气候变化领域集成服务门户(CCPortal): Estimating parameters in a sea ice model using an ensemble Kalman filter

CCPortal

DOI	10.5194/tc-15-1277-2021
	Estimating parameters in a sea ice model using an ensemble Kalman filter
	Zhang Y.-F.; Bitz C.M.; Anderson J.L.; Collins N.S.; Hoar T.J.; Raeder K.D.; Blanchard-Wrigglesworth E.
发表日期	2021
ISSN	19940416
起始页码	1277
结束页码	1284
卷号	15 期号:3
英文摘要	Uncertain or inaccurate parameters in sea ice models influence seasonal predictions and climate change projections in terms of both mean and trend. We explore the feasibility and benefits of applying an ensemble Kalman filter (EnKF) to estimate parameters in the Los Alamos sea ice model (CICE). Parameter estimation (PE) is applied to the highly influential dry snow grain radius and combined with state estimation in a series of perfect model observing system simulation experiments (OSSEs). Allowing the parameter to vary in space improves performance along the sea ice edge but degrades in the central Arctic compared to requiring the parameter to be uniform everywhere, suggesting that spatially varying parameters will likely improve PE performance at local scales and should be considered with caution. We compare experiments with both PE and state estimation to experiments with only the latter and have found that the benefits of PE mostly occur after the data assimilation period, when no observations are available to assimilate (i.e., the forecast period), which suggests PE's relevance for improving seasonal predictions of Arctic sea ice. © 2021 BMJ Publishing Group. All rights reserved.
英文关键词	climate change; data assimilation; Kalman filter; observational method; parameter estimation; sea ice; snow cover; Arctic; Los Alamos; New Mexico; United States
语种	英语
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/202458
作者单位	Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States; IMAGe, CISL, National Center for Atmospheric Research, Boulder, CO, United States; Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, United States
推荐引用方式 GB/T 7714	Zhang Y.-F.,Bitz C.M.,Anderson J.L.,et al. Estimating parameters in a sea ice model using an ensemble Kalman filter[J],2021,15(3).
APA	Zhang Y.-F..,Bitz C.M..,Anderson J.L..,Collins N.S..,Hoar T.J..,...&Blanchard-Wrigglesworth E..(2021).Estimating parameters in a sea ice model using an ensemble Kalman filter.Cryosphere,15(3).
MLA	Zhang Y.-F.,et al."Estimating parameters in a sea ice model using an ensemble Kalman filter".Cryosphere 15.3(2021).