秦皇岛寒潮过程的时空特征及成因分析

Analysis on the Spatial-temporal Characteristics and Causes of Cold Wave in Qinhuangdao

[目的]研究秦皇岛地区寒潮的时空分布及成因。[方法]基于1970～2009年秦皇岛地区5个地面气象站的气温资料以及最新的寒潮预警信号的发布标准,对发生在该地区的寒潮天气过程进行统计,分析其区域分布特征和长期变化特征,并对其原因也进行了初步探讨。[结果]1970～2009年秦皇岛地区共计出现蓝色寒潮2334站次,黄色寒潮105站次,出现寒潮最多的地区是青龙县,最少是卢龙县;主要是因受下垫面、纬度和海拔高度等因素的影响。寒潮发生的月份从当年的9月一直到次年5月均有可能发生,寒潮最早开始为9月9日,最晚结束为5月26日。出现寒潮最多的月份是1月,最少的月份是5月。达到寒潮蓝色预警标准的寒潮出现最多的年份是1972和1979年,出现最少的年份是1984年;黄色预警标准的寒潮出现最多的年份是1979年,出现最少的年份有9年;从年代际来看,寒潮出现最多的是70年代,最少的是90年代。随着气候变暖,寒潮总次数趋于减少,寒潮开始期趋于推后,而寒潮结束期提前,说明气候变暖是寒潮发生变化的主要气候背景。[结论]该研究为气象防灾减灾和地方农业服务提供一定指导。

[ Objective ] The aim was to study the spatial-temporal characteristics and causes of cold wave in Qinhuangdao. [ Method ] Based on temperature data from five surface meteorological stations in Qinhuangdao from 1970 to 2009 and the latest standard of releasing cold wave early warning signal, statistical analysis on the regional distribution and secular variation of cold wave was carried out, and its causes were dis- cussed preliminarily. [ Result] In Qinhuangdao from 1970 to 2009, the frequencies of blue and yellow cold wave were 2 334 and 105 times, respectively, and cold wave occurred most frequently in Qinglong County and least frequently in Lulong County, which was related to the effects of underlying surface, latitude and altitude. Cold wave might happen from September to next May, and the earliest occurrence date was September 9th , while the latest end date was May 26＇h. In a year, the frequency of cold wave was the highest in January and lowest in May. From 1970 to 2009, blue cold wave occurred most frequently in 1972 and 1979 and least frequently in 1984, while the frequency of yellow cold wave was the highest in 1979 and lowest in 9 years. From decadal variation, cold wave appeared most frequently in 1970s and least frequently in 1990s. With the increase of temperature, the frequency of cold wave showed decrease trend, and the beginning date tended to postpone, while its end date advanced, and it showed that the changes of cold wave was mainly caused by climate warming. [ Conclusion ] The study could provide theoretical guidance for the meteorological disaster prevention and reduction and local agricultural service.