globalchange  > 影响、适应和脆弱性
DOI: 10.5194/tc-10-103-2016
Scopus记录号: 2-s2.0-85009387545
论文题名:
Feasibility of improving a priori regional climate model estimates of Greenland ice sheet surface mass loss through assimilation of measured ice surface temperatures
作者: Navari M; , Margulis S; A; , Bateni S; M; , Tedesco M; , Alexander P; , Fettweis X
刊名: Cryosphere
ISSN: 19940416
出版年: 2016
卷: 10, 期:1
起始页码: 103
结束页码: 120
语种: 英语
英文关键词: climate modeling ; data assimilation ; ensemble forecasting ; error analysis ; estimation method ; feasibility study ; glacier mass balance ; performance assessment ; regional climate ; remote sensing ; sea level change ; smoothing ; surface temperature ; Arctic ; Greenland ; Greenland Ice Sheet
英文摘要: The Greenland ice sheet (GrIS) has been the focus of climate studies due to its considerable impact on sea level rise. Accurate estimates of surface mass fluxes would contribute to understanding the cause of its recent changes and would help to better estimate the past, current and future contribution of the GrIS to sea level rise. Though the estimates of the GrIS surface mass fluxes have improved significantly over the last decade, there is still considerable disparity between the results from different methodologies (e.g., Rae et al., 2012; Vernon et al., 2013). The data assimilation approach can merge information from different methodologies in a consistent way to improve the GrIS surface mass fluxes. In this study, an ensemble batch smoother data assimilation approach was developed to assess the feasibility of generating a reanalysis estimate of the GrIS surface mass fluxes via integrating remotely sensed ice surface temperature measurements with a regional climate model (a priori) estimate. The performance of the proposed methodology for generating an improved posterior estimate was investigated within an observing system simulation experiment (OSSE) framework using synthetically generated ice surface temperature measurements. The results showed that assimilation of ice surface temperature time series were able to overcome uncertainties in near-surface meteorological forcing variables that drive the GrIS surface processes. Our findings show that the proposed methodology is able to generate posterior reanalysis estimates of the surface mass fluxes that are in good agreement with the synthetic true estimates. The results also showed that the proposed data assimilation framework improves the root-mean-square error of the posterior estimates of runoff, sublimation/evaporation, surface condensation, and surface mass loss fluxes by 61, 64, 76, and 62 %, respectively, over the nominal a priori climate model estimates. © 2016 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75197
Appears in Collections:影响、适应和脆弱性
气候变化与战略

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作者单位: Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, United States; Department of Civil and Environmental Engineering, Water Resources Research Center, University of Hawaii at Manoa, Manoa, HI, United States; Department of Earth and Atmospheric Sciences, City College of New York, New York, NY, United States; Lamont Doherty Earth Observatory of Columbia University, Palisades, NY, United States; Graduate Center of the City University of New York, New York, NY, United States; Department of Geography, University of Liege, Liege, Belgium

Recommended Citation:
Navari M,, Margulis S,A,et al. Feasibility of improving a priori regional climate model estimates of Greenland ice sheet surface mass loss through assimilation of measured ice surface temperatures[J]. Cryosphere,2016-01-01,10(1)
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