scholarly journals Storm surge risk mitigation under ambiguity by coupled tropical cyclone and decision model

2021 ◽  
Author(s):  
Toshio Fujimi ◽  
Ha Si ◽  
Xinyu Jiang ◽  
Nobuhito Mori ◽  
Rawshan Begum ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Storm Surge ◽  
Risk Premium ◽  
Stated Preference ◽  
Risk Mitigation ◽  
Storm Surges ◽  
Worst Case ◽  
Important Conclusion ◽  
Stated Preference Experiments ◽  
Fresh Perspective

Abstract Even as storm surge risks are increasing, the projections of such risks have an element of ambiguity. Consequently, policymakers find it extremely difficult to design policies to deal with storm surge risks. Therefore, in this study, we have linked the tropical cyclone models and stated preference experiments with decision models to provide a fresh perspective on households’ preferences for storm surge risk mitigation under ambiguity. We have validated households’ choices under the average and worst projections of storm surges and estimated the expected loss reduction, risk premium, and ambiguity premium for storm surge risk mitigation. Our study reveals that households pay disproportionately more attention to the worst case and that the ambiguity premium is not negligible. This leads to an important conclusion that policymakers should factor in the ambiguity premium to formulate risk mitigation policies.

scholarly journals APPLICABILITY OF THE VERTICAL TELESCOPIC BREAKWATER USING THE PAST TYPHOON IN TOKYO BAY

2020 ◽  
pp. 35
Author(s):  
Yako Harada ◽  
Yukihisa Matsumoto ◽  
Kazuho Morishita ◽  
Nobuyuki Oonishi ◽  
Kazuyoshi Kihara ◽  
...  
Keyword(s):  
Climate Change ◽  
Storm Surge ◽  
Storm Surges ◽  
Numerical Calculations ◽  
Numerical Analyses ◽  
Tokyo Bay ◽  
Worst Case ◽  
Sea Levels ◽  
Long Period ◽  
The Past

The vertical telescopic breakwater(VTB), which is a new breakwater that permits the navigation of ships, remain at the bottom of the sea during calm and rise to the surface during tsunamis or storm surges. Kawai et al. (2017) and Arikawa et al. (2019) found that it is effective not only for swell waves, but also for long-period waves simulating tsunamis and storm surges by previous experiments and numerical analyses. However, there have been few studies on the performance of VTB by numerical calculations in actual ports using actual typhoons. In addition, sea levels and changes in characteristics of typhoon due to climate change are predicted to occur; hence, we are concerned about the damage in all quarters caused by storm surge inundation, especially at Tokyo. Therefore, in this study, we used hypothetical typhoons under worst-case scenarios and quantitatively evaluated the protection performance of VTB against hypothetical typhoons with different aperture rates of VTB in Tokyo Bay by the numerical simulation.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/qof5ixKqIiA

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>

scholarly journals Repeat Storm Surge Disasters of Typhoon Haiyan and Its 1897 Predecessor in the Philippines

2016 ◽  
Vol 97 (1) ◽  
pp. 31-48 ◽  
Author(s):  
Janneli Lea A. Soria ◽  
Adam D. Switzer ◽  
Cesar L. Villanoy ◽  
Hermann M. Fritz ◽  
Princess Hope T. Bilgera ◽  
...  
Keyword(s):  
Storm Surge ◽  
Field Measurements ◽  
Storm Surges ◽  
The Philippines ◽  
Risk Awareness ◽  
Community Based ◽  
Worst Case ◽  
Video Recordings ◽  
San Pedro ◽  
San Pedro Bay

