DOI: 10.1007/s10584-016-1858-z
Scopus记录号: 2-s2.0-85000417272
论文题名: The effects of time-varying observation errors on semi-empirical sea-level projections
作者: Ruckert K.L. ; Guan Y. ; Bakker A.M.R. ; Forest C.E. ; Keller K.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2017
卷: 140, 期: 2018-03-04 起始页码: 349
结束页码: 360
语种: 英语
Scopus关键词: Decision making
; Errors
; Bayesian inversion
; Decision makers
; Error structures
; Heteroskedasticity
; Observation errors
; Parameter distributions
; Parametric distributions
; Sea level anomaly
; Sea level
; autocorrelation
; bootstrapping
; data inversion
; decision making
; empirical analysis
; error analysis
; flooding
; hindcasting
; parameter estimation
; probability
; sea level change
; uncertainty analysis
英文摘要: Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentist bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. Our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections. © 2016, The Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84094
Appears in Collections: 气候减缓与适应 气候变化事实与影响
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作者单位: Department of Geosciences, The Pennsylvania State University, University Park, PA, United States; Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, United States; Department of Statistics, The Pennsylvania State University, University Park, PA, United States; Department of Meteorology, The Pennsylvania State University, University Park, PA, United States; Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, United States
Recommended Citation:
Ruckert K.L.,Guan Y.,Bakker A.M.R.,et al. The effects of time-varying observation errors on semi-empirical sea-level projections[J]. Climatic Change,2017-01-01,140(2018-03-04)