Numerical Modeling of Tropical Cyclone Generated Waves; Case studies of Irma, Maria and Dorian

2020 ◽  
Author(s):  
Gozde Guney Dogan ◽  
Pamela Probst ◽  
Bora Yalciner ◽  
Alessandro Annunziato ◽  
Narcisse Zahibo ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Numerical Model ◽  
Tropical Cyclone ◽  
Atlantic Ocean ◽  
Tropical Cyclones ◽  
Storm Surge ◽  
Coastal Areas ◽  
Wind Fields ◽  
Caribbean Islands ◽  
The Caribbean

<p>Tropical cyclones can be considered one type of extreme event, with their destructive winds, torrential rainfall and storm surge. Every year these natural phenomena affect millions of people around the world, leaving a trail of destruction in several countries, especially along the coastal areas. Only in 2017, two devastating major hurricanes (Irma and Maria) moved across the Caribbean and south-eastern USA, causing extensive damage and deaths. Irma formed in the far eastern Atlantic Ocean on 30 August 2017 and moved towards the Caribbean islands during the following week, significantly strengthening, becoming a Category 5 Hurricane. It caused wide-ranging impacts such as significant storm surge (up to 3m according to US National Oceanic and Atmospheric Administration, NOAA report) to several islands in the Caribbean and Florida. On the second half of September, 2017, another strong Category 5 Hurricane named Maria formed over the Atlantic and moved west towards the Caribbean Sea. Maria also caused several impacts and severe damage in Caribbean Islands, Puerto Rico and the U.S. Virgin Islands due to high speed winds, rainfall, flooding and storm surge with a maximum runup of 3.7 m (US NOAA) on the southern tip of Dominica Island. The most recent devastating event for the Atlantic is Hurricane Dorian. It formed on August 24, 2019 over the Atlantic Ocean and it moved towards the Caribbean islands, as getting stronger as moving, becoming a Category 5 before reaching the Bahamas, where it left a trail of destruction after its passage. The major effect of Dorian was on north-western Bahamas with very strong winds, heavy rainfall and a large storm surge.</p><p>In this context, a rapid and reliable modeling of storm surge generated by such kind of events is essential for many purposes such as early accurate assessment of the situation, forecasting, estimation of potential impact in coastal areas, and operational issues like emergency management.</p><p>A numerical model, NAMI DANCE GPU T-SS (Tsunami-Storm Surge) is developed building up on tsunami numerical model NAMI DANCE GPU version to solve nonlinear shallow water equations, using the pressure and wind fields as inputs to compute spatial and temporal distribution of water level throughout the study domain and respective inundation related to tropical cyclones, based on the equations used in the HyFlux2 Code developed by the Joint Research Centre of the European Commission. The code provides a rapid calculation since it is structured for Graphical Processing Unit (GPU) using CUDA API.</p><p>NAMI DANCE GPU T-SS has been applied to many cases as regular shaped basins under circular static and dynamic pressure fields separately and also different wind fields for validation together with combinations of pressure and wind fields. This study has been conducted to investigate the potential of numerical modeling of tropical cyclone generated storm surge based on recent events Irma, Maria and Dorian. The results are presented and discussed based on comparison with the measurements and observations. The study shows promise for developing a cyclone modeling capability based on available measurement and observational data.</p>

scholarly journals Generating reliable estimates of tropical cyclone induced coastal hazards along the Bay of Bengal for current and future climates using synthetic tracks

2021 ◽  
Author(s):  
Tim Willem Bart Leijnse ◽  
Alessio Giardino ◽  
Kees Nederhoff ◽  
Sofia Caires
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Storm Surge ◽  
Bay Of Bengal ◽  
Coastal Hazards ◽  
Wind Fields ◽  
Tropical Cyclone Frequency ◽  
Wind Speeds ◽  
Wave Heights ◽  
Cyclone Frequency

