Detection and attribution of anthropogenic climate change signals in sea level rise (SLR) has experienced considerable attention during the last decades. Here we provide evidence that superimposed on any possible anthropogenic trend there is a significant amount of natural decadal and multidecadal variability. Using a set of 60 centennial tide gauge records and an ocean reanalysis, we find that sea levels exhibit long-term correlations on time scales up to several decades that are independent of any systematic rise. A large fraction of this long-term variability is related to the steric component of sea level, but we also find long-term correlations in current estimates of mass loss from glaciers and ice caps. These findings suggest that (i) recent attempts to detect a significant acceleration in regional SLR might underestimate the impact of natural variability and (ii) any future regional SLR threshold might be exceeded earlier/later than from anthropogenic change alone.
Abstract. This paper presents an advanced approach to statistically analyse storm surge events. In former studies the highest water level during a storm surge event usually was the only parameter that was used for the statistical assessment. This is not always sufficient, especially when statistically analysing storm surge scenarios for event-based risk analyses. Here, Archimedean Copula functions are applied and allow for the consideration of further important parameters in addition to the highest storm surge water levels. First, a bivariate model is presented and used to estimate exceedance probabilities of storm surges (for two tide gauges in the German Bight) by jointly analysing the important storm surge parameters "highest turning point" and "intensity". Second, another dimension is added and a trivariate fully nested Archimedean Copula model is applied to additionally incorporate the significant wave height as an important wave parameter. With the presented methodology, reliable and realistic exceedance probabilities are derived and can be considered (among others) for integrated flood risk analyses contributing to improve the overall results. It is highlighted that the concept of Copulas represents a promising alternative for facing multivariate problems in coastal engineering.
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