Near-surface seasonal and annual mean wind speed in Switzerland is investigated using homogenized observations, Twentieth Century Reanalysis (20CRv2c) data and raw model output of a 75 member EURO-COoRdinated Downscaling EXperiment regional climate model (RCM) ensemble for present day and future scenarios. The wind speed observations show a significant decrease in the Alps and on the southern Alpine slopes in the period 1981-2010. However, the 20CRv2c data reveal that the recent trends lie well within the decadal variability over longer time periods and no clear signs of a systematic wind stilling can be found for Switzerland. The ensemble of RCMs shows large biases in the annual mean wind speed over the Jura mountains, and some members also show large biases in the Alps compared to station observations. The spatial distribution of the model biases varies strongly between the RCMs, while the resolution and the driving global model have less impact on the pattern of the model bias. The RCMs are mostly able to represent the seasonality of wind speed on the Plateau but miss important details in complex terrain related to local wind systems. Most models show no significant changes in near-surface mean wind speed until the end of the 21st century. The model ensemble changes range from a 7% decrease to a 6% increase with an ensemble mean decrease of 1 to 2%. Due to model biases, the scale mismatch between model grid and station observations and the missing representation of local winds in the simulations, the changes need to be interpreted with utmost care. Future assessments might lead to major revisions even for the sign of the projected changes, in particular over complex terrain.

Extratropical cyclones experience vastly different genesis conditions at the first point of their tracks. A novel method is introduced to characterize this variability and classify genesis events by computing 30 diagnostic variables that describe the synoptic‐scale environment of 16 029 genesis events in the Northern Hemisphere extratropics, using ERA‐Interim reanalyses from 2000–2011. These variables are referred to as precursors and include parameters characterizing upper‐level forcing, low‐level baroclinicity, thermodynamic stability, surface fluxes and moist processes. The genesis events spread over a large portion of the 30‐dimensional precursor phase space and no obvious clusters occur, which highlights the high variability of cyclogenesis processes and indicates that they form in a continuum rather than a few distinct categories. A projection of the genesis events to the first two principle components (PC) of the precursor phase space allows reduction of the dimensionality and introduction of a meaningful segmentation of the genesis events in five classes. The first two PCs are characterized by upper‐level forcing (e.g. the amplitude of the upper‐level potential vorticity (PV) anomaly) and low‐tropospheric diabatic processes (e.g. precipitation and diabatically produced low‐level PV), respectively. The first of the five classes identified constitutes the centre of the PC1–PC2 phase space and represents average conditions. Composites reveal that the four classes of events characterized by large positive or negative scores of PC1 and PC2 occur in distinct and strongly differing flow regimes, characterized by the strength of the upper‐level forcing, the structure of the upper‐level jet and the amplitude of low‐level moist processes and baroclinicity. The four classes also have clearly differing geographical distributions. Many well‐known cyclogenesis events fall within classes characterized by strong low‐level moist processes with or without strong upper‐level forcing. Also discussed are the robustness of the method and the linkage to classical concepts of cyclone classifications.

The spectral wave model SWAN (Simulating Waves Nearshore) was applied to Lake Zurich, a narrow preAlpine lake in Switzerland. The aim of the study is to investigate whether the model system consisting of SWAN and the numerical weather prediction model COSMO-2 is a suitable tool for wave forecasts for the pre-Alpine Lake Zurich. SWAN is able to simulate short-crested wind-generated surface waves. The model was forced with a time varying wind field taken from COSMO-2 with hourly outputs. Model simulations were compared with measured wave data at one near-shore site during a frontal passage associated with strong on-shore winds. The overall course of the measured wave height is well captured in the SWAN simulation: the wave amplitude significantly increases during the frontal passage followed by a transient drop in amplitude. The wave pattern on Lake Zurich is quite complex. It strongly depends on the inherent variability of the wind field and on the external forcing due to the surrounding complex topography. The influence of the temporal wind resolution is further studied with two sensitivity experiments. The first one considers a low-pass filtered wind field, based on a 2-h running mean of COSMO-2 output, and the second experiment uses simple synthetic gusts, which are implemented into the SWAN model and take into account short-term fluctuations of wind speed at 1-sec resolution. The wave field significantly differs for the 1-h and 2-h simulations, but is only negligibly affected by the gusts.

We determine wind‐wave properties and estimate the wave exposure along the entire shore of Lake Überlingen, a subbasin of Lake Constance, using a third‐generation spectral wave model (SWAN), and compare results to field data on surface waves at three different sites and to predictions from a simple fetch‐based model (FETCH). Forcing the models with local wind data measured at a meteorological station in the center of Lake Überlingen provides better simulation results than a spatially resolved wind field obtained from the numerical weather system of the Consortium for Small Scale Modeling (COSMO). Because wave diffraction is considered in SWAN but not in FETCH, SWAN provides on average higher wave heights than FETCH and agrees better with observations for waves with heights above 0.15 m. Wave exposure, that is, the frequency of occurrence of wind waves with heights above 0.15 m, varied substantially between different sites along the shore even at small spatial scales. Although the general pattern of wave exposure was similar for simulations with SWAN and FETCH, the model results differed at specific sites, especially at bays and headlands, and also with respect to the absolute values for wave exposure and its variation between sites. Simple fetch models may be insufficient to reliably quantify the spatial variability of wave exposure at small spatial scales, and complex wave models such as SWAN may be required even in medium‐size lakes.

ECMWF analysis data in conjunction with infrared satellite imagery and surface weather analyses from the German Weather Service are used to investigate 15 significant central European tornadoes (F2 intensity on the Fujita scale) that occurred in 2005 and 2006. The primary goals of the work are to: (i) determine the typical synoptic and mesoscale environments that are conducive to European tornadogenesis; (ii) compare and contrast the said environments with those found in the central United States (US), with a specific focus on severe storm predictors: and (iii) elucidate a methodology for the real-time forecasting of these destructive storms that, in addition to the use of severe storm predictors, leans heavily on the potential vorticity (PV) and Lagrangian frameworks of analysis.With the caveats that there is significant case-to-case variability and the sample size is relatively small, the results illustrate that most European tornadoes form close to (within 200 km of) a distinct upper-level PV anomaly and a majority under the cyclonic side of an upper-level jet streak. Lower-level forcing, in the form of surface fronts, is also found to be present in a number of cases. With regards to severe storm predictors (convective available potential energy, storm-relative helicity and the energy helicity index), this study confirms the earlier findings that, while representative values for European tornadic environments are substantially lower than their US counterparts, they do provide useful predictive information in that their values tend to be markedly higher than the local, monthly climatology. A subsequent Lagrangian analysis that isolates the coherent air streams present in US and European tornadoes provides significant insight into the discrepancies in both the synoptic environments and the absolute magnitude of the severe storm predictors. Backward trajectories launched from the tornado genesis time and position, illustrate that low-level flow blocking by the Alps and the relatively-colder sea surface temperatures found over the Atlantic Ocean (in contrast to the Gulf of Mexico) play a primary role in reducing the dynamic and thermodynamic instabilities in European tornado environments. (C) 2011 Elsevier B.V. All rights reserved.