中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A Multivariate Regression Model for Predicting Precipitation in the Daqing Mountains

文献类型:SCI/SSCI论文

作者Sun R. H. ; Zhang B. P. ; Tan J.
发表日期2008
关键词Precipitation multivariate regression modeling prediction GIS Daqing Mountains China spatial interpolation temperature elevation terrain gis climate
英文摘要Multivariate regression analysis, combined with residuals correction, was carried out to develop a precipitation prediction model for the Daqing Mountains of Inner Mongolia in northern China. Precipitation data collected at 56 stations between 1955 and 1990 were used: data from 48 stations for model development and data from 8 stations for additional tests. Five topographic factors-altitude, slope, aspect, longitude, and latitude-were taken into account for model development. These topographic variables were acquired from a 100-m resolution digital elevation model (DEM) of the study region, and the mean values of the sub-basin in which a precipitation station is located were used as the values of the respective variables of that station. The multivariate regression model can explain 72.6% of the spatial variability of precipitation over the whole year and 74.4% of variability in the wet season (June-September). Precipitation in the dry season (October-May) is hard to model owing to little rainfall (21.78% of annual rainfall) and a different synoptic system. Interpolation-based residuals correction did not significantly improve the accuracy of our model, which shows that our model is quite effective. The model, as presented in this paper, could potentially be applied to other mountains and in mountain climate research.
出处Mountain Research and Development
28
3-4
318-325
收录类别SCI
语种英语
ISSN号0276-4741
源URL[http://ir.igsnrr.ac.cn/handle/311030/23035]  
专题地理科学与资源研究所_历年回溯文献
推荐引用方式
GB/T 7714
Sun R. H.,Zhang B. P.,Tan J.. A Multivariate Regression Model for Predicting Precipitation in the Daqing Mountains. 2008.

入库方式: OAI收割

来源:地理科学与资源研究所

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