Abstract On 8 November 2013, Typhoon Haiyan impacted the Philippines with estimated winds of approximately 314 km h-1 and an associated 5–7-m-high storm surge that struck Tacloban City and the surrounding coast of the shallow, funnel-shaped San Pedro Bay. Typhoon Haiyan killed more than 6,000 people, superseding Tropical Storm Thelma of November 1991 as the deadliest typhoon in the Philippines. Globally, it was the deadliest tropical cyclone since Nargis hit Myanmar in 2008. Here, we use field measurements, eyewitness accounts, and video recordings to corroborate numerical simulations and to characterize the extremely high velocity flooding caused by the Typhoon Haiyan storm surge in both San Pedro Bay and on the more open Pacific Ocean coast. We then compare the surge heights from Typhoon Haiyan with historical records of an unnamed typhoon that took a similar path of destruction in October 1897 (Ty 1897) but which was less intense, smaller, and moved more slowly. The Haiyan surge was about twice the height of the 1897 event in San Pedro Bay, but the two storm surges had similar heights on the open Pacific coast. Until stronger prehistoric events are explored, these two storm surges serve as worst-case scenarios for this region. This study highlights that rare but disastrous events should be carefully evaluated in the context of enhancing community-based disaster risk awareness, planning, and response.

scholarly journals An Empirical Analysis on the Relationship between Tropical Cyclone Size and Storm Surge Heights along the U.S. Gulf Coast

2014 ◽  
Vol 18 (8) ◽  
pp. 1-15 ◽  
Author(s):  
Hal F. Needham ◽  
Barry D. Keim
Keyword(s):  
Tropical Cyclone ◽  
Hurricane Katrina ◽  
Storm Surge ◽  
Empirical Analysis ◽  
Gulf Coast ◽  
Inverse Correlation ◽  
Storm Surges ◽  
Wind Fields ◽  
The U.S

Abstract In the past decade, several large tropical cyclones have generated catastrophic storm surges along the U.S. Gulf and Atlantic Coasts. These storms include Hurricanes Katrina, Ike, Isaac, and Sandy. This study uses empirical analysis of tropical cyclone data and maximum storm surge observations to investigate the role of tropical cyclone size in storm surge generation. Storm surge data are provided by the Storm Surge Database (SURGEDAT), a global storm surge database, while a unique tropical cyclone size dataset built from nine different data sources provides the size of the radius of maximum winds (Rmax) and the radii of 63 (34 kt), 93 (50 kt), and 119 km h−1 (64 kt) winds. Statistical analysis reveals an inverse correlation between storm surge magnitudes and Rmax sizes, while positive correlations exist between storm surge heights and the radius of 63 (34 kt), 93 (50 kt), and 119 km h−1 (64 kt) winds. Storm surge heights correlate best with the prelandfall radius of 93 km h−1 (50 kt) winds, with a Spearman correlation coefficient value of 0.82, significant at the 99.9% confidence level. Many historical examples support these statistical results. For example, the 1900 Galveston hurricane, the 1935 Labor Day hurricane, and Hurricane Camille all had small Rmax sizes but generated catastrophic surges. Hurricane Katrina provides an example of the importance of large wind fields, as hurricane-force winds extending 167 km [90 nautical miles (n mi)] from the center of circulation enabled this large storm to generate a higher storm surge level than Hurricane Camille along the same stretch of coast, even though Camille’s prelandfall winds were slightly stronger than Katrina’s. These results may be useful to the storm surge modeling community, as well as disaster science and emergency management professionals, who will benefit from better understanding the role of tropical cyclone size for storm surge generation.

scholarly journals STUDY ON INTERACTION BETWEEN THE ESTUARY DYNAMIC AND STORM SURGE INDUCED BY TROPICAL CYCLONE WINNIE(1997) IN YANGTZE RIVER ESTUARY

2011 ◽  
Vol 1 (32) ◽  
pp. 22
Author(s):  
Jinshan Zhang ◽  
Jun Kong ◽  
Zhiyi Lei ◽  
Weisheng Zhang
Keyword(s):  
Tropical Cyclone ◽  
Water Level ◽  
Storm Surge ◽  
Yangtze River ◽  
River Estuary ◽  
Storm Surges ◽  
Yangtze River Estuary ◽  
Meteorological Model ◽  
Astronomical Tide ◽  
Level Increase

