中国农业气象

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武威市霜冻气候特征及预报

杨晓玲;郭丽梅;丁文魁;   

  1. 中国气象局兰州干旱气象研究所/甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点开放实验室;甘肃省武威市气象局;
  • 出版日期:2010-08-10 发布日期:2010-08-10
  • 基金资助:
    甘肃省气象局重点项目“甘肃省河西酿造作物精细化服务平台建设”(2010-11)

Climate Characteristics of Frost and Its Forecast in Wuwei City

YANG Xiao-ling1,2,GUO Li-mei2,DING Wen-kui2(1.Lanzhou Institute of Arid Meteorology,China Meteorological Administration/Key Laboratory of Arid Climatic Changing and ReducingDisaster of Gansu Province/Key Laboratory of Arid Climatic Changing and Reducing Disaster,CMA,Lanzhou 730020,China;2.Wuwei Meteorological Bureau,Wuwei 733000)   

  • Online:2010-08-10 Published:2010-08-10

摘要: 利用武威市1960-2009年4个气象站霜冻(最低地温≤0℃)资料,系统分析了该区霜冻的时空分布、强度和持续性等气候特征。结果表明,武威市霜冻天气主要发生在北部山区和沙漠边缘;年、年代霜冻日数总体呈减少趋势,霜冻主要发生在5月上、中旬和9月下旬;各种强度霜冻日数的变率较大,随着霜冻强度的增强,霜冻日数逐渐减少;霜冻天气具有持续性特征,持续2d以上的霜冻次数占总次数的56.4%~65.1%,强霜冻日大多出现在持续霜冻时段内。运用2003-2007年的5月和9月逐日20时ECMWF数值预报格点场资料,采用Press准则进行预报因子初选,逐步回归预报方法进行预报因子精选,使用最优子集回归建立最低地温预报方程,采用CSC双评分准则确定5月、9月各站最低地温预报全局最优的显著性方程。预报方程通过了0.01水平的显著性检验,回代拟合率为56.7%~66.7%,预报准确率为51.8%~60.0%,达到了一定的预报水平,可为当地霜冻预报服务。采用最大靠近原则确定了霜冻预报临界值和霜冻预报、预警的级别。

关键词: 霜冻, 气候特征, ECMWF, 数值预报

Abstract: Based on frost data(the lowest ground temperature ≤0℃) of four meteorological stations in Wuwei city from 1960 to 2009,the climate characteristics,including temporal and spatial distribution,intensity,and sustainability were analyzed.The result showed that frost mainly occurred in the north mountainous area and edge of the desert.Annual and decadal frost days decreased.Frost mainly occurred in early and mid of May and the later of September.Frost days decreased gradually along with the frost intensity's enhancement.Frost more than 2 days occupied 56.4%~65.1%.By using ECMWF numerical forecast grid field of May and September from 2003 to 2007,the lowest ground temperature forecast equation was established with optimal subset regression.The prognostic equations was significant(α=0.01),its back substitution fitting rate was 56.7%~66.7%;forecast accuracy rate was 51.8%~60.0%,which had achieved certain forecast level.

Key words: Frost, Frost, Climate characteristic, ECMWF, Numerical forecast