Abstract. Deriving reliable estimates of design water levels and wave conditions resulting from tropical cyclones is a challenging problem of high relevance for, among others, coastal and offshore engineering projects and risk assessment studies. Tropical cyclone geometry and wind speeds have been recorded for the past few decades only, therefore resulting in poorly reliable estimates of the extremes, especially at regions characterized by a low number of past tropical cyclone events. In this paper, this challenge is overcome by using synthetic tropical cyclone tracks and wind fields generated by the open source tool TCWiSE (Tropical Cyclone Wind Statistical Estimation), to create thousands of realizations representative for 1,000 years of tropical cyclone activity for the Bay of Bengal. Each of these realizations is used to force coupled storm surge and wave simulations by means of the processed-based Delft3D Flexible Mesh Suite. It is shown that the use of synthetic tracks provides reliable estimates of the statistics of the first-order hazard (i.e. wind speed) compared to the statistics derived for historical tropical cyclones. Based on estimated wind fields, second-order hazards (i.e. storm surge and waves) are computed. The estimates of the extreme values derived for wind speed, wave height and storm surge are shown to converge within the 1,000 years of simulated cyclone tracks. Comparing second-order hazard estimates based on historical and synthetic tracks show that, for this case study, the use of historical tracks (a deterministic approach) leads to an underestimation of the mean computed storm surge up to −30 %. Differences between the use of synthetic versus historical tracks are characterized by a large spatial variability along the Bay of Bengal, where regions with a lower probability of occurrence of tropical cyclones show the largest difference in predicted storm surge and wave heights. In addition, the use of historical tracks leads to much larger uncertainty bands in the estimation of both storm surges and wave heights, with confidence intervals being +80 % larger compared to those estimated by using synthetic tracks (probabilistic approach). Based on the same tropical cyclone realizations, the effect that changes in tropical cyclone frequency and intensity, possibly resulting from climate change, may have on modelled storm surge and wave heights were computed. An increase in tropical cyclone frequency of +25.6 % and wind intensity of +1.6 %, based on literature values, could result in an increase of storm surge and wave heights of +11 % and +9 % respectively. This suggest that climate change could increase tropical cyclone induced coastal hazards more than just the actual increase in maximum wind speeds.

scholarly journals Impact Analysis of Tropical Cyclone Cempaka-Dahlia on Wave Heights in Indonesian Waters from Numerical Model and Altimetry Satellite

2019 ◽  
Author(s):  
Wiwin Windupranata ◽  
Candida A.D.S. Nusantara ◽  
Dudy D. Wijaya ◽  
Kosasih Prijatna
Keyword(s):  
Numerical Modeling ◽  
Tropical Cyclone ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
Wave Height ◽  
Power Plants ◽  
Impact Analysis ◽  
Observation Point ◽  
Coastal Areas ◽  
The Indian Ocean

Indonesia is located side by side with the Pacific Ocean and the Indian Ocean where there are often tropical cyclones in these two oceans. As was the case some time ago in the Indian Ocean a tropical cyclone of Cempaka and Dahlia occurred which had a significant impact on Indonesian areas. Another impact felt is the disruption of economic activity in the area of tourism, ports, and power plants. Numerical modeling is carried out to simulate the phenomena of Cempaka and Dahlia tropical cyclones to determine the impacts caused especially in Lampung to Lombok areas. Numerical modeling is done using SWAN version 41.20. SWAN was chosen because it has good modeling calculations in coastal areas and is very suitable for wave analysis in coastal areas. The results of the modeling are verified by the significant wave height correlation coefficient from altimetry satellites that cross the tropical cyclones of Cempaka and Dahlia. The results showed a significant increase in wave height in the study area with an increase of up to 1028.31% at the observation point in Pelabuhan Ratu, West Java Province.

scholarly journals Advancing global storm surge modelling using the new ERA5 climate reanalysis

2019 ◽  
Vol 54 (1-2) ◽  
pp. 1007-1021 ◽  
Author(s):  
Job C. M. Dullaart ◽  
Sanne Muis ◽  
Nadia Bloemendaal ◽  
Jeroen C. J. H. Aerts
Keyword(s):  
Tropical Cyclones ◽  
Storm Surge ◽  
Global Climate ◽  
Storm Surges ◽  
Early Warning Systems ◽  
Climate Modelling ◽  
Wind Fields ◽  
Recent Advances ◽  
Global Climate Modelling ◽  
Surge Height

Abstract This study examines the implications of recent advances in global climate modelling for simulating storm surges. Following the ERA-Interim (0.75° × 0.75°) global climate reanalysis, in 2018 the European Centre for Medium-range Weather Forecasts released its successor, the ERA5 (0.25° × 0.25°) reanalysis. Using the Global Tide and Surge Model, we analyse eight historical storm surge events driven by tropical—and extra-tropical cyclones. For these events we extract wind fields from the two reanalysis datasets and compare these against satellite-based wind field observations from the Advanced SCATterometer. The root mean squared errors in tropical cyclone wind speed reduce by 58% in ERA5, compared to ERA-Interim, indicating that the mean sea-level pressure and corresponding strong 10-m winds in tropical cyclones greatly improved from ERA-Interim to ERA5. For four of the eight historical events we validate the modelled storm surge heights with tide gauge observations. For Hurricane Irma, the modelled surge height increases from 0.88 m with ERA-Interim to 2.68 m with ERA5, compared to an observed surge height of 2.64 m. We also examine how future advances in climate modelling can potentially further improve global storm surge modelling by comparing the results for ERA-Interim and ERA5 against the operational Integrated Forecasting System (0.125° × 0.125°). We find that a further increase in model resolution results in a better representation of the wind fields and associated storm surges, especially for small size tropical cyclones. Overall, our results show that recent advances in global climate modelling have the potential to increase the accuracy of early-warning systems and coastal flood hazard assessments at the global scale.

