Articles | Volume 18, issue 12
https://doi.org/10.5194/nhess-18-3225-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-18-3225-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Dec 2018
Research article |
| 06 Dec 2018
| 06 Dec 2018
Dependency of tropical cyclone risk on track in South Korea
Chaehyeon C. Nam
School of Earth and Environmental Sciences, Seoul National University,
Seoul, South Korea
current address: Department of Atmospheric Science, Colorado State
University, Fort Collins, Colorado, USA
School of Earth and Environmental Sciences, Seoul National University,
Seoul, South Korea
current address: Department of Earth Sciences, Chosun University,
Gwangju, South Korea
Chang-Hoi Ho
School of Earth and Environmental Sciences, Seoul National University,
Seoul, South Korea
Deliang Chen
Department of Earth Sciences, University of Gothenburg, Gothenburg,
Sweden
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Cited
18 citations as recorded by crossref.
- Convection-permitting simulations reveal expanded rainfall extremes of tropical cyclones affecting South Korea due to anthropogenic warming M. Lee et al. 10.1038/s41612-023-00509-w
- Decision-Tree-Based Classification of Lifetime Maximum Intensity of Tropical Cyclones in the Tropical Western North Pacific S. Kim et al. 10.3390/atmos12070802
- A study of tropical cyclone impact on the power distribution grid in South Korea for estimating damage S. Oh et al. 10.1016/j.rser.2021.112010
- The parametric hurricane rainfall model with moisture and its application to climate change projections D. Kim et al. 10.1038/s41612-022-00308-9
- Dynamic bivariate hazard forecasting of hurricanes for improved disaster preparedness S. Tripathy et al. 10.1038/s43247-023-01198-2
- Study of tropical cyclone wave characteristics based on a hybrid track clustering method J. Li et al. 10.1016/j.ocecoaman.2024.107448
- A decision tree approach to identify predictors of extreme rainfall events – A case study for the Fiji Islands K. Sharma et al. 10.1016/j.wace.2021.100405
- Typhoon Disaster Risk Assessment Based on Emergy Theory: A Case Study of Zhuhai City, Guangdong Province, China Z. Gao et al. 10.3390/su12104212
- Tropical cyclone damages in Mainland China over 2005–2016: losses analysis and implications H. Wang et al. 10.1007/s10668-019-00481-7
- Quantitative assessment of population risk to tropical cyclones using hybrid modeling combining GAM and XGBoost: A case study of Hainan Province C. Meng et al. 10.1016/j.ijdrr.2024.104650
- Changes in Tropical Cyclone Disasters Over China During 2001–2020 Y. Li et al. 10.1029/2022EA002795
- Dependence of tropical cyclone damage on maximum wind speed and socioeconomic factors M. Ye et al. 10.1088/1748-9326/ab9be2
- Storm-Induced Power Grid Damage Forecasting Method for Solving Low Probability Event Data S. Oh et al. 10.1109/ACCESS.2021.3055146
- A Performance Evaluation of Potential Intensity over the Tropical Cyclone Passage to South Korea Simulated by CMIP5 and CMIP6 Models D. Park et al. 10.3390/atmos12091214
- Major Decisive Factors of Tropical Cyclone Risk in the Republic of Korea: Intensity, Track, and Extratropical Transition C. Nam et al. 10.1007/s13143-023-00318-4
- Evaluation of Tropical Cyclone Disaster Loss Using Machine Learning Algorithms with an eXplainable Artificial Intelligence Approach S. Liu et al. 10.3390/su151612261
- Tropical cyclone risk assessment reflecting the climate change trend: the case of South Korea K. Jung et al. 10.1007/s11069-024-06428-0
- How Quickly Can We Adapt to Change? An Assessment Of Hurricane Damage Mitigation Efforts Using Forecast Uncertainty A. Martinez 10.2139/ssrn.3070154
17 citations as recorded by crossref.
- Convection-permitting simulations reveal expanded rainfall extremes of tropical cyclones affecting South Korea due to anthropogenic warming M. Lee et al. 10.1038/s41612-023-00509-w
- Decision-Tree-Based Classification of Lifetime Maximum Intensity of Tropical Cyclones in the Tropical Western North Pacific S. Kim et al. 10.3390/atmos12070802
- A study of tropical cyclone impact on the power distribution grid in South Korea for estimating damage S. Oh et al. 10.1016/j.rser.2021.112010
- The parametric hurricane rainfall model with moisture and its application to climate change projections D. Kim et al. 10.1038/s41612-022-00308-9
- Dynamic bivariate hazard forecasting of hurricanes for improved disaster preparedness S. Tripathy et al. 10.1038/s43247-023-01198-2
- Study of tropical cyclone wave characteristics based on a hybrid track clustering method J. Li et al. 10.1016/j.ocecoaman.2024.107448
- A decision tree approach to identify predictors of extreme rainfall events – A case study for the Fiji Islands K. Sharma et al. 10.1016/j.wace.2021.100405
- Typhoon Disaster Risk Assessment Based on Emergy Theory: A Case Study of Zhuhai City, Guangdong Province, China Z. Gao et al. 10.3390/su12104212
- Tropical cyclone damages in Mainland China over 2005–2016: losses analysis and implications H. Wang et al. 10.1007/s10668-019-00481-7
- Quantitative assessment of population risk to tropical cyclones using hybrid modeling combining GAM and XGBoost: A case study of Hainan Province C. Meng et al. 10.1016/j.ijdrr.2024.104650
- Changes in Tropical Cyclone Disasters Over China During 2001–2020 Y. Li et al. 10.1029/2022EA002795
- Dependence of tropical cyclone damage on maximum wind speed and socioeconomic factors M. Ye et al. 10.1088/1748-9326/ab9be2
- Storm-Induced Power Grid Damage Forecasting Method for Solving Low Probability Event Data S. Oh et al. 10.1109/ACCESS.2021.3055146
- A Performance Evaluation of Potential Intensity over the Tropical Cyclone Passage to South Korea Simulated by CMIP5 and CMIP6 Models D. Park et al. 10.3390/atmos12091214
- Major Decisive Factors of Tropical Cyclone Risk in the Republic of Korea: Intensity, Track, and Extratropical Transition C. Nam et al. 10.1007/s13143-023-00318-4
- Evaluation of Tropical Cyclone Disaster Loss Using Machine Learning Algorithms with an eXplainable Artificial Intelligence Approach S. Liu et al. 10.3390/su151612261
- Tropical cyclone risk assessment reflecting the climate change trend: the case of South Korea K. Jung et al. 10.1007/s11069-024-06428-0
1 citations as recorded by crossref.
Latest update: 21 Nov 2024
Short summary
This study shows that a small deviation of the tropical cyclone (TC) track in the west–east direction (less than 250 km smaller than the average radius of the TC) has a more dominant effect on the extent and distribution of TC damage than TC intensity or size. This suggests that track information should be considered more carefully in assessments of future TC risk.
This study shows that a small deviation of the tropical cyclone (TC) track in the west–east...
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