DOI: 10.1002/2015JD024159
论文题名: A nonstationary bias-correction technique to remove bias in GCM simulations
作者: Miao C. ; Su L. ; Sun Q. ; Duan Q.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2016
语种: 英语
英文关键词: Bias-correction
; GCM
; Nonstationary
; Quantile mapping
英文摘要: We developed an updated nonstationary bias-correction method for a monthly global climate model of temperature and precipitation. The proposed method combines two widely used quantile mapping bias-correction methods to eliminate potential illogical values of the variable. Instead of empirical parameter estimation in the more-common quantile mapping method, our study compared bias-correction performance when parametric or nonparametric procedures were used to estimate the probability distribution. The results showed our proposed bias-correction method to be very effective in reducing the model bias: it removed over 80% and 83% of model bias for surface air temperature and precipitation, respectively, during the validation period. Compared with a widely used method of bias correction (delta change), our proposed technique demonstrates improved correction of the distribution of variables. In addition, nonparametric estimation procedures further reduced the mean absolute errors in temperature and precipitation during the validation period by approximately 2% and 0.4%, respectively, compared with parametric procedures. The proposed method can remove over 40% and 60% of the uncertainty from model temperature and precipitation projections, respectively, at the global land scale. © 2016. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62931
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science Beijing Normal University Beijing China; Joint Center for Global Change Studies Beijing China
Recommended Citation:
Miao C.,Su L.,Sun Q.,et al. A nonstationary bias-correction technique to remove bias in GCM simulations[J]. Journal of Geophysical Research: Atmospheres,2016-01-01