scholarly journals NUMERICAL MODELING OF SHORT AND LONG TERM WAVES AND SURGES BY HURRICANE IRMA AND MARIA IN US VIRGIN ISLANDS

2018 ◽  
pp. 59
Author(s):  
Nobuhito Mori ◽  
Takenori Shimozono ◽  
Taro Arikawa ◽  
Daisuke Inazu ◽  
Tomoya Shimura ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Survey Data ◽  
Rare Event ◽  
Virgin Islands ◽  
Us Virgin Islands ◽  
Caribbean Islands ◽  
Short And Long Term ◽  
The Caribbean ◽  
Hurricane Irma

Two powerful hurricanes successively passed close to US Virgin Islands in September 2017. Hurricane Irma developed into CAT5 with the lowest pressure around 914 hPa on 5th of September and passed north of USVI. Sequentially, CAT5 Hurricane Maria followed the similar track, but passed south of USVI. Two CAT5 hurricanes gave devastated damage along the Caribbean Islands. It is a rare event having two CAT5 with similar tracks within two weeks. This study presents hindcasts of waves and storm surge for the two hurricanes and discusses coastal damages with our survey data targeting on USVI.

scholarly journals A New Compilation of North Atlantic Tropical Cyclones, 1851–98*

2014 ◽  
Vol 27 (23) ◽  
pp. 8674-8685 ◽  
Author(s):  
Michael Chenoweth
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
The United States ◽  
Caribbean Region ◽  
News Reports ◽  
The North ◽  
Hurricane Wind ◽  
The Caribbean ◽  
First Time

Abstract A comprehensive new compilation of North Atlantic tropical cyclone activity for the years 1851–98 is presented and compared with the second-generation North Atlantic hurricane database (HURDAT2) for the same years. This new analysis is based on the retrieval of 9072 newspaper marine shipping news reports, 1260 original logbook records, 271 Maury abstract logs, 147 U.S. marine meteorological journals, and 34 Met Office (UKMO) logbooks. Records from throughout North America and the Caribbean region were used along with other primary and secondary references holding unique land and marine data. For the first time, North Atlantic daily weather maps for 1864/65, 1873, and 1881–98 were used in historical tropical cyclone research. Results for the years 1851–98 include the omission of 62 of the 361 HURDAT2 storms, and the further reduction resulting from the merging of storms to a total of 288 unique HURDAT2 tropical cyclones. The new compilation gave a total of 497 tropical cyclones in the 48-yr record, or an average of 10.4 storms per year compared to 6.0 per year in HURDAT2 less the author’s omissions. Of this total, 209 storms are completely new. A total of 90 hurricanes made landfall in the United States during this time. Seven new U.S. landfalling hurricanes are present in the new dataset but not in HURDAT2. Eight U.S. landfalling hurricanes in HURDAT2 are now considered to have only tropical storm impact or were actually extratropical at landfall. Across the North Atlantic, the number of category-4 hurricanes based on the Saffir–Simpson hurricane wind scale, compared with HURDAT2, increased from 11 to 25, 6 of which made U.S. landfall at category-4 level.

A downward counter-factual climate risk analysis of the impact of tropical cyclones in the Caribbean islands

2020 ◽  
Author(s):  
Alessio Ciullo ◽  
Olivia Romppainen-Martius ◽  
Eric Strobl ◽  
David Bresch
Keyword(s):  
Risk Analysis ◽  
Tropical Cyclones ◽  
South Florida ◽  
Climate Risk ◽  
Worst Case Analysis ◽  
Worst Case ◽  
Analysis Study ◽  
Caribbean Islands ◽  
The Caribbean ◽  
The Impact

