哈尔滨地区雷电日数的演变特征
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摘要
深入研究雷暴日数时空演变特征,对该区域灾害性天气的监测预测及防灾减灾具有应用价值。选用1981—2018年哈尔滨市13个台站逐年雷暴日数观测资料,采用EOF、小波分析等方法,研究雷暴日数时空变化规律。结果表明:哈尔滨市1981—2018年雷暴日数呈现显著减少趋势,倾向率为-0.31 d/10 a;雷暴日数周期变化不十分显著,存在28、4、9年主周期变化;雷暴日数的3个主要空间分布类型,主要为雷暴日数呈现"双曲抛物面"形状正向变化趋势,以双城—阿城—木兰和通河中部—依兰一线(西南—东北向)为轴,左抛物面,沿轴线向西南方向递增,右抛物面,沿轴线向东北方向递减,递增幅度大于递减幅度,均没形成闭合的低值区域,且等值线相对密集;可以为雷电灾害管理及预测预防提供参考依据。
The study of temporal and spatial evolution of lightning days has application value to the monitoring and prediction of disastrous weather and disaster prevention and mitigation. Based on the daily data of lightning days from 13 meteorological stations in Harbin from 1981 to 2018, the EOF and wavelet analysis were used to examine the temporal-spatial variation of lightning days in Harbin. The results showed that lightning days decreased significantly since 1981, which had a decreasing rate of-0.31 d/10 a. There were 3 periodic changes of scales in lightning days, which were 28 years, 4 years and 9 years, but non-significant cycle change. The spatial distribution of lightning days were mainly"hyperbolic paraboloid"shape and positive change trend, it was a line of the Shuangcheng—Acheng—Mulan and the middle of Tonghe—Yilan as the axis(southwest—northeast), the left paraboloid increased along the axis to the southwest, the right paraboloid decreased along the axis to the northeast, the range of left paraboloid was greater than the right paraboloid, and it was an unclosed low-value region with relatively dense contours. The study could provide references for lightning disaster management, prediction and prevention.
The study of temporal and spatial evolution of lightning days has application value to the monitoring and prediction of disastrous weather and disaster prevention and mitigation. Based on the daily data of lightning days from 13 meteorological stations in Harbin from 1981 to 2018, the EOF and wavelet analysis were used to examine the temporal-spatial variation of lightning days in Harbin. The results showed that lightning days decreased significantly since 1981, which had a decreasing rate of-0.31 d/10 a. There were 3 periodic changes of scales in lightning days, which were 28 years, 4 years and 9 years, but non-significant cycle change. The spatial distribution of lightning days were mainly"hyperbolic paraboloid"shape and positive change trend, it was a line of the Shuangcheng—Acheng—Mulan and the middle of Tonghe—Yilan as the axis(southwest—northeast), the left paraboloid increased along the axis to the southwest, the right paraboloid decreased along the axis to the northeast, the range of left paraboloid was greater than the right paraboloid, and it was an unclosed low-value region with relatively dense contours. The study could provide references for lightning disaster management, prediction and prevention.
引文
[1]曹久才,孙立德,潘成军.喀左县雷暴日数的变化特征及对策[J].农学学报,2015,5(10):113-117.
[2]姚蓉,许霖,唐佳,等.湖南省雷暴时空特征及变化趋势[J].气象与环境科学,2017,40(3):65-70.
[3]林永强,陈乙东,许荣华,等.莆田市年雷暴日时间序列的小波分析[J].气象科学,2016,28(3):22-24.
[4]孔峰,郭君,王一飞,等.近56年来中国雷暴日数的时空分异特征[J].灾害学,2018,33(3):87-95.
[5] Tippett M K, Allen J T, Gensini V A, et al. Climate and hazard-ous convective weather[J].Current Climate Change Reports,2015,1(2):60-73.
[6] Chen J, Zheng J, Feng W, et al. Statistical method of thunder-storm day[J].High Voltage Engineering,2006,32(11):115-118.
[7]刘江.1967—2012年长丰雷暴气候特征分析[J].防灾科技学院学报,2016,18(1):37-41.
[8]王学良,张科杰,黄小彦,等.湖北省雷暴日数与云地闪电密度关系研究[J].气象,2012,38(6):728-732.
[9]丁旻.贵州省雷暴日数的时空分布、周期及突变特征[J].防灾科技学院学报,2013,15(4):36-42.
[10]王一婧.1981—2010年辉县市雷暴日数变化特征及其对农业的影响分析[J].现代农业科技,2018(12):187-189.
[11]康晓燕,周万福,金惠瑛,等.1961—2013年青海省雷暴变化特征分析及趋势预测[J].中国农学通报,2016,32(5):144-151.
