North Sea storm surge statistics based on projections in a warmer climate: How important are the driving GCM and the chosen emission scenario?

Climate models, simulating the effect of plausible future emission concentrations (scenarios), describe for the future an increase of high wind speeds over Northwest Europe during winter. With the help of a hydrodynamic model of the North Sea, these atmospheric future conditions are used to project storm surge heights for the Northwest European Shelf Sea. Four different projections are presented, all generated with the same Regional Climate Model, which itself is driven with two different Global Climate Model scenarios both exposed to two different emission scenarios. The analyses are carried out for a 30‐year time‐slice at the end of the 21st century. All four ensemble members point to a significant increase of storm surge elevations for the continental North Sea coast of between 15 and almost 25 cm. However, the different storm surge projections are not statistically distinguishable from each other but can provide a range of possible evolutions of surge extremes in a warmer climate

Storm surges: perspectives and options

This review paper attempts to summarize the scattered and fragmented knowledge about past and possible future changing storm-surge statistics using the particularly well-studied case of the North Sea as an example. For this region, a complete and robust analysis methodology has been developed in recent years. This methodology is based on dynamical and statistical models. Using the concept of dynamical downscaling, development during recent decades, when sufficiently good and homogeneous weather data exist, has been "reconstructed,'' and scenarios of possible future change are described. "Localization'' allows estimation of changes at specific sites, e. g., harbors. As local water-level statistics depend not only on climate variations but also on local modifications of the local bathymetry, new options for adaptation emerge. For the case of Hamburg, an option for such future adaptations is discussed

Climate change and North Sea storm surge extremes: an ensemble study of storm surge extremes expected in a changed climate projected by four different regional climate models

The coastal zones are facing the prospect of changing storm surge statistics due to anthropogenic climate change. In the present study, we examine these prospects for the North Sea based on numerical modelling. The main tool is the barotropic tide-surge model TRIMGEO (Tidal Residual and Intertidal Mudflat Model) to derive storm surge climate and extremes from atmospheric conditions. The analysis is carried out by using an ensemble of four 30-year atmospheric regional simulations under present-day and possible future-enhanced greenhouse gas conditions. The atmospheric regional simulations were prepared within the EU project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). The research strategy of PRUDENCE is to compare simulations of different regional models driven by the same global control and climate change simulations. These global conditions, representative for 1961--1990 and 2071--2100 were prepared by the Hadley Center based on the IPCC A2 SRES scenario. The results suggest that under future climatic conditions, storm surge extremes may increase along the North Sea coast towards the end of this century. Based on a comparison between the results of the different ensemble members as well as on the variability estimated from a high-resolution storm surge reconstruction of the recent decades it is found that this increase is significantly different from zero at the 95% confidence level for most of the North Sea coast. An exception represents the East coast of the UK which is not affected by this increase of storm surge extremes

Abschaetzung einer zukuenftigen Niederschlagsentwicklung mit statistischen Methoden unter Einbezug raeumlicher Differenzierungsverfahren am Beispiel des suedwesteuropaeischen Raums

This study presents a method to identify homogenous sub-regions and their corresponding large-scale sector in statistical-empirical downscaling models systematically. The analysis was done with a gridded observed sea level pressure field (SLP) of the North Atlantic sector as predictor and time series of precipitation at 82 Stations as dependent variable, distributed nearly homogeneously in Spain and the south of France. The precipitation stations were classified in more homogeneous groups by cluster analysis. For some of the resulting groups the domain of the SLP field with the highest influence on rainfall was also identified. In the next step Canonical Correlation Analysis was applied between the groups suitable for a statistical downscaling and their corresponding SLP sector. The result is that the statistical skill in the validation period is increased compared to the standard downscaling model. Last, this statistical downscaling model are applied to a climate change experiment with ECHAM4-OPYC3 under increasing atmospheric CO_2 concentrations. (orig.)Available from TIB Hannover: RA 3251(2001/28) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

A methodology for spatial data selection for statistical downscaling purposes A case study of precipitation in southwestern Europe

In this study, the sensitivity of the estimation of small-scale climate variables using the technique of statistical downscaling is investigated and one method to select the most suitable input data is presented. For the example of precipitation in southwest Europe, the input data are selected systematically by extracting those stations that show a strong statistical relation in time with North Atlantic sea level pressure (SLP). From these stations the sector of North Atlantic SLP is selected that best explains the dominant spatial pattern of regional precipitation. For comparison, one alternative, slightly different geographical box is used. For both sectors a statistical model for the estimation of future rainfall in the southwest of Europe is constructed. It is shown that the method of statistical downscaling is sensitive to small changes of the input data and that the estimations of future precipitation show remarkable differences for the two different Atlantic SLP sectors considered. Possible reasons are discussed. (orig.)Available from TIB Hannover: RA 3251(2001/35) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Salt Marsh Accretion and Storm Tide Variation: an Example from a Barrier Island in the North Sea

We reconstruct past accretion rates of a salt marsh on the island of Sylt, Germany, using measurements of the radioisotopes 210Pb and 137Cs, as well as historical aerial photographs. Results from three cores indicate accretion rates varying between 1 and 16 mm year−1. Comparisons with tide gauge data show that high accretion rates during the 1980s and 1990s coincide with periods of increased storm activity. We identify a critical inundation height of 18 cm below which the strength of a storm seems to positively influence salt marsh accretion rates and above which the frequency of storms becomes the major factor. In addition to sea level rise, we conclude that in low marsh zones subject to higher inundation levels, mean storm strength is the major factor affecting marsh accretion, whereas in high marsh zones with lower inundation levels, it is storm frequency that impacts marsh accretion