检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:陆忠艳[1] 袁子鹏[1] 蔡福[2] 吴曼丽[1] 刘文明[1]
机构地区:[1]沈阳中心气象台 [2]中国气象局沈阳大气环境研究所,沈阳110016
出 处:《气象科技》2008年第4期389-395,共7页Meteorological Science and Technology
基 金:辽宁省气象局农村防灾减灾课题资助
摘 要:针对开展乡镇天气预报对高精度逐日气象要素输入值的需 求,以辽宁地区为例,选用克立格法(Kriging)、距离权重反比法(IDW)、带高度梯度订正的距离权重反比法(GIDW)及样条函数法(Spline)4种插值方法,进行有限气象站点1~12月逐日气象要素空间插值方法研究并对估值进行检验。结果表明:对温度而言,GIDW方法估值精度较高,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估值精度高于其他插值方法,更适合于日降水量的空间插值。Aiming at the needs for high-resolution daily weather data, taking Liaoning Province as an example, the spatial interpolation methods of daily weather data from January to December are studied using the ordinary Kriging, Inverse Distance Weighting (IDW), the IDW with weighting of Gradient Inverse Distance Weighting (GIDW), and spline function methods. The statistic analysis for interpolated values and estimated values are made. The results indicate that for temperature, the precision of the estimated values is the highest, and the space-distributing trend of the interpolated result is the closest to the actual data byusing GIDW method. For precipitation, the precision of the estimated values with the IDW method is higher than those with the other methods, which is more fit for the interpolation of daily precipitation.
分 类 号:P426.613[天文地球—大气科学及气象学] S151.95[农业科学—土壤学]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.66