Impact of Major Typhoons in 2016 on Sea Surface Features in the Northwestern Pacific

Song, Dan; Guo, Linghui; Duan, Zhigang; Xiang, Lulu

doi:10.3390/w10101326

Cited by 11 publications

(7 citation statements)

References 40 publications

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“…In 2016, many typhoons have passed in many Asian countries including South Korea and China. Representative strong typhoons include LionRock, Meranti, Melakas, and Megi, and their impact analysis has been studied [11].…”

Section: Prediction and Analysis Systemmentioning

confidence: 99%

“…The increase of sea temperature due to climate change may cause the sea level to rise and an increase of typhoon intensity, leading to extreme damages from flood disaster in coastal areas, including river mouth and river reaches [1][2][3][4][5][6][7][8][9][10]. Coastal flooding can be driven by water level rise due to a combination of tide, surge, and wave, and it can be maximized by the breaking and run-up of strong waves during high sea level by high tide and storm-induced surge [11,12]. In addition, undesirable erosion and loss of beaches along the coastline have continuously been generated with extreme flood events and storm-induced surge [13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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The Downscaling Study for Typhoon-Induced Coastal Inundation

Jang

Joo

Jeong

et al. 2020

Water

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Typhoons can often cause inundation in lower coastal cities by inducing strong surges and waves. Being affected by typhoon annually, the coastal cities in South Korea are very vulnerable to typhoons. In 2016, a typhoon ‘CHABA’, with a maximum 10 min sustained wind speed of about 50 m/s and a minimum central pressure of 905 hPa, hit South Korea, suffering tremendous damage. In particular, ‘CHABA’-induced coastal inundation resulted in serious damage to the coastal area of Busan where a lot of high-rise buildings and residential areas are concentrated, and was caused by the combined effect of tide, surge, and wave. The typhoon-induced surge raised sea levels during high tide, and the strong wave with a long period of more than 10 s eventually led to the coastal inundation at the same time. The present research focuses a numerical downscaling considering the effects of tide, surge and wave for coastal inundation induced by Typhoon ‘CHABA’. This downscaling approach applied several numerical models, which are the Weather Research and Forecasting model (WRF) for typhoon simulation, the Finite Volume Community Ocean Model (FVCOM) for tide and surge simulation, and the Simulating WAve Nearshore (SWAN) for wave simulation. In a domain covering the Korean Peninsula, typhoon-induced surges and waves were simulated applying the results simulated by WRF as meteorological conditions. In the downscaled domain ranged near the coastal area of Busan, the coastal inundation was simulated blending a storm tide height and an irregular wave height obtained from the domain, in which each height has 1 s interval. The irregular wave height was calculated using the significant wave height and peak period. Through this downscaling study, the impact of storm tide and wave on coastal inundation was estimated.

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Section: Prediction and Analysis Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Downscaling Study for Typhoon-Induced Coastal Inundation

Jang

Joo

Jeong

et al. 2020

Water

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“…Tropical cyclones are some of the most destructive natural disasters, which often bring huge losses to people's life and property. The Northwest Pacific and the South China Sea regions are the birthplaces of most monsoons and typhoons and are important channels for the generation and transmission of water vapor [1][2][3][4][5]. With an increase in sea surface temperature (SST), the total number of tropical cyclones in the North Pacific, Indian Ocean, and southwest Pacific Ocean decreases, and the cyclone development period shortens, but the number and proportion of tropical cyclones reaching super typhoon intensity increases greatly [6,7].…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Temperature Field Change in the South China Sea during Typhoon Kai-Tak (1213) Based on a Fully Coupled Atmosphere–Wave–Ocean Model

Jiang

Chen

et al. 2019

Water

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Studying the sea–air interaction between the upper ocean and typhoons is crucial to improve our understanding of heat and momentum exchange between the atmosphere and the ocean. There is a strong heat flux exchange between the atmosphere and the ocean during the impact of a typhoon, and the physical fields, such as the wind field, wave field, flow field, and SST field, also interact with each other. A fully coupled Atmosphere–Wave–Ocean model in the South China Sea was established by the mesoscale atmospheric model WRF, wave model SWAN, and the regional ocean model ROMS based on the COAWST model system. Typhoon Kai-tak was simulated using this fully coupled model and some other coupled schemes. In this paper, the variation of sea surface temperature (SST) and ocean subsurface temperature caused by Typhoon Kai-tak is analyzed by the fully coupled model, and the basic characteristics of the response of the upper ocean to the typhoon are given. The simulation results demonstrate that the fully coupled WRF-SWAN-ROMS model shows that the typhoon passes through the sea with obvious cooling. In the cold eddy region, the sea surface temperature cools 4 to 5 °C, and the cooling zone is concentrated on the right side of the track. The change of sea surface temperature lags more than 12 h behind the change of sea surface height. The decrease of SST on the left side of the track was relatively small: ranging from 1.5 to 2.5 °C. The disturbance of typhoon causes the subsurface water to surge to the surface, changes the temperature distribution of the surface, and causes the mixing layer to deepen about 40 m to 60 m. The simulation results reveal the temporal and spatial distribution of sea temperature and mixed layer depth. The sea surface temperature field has an asymmetrical distribution in space and has a lag in time. The heat exchange at the air–sea interface is very strong under the influence of the typhoon. The heat exchange between the air and sea is divided into latent heat and sensible heat, and the latent heat generated by water vapor evaporation plays a dominant role in the heat exchange at the air–sea interface, which shows that the heat carried by the vaporization of the sea surface is one of the important factors for the decrease of sea temperature under the influence of the typhoon.

