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The effects of time-varying observation errors on semi-empirical sea-level projections
2016
Climatic Change
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 decisionmakers 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
doi:10.1007/s10584-016-1858-z
fatcat:3y6pmg5eafa6pmaegwxucpdqke