DOI: 10.1002/joc.5259
论文题名: Constructing a long-term monthly climate data set in central Asia
作者: Zhou H. ; Aizen E. ; Aizen V.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 3 起始页码: 1463
结束页码: 1475
语种: 英语
英文关键词: Altai
; Central Asia
; Climate change
; Climate data
; Gap-filling
; Pamir
; Spatial interpolation
; Tien Shan
Scopus关键词: Atmospheric temperature
; Interpolation
; Iterative methods
; Mean square error
; Principal component analysis
; Regression analysis
; Time series
; Time series analysis
; Altai
; Central Asia
; Climate data
; Gap filling
; Pamir
; Spatial interpolation
; Tien Shan
; Climate change
; air temperature
; climate change
; data set
; interpolation
; precipitation (climatology)
; spatial data
; Altai Mountains
; Pamirs
; Tien Shan
英文摘要: We compiled and merged in situ observation data from several sources, creating a comprehensive unified monthly air temperature and precipitation data set with 457 stations in central Asia (CA). Stations with a valid data rate higher than 80% were selected, and the remaining gaps in selected station time series were filled with an iterative-principal component analysis (PCA) gap-fillingmethod. The result is a gap-filled station data set for the period 1951-2010, with 369 and 381 stations for air temperature and precipitation, respectively. The cross-validation shows that the iterative-PCA gap-filling algorithm provides stable and trustworthy estimations of gaps, with mean root mean squared error (RMSE) of 0.03°C (in the range of 0.01-0.13°C) for air temperature, and mean RMSE of 0.60mm (in the range of 0.10-1.99 mm) for precipitation. A gridded data setwas created by interpolating the gap-filled station data set with the geographically weighted regression method. Comparison of the gridded data set with the National Centers for Environmental Prediction (NCEP) reanalysis data set shows that though both data sets present the long-term mean climate situation similarly, the gridded data set exhibits less annual and monthly variability. And the gridded data set has stronger correlations with stations time series than the reanalysis data set (mean correlations are 0.994 vs 0.975 for air temperature, and 0.787 vs 0.515 for precipitation), especially for precipitation in high mountain stations. The gridded data set is more suitable for climate and hydrological studies in CA, especially in high mountains regions. © 2017 Royal Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117123
Appears in Collections: 气候减缓与适应
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作者单位: Department of Geography, University of Idaho, Moscow, ID, United States
Recommended Citation:
Zhou H.,Aizen E.,Aizen V.. Constructing a long-term monthly climate data set in central Asia[J]. International Journal of Climatology,2018-01-01,38(3)