Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

doi:10.1002/joc.3835

	Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation
	Alvarez, Otto ; Guo, Qinghua1 ; Klinger, Robert C.; Li, Wenkai ; Doherty, Paul
	2014
发表期刊	INTERNATIONAL JOURNAL OF CLIMATOLOGY
ISSN	0899-8418
卷号	34 期号:7 页码:2258-2268
摘要	Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32 degrees to 49 degrees latitude and -124.7 degrees to -112.9 degrees longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.
关键词	climate surfaces spatial interpolation temperature precipitation Thin Plate Spline
学科领域	Meteorology & Atmospheric Sciences
DOI	10.1002/joc.3835
收录类别	SCI
语种	英语
WOS关键词	PLATE SMOOTHING SPLINES ; GLOBAL LAND AREAS ; SPATIAL INTERPOLATION ; DATA SETS ; RESOURCE MANAGEMENT ; COMPLEX TERRAIN ; UNITED-STATES ; VARIABILITY ; VEGETATION ; VARIABLES
WOS研究方向	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000337558200011
出版者	WILEY-BLACKWELL
文献子类	Article
出版地	HOBOKEN
EISSN	1097-0088
资助机构	973 Program [2013 CB956604] ; National Science Foundation of China [31270563] ; USGS National Climate Change and Wildlife Science Center
作者邮箱	qguo@ucmerced.edu
引用统计	被引频次：20[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/27128
专题	植被与环境变化国家重点实验室
作者单位	1.Univ Calif Merced, Sierra Nevada Res Inst, Sch Engn, Merced, CA 95343 USA 2.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China 3.Klinger, Robert C.] USGS, Western Ecol Res Ctr, Yosemite Field Stn, Bishop, CA USA
推荐引用方式 GB/T 7714	Alvarez, Otto,Guo, Qinghua,Klinger, Robert C.,et al. Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2014,34(7):2258-2268.
APA	Alvarez, Otto,Guo, Qinghua,Klinger, Robert C.,Li, Wenkai,&Doherty, Paul.(2014).Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation.INTERNATIONAL JOURNAL OF CLIMATOLOGY,34(7),2258-2268.
MLA	Alvarez, Otto,et al."Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation".INTERNATIONAL JOURNAL OF CLIMATOLOGY 34.7(2014):2258-2268.

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