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Locarno, Switzerland

Philipona R.,MeteoSwiss | Krauchi A.,ETH Zurich | Brocard E.,MeteoSwiss
Geophysical Research Letters | Year: 2012

Solar shortwave and thermal longwave radiation at the Earth's surface and at the top of the atmosphere is commonly measured at surface stations, from airplanes and from satellites. Here we show radiative flux profiles measured with radiosondes ascending from the Earth's surface to 35km into the stratosphere. During two-hour flights solar shortwave and thermal longwave radiation are measured both downward and upward with four individual sensors. Daytime solar and thermal radiation is compared to nighttime measurements and 24-hour average radiation budget profiles are shown through the atmosphere. However, of even greater importance with regard to climate change are measured upward and downward longwave greenhouse radiation profiles. Their changes with temperature and water vapor enable direct measurement of radiative forcing through the atmosphere. Measurements during two cloud-free nights with different temperature and different water vapor amount, show an almost equal but opposite net longwave radiation change, or water vapor greenhouse forcing, downwards to the surface and upward into space. Radiative flux profiles clearly illustrate the Earth's atmospheric greenhouse effect, and allow important investigations of clouds and other atmospheric constituents and their effects on shortwave reflection, as well as longwave emission towards the surface and into space. © 2012. American Geophysical Union. All Rights Reserved. Source

Teuling A.J.,ETH Zurich | Teuling A.J.,Wageningen University | Stockli R.,MeteoSwiss | Seneviratne S.I.,ETH Zurich
International Journal of Climatology | Year: 2011

The increasing availability of gridded, high-resolution, multivariate climatological data sets calls for innovative approaches to visualize inter-variable relations. In this study, we present a methodology, based on properties of common colour schemes, to plot two variables in a single colour map by using a two-dimensional colour legend for both sequential and diverging data. This is especially suited for climate data as the spatial distribution of the relation between different variables is often as important as the distribution of variables individually. Two example applications are given to illustrate the use of the method: one that shows the global distribution of climate based on observed temperature and relative humidity, and the other showing the distribution of recent changes in observed temperature and precipitation over Europe. A flexible and easy-to-implement method is provided to construct different colour legends for sequential and diverging data. © 2010 Royal Meteorological Society. Source

Rudolph J.V.,University of Colorado at Boulder | Friedrich K.,University of Colorado at Boulder | Germann U.,MeteoSwiss
Journal of Applied Meteorology and Climatology | Year: 2011

A 9-yr (2000-08) analysis of precipitation characteristics for the central and western European Alps has been generated from ground-based operational weather radar data provided by the Swiss radar network. The radar-based precipitation analysis focuses on the relationship between synoptic-scale weather patterns and mesoscale precipitation distribution over complex alpine terrain. The analysis divides the Alps into six regions (each approximately 200×200 km2 in size)-one on the northern side, two each on the western and southern sides of the Alps, and one in the Massif Central-representing various orographic aspects and localized climates within the radar coverage area. For each region, estimated precipitation rate derived from radar data is analyzed on a seasonal basis for total daily precipitation and frequency of high-precipitation-rate events. The summer season has the highest total daily precipitation for all regions in the study, whereas median values of daily precipitation in winter are less than one-half of median daily precipitation for summer. For all regions, high-precipitation-rate events occur most frequently in the summer. Daily synoptic-scale weather patterns are associated with total daily precipitation and frequency of high precipitation rate to show that an advective synoptic-scale pattern with southerly midtropospheric flow results in the highest median and 90th-quantile values for total daily precipitation and that a convective synoptic-scale pattern results in elevated frequency of extreme-precipitation-rate events. © 2011 American Meteorological Society. Source

In several cases (e.g., thermal noise, weather echoes,.), the incoming signal to a radar receiver can be assumed to be Rayleigh distributed. When estimating the mean power from the inherently fluctuating Rayleigh signals, it is necessary to average either the echo power intensities or the echo logarithmic levels. Until now, it has been accepted that averaging the echo intensities provides smaller variance values, for the same number of independent samples. This has been known for decades as the implicit consequence of two works that were presented in the open literature. The present note deals with the deriving of analytical expressions of the variance of the two typical estimators of mean values of echo power, based on echo intensities and echo logarithmic levels. The derived expressions explicitly show that the variance associated to an average of the echo intensities is lower than that associated to an average of logarithmic levels. Consequently, it is better to average echo intensities rather than logarithms. With the availability of digital IF receivers, which facilitate the averaging of echo power, the result has a practical value. As a practical example, the variance obtained from two sets of noise samples, is compared with that predicted with the analytical expression derived in this note (Section 3): Tthe measurements and theory show good agreement. © 2014 by the authors. Source

Craig G.C.,Ludwig Maximilians University of Munich | Keil C.,Ludwig Maximilians University of Munich | Leuenberger D.,MeteoSwiss
Quarterly Journal of the Royal Meteorological Society | Year: 2012

Experience from operational trials of assimilation of radar data in kilometre-scale numerical weather prediction models (operating without cumulus parametrization) shows that the positive impact of the radar data on convective precipitation forecasts typically decays within a few hours, although certain cases show much longer impact time-scales. In this work the impact time of radar data assimilation is related to characteristics of the meteorological environment. Three cases of convection over southern Germany with different synoptic conditions are investigated (one case with two data assimilation cut-off times), each with an ensemble of ten forecasts at 2.8 km horizontal resolution based on different initial and boundary conditions from a global forecast ensemble. Control forecasts are compared with forecasts where radar rainfall data are assimilated using latent heat nudging. The impact time of the radar data on total precipitation is quantified, and found to correlate well with a convective time-scale that measures the rate at which convection is responding to changes in large-scale forcing. Short impact times were associated with short convective time-scales that are characteristic of equilibrium convection. In this regime the statistical properties of the convection are constrained by the large-scale forcing, and effects of the radar data are lost within a few hours as the convection rapidly returns to equilibrium. When the convective time-scale was large (non-equilibrium conditions), the impact of the radar data was longer since convective systems were triggered by the latent heat nudging and were able to persist for many hours in the very unstable conditions present in these cases. The impact of the assimilated radar data on the location of precipitation was assessed using the equitable threat score (ETS) and the displacement and amplitude score (DAS). The impact times for these measures were consistently shorter than for total precipitation, but again shortest for the equilibrium conditions. © 2011 Royal Meteorological Society. Source

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