Vernez D.,University of Geneva |
Milon A.,University of Geneva |
Vuilleumier L.,Federal Office of Meteorology and Climatology MeteoSwiss |
Bulliard J.-L.,University of Lausanne
British Journal of Dermatology | Year: 2012
Background The dose-response between ultraviolet (UV) exposure patterns and skin cancer occurrence is not fully understood. Sun-protection messages often focus on acute exposure, implicitly assuming that direct UV radiation is the key contributor to the overall UV exposure. However, little is known about the relative contribution of the direct, diffuse and reflected radiation components. Objective To investigate solar UV exposure patterns at different body sites with respect to the relative contribution of the direct, diffuse and reflected radiation. Methods A three-dimensional numerical model was used to assess exposure doses for various body parts and exposure scenarios of a standing individual (static and dynamic postures). The model was fed with erythemally weighted ground irradiance data for the year 2009 in Payerne, Switzerland. A year-round daily exposure (08:00-17:00 h) without protection was assumed. Results For most anatomical sites, mean daily doses were high (typically 6·2-14·6 standard erythemal doses) and exceeded the recommended exposure values. Direct exposure was important during specific periods (e.g. midday during summer), but contributed moderately to the annual dose, ranging from 15% to 24% for vertical and horizontal body parts, respectively. Diffuse irradiation explained about 80% of the cumulative annual exposure dose. Acute diffuse exposures were also observed during cloudy summer days. Conclusions The importance of diffuse UV radiation should not be underestimated when advocating preventive measures. Messages focused on avoiding acute direct exposures may be of limited efficiency to prevent skin cancers associated with chronic exposure. © 2012 The Authors. BJD © 2012 British Association of Dermatologists.
Hurter F.,ETH Zurich |
Maier O.,Federal Office of Meteorology and Climatology MeteoSwiss
Atmospheric Measurement Techniques | Year: 2013
We reconstruct atmospheric wet refractivity profiles for the western part of Switzerland with a least-squares collocation approach from data sets of (a) zenith path delays that are a byproduct of the GPS (global positioning system) processing, (b) ground meteorological measurements, (c) wet refractivity profiles from radio occultations whose tangent points lie within the study area, and (d) radiosonde measurements. Wet refractivity is a parameter partly describing the propagation of electromagnetic waves and depends on the atmospheric parameters temperature and water vapour pressure. In addition, we have measurements of a lower V-band microwave radiometer at Payerne. It delivers temperature profiles at high temporal resolution, especially in the range from ground to 3000 m a.g.l., though vertical information content decreases with height. The temperature profiles together with the collocated wet refractivity profiles provide near-continuous dew point temperature or relative humidity profiles at Payerne for the study period from 2009 to 2011. In the validation of the humidity profiles, we adopt a two-step procedure. We first investigate the reconstruction quality of the wet refractivity profiles at the location of Payerne by comparing them to wet refractivity profiles computed from radiosonde profiles available for that location. We also assess the individual contributions of the data sets to the reconstruction quality and demonstrate a clear benefit from the data combination. Secondly, the accuracy of the conversion from wet refractivity to dew point temperature and relative humidity profiles with the radiometer temperature profiles is examined, comparing them also to radiosonde profiles. For the least-squares collocation solution combining GPS and ground meteorological measurements, we achieve the following error figures with respect to the radiosonde reference: maximum median offset of relative refractivity error is -16% and quartiles are 5% to 40% for the lower troposphere. We further added 189 radio occultations that met our requirements. They mostly improved the accuracy in the upper troposphere. Maximum median offsets have decreased from 120% relative error to 44% at 8 km height. Dew point temperature profiles after the conversion with radiometer temperatures compare to radiosonde profiles as to: absolute dew point temperature errors in the lower troposphere have a maximum median offset of -2 K and maximum quartiles of 4.5 K. For relative humidity, we get a maximum mean offset of 7.3%, with standard deviations of 12-20%. The methodology presented allows us to reconstruct humidity profiles at any location where temperature profiles, but no atmospheric humidity measurements other than from GPS are available. Additional data sets of wet refractivity are shown to be easily integrated into the framework and strongly aid the reconstruction. Since the used data sets are all operational and available in near-realtime, we envisage the methodology of this paper to be a tool for nowcasting of clouds and rain and to understand processes in the boundary layer and at its top. © Author(s) 2013.
