Suchergebnisse

Abstract. Storm surges represent a major threat to many low-lying coastal
areas in the world. In the aftermath of an extreme event, the extent to
which the event was unusual and the potential contribution of climate change
in shaping the event are often debated. Commonly analyzes that allow for
such assessments are not available right away but are only provided with
often considerable time delay. To address this gap, a new tool was developed
and applied to storm surges along the German North Sea and Baltic Sea coasts.
The tool integrates real-time measurements with long-term statistics to put
ongoing extremes or the course of a storm surge season into a climatological
perspective in near real time. The approach and the concept of the tool are
described and discussed. To illustrate the capabilities, several exemplary
cases from the storm surge seasons 2018/2019 and 2019/2020 are discussed. It
is concluded that the tool provides support in the near-real-time assessment
and evaluation of storm surge extremes. It is further argued that the
concept is transferable to other regions and/or coastal hazards.

Abstract. Extratropical storms are one of the major coastal hazards along the coastline of the German Bight, the southeastern part of the North Sea, and a major driver of coastal protection efforts. However, the predictability of these regional extreme events on a seasonal scale is still limited. We therefore improve the seasonal prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) large-ensemble decadal hindcast system for German Bight storm activity (GBSA) in winter. We define GBSA as the 95th percentiles of three-hourly geostrophic wind speeds in winter, which we derive from mean sea-level pressure (MSLP) data. The hindcast system consists of an ensemble of 64 members, which are initialized annually in November and cover the winters of 1960/61–2017/18. We consider both deterministic and probabilistic predictions of GBSA, for both of which the full ensemble produces poor predictions in the first winter. To improve the skill, we observe the state of two physical predictors of GBSA, namely 70 hPa temperature anomalies in September, as well as 500 hPa geopotential height anomalies in November, in areas where these two predictors are correlated with winter GBSA. We translate the state of these predictors into a first guess of GBSA and remove ensemble members with a GBSA prediction too far away from this first guess. The resulting subselected ensemble exhibits a significantly improved skill in both deterministic and probabilistic predictions of winter GBSA. We also show how this skill increase is associated with better predictability of large-scale atmospheric patterns.

Abstract. The shallow waters off the coast of Norderney in the southern North Sea are characterised by a higher frequency of rogue wave occurrences than expected. Here, rogue waves refer to waves exceeding twice the significant wave height. The role of nonlinear processes in the generation of rogue waves at this location is currently unclear. Within the framework of the Korteweg–de Vries (KdV) equation, we investigated the discrete soliton spectra of measured time series at Norderney to determine differences between time series with and without rogue waves. For this purpose, we applied a nonlinear Fourier transform (NLFT) based on the Korteweg–de Vries equation with vanishing boundary conditions (vKdV-NLFT). At measurement
sites where the propagation of waves can be described by the KdV equation, the solitons in the discrete nonlinear vKdV-NLFT spectrum correspond to physical solitons. We do not know whether this is the case at the considered measurement site. In this paper, we use the nonlinear spectrum to classify rogue wave and non-rogue wave time series. More specifically, we investigate if the discrete nonlinear spectra of measured time series with visible rogue waves differ from those without rogue waves. Whether or not the discrete part of the nonlinear spectrum corresponds to solitons with respect to the conditions at the measurement site is not relevant in this case, as we are not concerned with how these spectra change during propagation. For each time series containing a rogue wave, we were able to identify at least one soliton in the nonlinear spectrum that contributed to the occurrence of the rogue wave in that time series. The amplitudes of these solitons were found to be smaller than the crest height of the corresponding rogue wave, and interaction with the continuous wave spectrum is needed to fully explain the observed rogue wave.
Time series with and without rogue waves showed different characteristic soliton spectra. In most of the spectra calculated from rogue wave time series, most of the solitons clustered around similar heights, but the largest soliton was outstanding, with an amplitude significantly larger than all other solitons. The presence of a clearly outstanding soliton in the spectrum was found to be an indicator pointing towards the enhanced probability of the occurrence of a rogue wave in the time series. Similarly, when the discrete spectrum appears as a cluster of solitons without the presence of a clearly outstanding soliton, the presence of a rogue wave in the observed time series is unlikely. These results suggest that soliton-like and nonlinear processes substantially contribute to the enhanced occurrence of rogue waves off Norderney.

Abstract. A new wave data set from the southern North Sea covering the period 2011–2016 and composed of wave buoy and radar measurements sampling the sea surface height at frequencies between 1.28 and 4 Hz was quality controlled and scanned for the presence of rogue waves. Here, rogue waves refer to waves whose height exceeds twice the significant wave height. Rogue wave frequencies were analyzed and compared to Rayleigh and Forristall distributions, and spatial, seasonal, and long-term variability was assessed. Rogue wave frequency appeared to be relatively constant over the course of the year and uncorrelated among the different measurement sites. While data from buoys basically correspond with expectations from the Forristall distribution, radar measurement showed some deviations in the upper tail pointing towards higher rogue wave frequencies. The amount of data available in the upper tail is, however, still too limited to allow a robust assessment. Some indications were found that the distribution of waves in samples with and without rogue waves was different in a statistical sense. However, differences were small and deemed not to be relevant as attempts to use them as a criterion for rogue wave detection were not successful in Monte Carlo experiments based on the available data.

