Estimation of wind storm impacts over Western Germany under future climate conditions using a statistical-dynamical downscaling approach (original) (raw)

Extreme wind storms over Europe in present and future climate: a cluster analysis approach

Meteorologische Zeitschrift, 2008

Boreal winter wind storm situations over Central Europe are investigated by means of an objective cluster analysis. Surface data from the NCEP-Reanalysis and ECHAM4/OPYC3-climate change GHG simulation (IS92a) are considered. To achieve an optimum separation of clusters of extreme storm conditions, 55 clusters of weather patterns are differentiated. To reduce the computational effort, a PCA is initially performed, leading to a data reduction of about 98 %. The clustering itself was computed on 3-day periods constructed with the first six PCs using "k-means" clustering algorithm. The applied method enables an evaluation of the time evolution of the synoptic developments. The climate change signal is constructed by a projection of the GCM simulation on the EOFs attained from the NCEP-Reanalysis. Consequently, the same clusters are obtained and frequency distributions can be compared. For Central Europe, four primary storm clusters are identified. These clusters feature almost 72 % of the historical extreme storms events and add only to 5 % of the total relative frequency. Moreover, they show a statistically significant signature in the associated wind fields over Europe. An increased frequency of Central European storm clusters is detected with enhanced GHG conditions, associated with an enhancement of the pressure gradient over Central Europe. Consequently, more intense wind events over Central Europe are expected. The presented algorithm will be highly valuable for the analysis of huge data amounts as is required for e.g. multi-model ensemble analysis, particularly because of the enormous data reduction.

Return periods of losses associated with European windstorm series in a changing climate

Environmental Research Letters, 2014

Possible future changes of clustering and return periods (RPs) of European storm series with high potential losses are quantified. Historical storm series are identified using 40 winters of reanalysis. Time series of top events (1, 2 or 5 year return levels (RLs)) are used to assess RPs of storm series both empirically and theoretically. Additionally, 800 winters of general circulation model simulations for present and future (2060-2100) climate conditions are investigated. Clustering is identified for most countries, and estimated RPs are similar for reanalysis and present day simulations. Future changes of RPs are estimated for fixed RLs and fixed loss index thresholds. For the former, shorter RPs are found for Western Europe, but changes are small and spatially heterogeneous. For the latter, which combines the effects of clustering and event ranking shifts, shorter RPs are found everywhere except for Mediterranean countries. These changes are generally not statistically significant between recent and future climate. However, the RPs for the fixed loss index approach are mostly beyond the range of preindustrial natural climate variability. This is not true for fixed RLs. The quantification of losses associated with storm series permits a more adequate windstorm risk assessment in a changing climate.

Modelling European winter wind storm losses in current and future climate

Climatic Change, 2010

Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured stormrelated losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs-to our knowledge for the first time-a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climatedamage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for

Analysis of frequency and intensity of European winter storm events from a multi-model perspective, at synoptic and regional scales

2006

This study focuses on the analysis of winter (October-November-December-January-February-March; ONDJFM) storm events and their changes due to increased anthropogenic greenhouse gas concentrations over Europe. In order to assess uncertainties that are due to model formulation, 4 regional climate models (RCMs) with 5 high resolution experiments, and 4 global general circulation models (GCMs) are considered. Firstly, cyclone systems as synoptic scale processes in winter are investigated, as they are a principal cause of the occurrence of extreme, damage-causing wind speeds. This is achieved by use of an objective cyclone identification and tracking algorithm applied to GCMs. Secondly, changes in extreme near-surface wind speeds are analysed. Based on percentile thresholds, the studied extreme wind speed indices allow a consistent analysis over Europe that takes systematic deviations of the models into account. Relative changes in both intensity and frequency of extreme winds and their related uncertainties are assessed and related to changing patterns of extreme cyclones. A common feature of all investigated GCMs is a reduced track density over central Europe under climate change conditions, if all systems are considered. If only extreme (i.e. the strongest 5%) cyclones are taken into account, an increasing cyclone activity for western parts of central Europe is apparent; however, the climate change signal reveals a reduced spatial coherency when compared to all systems, which exposes partially contrary results. With respect to extreme wind speeds, significant positive changes in intensity and frequency are obtained over at least 3 and 20% of the European domain under study (35-72°N and 15°W-43°E), respectively. Location and extension of the affected areas (up to 60 and 50% of the domain for intensity and frequency, respectively), as well as levels of changes (up to +15 and + 200% for intensity and frequency, respectively) are shown to be highly dependent on the driving GCM, whereas differences between RCMs when driven by the same GCM are relatively small.