ABSTRACT This paper studied the interaction between the Estuary dynamic and storm surge induced by super tropical cyclone Winnie(1997) in Yangtze River Estuary with nested numerical model, which is driven by meso-scale meteorological model established. And the results indicate that, storm surges have significant influences on the Yangtze River Estuary. The maximum water level increase caused by storm surge can be monitored between Jiangyin and Xuliujing, whose exact position fluctuates owing to effects of the upstream runoff and estuarine tide. Furthermore the general laws about the relationships among astronomical tide, storm surge, and flood are revealed in this paper, and flood water level under storm surge events is predicted also.

scholarly journals Hurricane Flood Hazard Assessment for the Archipelago of San Andres, Providencia and Santa Catalina, Colombia

2021 ◽  
Vol 8 ◽  
Author(s):  
Wilmer Rey ◽  
Pablo Ruiz-Salcines ◽  
Paulo Salles ◽  
Claudia P. Urbano-Latorre ◽  
Germán Escobar-Olaya ◽  
...  
Keyword(s):  
Water Level ◽  
Tropical Cyclones ◽  
Storm Surge ◽  
Sea Water ◽  
Storm Surges ◽  
Development Planning ◽  
Worst Case ◽  
Flooded Area ◽  
Hurricane Storm Surge ◽  
San Andres

Despite the low occurrence of tropical cyclones at the archipelago of San Andres, Providencia, and Santa Catalina (Colombia), Hurricane Iota in 2020 made evident the area vulnerability to tropical cyclones as major hazards by obliterating 56.4 % of housing, partially destroying the remaining houses in Providencia. We investigated the hurricane storm surge inundation in the archipelago by forcing hydrodynamic models with synthetic tropical cyclones and hypothetical hurricanes. The storm surge from synthetic events allowed identifying the strongest surges using the probability distribution, enabling the generation of hurricane storm surge flood maps for 100 and 500 year return periods. This analysis suggested that the east of San Andres and Providencia are the more likely areas to be flooded from hurricanes storm surges. The hypothetical events were used to force the hydrodynamic model to create worst-case flood scenario maps, useful for contingency and development planning. Additionally, Hurricane Iota flood levels were calculated using 2D and 1D models. The 2D model included storm surge (SS), SS with astronomical tides (AT), and SS with AT and wave setup (WS), resulting in a total flooded area (percentage related to Providencia’s total area) of 67.05 ha (3.25 %), 65.23 ha (3.16 %), and 76.68 ha (3.68%), respectively. While Hurricane Iota occurred during low tide, the WS contributed 14.93 % (11.45 ha) of the total flooded area in Providencia. The 1D approximation showed that during the storm peak in the eastern of the island, the contribution of AT, SS, and wave runup to the maximum sea water level was −3.01%, 46.36%, and 56.55 %, respectively. This finding provides evidence of the water level underestimation in insular environments when modeling SS without wave contributions. The maximum SS derived from Iota was 1.25 m at the east of Providencia, which according to this study has an associated return period of 3,234 years. The methodology proposed in this study can be applied to other coastal zones and may include the effect of climate change on hurricane storm surges and sea-level rise. Results from this study are useful for emergency managers, government, coastal communities, and policymakers as civil protection measures.

scholarly journals Studying the Intensity and Storm Surge Phenomena of Tropical Cyclone Roanu (2016) over the Bay of Bengal Using NWP Model

2020 ◽  
Vol 12 (1) ◽  
pp. 55-68
Author(s):  
M. I. Ali ◽  
M. Saifullah ◽  
A. Imran ◽  
I. M. Syed ◽  
M. A. K. Mallik
Keyword(s):  
Tropical Cyclone ◽  
Storm Surge ◽  
Bay Of Bengal ◽  
Sea Water ◽  
Monsoon Season ◽  
Wrf Model ◽  
Simulated Data ◽  
Storm Surges ◽  
Reported Data ◽  
Surge Height