Abstract. We evaluate the prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcast system for German Bight storm activity (GBSA) on a multiannual to decadal scale. We define GBSA every year via the most extreme 3-hourly geostrophic wind speeds, which are derived from mean sea-level pressure (MSLP) data. Our 64-member ensemble of annually initialized hindcast simulations spans the time period 1960–2018. For this period, we compare deterministically and probabilistically predicted winter MSLP anomalies and annual GBSA with a lead time of up to 10 years against observations. The model produces poor deterministic predictions of GBSA and winter MSLP anomalies for individual years but fair predictions for longer averaging periods. A similar but smaller skill difference between short and long averaging periods also emerges for probabilistic predictions of high storm activity. At long averaging periods (longer than 5 years), the model is more skillful than persistence- and climatology-based predictions. For short aggregation periods (4 years and less), probabilistic predictions are more skillful than persistence but insignificantly differ from climatological predictions. We therefore conclude that, for the German Bight, probabilistic decadal predictions (based on a large ensemble) of high storm activity are skillful for averaging periods longer than 5 years. Notably, a differentiation between low, moderate, and high storm activity is necessary to expose this skill.

Abstract. The simultaneous occurrence of extreme events gained more and more attention from scientific research in the last couple of years.
Compared to the occurrence of single extreme events, co-occurring or compound extremes may substantially increase risks.
To adequately address such risks, improving our understanding of compound flood events in Europe is necessary and requires reliable estimates of their probability of occurrence together with potential future changes.
In this study compound flood events in northern and central Europe were studied using a Monte Carlo-based approach that avoids the use of copulas.
Second, we investigate if the number of observed compound extreme events is within the expected range of 2 standard deviations of randomly occurring compound events. This includes variations of several parameters to test the stability of the identified patterns. Finally, we analyse if the observed compound extreme events had a common large-scale meteorological driver.
The results of our investigation show that rivers along the west-facing coasts of Europe experienced a
higher amount of compound flood events than expected by pure chance.
In these regions, the vast majority of the observed compound flood events seem to be related to the cyclonic westerly general weather pattern (Großwetterlage).

Abstract. Storm tides represent a major threat to the low-lying German North Sea
coast. Knowledge of extremes is essential for the design of reliable and
robust coastal defences. A storm tide that occurred on 12–13 March 1906
along the German Bight coastline still represents one of the strongest
events on record. For this event, detailed knowledge of atmospheric and
hydrodynamic conditions is still lacking. To assess the potential impact of
such an event on today's coastline, century-long atmospheric reanalysis data
together with a manual synoptic reconstruction based on archived weather
data were used to drive a tide-surge model and to simulate water levels
during the event. Sensitivity experiments were performed to estimate
potential amplification of water levels that could have been caused by
different time lags between the storm and the astronomical tide. Comparison
between the model results and the limited available observational data
indicated that the water levels could be reasonably reconstructed using
wind fields from the manual synoptic approach and some of the reanalysis
ensemble members. The amplification potential was found to be low because
the storm occurred during spring tide and shifts in the phase of the
astronomic tide yielded only small changes in total water levels. To
summarise, if pressure data are available at relevant locations, historical
storm surges can be simulated with reanalysis products and also with a
manual synoptic reconstruction.

Global and regional change clearly affects the structure and functioning of ecosystems in shelf seas. However, complex interactions within the shelf seas hinder the identification and unambiguous attribution of observed changes to drivers. These include variability in the climate system, in ocean dynamics, in biogeochemistry, and in shelf sea resource exploitation in the widest sense by societies. Observational time series are commonly too short, and resolution, integration time, and complexity of models are often insufficient to unravel natural variability from anthropogenic perturbation. The North Sea is a shelf sea of the North Atlantic and is impacted by virtually all global and regional developments. Natural variability (from interannual to multidecadal time scales) as response to forcing in the North Atlantic is overlain by global trends (sea level, temperature, acidification) and alternating phases of direct human impacts and attempts to remedy those. Human intervention started some 1000 years ago (diking and associated loss of wetlands), expanded to near-coastal parts in the industrial revolution of the mid-19th century (river management, waste disposal in rivers), and greatly accelerated in the mid-1950s (eutrophication, pollution, fisheries). The North Sea is now a heavily regulated shelf sea, yet societal goals (good environmental status versus increased uses), demands for benefits and policies diverge increasingly. Likely, the southern North Sea will be re-zoned as riparian countries dedicate increasing sea space for offshore wind energy generation - with uncertain consequences for the system's environmental status. We review available observational and model data (predominantly from the southeastern North Sea region) to identify and describe effects of natural variability, of secular changes, and of human impacts on the North Sea ecosystem, and outline developments in the next decades in response to environmental legislation, and in response to increased use of shelf sea space