Applicability Evaluation of the Global Synthetic Tropical Cyclone Hazard Dataset in Coastal China
被引:0
|
作者:
Li, Xiaomin
论文数: 0引用数: 0
h-index: 0
机构:
Minist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R ChinaMinist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
Li, Xiaomin
[1
]
Hou, Qi
论文数: 0引用数: 0
h-index: 0
机构:
China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R ChinaMinist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
Hou, Qi
[2
]
Zhang, Jie
论文数: 0引用数: 0
h-index: 0
机构:
Minist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R ChinaMinist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
Zhang, Jie
[1
,2
]
Zhang, Suming
论文数: 0引用数: 0
h-index: 0
机构:
China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R ChinaMinist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
Zhang, Suming
[2
]
Du, Xuexue
论文数: 0引用数: 0
h-index: 0
机构:
China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R China
Guizhou Power Grid Co Ltd, Duyun Power Supply Bur, Duyun 558000, Peoples R ChinaMinist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
Du, Xuexue
[2
,3
]
Zhao, Tangqi
论文数: 0引用数: 0
h-index: 0
机构:
China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R ChinaMinist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
Zhao, Tangqi
[2
]
机构:
[1] Minist Nat Resources China, Inst Oceanog 1, Qingdao 266061, Peoples R China
[2] China Univ Petr East China, Coll Oceanog & Space Informat, Qingdao 266580, Peoples R China
[3] Guizhou Power Grid Co Ltd, Duyun Power Supply Bur, Duyun 558000, Peoples R China
A tropical cyclone dataset is an important data source for tropical cyclone disaster research, and the evaluation of its applicability is a necessary prerequisite. The Global Synthetic Tropical Cyclone Hazard (GSTCH) dataset is a dataset of global tropical cyclone activity for 10,000 years from 2018, and has become accepted as a major data source for the study of global tropical cyclone hazards. On the basis of the authoritative Tropical Cyclone Best Track (TCBT) dataset proposed by the China Meteorological Administration, this study evaluated the applicability of the GSTCH dataset in relation to two regions: the Northwest Pacific and China ' s coastal provinces. For the Northwest Pacific, the results show no significant differences in the means and standard deviations of landfall wind speed, landfall pressure, and annual occurrence number between the two datasets at the 95% confidence level. They also show the cumulative distributions of central minimum pressure and central maximum wind speed along the track passed the Kolmogorov-Smirnov (K-S) test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at sea-area scale. For China's coastal provinces, the results show that the means or standard deviations of tropical cyclone characteristics between the two datasets were not significantly different in provinces other than Guangdong and Hainan, and further analysis revealed that the cumulative distributions of the tropical cyclone characteristics in Guangdong and Hainan provinces passed the K-S test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at province scale. The applicability evaluation revealed that no significant differences exist between most of the tropical cyclone characteristics in the TCBT and GSTCH datasets, and that the GSTCH dataset is an available and reliable data source for tropical cyclone hazard studies in China's coastal areas.
机构:
Columbia Univ, Lamont Doherty Earth Observ, New York, NY 10027 USA
Univ Nacl Autonoma Mex, Escuela Nacl Ciencias Tierra, Mexico City, MexicoUniv Quebec Montreal, Dept Math, Montreal, PQ, Canada
机构:
Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R China
Clemson Univ, Glenn Dept Civil Engn, Clemson, SC 29634 USATongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R China
Fang, Genshen
论文数: 引用数:
h-index:
机构:
Zhao, Lin
论文数: 引用数:
h-index:
机构:
Cao, Shuyang
Zhu, Ledong
论文数: 0引用数: 0
h-index: 0
机构:
Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R China
Tongji Univ, Key Lab Transport Ind Wind Resistant Technol Brid, Shanghai 200092, Peoples R ChinaTongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R China