青藏高原东南缘气象要素Anusplin和Cokriging空间插值对比分析
Contrast on Anusplin and Cokriging Meteorological Spatial Interpolation in Southeastern Margin of Qinghai-Xizang Plateau
查看参考文献32篇
文摘
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选取地形起伏度巨大的青藏高原东南缘为研究区,利用该研究区96个气象站点,结合高程数据,分别采用Cokriging和Anusplin空间插值方法,获取2010年250 m分辨率的年均温度和年累计降水插值曲面。并采用交叉验证方法对比Anusplin与Cokriging插值精度,分析了误差的空间分布特征,重点对比两种插值曲面差异较大的区域精度优劣,评价两种方法在复杂地区的适用性。结果表明,Anusplin在复杂地表的插值表现优于Cokriging,其中Anusplin气温插值的均方差仅为0. 82 ℃,而Cokriging的均方差为1. 45 ℃;两者的降水插值精度基本一致,但Anusplin在气象要素空间异质性大的区域优于Cokriging。因此,与Cokriging相比,Anusplin更适合青藏高原东南缘复杂地表气象要素空间插值。 |
其他语种文摘
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Meteorological data is the essential data of ecological, resources, environment, global change and other research areas. However, the meteorological in Mountain are rare and complex than in plain. And acquiring precise spatial grid meteorological data has been a difficult task in this area. Anusplin and Cokriging interpolation method are one of the most common method that considering terrain'impacts during the Meteorological Spatial Interpolation. To ensure which one is more suit for complex area, we take the most complex mountain area (the Southeastern margin of the Qinghai-Xizang Plateau) as study area to compare the two methods. Based on Anusplin and Cokriging meteorological spatial interpolation method separately, combined with the terrain data and 96 meteorological stations in the southeastern margin of the Qinghai-Xizang Plateau region, 250 m resolution average temperature and total precipitation interpolated surfaces in 2010 was obtained. With the cross-validation method comparison method, the interpolation accuracy of Anusplin and Cokriging was compared, and the spatial distribution of errors was analyzed. Applying relevant information, accurate of the two methods in local area where the result of interpolation are quite different was qualitatively analyzed. Through this, the method which is more suit for this area is sought out and the applicability of Anusplin in this area was assessed. The results showed that, Anusplin interpolation outperformed Cokriging. In the comparing of mean square error(RMSE) of the interpolation of temperature and precipitation, Anusplin temperature is only 0. 82 ℃ and Cokriging is 1. 45 ℃, the RMSE of precipitation of the two methodes are consistent, but Anusplin are superior to Cokriging in the highly heterogeneous area. Therefore Anusplin can achieve better results than Cokriging, indicating that Anusplin is suit for the interpolation in Southeastern Margin of Qinghai-Xizang Plateau. |
来源
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高原气象
,2016,35(4):875-886 【核心库】
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DOI
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10.7522/j.issn.1000-0534.2015.00037
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关键词
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青藏高原东南缘
;
空间插值
;
年均温
;
年累计降水
;
Anusplin
;
Cokriging
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地址
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中国科学院成都山地灾害与环境研究所, 成都, 610041
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1000-0534 |
学科
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大气科学(气象学) |
基金
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中国科学院战略性先导科技专项
;
中国科学院委托研究与专项咨询服务课题
;
国家自然科学基金项目
;
中国科学院对外合作重点项目
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文献收藏号
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CSCD:5798734
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参考文献 共
32
共2页
|
1.
Atkinson P M. Mapping precipitation in Switzerland with ordinary and indicator kriging. Special issue:Spatial interpolation comparison 97.
Journal of Geographic Information and Decision Analysis,1998,2(1/2):72-86
|
被引
2
次
|
|
|
|
2.
Bookstein F L. Principal warps:Thin-plate splines and the decomposition of deformations.
IEEE Transactions on pattern analysis and machine intelligence,1989,11(6):567-585
|
被引
136
次
|
|
|
|
3.
Galway L. Spline models for observational data.
Philadelphia:Society for Industrial and Applied Mathematics,1990:169
|
被引
1
次
|
|
|
|
4.
Hartkamp A D.
Interpolation techniques for climate variables,1999:26
|
被引
2
次
|
|
|
|
5.
Hijmans R J. Very high resolution interpolated climate surfaces for global land areas.
Int J Climatol,2005,25(15):1965-1978
|
被引
624
次
|
|
|
|
6.
Hutchinson M F.
Anusplin Version 4.4 User Guide,2013:55
|
被引
1
次
|
|
|
|
7.
Hutchinson M F. Interpolation of rainfall data with thin plate smoothing splines. Part I:Two dimensional smoothing of data with short range correlation.
Journal of Geographic Information and Decision Analysis,1998,2(2):139-151
|
被引
47
次
|
|
|
|
8.
Hutchinson M. Splines-more than just a smooth interpolator.
Geoderma,1994,62(1):45-67
|
被引
46
次
|
|
|
|
9.
Hutchinson M. Interpolating mean rainfall using thin plate smoothing splines.
International Journal of Geographical Information Systems,1995,9(4):385-403
|
被引
72
次
|
|
|
|
10.
Journel A G.
Geostatistical software library and user's guide,1992:369
|
被引
1
次
|
|
|
|
11.
Knotters M. A comparison of kriging,co-kriging and kriging combined with regression for spatial interpolation of horizon depth with censored observations.
Geoderma,1995,67(3):227-246
|
被引
24
次
|
|
|
|
12.
Kohavi R. A Study of cross-validation and bootstrap for accuracy estimation and model selection.
International Joint Conference on Artificial Intelligence,2001,2001:1137-1143
|
被引
1
次
|
|
|
|
13.
Li A. China land cover monitoring in mountainous regions by remote sensing technology-Taking the Southwestern China as a case.
Geoscience and Remote Sensing Symposium (IGARSS),2014 IEEE International,2014
|
被引
1
次
|
|
|
|
14.
Thomas A. Seasonal and spatial variation of evapotranspiration in the mountains of Southwest China.
Journal of Mountain Research,2002,20(4):385-393
|
被引
1
次
|
|
|
|
15.
程宸. 城市下垫面对北京冬季气象要素影响的模拟研究.
高原气象,2014,33(4):1045-1056
|
被引
1
次
|
|
|
|
16.
邓伟. 中国山地科学发展构想.
中国科学院院刊,2008,23(2):156-161
|
被引
15
次
|
|
|
|
17.
李新. 青藏高原气温分布的空间插值方法比较.
高原气象,2003,22(6):565-573
|
被引
90
次
|
|
|
|
18.
刘正佳. 薄盘光滑样条插值中三种协变量方法的降水量插值精度比较.
地理科学进展,2012,31(1):56-62
|
被引
27
次
|
|
|
|
19.
刘志红. 基于ANUSPLIN的时间序列气象要素空间插值.
西北农林科技大学学报:自然科学版,2008,36(10):227-234
|
被引
49
次
|
|
|
|
20.
刘志红. 专用气候数据空间插值软件ANUSPLIN及其应用.
气象,2008,34(2):92-100
|
被引
114
次
|
|
|
|
|