Hisato Iwashita, Toshiaki Morita, Koji Shibata, F. Kobayashi
{"title":"高密度地面观测网阵风预报","authors":"Hisato Iwashita, Toshiaki Morita, Koji Shibata, F. Kobayashi","doi":"10.1541/jae.38.53","DOIUrl":null,"url":null,"abstract":". POTEKA (POint TEnki KAnsoku in Japanese) compact weather stations can observe seven meteorological variables, including temperature and pressure. In Gunma and Saitama prefectures, Japan, about 150 POTEKAs have been installed to create a high density ground surface observation network which has a resolution of approximately 2 km. This observation network has observed multiple downburst and damaging wind events, and has revealed the characteristics of downbursts, such as changes in the meteorological variables and phenomena proceeding these events (Iwashita et al. 2019). By analyzing the downburst event on Jun 15, 2015, which was the most damaging event observed by the network, we have succeeded in developing a downburst gust prediction system that utilizes the high density ground surface observation data. The high density ground surface observation network can be used to predict the occurrence of a downburst event several minutes in advance using temperature and pressure data. The cumulonimbus forward velocity can be calculated from the distance and time between the locations of temperature drops. Areas with a high probability of gust occurrence can be estimated based on the magnitude of the temperature drop. Thus, it may be possible to predict the occurrence times and locations of downburst gust events by utilizing high-resolution observations of the temperature and pressure.","PeriodicalId":274637,"journal":{"name":"Journal of atmospheric electricity","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gust prediction by a high density ground surface observation network (POTEKA)\",\"authors\":\"Hisato Iwashita, Toshiaki Morita, Koji Shibata, F. Kobayashi\",\"doi\":\"10.1541/jae.38.53\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". POTEKA (POint TEnki KAnsoku in Japanese) compact weather stations can observe seven meteorological variables, including temperature and pressure. In Gunma and Saitama prefectures, Japan, about 150 POTEKAs have been installed to create a high density ground surface observation network which has a resolution of approximately 2 km. This observation network has observed multiple downburst and damaging wind events, and has revealed the characteristics of downbursts, such as changes in the meteorological variables and phenomena proceeding these events (Iwashita et al. 2019). By analyzing the downburst event on Jun 15, 2015, which was the most damaging event observed by the network, we have succeeded in developing a downburst gust prediction system that utilizes the high density ground surface observation data. The high density ground surface observation network can be used to predict the occurrence of a downburst event several minutes in advance using temperature and pressure data. The cumulonimbus forward velocity can be calculated from the distance and time between the locations of temperature drops. Areas with a high probability of gust occurrence can be estimated based on the magnitude of the temperature drop. Thus, it may be possible to predict the occurrence times and locations of downburst gust events by utilizing high-resolution observations of the temperature and pressure.\",\"PeriodicalId\":274637,\"journal\":{\"name\":\"Journal of atmospheric electricity\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of atmospheric electricity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1541/jae.38.53\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of atmospheric electricity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1541/jae.38.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
. POTEKA (POint TEnki KAnsoku)是小型气象站,可以观测温度和压力等7种气象变量。在日本群马县和埼玉县,大约安装了150个poteka,以建立一个分辨率约为2公里的高密度地面观测网。该观测网络观测了多次降暴和破坏性风事件,并揭示了降暴的特征,如气象变量的变化和发生这些事件的现象(Iwashita et al. 2019)。通过对2015年6月15日网络观测到的破坏性最大的降暴事件的分析,成功开发了利用高密度地面观测资料的降暴阵风预报系统。高密度地面观测网可以利用温度和压力数据提前几分钟预测下爆事件的发生。积雨云的前进速度可以通过温度下降点之间的距离和时间来计算。根据气温下降的幅度,可以估计出阵风发生的高概率地区。因此,利用高分辨率的温度和压力观测,有可能预测下突阵风事件的发生时间和地点。
Gust prediction by a high density ground surface observation network (POTEKA)
. POTEKA (POint TEnki KAnsoku in Japanese) compact weather stations can observe seven meteorological variables, including temperature and pressure. In Gunma and Saitama prefectures, Japan, about 150 POTEKAs have been installed to create a high density ground surface observation network which has a resolution of approximately 2 km. This observation network has observed multiple downburst and damaging wind events, and has revealed the characteristics of downbursts, such as changes in the meteorological variables and phenomena proceeding these events (Iwashita et al. 2019). By analyzing the downburst event on Jun 15, 2015, which was the most damaging event observed by the network, we have succeeded in developing a downburst gust prediction system that utilizes the high density ground surface observation data. The high density ground surface observation network can be used to predict the occurrence of a downburst event several minutes in advance using temperature and pressure data. The cumulonimbus forward velocity can be calculated from the distance and time between the locations of temperature drops. Areas with a high probability of gust occurrence can be estimated based on the magnitude of the temperature drop. Thus, it may be possible to predict the occurrence times and locations of downburst gust events by utilizing high-resolution observations of the temperature and pressure.