Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation
文献类型：期刊论文
| 作者 | Alvarez, Otto; Guo, Qinghua1 ; Klinger, Robert C.; Li, Wenkai; Doherty, Paul
|
| 刊名 | INTERNATIONAL JOURNAL OF CLIMATOLOGY
 |
| 出版日期 | 2014 |
| 卷号 | 34期号:7页码:2258-2268 |
| 关键词 | climate surfaces spatial interpolation temperature precipitation Thin Plate Spline |
| ISSN号 | 0899-8418 |
| DOI | 10.1002/joc.3835 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| 学科主题 | Meteorology & Atmospheric Sciences |
| 出版地 | HOBOKEN |
| 电子版国际标准刊号 | 1097-0088 |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:000337558200011 |
| 出版者 | WILEY-BLACKWELL |
| 资助机构 | 973 Program [2013 CB956604] ; National Science Foundation of China [31270563] ; USGS National Climate Change and Wildlife Science Center |
| 源URL | [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. |
入库方式： OAI收割
来源：植物研究所
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