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| 基于地统计方法的气候要素空间插值研究 | |
| 引用本文： | 岳文泽,徐建华,徐丽华.基于地统计方法的气候要素空间插值研究[J].高原气象,2005,24(6):974-980. |
| 作者姓名： | 岳文泽 徐建华 徐丽华 |
| 作者单位： | 1. 浙江大学,东南土地管理学院,浙江,杭州,310029 2. 华东师范大学,地理系,上海,200062 3. 浙江林学院,浙江,临安,311300 |
| 基金项目： | 国家自然科学基金项目（40371092）资助 |
| 摘 要： | 在回顾了地统计学的产生、发展及其基本原理的基础上，对于目前众多可以提供计算网格的气候要素的空间插值方法中，具体探讨了普通克里格法和协同克里格法。将甘肃省1961—1990年30年平均降水量和蒸发量作为区域化变量，根据不同的半变异函数理论模型，采用普通克里格法和双变量协同克里格法，通过对比分析得到：（1）不论是多年均降水量还是多年平均蒸发量在空间上都呈现明显的梯度变化，二者的空间变程都很大，而降水量变化幅度更大。降水量从东南部向西北部逐渐减少，蒸发量则相反，从东南向西北逐渐增加。（2）基于地统计的插值方法，根据半变异函数云图和试验方差最小的原理，选择合适的半变异函数理论模型进行变量的空间插值，能够较好地模拟区域化变量的空间连续分布格局，并取得较好的效果。对比普通克里格法和协同克里格法，后者增加了高度对降水量和蒸发量的影响，在空间分布上更为合理，插值的精度也要明显好于普通克里格法。（3）采用地统计方法虽然在总体上能够较好地反映气候要素的空间分布格局，但检验显示，两种方法空间插值的精度都还不是很高，插值的精度还有待进一步提高。 |
| 关 键 词： | 地统计学 变量 空间插值 普通克里格法 协同克里格法 多年平均降雨量 年平均蒸发量 |
| 文章编号： | 1000-0534（2005）06-0974-07 |
| 收稿时间： | 2004-04-28 |
| 修稿时间： | 2004-04-282004-07-30 |
A Study on Spatial Interpolation Methods for Climate Variables Based on Geostatistics |
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| YUE Wen-ze,XU Jian-hua,XU Li-hua.A Study on Spatial Interpolation Methods for Climate Variables Based on Geostatistics[J].Plateau Meteorology,2005,24(6):974-980. | |
| Authors: | YUE Wen-ze XU Jian-hua XU Li-hua |
| Abstract: | Based on reviewing the origin,development and basic principles of Geostatistics,two kinds of interpolationmethods concretely ordinary Kriging and Cokriging are discussed.As no single method among so many available ones to spatial interpolation of climate variables is optimalfor all regions and all variables,the interpolationmethods are discussed based on Geostatistics by using annual average precipitation and evaporationin Gansu province from 1961 to 1990.Based on different semivariogram theory models we adopt ordinary Kriging and BivariateCokriging,by comparing of them the obtained conclusions are as follows: (1) No mattermulti-year average precipitation or evaporation all presentedobvious gradient change on space,the change ranges of both weregreat,the former was larger than the latter.Multi-year Annual average precipitationdecreasedgradually from southeast to northwestward,but evaporationwasopposite,increasedgradually from southeast to northwest.(2) According to semivariogram cloud plotsand experiment variance minimum principle selectedsuitable semivariogram theory modelsbased on Geostatistics interpolation methodtointerpolate,which could simulatespace pattern spreadingcontinuously of regionalized variable well,then get better interpolation effect.Comparing ordinary Kriging with Cokriging,as the latter input altitude which had an influence on precipitation and evaporation,it was more rational on space distribution and had a higher interpolation precision.(3) With Geostatisticsmethods the spatial interpolations couldreflect the general space patternof climate variables better in general,but the spatialinterpolations precisionoftwo methods werestill not high,whichstill remainedfurtherimproving. |
| Keywords: | Geostatistics Spatial interpolation Ordinary Kriging Cokriging Multi-year average precipitation Annual average evaporation |
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