DOI: 10.1002/joc.5502
论文题名: An improved statistical downscaling scheme of Tropical Rainfall Measuring Mission precipitation in the Heihe River basin, China
作者: Zhao N. ; Yue T. ; Chen C. ; Zhao M. ; Fan Z.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 8 起始页码: 3309
结束页码: 3322
语种: 英语
英文关键词: downscaling
; Heihe River basin
; precipitation
; TRMM
Scopus关键词: Climate change
; Image resolution
; Interpolation
; Precipitation (chemical)
; Rain
; Rivers
; Watersheds
; Down-scaling
; Geographical weighted regressions
; Heihe river basin
; Meteorological observation
; Precipitation estimation
; Statistical downscaling
; TRMM
; Tropical rainfall measuring missions
; Rain gages
; downscaling
; interpolation
; precipitation (climatology)
; regression analysis
; river basin
; spatial distribution
; spatial resolution
; TRMM
; China
; Gansu
; Heihe Basin
英文摘要: Estimating an accurate spatial distribution of precipitation with high resolution is necessary for hydrological and ecological applications, especially in data-scarce and terrain-complicated river basins. Satellite-based precipitation data have been widely used to measure the spatial patterns of precipitation, but an improvement in accuracy and resolution is needed. In this article, a new statistical downscaling method is proposed to generate improved monthly precipitation fields at a higher spatial resolution of 1 km in Heihe River basin (HRB), China. The presented methods employed the geographical weighted regression (GWR) method to explore the non-stationarity between precipitation and its factors, and used the high-accuracy surface modelling method (HASM) to compensate for the errors produced in the GWR downscaling process. The GWR model was first established under five different spatial scales, and the optimal relation between precipitation derived from the Tropical Rainfall Measuring Mission (TRMM) and its influencing factors was found for each month. The errors caused during the scale change were modified by performing HASM as a data merging framework, which considered both the local climate characteristics and meteorological observations. Results showed that the GWR downscaling method could not generate spatial patterns of precipitation similar to those of the original TRMM products. Although the performance of the GWR method after residual interpolations using Kriging, IDW, and tension Spline was improved, there existed significant variations in some regions, and the accuracy of those methods was still not satisfactory. In comparison with the other four models, GWR-HASM showed better performance in reproducing the precipitation field at a high spatial resolution. Results indicate that the proposed downscaling method appears feasible for precipitation estimation in data-scarce river basins. © 2018 Royal Meteorological Society Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116858
Appears in Collections: 气候减缓与适应
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作者单位: State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China; Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing, China; Geomatics College, Shandong University of Science and Technology, Qingdao, China; Auhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou, China
Recommended Citation:
Zhao N.,Yue T.,Chen C.,et al. An improved statistical downscaling scheme of Tropical Rainfall Measuring Mission precipitation in the Heihe River basin, China[J]. International Journal of Climatology,2018-01-01,38(8)