DOI: 10.1002/joc.5162
论文题名: High-resolution precipitation downscaling in mountainous areas over China: development and application of a statistical mapping approach
作者: Zhu X. ; Qiu X. ; Zeng Y. ; Ren W. ; Tao B. ; Pan H. ; Gao T. ; Gao J.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 1 起始页码: 77
结束页码: 93
语种: 英语
英文关键词: maximum precipitation increment direction (MPID)
; mountainous areas
; precipitation downscaling
; prevailing precipitation direction (PPD)
; statistical mapping
; TRMM 3B43
Scopus关键词: Errors
; Mapping
; Rain gages
; Down-scaling
; maximum precipitation increment direction (MPID)
; Mountainous area
; Precipitation direction
; TRMM 3B43
; Mean square error
; accuracy assessment
; downscaling
; geostatistics
; kriging
; mapping
; mountain region
; precipitation assessment
; TRMM
; China
英文摘要: High-resolution precipitation distributions in mountainous areas are important for hydrological and ecological assessments, especially in regions with few weather stations. In this study, we proposed an improved model for precipitation downscaling by adding two new parameters, i.e. the maximum precipitation increment direction and the prevailing precipitation direction, which represent the impacts of elevation and the sources of precipitation, respectively. The model parameterization is based on observations made at meteorological stations, terrain factors (e.g. elevation, aspect, and slope), and the new parameters. To evaluate the model, we used six sub-models, each of which considers different influencing factors, to estimate the precipitation distribution and compare their estimation errors. Based on the mean absolute error (MAE) and the root-mean-square error (RMSE) at the validation stations, we found that the sixth sub-model, which includes all the influencing factors, clearly ranks above the others in terms of precipitation downscaling. The monthly MAE and the RMSE of our downscaled precipitation range from 2.2 to 16.1 mm and from 3.4 to 22.7 mm, respectively, indicating more accurate estimation than the raw tropical precipitation measuring mission (TRMM) products (monthly MAE: 3.6–22.0 mm; monthly RMSE: 5.1–28.6%). Our results also show that the sixth sub-model performs better than the Auto-Searched Orographic and Atmospheric Effects Detrended Kriging model (ASOADeK model or Guan's model) due to the inclusion of the elevation and the sources of precipitation. Based on the sixth sub-model and the TRMM 3B43 products, we developed the monthly precipitation products in China from 2000 to 2007 at a spatial resolution of 1 km. Our improved approach to precipitation downscaling could be used for regions where the precipitation distribution is greatly affected by the terrain and few observations are available for estimating the precipitation distribution. © 2017 Royal Meteorological Society Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117148
Appears in Collections: 气候减缓与适应
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作者单位: School of Geography and Remote Sensing, Nanjing University of Information Science and Technology, Nanjing, China; Department of Plant and Soil Sciences, University of Kentucky, Lexington, KY, United States; College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China; Climate Center of Jiangsu Province, Jiangsu Meteorological Bureau, Nanjing, China; School of Cultural Industry and Tourism Management, Sanjiang University, Nanjing, China; Zhejiang Meteorology Information Networks Center, Zhejiang Meteorological Bureau, Hangzhou, China; College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China
Recommended Citation:
Zhu X.,Qiu X.,Zeng Y.,et al. High-resolution precipitation downscaling in mountainous areas over China: development and application of a statistical mapping approach[J]. International Journal of Climatology,2018-01-01,38(1)