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“…The frequency of TCs in the Western North Pacific (WNP) is very high compared to other regions [1]. As a result, coastal communities around the WNP suffer serious casualties and property losses annually [2][3][4]. The area covered by the Northwest Pacific Basin is to the north of the equator and to the west of 180 • E, and includes the South China Sea.…”

Section: Introductionmentioning

confidence: 99%

Using eXtreme Gradient BOOSTing to Predict Changes in Tropical Cyclone Intensity over the Western North Pacific

et al. 2019

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Coastal cities in China are frequently hit by tropical cyclones (TCs), which result in tremendous loss of life and property. Even though the capability of numerical weather prediction models to forecast and track TCs has considerably improved in recent years, forecasting the intensity of a TC is still very difficult; thus, it is necessary to improve the accuracy of TC intensity prediction. To this end, we established a series of predictors using the Best Track TC dataset to predict the intensity of TCs in the Western North Pacific with an eXtreme Gradient BOOSTing (XGBOOST) model. The climatology and persistence factors, environmental factors, brainstorm features, intensity categories, and TC months are considered inputs for the models while the output is the TC intensity. The performance of the XGBOOST model was tested for very strong TCs such as Hato (2017), Rammasum (2014), Mujiage (2015, and Hagupit (2014). The results obtained show that the combination of inputs chosen were the optimal predictors for TC intensification with lead times of 6, 12, 18, and 24 h. Furthermore, the mean absolute error (MAE) of the XGBOOST model was much smaller than the MAEs of a back propagation neural network (BPNN) used to predict TC intensity. The MAEs of the forecasts with 6, 12, 18, and 24 h lead times for the test samples used were 1.61, 2.44, 3.10, and 3.70 m/s, respectively, for the XGBOOST model. The results indicate that the XGBOOST model developed in this study can be used to improve TC intensity forecast accuracy and can be considered a better alternative to conventional operational forecast models for TC intensity prediction.The characteristics that affect TC intensity are nonlinear and thus difficult to predict [2]. In recent years, many researchers have studied TC intensity prediction primarily using numerical forecasting and statistical methods [6][7][8][9][10]. Numerical forecasting is the main tool used to forecast TCs around the world, and systems such as the European Centre for Medium-Range Weather Forecasts-Integrated Forecasting System (ECMWF-IFS) [11], the Japan Meteorological Agency's global spectral model (JMA-GSM) [12], and the National Centers for Environmental Prediction-Global Forecast System (NCEP-GFS) [13] have been developed as operational techniques. Statistical intensity forecast methods such as Climatology and Persistence (CLIPER) [14] and the Statistical Hurricane Intensity Prediction Scheme (SHIPS) [15] have also been developed as operational techniques. However, advancements in TC intensity prediction have been relatively slow, although notable work has been done in the past 20 years on predicting TC paths [16]. One of the reasons for this is that the internal structure of storms is not yet sufficiently understood. TCs have an asymmetric structure, which may be caused by thermal and dynamic factors such as uneven distribution of sea surface temperature and humidity, horizontal or vertical shear, and asymmetric distribution of convection [2,17]. Changes in TC intensity are controlled by many e...

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Impact of Major Typhoons in 2016 on Sea Surface Features in the Northwestern Pacific

Cited by 11 publications

References 40 publications

The Downscaling Study for Typhoon-Induced Coastal Inundation

The Downscaling Study for Typhoon-Induced Coastal Inundation

Three-Dimensional Temperature Field Change in the South China Sea during Typhoon Kai-Tak (1213) Based on a Fully Coupled Atmosphere–Wave–Ocean Model

Using eXtreme Gradient BOOSTing to Predict Changes in Tropical Cyclone Intensity over the Western North Pacific

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