Storm Surge Hindcast and Return Period of a Haiyan-Like Super Typhoon

Kumagai, Kenzou; Mori, Nobuhito; Nakajo, Sota

doi:10.1142/s0578563416400015

Cited by 7 publications

(14 citation statements)

References 3 publications

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“…The effect of R max to storm surge modeling has been investigated by Kim et al (2015) [18] and R max of 50 km with the leveling-off drag coefficient fulfills the survey data. However, smaller R max (accurately, R max = 23 and 30 km) is used to perform the storm surge simulation of Haiyan by Kumagai et al (2016) [19]. However, the pressure distributions used in Kim et al (2015) and Kumagai et al (2016) are different from the one in this study.…”

Section: Storm Track and Parameters Of Haiyanmentioning

confidence: 96%

“…However, smaller R max (accurately, R max = 23 and 30 km) is used to perform the storm surge simulation of Haiyan by Kumagai et al (2016) [19]. However, the pressure distributions used in Kim et al (2015) and Kumagai et al (2016) are different from the one in this study. Therefore, RMW shall be examined again.…”

Section: Storm Track and Parameters Of Haiyanmentioning

confidence: 96%

“…Hence, the bottom friction using this formula is less important in deep waters, more significant in shallow waters, and crucial in coastal regions (including inland areas). Since the inundation calculation is not involved in this study, the Manning's coefficient is 0.025 over the whole computational domain, which is also adopted by other studies [18,19]. In fact, the Manning's coefficient shall be determined carefully, especially the inundation calculation involved.…”

Section: Storm Surge Modelmentioning

confidence: 99%

See 2 more Smart Citations

Discrepancies on Storm Surge Predictions by Parametric Wind Model and Numerical Weather Prediction Model in a Semi-Enclosed Bay: Case Study of Typhoon Haiyan

Tsai

Lin

et al. 2020

Water

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This study explores the discrepancies of storm surge predictions driven by the parametric wind model and the numerical weather prediction model. Serving as a leading-order storm wind predictive tool, the parametric Holland wind model provides the frictional-free, steady-state, and geostrophic-balancing solutions. On the other hand, WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) provides the results solving the 3D time-integrated, compressible, and non-hydrostatic Euler equations, but time-consuming. To shed light on their discrepancies for storm surge predictions, the storm surges of 2013 Typhoon Haiyan in the Leyte Gulf and the San Pedro Bay are selected. The Holland wind model predicts strong southeastern winds in the San Pedro Bay after Haiyan makes landfall at the Leyte Island than WRF-ARW 3 km and WRF-ARW 1 km. The storm surge simulation driven by the Holland wind model finds that the water piles up in the San Pedro Bay and its maximum computed storm surges are almost twice than those driven by WRF-ARW. This study also finds that the storm surge prediction in the San Pedro Bay is sensitive to winds, which can be affected by the landfall location, the storm intensity, and the storm forward speed. The numerical experiment points out that the maximum storm surges can be amplified by more 5–6% inside the San Pedro Bay if Haiyan’s forward speed is increased by 10%.

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Section: Storm Track and Parameters Of Haiyanmentioning

confidence: 96%

Section: Storm Track and Parameters Of Haiyanmentioning

confidence: 96%

Section: Storm Surge Modelmentioning

confidence: 99%

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Discrepancies on Storm Surge Predictions by Parametric Wind Model and Numerical Weather Prediction Model in a Semi-Enclosed Bay: Case Study of Typhoon Haiyan

Tsai

Lin

et al. 2020

Water

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“…It is important to consider the influence of climate change on storm surges as well as SLR and wave climate change. As storm surge height is highly sensitive to local bathymetry and TC characteristics (e.g., intensity and track), a long-term impact assessment is not easy due to infrequent occurrence O (100 years) at any particular bay (e.g., Kumagai et al, 2016). To evaluate the climate change impact on storm surges, there are several methodologies of storm surge assessment.…”

Section: Projection Of Storm Surgesmentioning

confidence: 99%

Impact assessment of climate change on coastal hazards in Japan

Mori

Kjerland

Nakajo

et al. 2016

Hydrological Research Letters

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Understanding future changes of ocean waves and storm surges is important for assessing and mitigating the impact of climate on coastal, marine and ocean environments and on engineering problems. This paper reviews the latest research results of climate change impacts on coastal hazards in Japan. First, future changes of wave climate and storm surges based on MRI-AGCM ensemble experiments are summarized. Second, the applications of coastal hazard projections to coastal structures and beach profiles are summarized as a series of climate impact assessment projects. There are clear increases in extreme values of wave heights and storm surges in the tropical cyclone dominant regions around the middle latitudes of the Western North Pacific including Japan. The influence of future climate change on caisson breakwaters is discussed considering sea level rise, extreme wave conditions and storm surges targeting the Pacific side of Japan.

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“…Traditionally, tide gauge observations have been considered the most reliable data for observing storm surges and have been widely used to understand relevant features (Bromirski et al, 2017; Ceres et al, 2017; Feng et al, 2018; S. L. Han, 2013; Kumagai et al, 2016; V. V. Kharin et al, 2018; Vousdoukas et al, 2018). However, current research on storm surge activity is based on the monitoring and analysis of each tide gauge.…”

Section: Introductionmentioning

confidence: 99%

Historical Reconstruction of Storm Surge Activity in the Southeastern Coastal Area of China for the Past 60 Years

Liu

2020

Earth and Space Science

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It is a very difficult task to analyze the spatial and temporal variability of storm surge activity with current monitoring methods, because tide gauge observation, satellite altimeter, and numerical simulation do not ensure sufficient spatial and temporal resolution and temporal coverage at the same time. We propose to use a reanalysis data set, which covers the period from 1958 to 2016, to statistically reconstruct the daily maximum storm surge levels in the southeastern coastal area of China. Then, we used the Geographical Differential Analysis (GDA) calibration to correct the reconstruction results. The verification of the statistical model and the calibration results show that both the statistical model and the GDA calibration have a good accuracy in terms of high correlations and small errors. However, they also reveal a variable spatial quality of the multivariate statistical model in the reconstructed maximum storm surge levels, especially in the extreme events of the storm surge activity, the daily maximum surge is often underestimated. The GDA calibration result readily solves this problem, as it can accurately reflect not only the daily maximum storm surge levels but also the whole spatial and temporal dynamic storm surge evolution process. Therefore, this work provides an effective method to establish long‐term sequence and high‐precision daily maximum storm surge levels. This method can reveal the spatial and temporal evolution features of storm surge intensity at a climatic scale and main variability features. Moreover, it can predict possible trends in the geospatial distribution pattern of storm surge intensity in the context of future climate change.

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Storm Surge Hindcast and Return Period of a Haiyan-Like Super Typhoon

Cited by 7 publications

References 3 publications

Discrepancies on Storm Surge Predictions by Parametric Wind Model and Numerical Weather Prediction Model in a Semi-Enclosed Bay: Case Study of Typhoon Haiyan

Discrepancies on Storm Surge Predictions by Parametric Wind Model and Numerical Weather Prediction Model in a Semi-Enclosed Bay: Case Study of Typhoon Haiyan

Impact assessment of climate change on coastal hazards in Japan

Historical Reconstruction of Storm Surge Activity in the Southeastern Coastal Area of China for the Past 60 Years

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