FAILED
首站-论文投稿智能助手
典型文献
Climatology of Shear Line and Related Rainstorm over the Southern Yangtze River Valley Based on an Improved Intelligent Identification Method
文献摘要:
Based on four reanalysis datasets including CMA-RA, ERA5, ERA-Interim, and FNL, this paper proposes an improved intelligent method for shear line identification by introducing a second-order zonal-wind shear. Climatic characteristics of shear lines and related rainstorms over the Southern Yangtze River Valley (SYRV) during the summers (June-August) from 2008 to 2018 are then analyzed by using two types of unsupervised machine learning algorithm, namely the t-distributed stochastic neighbor embedding method (t-SNE) and the k-means clustering method. The results are as follows:(1) The reproducibility of the 850 hPa wind fields over the SYRV using China's reanalysis product CMA-RA is superior to that of European and American products including ERA5, ERA-Interim, and FNL. (2) Theory and observations indicate that the introduction of a second-order zonal-wind shear criterion can effectively eliminate the continuous cyclonic curvature of the wind field and identify shear lines with significant discontinuities. (3) The occurrence frequency of shear lines appearing in the daytime and nighttime is almost equal, but the intensity and the accompanying rainstorm have a clear diurnal variation: they are significantly stronger during daytime than those at nighttime. (4) Half (47%) of the shear lines can cause short-duration rainstorms (≥20 mm (3h)-1), and shear line rainstorms account for one-sixth (16%) of the total summer short-duration rainstorms. Rainstorms caused by shear lines are significantly stronger than that caused by other synoptic forcing. (5) Under the influence of stronger water vapor transport and barotropic instability, shear lines and related rainstorms in the north and middle of the SYRV are stronger than those in the south.
文献关键词:
作者姓名:
LIU Jin-qing;CHEN He;XU Jing-yu
作者机构:
Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of RegionalNumerical Weather Prediction,CMA,Guangzhou 510641 China;Hunan Meteorological Observatory/Hunan Key Laboratory of Meteorological Disaster Prevention and Reduction,Changsha 410118 China;Heavy Rain andDrought Flood Disasters in Plateau and Basin Key Laboratory of Sichuan,Chengdu 610072 China
引用格式:
[1]LIU Jin-qing;CHEN He;XU Jing-yu-.Climatology of Shear Line and Related Rainstorm over the Southern Yangtze River Valley Based on an Improved Intelligent Identification Method)[J].热带气象学报(英文版),2022(04):413-424
A类:
Rainstorm,SYRV,Rainstorms
B类:
Climatology,Shear,Line,Related,over,Southern,Yangtze,River,Valley,Based,Improved,Intelligent,Identification,Method,four,reanalysis,datasets,including,CMA,ERA5,Interim,FNL,this,paper,proposes,improved,intelligent,method,shear,identification,by,introducing,second,order,zonal,wind,Climatic,characteristics,lines,related,rainstorms,during,summers,June,August,from,are,then,analyzed,using,two,types,unsupervised,machine,learning,algorithm,namely,distributed,stochastic,neighbor,embedding,SNE,means,clustering,results,follows,reproducibility,hPa,fields,China,superior,that,European,American,products,Theory,observations,indicate,introduction,criterion,effectively,eliminate,continuous,cyclonic,curvature,identify,discontinuities,occurrence,frequency,appearing,daytime,nighttime,almost,equal,intensity,accompanying,have,clear,diurnal,variation,they,significantly,stronger,than,those,Half,short,duration,3h,account,one,sixth,total,caused,other,synoptic,forcing,Under,influence,water,vapor,transport,barotropic,instability,north,middle,south
AB值:
0.528332
相似文献
Three-Dimensional Wind Field Retrieved from Dual-Doppler Radar Based on a Variational Method: Refinement ofVertical Velocity Estimates
Chenbin XUE;Zhiying DING;Xinyong SHEN;Xian CHEN-Key Laboratory of Meteorological Disaster,Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangxi Meteorological Observatory,Nanchang 330096,China;Guangdong Province Key Laboratory of Regional Numerical Weather Prediction,Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510080,China;Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China;Jiangxi Institute of Land and Space Survey and Planning/Jiangxi Geomatics Center,Nanchang 330000,China
Detection and Attribution of Changes in Thermal Discomfort over China during 1961?2014 and Future Projections
Wanling LI;Xin HAO;Li WANG;Yuqing LI;Jiandong LI;Huixin LI;Tingting HAN-Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster,Ministry of Education,Nanjing University of Information Science and Technology,Nanjing 210044,China;Nansen-Zhu International Research Center,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,School of Environmental Science and Engineering,Nanjing University of Information Science& Technology,Nanjing 210044,China
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。