Sönke Dangendorf

Timescales for detecting a significant acceleration in sea level rise

There is observational evidence that global sea level is rising and there is concern that the rate of rise will increase, significantly threatening coastal communities. However, considerable debate remains as to whether the rate of sea level rise is currently increasing and, if so, by how much. Here we provide new insights into sea level accelerations by applying the main methods that have been used previously to search for accelerations in historical data, to identify the timings (with uncertainties) at which accelerations might first be recognized in a statistically significant manner (if not apparent already) in sea level records that we have artificially extended to 2100. We find that the most important approach to earliest possible detection of a significant sea level acceleration lies in improved understanding (and subsequent removal) of interannual to multidecadal variability in sea level records.

Evidence for long‐term memory in sea level

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.

Mean sea level variability in the North Sea: Processes and implications

Mean sea level (MSL) variations across a range of time scales are examined for the North Sea under the consideration of different forcing factors since the late 19th century. We use multiple linear regression models, which are validated for the second half of the 20th century against the output of a tide+surge model, to determine the barotropic response of the ocean to fluctuations in atmospheric forcing. We find that local atmospheric forcing mainly initiates MSL variability on time scales up to a few years, with the inverted barometric effect dominating the variability along the UK and Norwegian coastlines and wind controlling the MSL variability in the south from Belgium up to Denmark. On decadal time scales, MSL variability mainly reflects steric changes, which are largely forced remotely. A spatial correlation analysis of altimetry observations and gridded steric heights suggests evidence for a coherent signal extending from the Norwegian shelf down to the Canary Islands. This fits with the theory of longshore wind forcing along the eastern boundary of the North Atlantic causing coastally trapped waves to propagate over thousands of kilometers along the continental slope. Implications of these findings are assessed with statistical Monte-Carlo experiments. It is demonstrated that the removal of known variability increases the signal to noise ratio with the result that: (i) linear trends can be estimated more accurately; (ii) possible accelerations (as expected, e.g., due to anthropogenic climate change) can be detected much earlier. Such information is of crucial importance for anticipatory coastal management, engineering, and planning.

Reassessment of 20th century global mean sea level rise

Significance Estimates of global mean sea level (GMSL) before the advent of satellite altimetry vary widely, mainly because of the uneven coverage and limited temporal sampling of tide gauge records, which track local sea level rather than the global mean. Here we introduce an approach that combines recent advances in solid Earth and geoid corrections for individual tide gauges with improved knowledge about their geographical representation of ocean internal variability. Our assessment yields smaller trends before 1990 than previously reported, leading to a larger overall acceleration; identifies three major explanations for differences with previous estimates; and reconciles observational GMSL estimates with the sum of individually modeled contributions from the Coupled Model Intercomparison Project 5 database for the entire 20th century. The rate at which global mean sea level (GMSL) rose during the 20th century is uncertain, with little consensus between various reconstructions that indicate rates of rise ranging from 1.3 to 2 mm⋅y−1. Here we present a 20th-century GMSL reconstruction computed using an area-weighting technique for averaging tide gauge records that both incorporates up-to-date observations of vertical land motion (VLM) and corrections for local geoid changes resulting from ice melting and terrestrial freshwater storage and allows for the identification of possible differences compared with earlier attempts. Our reconstructed GMSL trend of 1.1 ± 0.3 mm⋅y−1 (1σ) before 1990 falls below previous estimates, whereas our estimate of 3.1 ± 1.4 mm⋅y−1 from 1993 to 2012 is consistent with independent estimates from satellite altimetry, leading to overall acceleration larger than previously suggested. This feature is geographically dominated by the Indian Ocean–Southern Pacific region, marking a transition from lower-than-average rates before 1990 toward unprecedented high rates in recent decades. We demonstrate that VLM corrections, area weighting, and our use of a common reference datum for tide gauges may explain the lower rates compared with earlier GMSL estimates in approximately equal proportion. The trends and multidecadal variability of our GMSL curve also compare well to the sum of individual contributions obtained from historical outputs of the Coupled Model Intercomparison Project Phase 5. This, in turn, increases our confidence in process-based projections presented in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.

Detecting anthropogenic footprints in sea level rise

While there is scientific consensus that global and local mean sea level (GMSL and LMSL) has risen since the late nineteenth century, the relative contribution of natural and anthropogenic forcing remains unclear. Here we provide a probabilistic upper range of long-term persistent natural GMSL/LMSL variability (P=0.99), which in turn, determines the minimum/maximum anthropogenic contribution since 1900. To account for different spectral characteristics of various contributing processes, we separate LMSL into two components: a slowly varying volumetric component and a more rapidly changing atmospheric component. We find that the persistence of slow natural volumetric changes is underestimated in records where transient atmospheric processes dominate the spectrum. This leads to a local underestimation of possible natural trends of up to ∼1 mm per year erroneously enhancing the significance of anthropogenic footprints. The GMSL, however, remains unaffected by such biases. On the basis of a model assessment of the separate components, we conclude that it is virtually certain (P=0.99) that at least 45% of the observed increase in GMSL is of anthropogenic origin.

