Climate Change Data Portal
DOI | 10.1029/2020JC017140 |
Bias Correction of Ocean Bottom Temperature and Salinity Simulations From a Regional Circulation Model Using Regression Kriging | |
Chang J.-H.; Hart D.R.; Munroe D.M.; Curchitser E.N. | |
发表日期 | 2021 |
ISSN | 21699275 |
卷号 | 126期号:4 |
英文摘要 | It is well known that climate and circulation model simulation output are often systematically biased. However, existing bias correction methods typically ignore spatial autocorrelation of the biases and correct only the overall mean and variance, resulting in mismatched spatial variability between bias-corrected simulations and observations. In this study, we propose using regression kriging (RK) to correct for biased spatial patterns and apply this method to Regional Ocean Modeling System (ROMS) simulated ocean bottom temperature and salinity for the Mid-Atlantic Bight, USA. RK combines modeling non-stationary trends using (generalized) regression with ordinary kriging (OK) of the regression residuals. We compared the performance of RK to a simpler OK method and a quantile mapping (QM) method often used for bias correction of such model output. These methods were evaluated using the Structural Similarity (SSIM) index that can simultaneously evaluate model accuracy, precision, and spatial similarities. Our results show that while both RK and QM can correct for overall biases of the mean and variation, only RK can effectively reduce the spatial-temporal autocorrelation of the biases. The RK method was able to bias correct while preserving the spatial-temporal trends of the ROMS simulated bottom temperature and salinity surfaces. The RK approach can easily be applied to any similar climate and circulation model simulation output. This study has profound implications for studies that use the output from such a model for fine-scale mapping, habitat suitability modeling, species distribution modeling, or predicting the effects of climate change. © 2021. American Geophysical Union. All Rights Reserved. |
英文关键词 | bias correction; bottom salinity; bottom temperature; regional ocean modeling system; regression kriging; Structural Similarity Index |
语种 | 英语 |
来源期刊 | Journal of Geophysical Research: Oceans
![]() |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/186367 |
作者单位 | Northeast Fisheries Science Center, NMFS/NOAA, Woods Hole, MA, United States; Haskin Shellfish Research Laboratory, Rutgers University, Port Norris, NJ, United States; Department of Environmental Science, Rutgers University, New Brunswick, NJ, United States |
推荐引用方式 GB/T 7714 | Chang J.-H.,Hart D.R.,Munroe D.M.,et al. Bias Correction of Ocean Bottom Temperature and Salinity Simulations From a Regional Circulation Model Using Regression Kriging[J],2021,126(4). |
APA | Chang J.-H.,Hart D.R.,Munroe D.M.,&Curchitser E.N..(2021).Bias Correction of Ocean Bottom Temperature and Salinity Simulations From a Regional Circulation Model Using Regression Kriging.Journal of Geophysical Research: Oceans,126(4). |
MLA | Chang J.-H.,et al."Bias Correction of Ocean Bottom Temperature and Salinity Simulations From a Regional Circulation Model Using Regression Kriging".Journal of Geophysical Research: Oceans 126.4(2021). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。