DOI: 10.1002/joc.5283
论文题名: Does applying quantile mapping to subsamples improve the bias correction of daily precipitation?
作者: Reiter P. ; Gutjahr O. ; Schefczyk L. ; Heinemann G. ; Casper M.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 4 起始页码: 1623
结束页码: 1633
语种: 英语
英文关键词: annual cycle
; bias adjustment
; bias correction
; precipitation
; quantile mapping
; quantile matching
; sample size
; timescale
Scopus关键词: Calibration
; Climate models
; Mapping
; Precipitation (chemical)
; Annual cycle
; bias adjustment
; Bias correction
; quantile matching
; Sample sizes
; Time-scales
; Climate change
; annual variation
; climate change
; climate modeling
; diurnal variation
; error correction
; hindcasting
; precipitation (climatology)
; quantitative analysis
; sampling bias
; timescale
; weather forecasting
英文摘要: Quantile mapping (QM) is routinely applied in many climate change impact studies for the bias correction (BC) of daily precipitation data. It corrects the complete distribution, but does not correct for errors in the annual cycle. Therefore, QM is often applied separately to temporal subsamples of the data (e.g. each calendar month), which reduces the calibration sample size. The question arises whether this sample size reduction negates the benefit from applying QM to temporal subsamples. We applied four QM methods in a cross-validation approach to 40 years of daily precipitation data from 10 regional climate model (RCM) hindcast runs, without and with (semi-annual, seasonal, and monthly) subsampling. QM subsampling improved the BC of daily RCM precipitation; less distinct for independent data but considerably for the calibration data. The optimal subsampling timescale for the correction of independent data depended on the chosen QM method and ranged between semi-annual and monthly. Overall, a sub-annual QM improves the forcing for climate change impact studies and thus their reliability. © 2017 Royal Meteorological Society Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117042
Appears in Collections: 气候减缓与适应
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作者单位: Rhineland-Palatinate Centre of Excellence for Climate Change Impacts, Trippstadt, Germany; Department of Physical Geography, University of Trier, Germany; Max Planck Institute for Meteorology, Hamburg, Germany; Department of Environmental Meteorology, University of Trier, Germany
Recommended Citation:
Reiter P.,Gutjahr O.,Schefczyk L.,et al. Does applying quantile mapping to subsamples improve the bias correction of daily precipitation?[J]. International Journal of Climatology,2018-01-01,38(4)