{"title":"用多普勒天气雷达资料识别大风天气","authors":"Jinliang Zhou, M. Wei, Tao Wu, Nan Li","doi":"10.1109/RSETE.2011.5965731","DOIUrl":null,"url":null,"abstract":"With high temporal and spatial resolution, Doppler weather radars are important means for revealing structures and revolution of meso-micro scale weather processes. This article uses reflectivity characteristics to identify convective gale weather. 6 promising identification parameters are proposed (CR, VIL, DVIL, SWP, DCRH and SPEED), and an automated identification algorithm for convective gale is established based on fuzzy logic principles. 6 typical cases are used to obtain probability distribution characters based on the statistics of volume scan data, and then it is determined that CR, VIL, DVIL and SWP that have more concentrated probability densities are used as the input variables of the fuzzy logic technique for the identification of the convective gale. According to the statistics, these parameters can effectively identify convective gale. The algorithm identifies 150 from 174 gale wind events in 6 weather processes, with a POD probability 86.21%.","PeriodicalId":6296,"journal":{"name":"2011 International Conference on Remote Sensing, Environment and Transportation Engineering","volume":"27 1","pages":"6033-6036"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of gale weather with doppler weather radar data\",\"authors\":\"Jinliang Zhou, M. Wei, Tao Wu, Nan Li\",\"doi\":\"10.1109/RSETE.2011.5965731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With high temporal and spatial resolution, Doppler weather radars are important means for revealing structures and revolution of meso-micro scale weather processes. This article uses reflectivity characteristics to identify convective gale weather. 6 promising identification parameters are proposed (CR, VIL, DVIL, SWP, DCRH and SPEED), and an automated identification algorithm for convective gale is established based on fuzzy logic principles. 6 typical cases are used to obtain probability distribution characters based on the statistics of volume scan data, and then it is determined that CR, VIL, DVIL and SWP that have more concentrated probability densities are used as the input variables of the fuzzy logic technique for the identification of the convective gale. According to the statistics, these parameters can effectively identify convective gale. The algorithm identifies 150 from 174 gale wind events in 6 weather processes, with a POD probability 86.21%.\",\"PeriodicalId\":6296,\"journal\":{\"name\":\"2011 International Conference on Remote Sensing, Environment and Transportation Engineering\",\"volume\":\"27 1\",\"pages\":\"6033-6036\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Remote Sensing, Environment and Transportation Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RSETE.2011.5965731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Remote Sensing, Environment and Transportation Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RSETE.2011.5965731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of gale weather with doppler weather radar data
With high temporal and spatial resolution, Doppler weather radars are important means for revealing structures and revolution of meso-micro scale weather processes. This article uses reflectivity characteristics to identify convective gale weather. 6 promising identification parameters are proposed (CR, VIL, DVIL, SWP, DCRH and SPEED), and an automated identification algorithm for convective gale is established based on fuzzy logic principles. 6 typical cases are used to obtain probability distribution characters based on the statistics of volume scan data, and then it is determined that CR, VIL, DVIL and SWP that have more concentrated probability densities are used as the input variables of the fuzzy logic technique for the identification of the convective gale. According to the statistics, these parameters can effectively identify convective gale. The algorithm identifies 150 from 174 gale wind events in 6 weather processes, with a POD probability 86.21%.