DOI: 10.5194/hess-21-2649-2017
Scopus记录号: 2-s2.0-85020436712
论文题名: Scaled distribution mapping: A bias correction method that preserves raw climate model projected changes
作者: Switanek B ; M ; , Troch A ; P ; , Castro L ; C ; , Leuprecht A ; , Chang H ; -I ; , Mukherjee R ; , Demaria M ; C ; E
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 6 起始页码: 2649
结束页码: 2666
语种: 英语
Scopus关键词: Climate change
; Error correction
; Mapping
; Space division multiple access
; Bias-correction methods
; Meteorological variables
; Rain days
; Stationarity
; Time invariants
; Climate models
; climate change
; climate modeling
; error correction
; frequency analysis
; mapping method
; precipitation (climatology)
; rainfall
; signal
; spatial distribution
; temperature
英文摘要: Commonly used bias correction methods such as quantile mapping (QM) assume the function of error correction values between modeled and observed distributions are stationary or time invariant. This article finds that this function of the error correction values cannot be assumed to be stationary. As a result, QM lacks justification to inflate/deflate various moments of the climate change signal. Previous adaptations of QM, most notably quantile delta mapping (QDM), have been developed that do not rely on this assumption of stationarity. Here, we outline a methodology called scaled distribution mapping (SDM), which is conceptually similar to QDM, but more explicitly accounts for the frequency of rain days and the likelihood of individual events. The SDM method is found to outperform QM, QDM, and detrended QM in its ability to better preserve raw climate model projected changes to meteorological variables such as temperature and precipitation. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79164
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Wegener Center for Climate and Global Change, University of Graz, Graz, Austria; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, United States; Southwest Watershed Research Center, USDA - Agricultural Research Service, Tucson, AZ, United States
Recommended Citation:
Switanek B,M,, Troch A,et al. Scaled distribution mapping: A bias correction method that preserves raw climate model projected changes[J]. Hydrology and Earth System Sciences,2017-01-01,21(6)