An elliptical wind field model of typhoons

Wang, Xiuqin; Chengchun, Qian; Wang, Wei; Tong, Yan

doi:10.1007/s11802-004-0005-z

Cited by 15 publications

(9 citation statements)

References 11 publications

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“…Nano-HA was prepared by hydrothermal method according to the literature [32,33]. The morphology of the Nano-HA was examined by TEM as shown in Fig.…”

Section: Preparation Of Nano-ha/chitosan/tyrosinase-modified Au Electmentioning

confidence: 99%

A novel tyrosinase biosensor based on hydroxyapatite–chitosan nanocomposite for the detection of phenolic compounds

Zhang

et al. 2010

Analytica Chimica Acta

119

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“…Nano-HA was prepared by hydrothermal method according to the literature [32,33]. The morphology of the Nano-HA was examined by TEM as shown in Fig.…”

Section: Preparation Of Nano-ha/chitosan/tyrosinase-modified Au Electmentioning

confidence: 99%

A novel tyrosinase biosensor based on hydroxyapatite–chitosan nanocomposite for the detection of phenolic compounds

Zhang

et al. 2010

Analytica Chimica Acta

119

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“…Many analytical parametric typhoon models have been developed to construct or reconstruct the wind and air pressure fields of typhoons for simulating storm waves and surges due to their simplicity [34][35][36][37][38][39][40]. The modified Rankine vortex (MRV) typhoon wind model proposed by [37] provides a more accurate wind field [41,42], which is satisfactory for ocean wave and storm surge modeling [4,37,43,44] and was therefore employed in the present study.…”

Section: Parametric Typhoon Wind Fieldmentioning

confidence: 99%

Numerical Simulation of Large Wave Heights from Super Typhoon Nepartak (2016) in the Eastern Waters of Taiwan

Hsiao

Chen

et al. 2020

JMSE

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Super Typhoon Nepartak (2016) was used for this case study because it is the most intense typhoon that made landfall in Taiwan in the past decade. Winds extracted from the Climate Forecast System version 2 (CFSV2) and ERA5 datasets and merged with a parametric typhoon model using two hybrid techniques served as the meteorological conditions for driving a coupled wave-circulation model. The computed significant wave heights were compared with the observations recorded at three wave buoys in the eastern waters of Taiwan. Model performance in terms of significant wave height was also investigated by employing the CFSV2 winds under varying spatial and temporal resolutions. The results of the numerical experiments reveal that the simulated storm wave heights tended to decrease significantly due to the lower spatial resolution of the hourly winds from the CFSV2 dataset; however, the variations in the storm wave height simulations were less sensitive to the temporal resolution of the wind field. Introducing the combination of the CFSV2 and the parametric typhoon winds greatly improved the storm wave simulations, and similar phenomena can be found in the exploitation of the ERA5 dataset blended into the parametric wind field. The overall performance of the hybrid winds derived from ERA5 was better than that from the CFSV2, especially in the outer region of Super Typhoon Nepartak (2016).

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“…Many parametric typhoon models have been developed to provide meteorological information for storm surge or storm wave modeling [41][42][43][44][45][46]. Since the authors of [47] found that the analytical models provided very similar results, the parametric typhoon model proposed in [43] was employed:…”

Section: Model Forcingmentioning

confidence: 99%

Hazard Assessment of Typhoon-Driven Storm Waves in the Nearshore Waters of Taiwan

Chang

Shih

Chen

et al. 2018

Water

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Abstract:In Taiwan, the coastal hazard from typhoon-induced storm waves poses a greater threat to human life and infrastructure than storm surges. Therefore, there has been increased interest in assessing the storm wave hazard levels for the nearshore waters of Taiwan. This study hindcasted the significant wave heights (SWHs) of 124 historical typhoon events from 1978 to 2017 using a fully coupled model and hybrid wind fields (a combination of the parametric typhoon model and reanalysis products). The maximum SWHs of each typhoon category were extracted to create individual storm wave hazard maps for the sea areas of the coastal zones (SACZs) in Taiwan. Each map was classified into five hazard levels (I to V) and used to generate a comprehensive storm wave hazard map. The results demonstrate that the northern and eastern nearshore waters of Taiwan are threatened by a hazard level IV (SWHs ranging from 9.0 to 12.0 m) over a SACZ of 510.0 km 2 and a hazard level V (SWHs exceeding 12.0 m) over a SACZ of 2152.3 km 2 . The SACZs threatened by hazard levels I (SWHs less than 3.0 m), II (SWHs ranging from 3.0 to 6.0 m), and III (SWHs ranging from 6.0-9.0 m) are of 1045.2 km 2 , 1793.9 km 2 , and 616.1 km 2 , respectively, and are located in the western waters of Taiwan.

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An elliptical wind field model of typhoons

Cited by 15 publications

References 11 publications

A novel tyrosinase biosensor based on hydroxyapatite–chitosan nanocomposite for the detection of phenolic compounds

A novel tyrosinase biosensor based on hydroxyapatite–chitosan nanocomposite for the detection of phenolic compounds

Numerical Simulation of Large Wave Heights from Super Typhoon Nepartak (2016) in the Eastern Waters of Taiwan

Hazard Assessment of Typhoon-Driven Storm Waves in the Nearshore Waters of Taiwan

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