<p>Climate risk analysis and assessment studies are typically conducted relying on historical data. These data, however, represent just one single realization of the past, which could have unfolded differently. As an example, Hurricane Irma might had struck South Florida at Category 4 and, had it done so, damages could have been as high as 150 billion, about three times higher than damage estimated from the actual event. To explore the impacts of these potentially catastrophic near-misses, downward counter-factual risk analysis (Woo, Maynard and Seria, 2017) complements standard risk analysis by exploring alternative, plausible realization of past climatic events. As downward counter-factual risk analysis frames risk in an event-oriented manner, corresponding more closely to how people perceive risk, it is expected to increase climate risk awareness among people and policy makers (Shepherd et al., 2018).</p><p>We present a counter-factual risk analysis study of climate risk from tropical cyclones on the Caribbean islands. The analysis is conducted using the natcat impact model CLIMADA (Aznar-Siguan and Bresch, 2019). Impact is estimated based on forecasts of past tropical cyclones tracks from the THORPEX Interactive Grand Global Ensemble (TIGGE) dataset, as they all represent plausible alternative realizations of past tropical cyclones. The goal is to study whether, and to what extent, the estimated impacts from forecasts provide new insights than those provided by historical records in terms of e.g. cumulated annual damages, maximum annual damages and, in so doing, perform a worst-case analysis study to support climate risk management planning.</p><p><br>Aznar-Siguan, G. and Bresch, D. N.: CLIMADA v1: a global weather and climate risk assessment platform, Geosci. Model Dev., 12, 3085-3097, doi.org/10.5194/gmd-12-3085-2019, 2019.</p><p>Woo, G., Maynard, T., and Seria, J. Reimagining history. Counterfactual risk analysis. Retrieved from: https://www.lloyds.com/~/media/files/news-and-insight/risk-insight/2017/reimagining-history.pdf, 2017.</p><p>Shepherd, T.G., Boyd, E., Calel, R.A. et al.: Storylines: an alternative approach to representing uncertainty in physical aspects of climate change. Climatic Change 151, 555–571, doi.org/10.1007/s10584-018-2317-9 , 2018.</p>

scholarly journals A global historical data set of tropical cyclone exposure (TCE-DAT)

2017 ◽  
Author(s):  
Tobias Geiger ◽  
Katja Frieler ◽  
David N. Bresch
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
The United States ◽  
Long Term Effects ◽  
Wind Fields ◽  
Damage Functions ◽  
Data Set ◽  
Wind Field Model ◽  
Wind Speeds ◽  
The Difference

Abstract. Tropical cyclones pose a major risk to societies worldwide with about 22 million directly-affected people and damages of $29 billion on average per year over the last 20 years. While data on observed cyclones tracks (location of the center) and wind speeds is publically available these data sets do not contain information about the spatial extent of the storm and people or assets exposed. Here, we apply a simplified wind field model to estimate the areas exposed to wind speeds above 34, 64, and 96 knots. Based on available spatially-explicit data on population densities and Gross Domestic Product (GDP) we estimate 1) the number of people and 2) the sum of assets exposed to wind speeds above these thresholds accounting for temporal changes in historical distribution of population and assets (TCE-hist) and assuming fixed 2015 patterns (TCE-2015). The associated country-event level exposure data (TCE-DAT) covers the period 1950 to 2015 and is freely available at http://doi.org/10.5880/pik.2017.005. It is considered key information to 1) assess the contribution of climatological versus socio-economic drivers of changes in exposure to tropical cyclones, 2) estimate changes in vulnerability from the difference in exposure and reported damages and calibrate associated damage functions, and 3) build improved exposure-based predictors to estimate higher-level societal impacts such as long-term effects on GDP, employment, or migration. We validate the adequateness of our methodology by comparing our exposure estimate to estimated exposure obtained from reported wind fields available since 1988 for the United States. We expect that the free availability of the underlying model and TCE-DAT will make research on tropical cyclone risks more accessible to non-experts and stakeholders.

Compound impact of rainfall, tidal level and storm surge on flood risk from tropical cyclones in the coastal area of shanghai

2020 ◽  
Author(s):  
Hanqing Xu
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Storm Surge ◽  
Extreme Events ◽  
Joint Probability ◽  
Storm Surges ◽  
Heavy Precipitation ◽  
Tidal Level ◽  
Sea Levels ◽  
The Impact

<p>Catastrophic flooding resulting from extreme tropical cyclones has occurred more frequently and drawn great attention in recent years in China. Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms surge. In coastal areas, floods caused by rainstorms and storm surges have been one of the most costly and devastating natural hazards in coastal regions. Extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. Usually, extreme events such as tidal level, storm surges, precipitation occur jointly, leading to compound flood events with significantly higher hazards compared to the sum of the single extreme events. The purpose of this study is to improve our understanding of multiple drivers to compound flooding in shanghai. The Wind Enhance Scheme (WES) model characterized by Holland model is devised to generate wind "spiderweb" both for historical (1949-2018) and future (2031-2060, 2069-2098) tropical cyclones. The tidal level and storm surge model based on Delft3D-FLOW is employed with an unstructured grid to simulate the change of water level. For precipitation, maximum value between tropical cyclone events is selected. Following this, multivariate Copula model would be employed to compare the change of joint probability between tidal level, storm surge and heavy precipitation under climate change, taking into account sea-level rise and land subsidence. Finally, the impact of tropical cyclone on the joint risk of tidal, storm surge and heavy precipitation is investigated. </p>

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