Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.6020 |
Regression-based regionalization for bias correction of temperature and precipitation | |
Moghim, Sanaz1; Bras, Rafael L.2 | |
2019-06-15 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY
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ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2019 |
卷号 | 39期号:7页码:3298-3312 |
文章类型 | Article |
语种 | 英语 |
国家 | Iran; USA |
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. |
英文关键词 | artificial neural network bias correction CCSM regionalization South America training |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000475693500014 |
WOS关键词 | THUNDERSTORM FREQUENCIES ; GLOBAL PRECIPITATION ; NEURAL-NETWORKS ; CLIMATE ; LAND ; CIRCULATION ; PERFORMANCE ; RESOLUTION ; UTILITY |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/184056 |
专题 | 气候变化 |
作者单位 | 1.Sharif Univ Technol, Dept Civil Engn, Tehran, Iran; 2.Georgia Inst Technol, Sch Civil & Environm Engn, Atlanta, GA 30332 USA |
推荐引用方式 GB/T 7714 | Moghim, Sanaz,Bras, Rafael L.. Regression-based regionalization for bias correction of temperature and precipitation[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2019,39(7):3298-3312. |
APA | Moghim, Sanaz,&Bras, Rafael L..(2019).Regression-based regionalization for bias correction of temperature and precipitation.INTERNATIONAL JOURNAL OF CLIMATOLOGY,39(7),3298-3312. |
MLA | Moghim, Sanaz,et al."Regression-based regionalization for bias correction of temperature and precipitation".INTERNATIONAL JOURNAL OF CLIMATOLOGY 39.7(2019):3298-3312. |
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