A review of trend models applied to sea level data with reference to the “acceleration‐deceleration debate”

Global sea levels have been rising through the past century and are projected to rise at an accelerated rate throughout the 21st century. This has motivated a number of authors to search for already existing accelerations in observations, which would be, if present, vital for coastal protection planning purposes. No scientific consensus has been reached yet as to how a possible acceleration could be separated from intrinsic climate variability in sea level records. This has led to an intensive debate on its existence and, if absent, also on the general validity of current future projections. Here we shed light on the controversial discussion from a methodological point of view. To do so, we provide a comprehensive review of trend methods used in the community so far. This resulted in an overview of 30 methods, each having its individual mathematical formulation, flexibilities, and characteristics. We illustrate that varying trend approaches may lead to contradictory acceleration-deceleration inferences. As for statistics-oriented trend methods, we argue that checks on model assumptions and model selection techniques yield a way out. However, since these selection methods all have implicit assumptions, we show that good modeling practices are of importance too. We conclude at this point that (i) several differently characterized methods should be applied and discussed simultaneously, (ii) uncertainties should be taken into account to prevent biased or wrong conclusions, and (iii) removing internally generated climate variability by incorporating atmospheric or oceanographic information helps to uncover externally forced climate change signals.

Long‐term variations in global sea level extremes

Decadal to multidecadal variations in sea level extremes unrelated to mean sea level changes have been investigated using long tide gauge records distributed worldwide. A state space approach has been applied that provides robust solutions and uncertainties of the time evolving characteristics of extremes, allowing for data gaps and uneven sampling, both common features of historical sea level time series. Two different models have been formulated for the intensity and for the occurrence of extreme sea level events and have been applied independently to each tide gauge record. Our results reveal two key findings: first, the intensity and the frequency of occurrence of extreme sea levels unrelated to mean sea level vary coherently on decadal scales in most of the sites examined (63 out of 77) and, second, extreme sea level changes are regionally consistent, thus pointing toward a common large-scale forcing. This variability of extremes associated with climate drivers should be considered in the framework of climate change studies.

Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis

One of the main consequences of mean sea level rise (SLR) on human settlements is an increase in flood risk due to an increase in the intensity and frequency of extreme sea levels (ESL). While substantial research efforts are directed towards quantifying projections and uncertainties of future global and regional SLR, corresponding uncertainties in contemporary ESL have not been assessed and projections are limited. Here we quantify, for the first time at global scale, the uncertainties in present-day ESL estimates, which have by default been ignored in broad-scale sea-level rise impact assessments to date. ESL uncertainties exceed those from global SLR projections and, assuming that we meet the Paris agreement goals, the projected SLR itself by the end of the century in many regions. Both uncertainties in SLR projections and ESL estimates need to be understood and combined to fully assess potential impacts and adaptation needs.

Annual Sea Level Changes on the North American Northeast Coast: Influence of Local Winds and Barotropic Motions

AbstractUnderstanding the relationship between coastal sea level and the variable ocean circulation is crucial for interpreting tide gauge records and projecting sea level rise. In this study, annual sea level records (adjusted for the inverted barometer effect) from tide gauges along the North American northeast coast over 1980–2010 are compared to a set of data-assimilating ocean reanalysis products as well as a global barotropic model solution forced with wind stress and barometric pressure. Correspondence between models and data depends strongly on model and location. At sites north of Cape Hatteras, the barotropic model shows as much (if not more) skill than ocean reanalyses, explaining about 50% of the variance in the adjusted annual tide gauge sea level records. Additional numerical experiments show that annual sea level changes along this coast from the barotropic model are driven by local wind stress over the continental shelf and slope. This result is interpreted in the light of a simple dynamic...

The Seasonal Mean Sea Level Cycle in the Southeastern North Sea

ABSTRACT Dangendorf, S., Wahl, T., Mudersbach, C. and Jensen, J., 2013. The Seasonal Mean Sea Level Cycle in the Southeastern North Sea The seasonal cycle is a prominent feature in Mean Sea Level (MSL) time series with considerable influences on flood risk in coastal areas. When analyzing MSL it is often assumed that the seasonal cycle is a stationary process, independent from inter-annual variations, but there is no obvious reason for such an assumption. In this paper the seasonal cycle of MSL at 13 tide gauges in the German Bight is investigated for its average character as well as its time dependence over the past 166 years. A seasonal trend decomposition method is used to analyze the inter-annual fluctuations in amplitudes and phases of the seasonal cycle. In the German Bight the seasonal cycle accounts for up to 44 % of the observed monthly MSL variability. The mean seasonal cycle peaks during November at all stations. The mean amplitude varies between 14 and 20 cm and increases from the south-western to the north-eastern stations. Throughout the last 166 years it is found that the amplitudes as well as the phases of the seasonal cycle are marked by a considerable inter-annual variability. While most records, all starting in the 1930s or later, do not exhibit a significant trend the longest record at Cuxhaven displays a significant long-term trend of 0.2 ± 0.1 mm/yr. This trend is mainly caused by large values at the end of the 1970s and the beginning 1980s. Simultaneously, the annual peaks shift from the late autumn to winter months (December to February). These changes are caused by extraordinary large trends during the months from January to March, exceeding those in the remaining months by up to 4 mm/yr. These changes are in phase with an intensification of large-scale atmospheric circulation patterns over the North Atlantic bringing more frequent westerly winds over the North Sea.