[12]程萌.近50年菏泽地区雷暴日数的气候分布特征[J].中国农学通报,2016,32(25):166-169.
[13]于东,赖三钭,陈丹,等.平果县城区雷暴日数变化特征分析[J].气象研究与应用,2015,36(3):107-109.
[14]尼玛央珍,央金,洛桑曲珍.近30年西藏地区雷暴日数的气候分布特征[J].高原山地气象研究,2014,34(3):36-40.
[15]赵德龙,曹兴,万瑜.近33年来乌鲁木齐地区雷暴时空变化特征及趋势预测分析[J].安徽农业科学,2017,45(20):165-168.
[16]中国气象局.地面气象观测规范[M].北京:气象出版社,2005.
[17]巩崇水,曾淑玲,王嘉缘,等.近30年中国雷暴天气气候特征分析[J].高原气象,2013,32(5):1442-1449.
[18]余蓉,张小玲,李国平,等.1971—2000年我国东部地区雷暴、冰雹、雷暴大风发生频率的变化[J].气象,2012,38(10):1207-1216.
[19]孙丽,于淑琴,李岚.辽宁省雷暴日数的时空变化特征[J].气象与环境学报,2010,26(1):59-62.
[20]尹恒,杨占婷,任玮颖,等.基于小波变换和M-K检验的灰霾长期变化研究[J].科学技术与工程,2012,12(36):9810-9814.
[21]麦柳霞,郭亮.防城30年雷暴日数变化特征及相关因子[J].气象研究与应用,2013,32(2):60-64.
[2]姚蓉,许霖,唐佳,等.湖南省雷暴时空特征及变化趋势[J].气象与环境科学,2017,40(3):65-70.
[3]林永强,陈乙东,许荣华,等.莆田市年雷暴日时间序列的小波分析[J].气象科学,2016,28(3):22-24.
[4]孔峰,郭君,王一飞,等.近56年来中国雷暴日数的时空分异特征[J].灾害学,2018,33(3):87-95.
[5] Tippett M K, Allen J T, Gensini V A, et al. Climate and hazard-ous convective weather[J].Current Climate Change Reports,2015,1(2):60-73.
[6] Chen J, Zheng J, Feng W, et al. Statistical method of thunder-storm day[J].High Voltage Engineering,2006,32(11):115-118.
[7]刘江.1967—2012年长丰雷暴气候特征分析[J].防灾科技学院学报,2016,18(1):37-41.
[8]王学良,张科杰,黄小彦,等.湖北省雷暴日数与云地闪电密度关系研究[J].气象,2012,38(6):728-732.
[9]丁旻.贵州省雷暴日数的时空分布、周期及突变特征[J].防灾科技学院学报,2013,15(4):36-42.
[10]王一婧.1981—2010年辉县市雷暴日数变化特征及其对农业的影响分析[J].现代农业科技,2018(12):187-189.
[11]康晓燕,周万福,金惠瑛,等.1961—2013年青海省雷暴变化特征分析及趋势预测[J].中国农学通报,2016,32(5):144-151.
[12]程萌.近50年菏泽地区雷暴日数的气候分布特征[J].中国农学通报,2016,32(25):166-169.
[13]于东,赖三钭,陈丹,等.平果县城区雷暴日数变化特征分析[J].气象研究与应用,2015,36(3):107-109.
[14]尼玛央珍,央金,洛桑曲珍.近30年西藏地区雷暴日数的气候分布特征[J].高原山地气象研究,2014,34(3):36-40.
[15]赵德龙,曹兴,万瑜.近33年来乌鲁木齐地区雷暴时空变化特征及趋势预测分析[J].安徽农业科学,2017,45(20):165-168.
[16]中国气象局.地面气象观测规范[M].北京:气象出版社,2005.
[17]巩崇水,曾淑玲,王嘉缘,等.近30年中国雷暴天气气候特征分析[J].高原气象,2013,32(5):1442-1449.
[18]余蓉,张小玲,李国平,等.1971—2000年我国东部地区雷暴、冰雹、雷暴大风发生频率的变化[J].气象,2012,38(10):1207-1216.
[19]孙丽,于淑琴,李岚.辽宁省雷暴日数的时空变化特征[J].气象与环境学报,2010,26(1):59-62.
[20]尹恒,杨占婷,任玮颖,等.基于小波变换和M-K检验的灰霾长期变化研究[J].科学技术与工程,2012,12(36):9810-9814.
[21]麦柳霞,郭亮.防城30年雷暴日数变化特征及相关因子[J].气象研究与应用,2013,32(2):60-64.
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