摘要
基于湘潭市1985—2004年逐日气温和降水资料，统计分析了湘潭市夏季（5—9月）极端气候事件的变化趋势。结果表明湘潭市的夏季日最高温≥35℃日数呈上升趋势，但达不到90％的信度水平；夏季暴雨（日降水量≥50mm）出现的频次呈增加趋势（＋0．25d／5a），信度水平为90％；夏季干旱事件的频次呈下降趋势（-0．8d/5a）。信度水平为90％。马尔克夫预测显示：湘潭市2005—2009年间夏季中间状态（E2）的极端高温、极端降水和严重干旱事件发生的概率相对较大，一般大于40％；极端气候事件的极端状态（E1）以大暴雨发生的概率相对较高。各年概率值接近40％，2005年降大暴雨的概率在70％以上；严重干旱事件的极端状态（E1）发生的概率相对较低，基本上没超过14％，但严重干旱事件的轻微状态（E3）发生的概率为40％左右。
On the basis of the statistics of the meteorological data day by day in summer（5 -9）from 1985 to 2004 in Xiangtan, extremely high temperature incident （daily maximum temperature more than 35% ）, rainstorm （daily total precipitation more than 50mm） and extreme drought incident （ continuous days without precipitation） are analyzed. The result are as follows ; The annual number of days when extremely high temperature incidents occur shows a linear increase trend as a whole, but it has not yet passed the test of reliability from the 3-year-sliding average values three periods can be differentiated during the periods of 1985 - 1990 and 1995 -2004 the frequency of extremely high temperature incident increased, and during the period of 1991 - 1995 it slowly declined. The frequency of summer rainstorm incident shows an increasing trend with a rate of ＋ 0.25d/5a, while those of summer drought incident presents an evident falling trend with a rate of - 0.8d/5a, and their reliabilities are both 90%. However, the increase of frequency of summer rainstorm incident does not certainly correspond to the decrease of frequency of summer drought incident. According to their frequencies and severity, summer extreme climate incidents can be divided into three grades of state： the extreme state （E1）, the medium state （E2） and the gentle state （E3）. Form Markov method, it is predicted that the occurrence probability of summer extreme climate incidents in E2 is relatively high （ usually more than 40% ） ; that of summer rainstorm in E1 is about 40% ; and that of summer drought incidents is about 14% in E1 and 40% in E3.
出处
《热带地理》
2006年第1期29-34,共6页
Tropical Geography
基金
国家自然科学基金资助项目(40371027)
湖南省自然科学基金项目(04JJ30046)资助
