intense, smaller and rarer than their Atlantic counterparts, Medicanes remain very hazardous events threatening islands and continental coasts within the Mediterranean Sea. The latest strong episode Medicane Ianos (September 2020), resulted in severe damages in Greece and several casualties. This work investigates the oceanic response to these extreme events along the Mediterranean coasts under present-day and future (21 st century) conditions. To this end, a coupled hydrodynamic-wave model is used to simulate both storm surges and wind-waves generation and propagation in the Mediterranean Sea at high resolution (~2 km) along the coastlines. A dataset of thousands of Medicanes synthetically generated from twenty global climate models and two reanalyses is used to derive the atmospheric forcing fields. Regional coastal risks assessment is performed for the present and future climate. We found increased coastal extreme sea levels in line to the reported changes in Medicane activity, with fewer events but of larger intensity projected by late 21 st century.</p>

The dependence of UK extreme sea levels and storm surges on the North Atlantic Oscillation

2007 ◽  
Vol 27 (7) ◽  
pp. 935-946 ◽  
Author(s):  
P.L. Woodworth ◽  
R.A. Flather ◽  
J.A. Williams ◽  
S.L. Wakelin ◽  
S. Jevrejeva
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Storm Surges ◽  
Sea Levels ◽  
The North ◽  
Extreme Sea Levels ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

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>

Incorporating large datasets of synthetic tropical cyclones with Global Tide and Surge Model (GTSM) for global assessment of extreme sea levels.

2020 ◽  
Author(s):  
Maria Chertova ◽  
Sanne Muis ◽  
Inti Pelupessy ◽  
Philip Ward
Keyword(s):  
Tropical Cyclones ◽  
Large Scale ◽  
Large Datasets ◽  
Water Levels ◽  
Computational Time ◽  
Potential Hazard ◽  
Computationally Efficient ◽  
Sea Levels ◽  
Starting Point ◽  
Extreme Sea Levels

<p>Coastal flooding due to tropical cyclones (TC) is one of the world’s most threatening hazards. The potential increase in the probability of these events in the future, due to climate change, necessitates the more accurate simulation of their potential hazard and resulting risks. This contribution is a step of a MOSAIC (MOdelling Sea level And Inundation for Cyclones) project that aims at developing and validating a computationally efficient, scalable, framework for large-scale flood risk assessment, combining cutting-edge disciplinary science and eScience technologies. As the first step, we develop a computationally efficient method for more accurately simulating current and future TC hazard and risk, by incorporating large datasets of tropical cyclones within the Global Tide and Surge Model (GTSM). The starting point is simulating the spatially explicit extreme sea levels for a large number of synthetic TCs. The difficulty lies in high computational time required for running GTSM models, as with duration of one simulation running on 24 cores of 5 days ( for 1yr). Until present each TC was simulated separately*, which is not feasible when modelling thousands of TC events. Here we present the development of an algorithm for the spatio-temporal optimization of the placing of TCs within GTSM in order to allow optimal use of the computational resources. This can be achieved because the region of influence of a particular TC in the model is limited in space and time (e.g. a TC making landfall in Florida will not materially affect water levels near New York).  This will enable running a large number of TCs in one simulation and will significantly reduce the required total computation time. We investigate a large range of parameters, such as distance between cyclones, time to the landfall, category of cyclone, and others, to optimize the distribution of TC within a single model run. We demonstrate a significant speedup relative to the sequential running of the cyclones within a single simulation.</p><p>*Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C. J. H., & Ward, P. J. (2016). A global reanalysis of storm surge and extreme sea levels. Nature Communications, 7(7:11969), 1–11.</p>

scholarly journals A global reanalysis of storm surges and extreme sea levels

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Sanne Muis ◽  
Martin Verlaan ◽  
Hessel C. Winsemius ◽  
Jeroen C. J. H. Aerts ◽  
Philip J. Ward
Keyword(s):  
Storm Surges ◽  
Hydrodynamic Models ◽  
Data Set ◽  
Meteorological Forcing ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Global Reanalysis ◽  
Global Population ◽  
Good Agreement ◽  
Impacts Of Climate Change

AbstractExtreme sea levels, caused by storm surges and high tides, can have devastating societal impacts. To effectively protect our coasts, global information on coastal flooding is needed. Here we present the first global reanalysis of storm surges and extreme sea levels (GTSR data set) based on hydrodynamic modelling. GTSR covers the entire world's coastline and consists of time series of tides and surges, and estimates of extreme sea levels. Validation shows that there is good agreement between modelled and observed sea levels, and that the performance of GTSR is similar to that of many regional hydrodynamic models. Due to the limited resolution of the meteorological forcing, extremes are slightly underestimated. This particularly affects tropical cyclones, which requires further research. We foresee applications in assessing flood risk and impacts of climate change. As a first application of GTSR, we estimate that 1.3% of the global population is exposed to a 1 in 100-year flood.

scholarly journals A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections

2020 ◽  
Vol 7 ◽  
Author(s):  
Sanne Muis ◽  
Maialen Irazoqui Apecechea ◽  
Job Dullaart ◽  
Joao de Lima Rego ◽  
Kristine Skovgaard Madsen ◽  
...  
Keyword(s):  
High Resolution ◽  
Storm Surges ◽  
Future Projections ◽  
Sea Levels ◽  
Extreme Sea Levels
Sign in / Sign up

Export Citation Format

Share Document