期刊文献+

东北地区逐日气象要素的空间插值方法应用研究 预览 被引量:113

SPATIAL INTERPOLATION METHODS OF DAILY WEATHER DATA IN NORTHEAST CHINA
在线阅读 下载PDF
收藏 分享 导出
摘要 针对作物生长动力模型区域应用时对高精度格点逐日气象要素输入值的需要,以东北地区为例,选用克立格法(Kriging)、以经纬度分布方向为权重的距离权重反比法(IDW)及带高度梯度订正的距离权重反比法(GIDW)3种插值方法进行有限气象站点4~10月逐日气象要素空间插值方法研究,并进行插值的统计量分析和估值的交叉验证.结果表明,对温度而言,GIDW方法估值精度较高,插值结果的平滑程度适中,插值结果分布趋势也较为接近实际站点的分布.对降水而言,IDW估值精度高于Kriging,而且插值结果的平滑程度较小,更适合于日降水量的空间插值.GIDW、IDW估值精度较高的原因是研究中考虑到日最高温度、最低温度和降水量的经向、纬向梯度、海拔高度梯度存在明显的季节性变化,采用了根据气象要素经纬度方向确定权重,以及根据气象要素高度梯度年内变化进行高度订正的结果. Aimed at requirement for daily weather data with high resolution which is used to scaling up the crop growth simulation models, the spatial interpolation methods of daily weather data from April to October in Northeast China are studied using ordinary Kriging and other two relatively simple methods: inverse distance weighting (IDW) technique with weighting of longitude and latitude, and gradient of height plus inverse distance weighting (GIDW) technique. The statistics analysis for interpolated values and cross verification for estimated values are made. The results indicate that for temperature, the precision of the evaluated value is the highest, and the smoothness is moderate, in addition, the space distributing trend of the interpolated result is more close to the actual data using GIDW method. For precipitation, the precision of the evaluated value with IDW method is higher than that with the Kriging method, and the smooth level of the interpolated result is smaller, and it is more fit to the interpolation of the daily precipitation. The cause of the higher precision of the evaluated values with GIDW and IDW methods is that the obvious season changes in longitude, latitude and sea level elevation gradient of the daily maximum temperature, minimum temperature and precipitation are considered, the weights in longitude and latitude for meteorological factors are determined, and the meteorological factors are also corrected by daily sea level elevation gradient.
作者 庄立伟 王石立 Zhuang Liwei Wang Shili (Chinese Academy of Meteorological Sciences, Beijing 100081)
出处 《应用气象学报》 CSCD 北大核心 2003年第5期 605-615,共11页 Quarterly Journal of Applied Meteorology
基金 科技部攻关项目,科技部社会公益研究项目
关键词 东北地区 气象要素 空间插值方法 数值天气预报 Northeast China Daily weather data Interpolation Kriging IDW GIDW
  • 相关文献

参考文献8

二级参考文献108

共引文献694

同被引文献1619

引证文献113

二级引证文献1208

投稿分析
职称考试

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部 意见反馈