DOI: 10.1002/joc.6020
Scopus记录号: 2-s2.0-85062373333
论文题名: Regression-based regionalization for bias correction of temperature and precipitation
作者: Moghim S. ; Bras R.L.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2019
语种: 英语
英文关键词: artificial neural network
; bias correction
; CCSM
; regionalization
; South America
; training
Scopus关键词: Neural networks
; Personnel training
; Pixels
; Regression analysis
; Artificial neural network models
; Bias correction
; CCSM
; Climate variables
; Community climate system model
; Computational time
; regionalization
; South America
; Climate models
英文摘要: Statistical bias correction methods are inferred relationships between inputs and outputs. The constructed functions are based on available observations, which are limited in time and space. This study investigates the ability of regression models (linear and nonlinear) to regionalize a domain by defining a minimum number of training pixels necessary to achieve a good level of bias correction performance. Linear regression is used to divide northern South America into five regions. To correct the biases of temperature and precipitation, an artificial neural network (ANN) model was trained with selected pixels within each region and then used to reproduce bias-corrected temperature and precipitation at all pixels within the delineated regions. The Community Climate System Model (CCSM) provided the climate model data. Results confirm that it is possible to identify regions in terms of physical features such as land cover, topography, and climatology over which models trained with a few pixels can correct the biases of climate variables with good accuracy over the entire domain. This approach saves computational time and reduces memory usage of using ANNs for correcting biases in climate model outputs. © 2019 Royal Meteorological Society Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116608
Appears in Collections: 全球变化的国际研究计划
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作者单位: Department of Civil Engineering, Sharif University of Technology, Tehran, Iran; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States
Recommended Citation:
Moghim S.,Bras R.L.. Regression-based regionalization for bias correction of temperature and precipitation[J]. International Journal of Climatology,2019-01-01