Erdin R.,Federal Office of Meteorology and Climatology MeteoSwiss |
Frei C.,Federal Office of Meteorology and Climatology MeteoSwiss |
Kunsch H.R.,ETH Zurich
Journal of Hydrometeorology | Year: 2012
Geostatistics provides a popular framework for deriving high-resolution quantitative precipitation estimates (QPE) by combining radar and rain gauge data. However, the skewed and heteroscedastic nature of precipitation is in contradiction to assumptions of classical geostatistics. This study examines the potential of trans-Gaussian kriging to overcome this contradiction. Combination experiments are undertaken with kriging with external drift (KED) using several settings of the Box-Cox transformation. Hourly precipitation data in Switzerland for the year 2008 serve as test bed to compareKED with and without transformation. The impact of transformation is examined with regard to compliance with model assumptions, accuracy of the point estimate, and reliability of the probabilistic estimate. Data transformation improves the compliance with model assumptions, but some level of contradiction remains in situations with many dry gauges. Very similar point estimates are found for KEDwith untransformed and appropriately transformed data. However, care is needed to avoid excessive transformation (close to log) because this can introduce a positive bias. Strong benefits from transformation are found for the probabilistic estimate, which is rendered positively skewed, sensitive to precipitation amount, and quantitatively more reliable. Without transformation, 44% of all precipitation observations larger than 5 mm h -1 are considered as extremely unlikely by the probabilistic estimate in the test application. Transformation reduces this rate to 4%. Although transformation cannot fully remedy the complications for geostatistics in radar-gauge combination, it seems a useful procedure if realistic and reliable estimation uncertainties are desired, such as for the stochastic simulation of QPE ensembles. © 2012 American Meteorological Society.
Ament F.,University of Hamburg |
Weusthoff T.,Federal Office of Meteorology and Climatology MeteoSwiss |
Arpagaus M.,Federal Office of Meteorology and Climatology MeteoSwiss
Atmospheric Research | Year: 2011
This paper evaluates the performance of 13 mesoscale atmospheric models with respect to heavy precipitation alerts issued by these models in Switzerland during the summer 2007. All considered models contributed to an experimental real-time warning system, which was operated within the WWRP Forecast Demonstration Project MAP D-PHASE at that time. Seven of the considered models are deep convection resolving systems with grid spacings equal or less than 3 km. The models produced alerts if the predicted precipitation accumulation in alert regions (order of a few thousand square kilometers) exceeded the amount for an event with a return frequency of six per year. With an average probability of detection of 30% and a false alarm ratio of 60%, the accuracy of these alerts is poor but still skillful. An analysis of relative value reveals a clear tendency of deep convection resolving models to produce more useful alerts. The robustness of this finding with respect to the settings of the evaluation, the observational data set and the limited length of the evaluation period is successfully proven by sensitivity studies and bootstrap resampling experiments. The benefit of high resolution systems can partly be attributed to the higher update frequency of these models, even without any direct assimilation of precipitation observations. Probabilistic forecasts allow for a significant gain in relative value by choosing user dependent probability thresholds. A multi-model ensemble consisting of all deterministic models outperforms every deterministic model. Remarkably, a simple static recalibration of the best deterministic model performs equally well. © 2010 Elsevier B.V.