European winter storms: Dynamical Aspects and Wind Gust Esitimation based on results of Regional Climate Model simulations

2015

Extratropical cyclones in the North Atlantic-European sector are among the most perilous and damaging natural hazards affecting Europe. While most of the severe extratropical cyclones pass by Europe in northeastern direction, a small number of strong storms hit Europe each year. Their destructive power is mainly related to strong wind gusts, sustained high wind speeds or huge amounts of precipitation. Especially the relation between Abschätzung von Schäden und bietet somit Anwendungsmöglichkeiten beispielsweise in der Versicherungswirtschaft. Zusätzlich erweitern die Erkenntnisse dieser Arbeit das Verständnis dynamischer Aspekte und mesoskaliger Prozesse, die entscheidend zur Entwicklung von Winterstürmen (Kyrill und Xynthia) beigetragen haben. Ein umfassendes Verständnis der physikalischen Mechanismen und atmosphärischen Randbedingungen, die mit der Entstehung einzelner Winterstürme in Verbindung stehen, ist für die Vorhersage zukünftiger Sturmereignisse von essentieller Bedeutung.

On the relationship between cyclones and extreme windstorm events over Europe under climate change

Global and Planetary Change, 2004

The relationship between cyclones and extreme wind events over Europe under climate change conditions is analysed using global as well as regional climate model simulations. In this study, climate change simulations based on the Special Report on Emission Scenarios (SRES) A2 and B2 are used. Cyclone systems over the Northeast Atlantic and Europe are identified for the Hadley Centre global general circulation model HadCM3 using an objective algorithm based on the search of the maxima of the Laplacian of the mean sea-level pressure (MSLP). Cyclone tracks are recognized in a second step of the procedure. Extreme cyclone systems are defined via the exceedance of the 95th percentile of the Laplacian of MSLP for each system. Extreme wind events are defined similar by values above the 95th percentile of the daily maximum wind speed at the lowest model level and related to the core pressure of the nearest cyclone system.

Winter storm risk of residential structures – model development and application to the German state of Baden-Württemberg

Natural Hazards and Earth System Science, 2006

The derivation of probabilities of high wind speeds and the establishment of risk curves for storm damage is of prime importance in natural hazard risk analysis. Risk curves allow the assessment of damage being exceeded at a given level of probability. In this paper, a method for the assessment of winter storm damage risk is described in detail and applied to the German state of Baden-Württemberg. Based on meteorological observations of the years 1971-2000 and on damage information of 4 severe storm events, storm hazard and damage risk of residential buildings is calculated on the level of communities. For this purpose, highly resolved simulations of storm wind fields with the Karlsruher Atmospheric Mesoscale Model (KAMM) are performed and a storm damage model is developed. Risk curves including the quantification of the uncertainties are calculated for every community. Local differences of hazard and risk are presented in statewide maps. An average annual winter storm damage to residential buildings of minimum 15 million Euro (reference year 2000) for Baden-Württemberg is expected.

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in Electronic supplementary material The online version of this article (Climatic Change the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statisticaldynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971-2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6-35 % for 2011-2040, of 20-30 % for 2041-2070, and of 40-55 % for 2071-2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.

Downscaling of ECMWF Ensemble Forecasts for Cases of Severe Weather: Ensemble Statistics and Cluster Analysis

Monthly Weather Review, 2008

Dynamical downscaling has been applied to global ensemble forecasts to assess its impact for four cases of severe weather (precipitation and wind) over various parts of Croatia. It was performed with the Croatian 12.2-km version of the Aire Limitée Adaptation Dynamique Développement International (ALADIN) limited-area model, nested in the ECMWF T L 255 (approximately 80 km) global ensemble prediction system (EPS). The 3-hourly EPS output was used to force the ALADIN model over the central European/northern Mediterranean domain.