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气象:2020,46(2):200-211
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基于加密自动气象观测站和国家气象观测站的山东省极端短时强降水时空分布特征的对比分析
侯淑梅,孙敬文,孙鹏程,谷山青,邱粲,刘程
(山东省气象台,济南 250031;南京信息工程大学,南京 210044; 中南财经政法大学,武汉 430073; 山东省海阳市气象局,海阳 265100; 山东省滨州市气象局,滨州 256612; 上海师范大学地理系,上海 200234; 山东省气候中心,济南 250031)
Comparative Analysis of Spatio Temporal Distribution Characteristics of Extreme Short Time Severe Precipitation in Shandong Based on the Dense Observations from Automatic Weather Stations and National Stations
HOU Shumei,SUN Jingwen,SUN Pengcheng,GU Shanqing,QIU Can,LIU Cheng
(Shandong Meteorological Observatory, Jinan 250031;Nanjing University of Information Science and Technology, Nanjing 210044; Zhongnan University of Economics and Law, Wuhan 430073; Haiyang Meteorological Office of Shandong Province, Haiyang 265100; Binzhou Meteorological Office of Shandong Province, Binzhou 256612; Department of Geography, Shanghai Normal University, Shanghai 200234; Shandong Climate Center, Jinan 250031)
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投稿时间:2018-09-14    修订日期:2019-12-02
中文摘要: 利用2008—2017年4—10月山东省加密自动气象观测站(简称全部站)和国家气象观测站(简称国家站)逐小时1 mm 以上降水量资料,通过对比分析,探究不同分辨率数据对极端短时强降水时空分布特征的刻画效果。结果表明如下:全部站小时降水量的偏态特征比国家站明显,若分析小时降水量的平均状态,两者均具有代表性,若分析短时强降水的极端性,全部站数据更具有优越性。将各站第99.5%分位数作为极端短时强降水的阈值最合理,全部站和国家站对于30~45 mm阈值的空间分布特征相似,45 mm以上的阈值,全部站的数值和范围均大于国家站。山东省大部地区的极端短时强降水强度集中在40~60 mm·h-1,〖JP2〗全部站和国家站在此区间的空间分布特征相似。国家站数据不能刻画40 mm·h-1以下和60 mm·h-1〖JP〗以上的极端短时强降水的空间分布特征。极端短时强降水强度的空间分布特征与地理位置及地形特征密切相关。鲁东南地区的极端短时强降水强度、日最大降水量及夏季降水量、年降水量均居山东省之首,鲁西北地区虽然强降水频次高、强度大,但与年降水量和夏季降水量没有正相关关系。全部站与国家站极端短时强降水频次的月变化和日变化特征一致,但国家站不能完全代表山东省极端短时强降水强度的月变化和日变化平均状况,全部站数据能更准确地反映山东省的时间变化特征。
Abstract:Using the densely observed hourly precipitation (>1 mm) data of the automatic weather stations (referred to as the all stations) and the national meteorological stations (referred to as the national stations) in Shandong Province from April to October 2008-2017, this paper compares the characteristics of spatio temporal distribution of extreme short time severe precipitation with different resolution data. The results are as follows. The skewed characteristics of hourly precipitation at all stations are more obvious than those of the national stations. For the average state of hourly precipitation, both are representative. However, for the analysis of the extremes of short time severe rainfall, the all stations data are more advantageous. It is most reasonable to use the 99.5th percentile of each station as the threshold for extreme short time severe precipitation. The spatial distribution characteristics of the 30-45 mm threshold are similar for all stations and national stations. For thresholds above 45 mm, the values and ranges of all stations are both greater than those of the national stations. The extreme short time severe precipitation intensity in most parts of the province is concentrated at 40-60 mm·h-1, and the spatial distribution characteristics of all stations and national stations in this interval are similar. National station data can not reflect the spatial distribution of extreme short time severe precipitation with intensity below 40 mm·h-1 and above 60 mm·h-1. The spatial distribution characteristics of extreme short time severe precipitation intensity are closely related to geographical location and topographical features. The extreme short time precipitation intensity, daily maximum precipitation, summer precipitation and annual precipitation in the southeastern Shandong Province rank first in the province. Although the frequency and intensity of severe precipitation are high in northwestern Shandong, they have no positive correlations with annual precipita tion and summer precipitation. The monthly and diurnal variations of the extreme short time severe precipitation frequency of all stations are consistent with those of the national stations. However, the national station data can not fully represent the monthly and diurnal variations of the extreme short time severe precipitation intensity in the province. The data of all stations can more accurately reflect the time variation features of precipitation in the province.
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基金项目:山东省自然科学基金项目(ZR2016DM20)、中国气象局预报员专项(CMAYBY2018 041)及山东省气象局课题(2016sdqxz01和2014sdqxm21)共同资助
引用文本:
侯淑梅,孙敬文,孙鹏程,谷山青,邱粲,刘程,2020.基于加密自动气象观测站和国家气象观测站的山东省极端短时强降水时空分布特征的对比分析[J].气象,46(2):200-211.
HOU Shumei,SUN Jingwen,SUN Pengcheng,GU Shanqing,QIU Can,LIU Cheng,2020.Comparative Analysis of Spatio Temporal Distribution Characteristics of Extreme Short Time Severe Precipitation in Shandong Based on the Dense Observations from Automatic Weather Stations and National Stations[J].Meteor Mon,46(2):200-211.