Bojanowski J.S.,Federal Office of Meteorology and Climatology MeteoSwiss |
Vrieling A.,University of Twente |
Skidmore A.K.,University of Twente
Solar Energy | Year: 2014
Satellite-derived surface solar radiation estimates are an alternative to the solar radiation measured at weather stations or modelled from other measured meteorological variables. The advantage of satellite-derived solar radiation is its high spatial and temporal resolution in comparison with solar radiation derived from weather stations, which has to be spatially interpolated. Solar radiation estimates at approximately 3-5km resolution derived from geostationary Meteosat satellites are available for Europe through the EUMETSAT Satellite Application Facilities (SAFs). The SAF responsible for land monitoring (LSA-SAF) has been providing daily solar radiation estimates in near real-time since 2005. The SAF on climate monitoring (CM-SAF) provided a 23-year long (1983-2005) consistent dataset of daily solar radiation. In this study we examine if these two solar radiation datasets may effectively be merged to generate a long-term gridded solar radiation time series for Europe. Further, we evaluate whether the ERA-Interim reanalysis or interpolated measured solar radiation (JRC-MARS) can be used as a replacement for existing and possible future data gaps in the satellite-based dataset. We show that the root mean square error and mean absolute error of LSA-SAF's and the CM-SAF's solar radiation estimates are similar (p<0.05), calculated against measured solar radiation data. A grid-based comparison of LSA-SAF's and CM-SAF's datasets showed an average root mean square difference over Europe of 2MJm-2 and a mean difference of 0.37MJm-2. For replacing data gaps in satellite-based radiation, we recommend the use of the ERA-Interim reanalysis data; they correspond better to both the ground reference and satellite-derived solar radiation data as compared to interpolated JRC-MARS. We conclude that both satellite-based products can be concatenated to create long-term gridded time series of solar radiation for Europe. © 2013 Elsevier Ltd.
Scherrer S.C.,Federal Office of Meteorology and Climatology MeteoSwiss
International Journal of Climatology | Year: 2011
Interannual variability (IAV) of 2m temperature (T), sea level pressure (SLP) and precipitation (P) in the CMIP3 20th century model simulations are compared with IAV in observational and reanalysis data sets using standard deviation based variability indices. Further, the relation between the representation of T IAV and the amplitude of future warming is investigated. In the Northern Hemisphere (NH) extratropics, T and SLP IAV are (in contrast to P) in general well represented although a few models perform much worse than others. General problem regions are: (1) sea ice boundary regions, where well-known biases in the mean states exist; and (2) the Pacific Ocean and Central Africa where SLP IAV is consistently underestimated. T and SLP IAV discrepancies are often found in similar regions and are large in well-known bias problem regions in the tropics and subtropics and high mountain regions. 'Bad' IAV representation also occurs in regions with small biases. T IAV is in general better reproduced over land than over sea and in the extratropics than in the tropics. Among the 'good' IAV models there is no robust relation between the tropics (sea only) and the extratropics (land only). The relation between the model's ability to correctly represent T IAV and projected temperature changes is slightly negative (more warming for better IAV representation) but except for the NH summer season not significant when the worst models in terms of IAV representation are omitted. This suggests that aggregated over large regions (with exception of NH summer) no robust relations are found between the model's ability to correctly represent T IAV and the projected temperature change. © 2010 Royal Meteorological Society.
Philipona R.,Federal Office of Meteorology and Climatology MeteoSwiss
International Journal of Climatology | Year: 2013
At low elevations (500 m a.s.l.) Central Europe's surface temperature increased about 1.3 °C since 1981. Interestingly, at high elevations (2200 m a.s.l.) in the Alps, temperature rose less than 1 °C over the same period. Detailed investigations of temperature, humidity and the radiation budget at lowland and alpine climate stations now show that the difference in temperature rise is likely related to unequal solar- and greenhouse warming. The analysis shows that the important decline of anthropogenic aerosols in Europe since the mid-1980s led to solar brightening at low elevations, whereas inherent low aerosol concentrations at high elevations led to only minor changes of solar radiation in the Alps. In the Lowland, absolute humidity and also total net radiation show an about 6% K-1 Clausius-Clapeyron conform increase with temperature since the 1980s. In the Alps, however, the percentage increase rate of humidity and total net radiation is more than twice as large. This large water vapour increase in the Alps is likely related to strong warming and thermal advection in the Lowlands, and may also have increased due to atmospheric circulation changes. Hence, while in the Alps temperature increased primarily due to strong water vapour enhanced greenhouse warming, solar brightening combined with anthropogenic greenhouse gas and water vapour feedback greenhouse warming led to a higher temperature increase at low elevations in Central Europe. © 2012 Royal Meteorological Society.
