摘要
每年我国沿海多地遭受不同程度的台风灾害影响,台风对我国多个省市地区人民造成严重的生命和财产安全危害。海洋热含量(TCHP)是影响台风的主要因素之一,文中将2019年利奇马台风数据与基于FY-4A融合海温数据反演得到的TCHP数据做时空匹配,得到利奇马台风路径上的TCHP。然后在地统计学的基础上,引入全局自相关分析和局部自相关分析方法,对台风路径上的TCHP进行分析研究。结果表明:TCHP的全局Moran′s I值为0.94,即在相邻空间位置上具有高度的正空间自相关性;TCHP局部空间自相关特征主要以高-高,低-低这2种空间聚集形态为主,在局部空间上没有表现出异质性,具有较高的空间相关性;在利奇马台风发生及发展过程中,随空间位置的变化,TCHP属性值逐渐由低-低聚集类型向高-高聚集类型转变,对海-气交换产生负反馈影响,此时TCHP和台风移速在此变化过程中虽然波动较大,但是变化后维持在一定的范围内。台风强度也在变化之后增速也逐渐变缓,形成一个稳定状态。
Every year,many coastal areas of China are affected by typhoon in different degrees,which causes serious damage to life and property safety of people in many provinces and regions of China.TCHP is one of the main factors affecting typhoon.In this paper,the data of typhoon Lekima of 2019 was matched with the TCHP data obtained by FY-4A fusion SST data inversion to obtain the TCHP under the path of typhoon Lekima.Then,on the basis of geostatistics,global autocorrelation analysis and local autocorrelation analysis are introduced to analyze and study TCHP under the typhoon path.The results show that the global Moran′s I value of TCHP is 0.94,that is,there is a high degree of positive spatial autocorrelation in adjacent spatial positions.The local spatial autocorrelation characteristics of TCHP were mainly high-high and low-low spatial aggregation forms,and there was no heterogeneity in local space,which showed a high spatial correlation.During the occurrence and development of Lekima,the TCHP attribute values gradually changed from low-low aggregation type to high-high aggregation type with the change of spatial location,negative feedback effect on sea-air exchange,at the moment,TCHP and typhoon movement speed fluctuated greatly in this process,but remained within a certain range after the change,while typhoon intensity gradually slowed down after the change,forming a stable state.
作者
张月
谢涛
鄢俊洁
赵立
方贺
ZHANG Yue;XIE Tao;YAN Junjie;ZHAO Li;FANG He(School of Remote Sensing&Geomatics Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Beijing Huayun Star Earth Technology Co.,Ltd.,Beijing 100081,China;School of Marine Sciences,Nanjing University of Information Science and Technology,Nanjing 210044,China;Climate Center of Zhejiang Province,Hangzhou 310000,China)
出处
《自然灾害学报》
CSCD
北大核心
2023年第1期199-207,共9页
Journal of Natural Disasters
基金
国家自然科学基金项目(42176180)
国家重点研发计划项目(2018YFC1506404)
江苏省研究生科研实践创新计划项目(KYCX20_0930,KYCX20_0977)
风云卫星先行计划(FY-APP-2021.0105)
浙江省气象科技计划项目(2021YB07)。
