[1] We report the observation of two stellar occultations by Titan on 14 November 2003, using stations in the Indian Ocean, southern Africa, Spain, and northern and southern Americas. These occultations probed altitudes between $550 and 250 km ($1 to 250 mbar) in Titan's upper stratosphere. The light curves reveal a sharp inversion layer near 515 ± 6 km altitude (1.5 mbar pressure level), where the temperature increases by 15 K in only 6 km. This layer is close to an inversion layer observed fourteen months later by the Huygens HASI instrument during the entry of the probe in Titan's atmosphere on 14 January 2005 [Fulchignoni et al., 2005]. Central flashes observed during the first occultation provide constraints on the zonal wind regime at 250 km, with a strong northern jet ($200 m s À1 ) around the latitude 55°N, wind velocities of $150 m s À1 near the equator, and progressively weaker winds as more southern latitudes are probed. The haze distribution around Titan's limb at 250 km altitude is close to that predicted by the Global Circulation Model of Rannou et al. (2004) in the southern hemisphere, but a clearing north of 40°N is necessary to explain our data. This contrasts with Rannou et al.'s (2004) model, which predicts a very thick polar hood over Titan's northern polar regions. Simultaneous observations of the flashes at various wavelengths provide a dependence of t / l Àq , with q = 1.8 ± 0.5 between 0.51 and 2.2 mm for the tangential optical depth of the hazes at 250 km altitude.

The purpose of this work is to present a methodology aimed at predicting extreme wind speeds over Switzerland. Generalized additive models are used to regionalize wind statistics for Swiss weather stations using a number of variables that describe the main physiographical features of the country. This procedure enables one to present the results for Switzerland in the form of a map that provides the 98th percentiles of daily maximum wind speeds (W98) at a 10-m anemometer height for cells with a 50-m grid interval. This investigation comprises three major steps. First, meteorological data recorded by the weather stations was gathered to build local wind statistics at each station. Then, data describing the topographic and landscape characteristics of the country were prepared using geographic information systems (GIS). Third, appropriate regression models were selected to make spatially explicit predictions of extreme wind speeds in Switzerland. The predictions undertaken in this study provide realistic values of the W98. The effects of topography on the results are particularly conspicuous. Wind speeds increase with altitude and are greatest on mountain peaks in the Alps, as would be intuitively expected. Relative errors between observations and model results calculated for the meteorological stations do not exceed 30%, and only 12 out of 70 stations exhibit errors that exceed 20%. The combination of GIS techniques and statistical models used to predict a highly uncertain variable, such as extreme wind speed, yields interesting results that can be extended to other fields, such as the assessment of storm damage on infrastructures.

This study reports on the ability of the Canadian Regional Climate Model to simulate the surface wind gusts of 24 severe mid-latitude storms in Switzerland during the period 1990-2010. A multiple self-nesting approach is used, reaching a final 2-km grid which is centred over Switzerland, a country characterised by complex topography. A physicallybased wind gust parameterization scheme is applied to simulate local surface gusts. Model performance is evaluated by comparing simulated wind speeds to time series at weather stations. While a number of simulated variables are reproduced in a realistic manner, the surface wind gusts show differences when compared to observed values. Results indicate that the performance of this parameterization scheme not only depends on the accuracy of the simulated planetary boundary layer, the vertical temperature, wind speed and atmospheric humidity profiles, but also on the accuracy of the reproduction of the surface fields such as temperature and moisture.

Abstract. A storm loss model that was first developed forGermany is applied to the much smaller geographic area of the canton of Vaud, in Western Switzerland. 24 major wind storms that struck the region during the period 1990-2010 are analysed, and outputs are compared to loss observations provided by an insurance company. Model inputs include population data and daily maximum wind speeds from weather stations. These measured wind speeds are regionalised in the canton of Vaud following different methods, using either basic interpolation techniques from Geographic Information Systems (GIS), or by using an existing extreme wind speed map of Switzerland whose values are used as thresholds. A third method considers the wind power, integrating wind speeds temporally over storm duration to calculate losses. Outputs show that the model leads to similar results for all methods, with Pearson's correlation and Spearman's rank coefficients of roughly 0.7. Bootstrap techniques are applied to test the model's robustness. Impacts of population growth and possible changes in storminess under conditions of climate change shifts are also examined for this region, emphasizing high shifts in economic losses related to small increases of input wind speeds.