Frei C.,Federal Office of Meteorology and Climatology MeteoSwiss
International Journal of Climatology | Year: 2014
In mountain regions, the distribution of surface air temperature happens to show marked horizontal gradients and nonlinear variations with topographic height. These pose a major challenge for the construction of area-wide temperature datasets on a regular grid. This study introduces a new deterministic method's for the spatial interpolation of daily temperature from station measurements. Building on a scale-separation concept, the methods main features are (1) a nonlinear parametric function to model nonlinearities in the vertical thermal profile at the scale of major basins, and (2) a distance weighting scheme with a non-Euclidean metric that accounts for terrain effects on the spatial representativity of measurements. The method is configured for the territory of Switzerland (European Alps) and is applied for the construction of a km-scale grid dataset from 70-100 stations over all days from 1961 to 2010. Several illustrative cases attest the method's potential, also under challenging conditions. Temperature patterns from basin-scale inversions and surface heated/cooled boundary layers are realistically reproduced. In situations with valley-scale cold-air pools and foehn, the method is less prone to artificial upslope/downslope extrapolation often observed with other techniques. With a network of 100 stations in Switzerland, typical interpolation errors (mean absolute error MAE, cross-validation) range from 0.5 °C over flat and hilly terrain in summer to 1.5 °C in the Alps in winter. Larger and partly systematic errors (MAE ≥ 3 °C) must be expected in un-sampled valleys in winter due to the missing out of local-scale cold pools. Interpolation accuracy was found to vary with the change in station density over time, demonstrating improvements in the overall representativity of the measurement network. But this also compromises the long-term homogeneity of the grid dataset, despite it being based on homogeneous records. The presented method may be applicable in other mountain regions after some configuration. © 2013 Royal Meteorological Society.
Haefele A.,Federal Office of Meteorology and Climatology MeteoSwiss |
Ruffieux D.,Federal Office of Meteorology and Climatology MeteoSwiss
Meteorological Applications | Year: 2015
The validation of a 1290 MHz wind profiler using 3 years of collocated wind profiler and radiosonde wind measurements is presented. The radiosonde wind information is derived from global positioning system data and is vertically averaged to match the vertical resolution of the wind profiler measurements. The integration period of the wind profiler is chosen such that it is centred around the radiosonde measurement time. Periods where bird migration must be expected have been systematically excluded. The standard deviation of the differences between wind profiler and radiosonde in the wind components u and v is between 1.75 and 2 m s-1 and the bias is smaller than 0.75 m s-1 for heights below 6 km for both modes. Some part of the obtained standard deviation can be explained by the fact that radiosonde and wind profiler measurements are not representative for each other. In order to reduce the representativeness error, a subset of cases has been selected, for which the wind field was stationary during the measurement period and uniform across the sampled volume of the wind profiler. The standard deviation derived from the subset is between 1 and 1.5 m s-1 while the bias changes only little. This reduction can be attributed to a reduction in the representativeness error and in the retrieval error of the wind profiler since atmospheric homogeneity is a basic assumption in the wind retrieval. The obtained value of 1.5 m s-1 can be taken as an upper limit of the measurement uncertainty of the wind profiler in favourable measurement conditions. © 2015 Royal Meteorological Society.
Schiemann R.,Federal Office of Meteorology and Climatology MeteoSwiss |
Frei C.,Federal Office of Meteorology and Climatology MeteoSwiss
Physics and Chemistry of the Earth | Year: 2010
A novel approach is presented for the evaluation of circulation type classifications (CTCs) in terms of their capability to predict surface climate variations. The approach is analogous to that for probabilistic meteorological forecasts and is based on the Brier skill score. This score is shown to take a particularly simple form in the context of CTCs and to quantify the resolution of a climate variable by the classifications. The sampling uncertainty of the skill can be estimated by means of nonparametric bootstrap resampling.The evaluation approach is applied for a systematic intercomparison of 71 CTCs (objective and manual, from COST Action 733) with respect to their ability to resolve daily precipitation in the Alpine region. For essentially all CTCs, the Brier skill score is found to be higher for weak and moderate compared to intense precipitation, for winter compared to summer, and over the north and west of the Alps compared to the south and east. Moreover, CTCs with a higher number of types exhibit better skill than CTCs with few types. Among CTCs with comparable type number, the best automatic classifications are found to outperform the best manual classifications. It is not possible to single out one 'best' classification for Alpine precipitation, but there is a small group showing particularly high skill. © 2009 Elsevier Ltd.