Evaluation of parametric wind models for more accurate modeling of storm surge: a case study of Hurricane Michael

Vijayan, Linoj; Huang, Wenrui; Yin, Kai; Özgüven, Eren Erman; Burns, Simone; Ghorbanzadeh, Mahyar

doi:10.1007/s11069-021-04525-y

Cited by 27 publications

(12 citation statements)

References 26 publications

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“…The Wilmott skill measures the degree of agreement between modeled and observed data, and ranges between 0 (complete disagreement) and 1 (complete agreement). The statistical metrics used here have been widely used in other studies that compare different wind data or surge data (Dullaart et al., 2020; Marsooli et al., 2019; Mayo & Lin, 2019; Torres et al., 2019; Vijayan et al., 2021). We also implement t ‐tests to determine whether differences in modeled storm tide errors across the coastline are statistically significant between different wind models.…”

Section: Methodsmentioning

confidence: 99%

Investigation of Tropical Cyclone Wind Models With Application to Storm Tide Simulations

2022

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The hazards induced by tropical cyclones (TCs), for example, high winds, extreme precipitation, and storm tides, are closely related to the TC surface wind field. Parametric models for TC surface wind distribution have been widely used for hazards and risk analysis due to their simplicity and efficiency in application. Here we revisit the parametric modeling of TC wind fields, including the symmetrical and asymmetrical components, and its applications in storm tide modeling in the North Atlantic. The asymmetrical wind field has been related to TC motion and vertical wind shear; however, we find that a simple and empirical background‐wind model, based solely on a rotation and scaling of the TC motion vector, can largely capture the observed surface wind asymmetry. The implicit inclusion of the wind shear effect can be understood with the climatological relationship between the general TC motion and wind shear directions during hurricane seasons. For the symmetric wind field, the widely used Holland wind profile is chosen as a benchmark model, and we find that a physics‐based complete wind profile model connecting the inner core and outer region performs superiorly compared to a wind analysis data set. When used as wind forcing for storm tide simulations, the physics‐based complete wind profile integrated with the background‐wind asymmetry model can reproduce the observed storm tides with lower errors than the often‐used Holland model coupled with a translation‐speed‐based method.

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Section: Methodsmentioning

confidence: 99%

Investigation of Tropical Cyclone Wind Models With Application to Storm Tide Simulations

2022

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“…Another study, evaluating the power outages during five hurricanes at North and South Carolina, found that maximum wind speeds were highly correlated with power grid disruptions ( 32 ). This is completely logical, as wind speed is one of the best known hurricane impact variables ( 33 ).…”

Section: Literature Review and Research Gapsmentioning

confidence: 99%

Post-Hurricane Vegetative Debris Assessment Using Spectral Indices Derived from Satellite Imagery

Karaer

Ulak

Abichou

et al. 2021

Transportation Research Record

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Transportation systems are vulnerable to hurricanes and yet their recovery plays a critical role in returning a community to its pre-hurricane state. Vegetative debris is among the most significant causes of disruptions on transportation infrastructure. Therefore, identifying the driving factors of hurricane-caused debris generation can help clear roadways faster and improve the recovery time of infrastructure systems. Previous studies on hurricane debris assessment are generally based on field data collection, which is expensive, time consuming, and dangerous. With the availability and convenience of remote sensing powered by the simple yet accurate estimations on the vigor of vegetation or density of manufactured features, spectral indices can change the way that emergency planners prepare for and perform vegetative debris removal operations. Thus, this study proposes a data fusion framework combining multispectral satellite imagery and various vector data to evaluate post-hurricane vegetative debris with an exploratory analysis in small geographical units. Actual debris removal data were obtained from the City of Tallahassee, Florida after Hurricane Michael (2018) and aggregated into U.S. Census Block Groups along with four groups of datasets representing vegetation, storm surge, land use, and socioeconomics. Findings suggest that vegetation and other land characteristics are more determinant factors on debris generation, and Modified Soil-Adjusted Vegetation Index (MSAVI2) outperforms other vegetation indices for hurricane debris assessment. The proposed framework can help better identify equipment stack locations and temporary debris collection centers while providing resilience enhancements with a focus on the transportation infrastructure.

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“…The coupled model was forced with Irma's wind field, hypothetically making landfall in the Miami area (Figure 4a). Hourly wind fields were calculated by the method used and validated for the region [64]. Figure 4b shows a snapshot of the hurricane wind field near the landfall.…”

Section: Storm Surge Modelingmentioning

confidence: 99%

Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

Ghorbanzadeh

Vijayan

Yang

et al. 2021

IJGI

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Hurricane Irma, in 2017, made an unusual landfall in South Florida and the unpredictability of the hurricane’s path challenged the evacuation process seriously and left many evacuees clueless. It was likely to hit Southeast Florida but suddenly shifted its path to the west coast of the peninsula, where the evacuation process had to change immediately without any time for individual decision-making. As such, this study aimed to develop a methodology to integrate evacuation and storm surge modeling with a case study analysis of Irma hitting Southeast Florida. For this purpose, a coupled storm surge and wave finite element model (ADCIRC+SWAN) was used to determine the inundation zones and roadways with higher inundation risk in Broward, Miami-Dade, and Palm Beach counties in Southeast Florida. This was fed into the evacuation modeling to estimate the regional clearance times and shelter availability in the selected counties. Findings show that it takes approximately three days to safely evacuate the populations in the study area. Modeling such integrated simulations before the hurricane hit the state could provide the information people in hurricane-prone areas need to decide to evacuate or not before the mandatory evacuation order is given.

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Evaluation of parametric wind models for more accurate modeling of storm surge: a case study of Hurricane Michael

Cited by 27 publications

References 26 publications

Investigation of Tropical Cyclone Wind Models With Application to Storm Tide Simulations

Investigation of Tropical Cyclone Wind Models With Application to Storm Tide Simulations

Post-Hurricane Vegetative Debris Assessment Using Spectral Indices Derived from Satellite Imagery

Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

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