Tropical Cyclone (TC) is the most devastating atmospheric incidents which occur frequently in pre-monsoon and the post-monsoon season in Bangladesh. The Bay of Bengal (BoB) is one of the most vulnerable places of TC induced storm surge. The triangular shape of BoB plays an important role to drive the sea water towards the coast and amplify the surges. In this study, minimum central pressure, maximum wind speed and track of TC Roanu are predicted by the WRF model. At the same time, prediction of cyclone induced storm surge for TC Roanu is done by using MRI storm surge model which is conducted by JMA. The input files for this parametric model is provided by using simulated data of WRF model and observed data of IMD. The results are compared with available recorded data of surge height for this cyclone. The differences in simulated output for two different input files are also studied. The maximum surge height from the MRI model is found 3 m using WRF simulated data and for IMD estimated data the maximum surge height is found 2.5 m. The simulated surge heights are found in decent contract with the available reported data of the storm surges.

scholarly journals Rapid prediction of peak storm surge from tropical cyclone track time series using machine learning

2021 ◽  
Author(s):  
Jun-Whan Lee ◽  
Jennifer Irish ◽  
Michelle Bensi ◽  
Doug Marcy
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
Storm Surge ◽  
Coastal Region ◽  
Surrogate Modeling ◽  
Storm Surges ◽  
High Fidelity ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Modeling Approaches

Rapid and accurate prediction of peak storm surges across an extensive coastal region is necessary to inform assessments used to design the systems that protect coastal communities’ life and property. Significant advances in high-fidelity, physics-based numerical models have been made in recent years, but use of these models for probabilistic forecasting and probabilistic hazard assessment is computationally intensive. Several surrogate modeling approaches based on existing databases of high-fidelity synthetic storm surge simulations have been recently suggested to reduce computational burden without substantial loss of accuracy. In these previous studies, however, the surrogate modeling approaches relied on a tropical cyclone condition at one moment (usually at or near landfall), which is not always most correlated with the peak storm surge. In this study, a new one-dimensional convolutional neural network model combined with principal component analysis and a k-means clustering (C1PKNet) is presented that can rapidly predict peak storm surge across an extensive coastal region from time-series of tropical cyclone conditions, namely the storm track. The C1PKNet model was trained and cross-validated for the Chesapeake Bay area of the United States using existing database of 1031 high-fidelity storm surge simulations, including both landfalling and bypassing storms. Moreover, the performance of the C1PKNet model was evaluated based on observations from three historical hurricanes (Hurricane Isabel in 2003, Hurricane Irene in 2011, and Hurricane Sandy in 2012). The results indicate that the C1PKNet model is computationally e cient and can predict peak storm surges from realistic tropical cyclone track time-series. We believe that this new surrogate model can enhance coastal resilience by providing rapid storm surge predictions.

scholarly journals Storm surge in the Bay of Bengal and Arabian Sea : The problem and its prediction

MAUSAM ◽  
2021 ◽  
Vol 48 (2) ◽  
pp. 283-304
Author(s):  
S.K. DUBE ◽  
A. D. RAO ◽  
P. C. SINHA ◽  
T. S. MURTY ◽  
N. BAHULAYAN
Keyword(s):  
Tropical Cyclone ◽  
Storm Surge ◽  
Bay Of Bengal ◽  
Arabian Sea ◽  
State Of The Art ◽  
Storm Surges ◽  
Economic Losses ◽  
Coastal Structures ◽  
Loss Of Life ◽  
Factors Affecting

India and its neighbourhood is threatened by the possibility of storm surge floods whenever a tropical cyclone approaches. Storm surge disasters cause heavy loss of life and property, damage to the coastal structures and agriculture which lead to annual economic losses in these countries. Thus, the real time monitoring and warning of storm surge is of great concern for this region. The goal of this paper is to provide an overview of major aspects of the storm surge problem in the Bay of Bengal and the Arabian Sea, the factors affecting the generation of storm surges and the present state-of-the-art in the numerical storm surge prediction.    

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