Abstract. This paper presents a model using rain gauge and weather radar data to predict the runoff of a small alpine catchment in Austria. The gapless spatial coverage of the radar is important to detect small convective shower cells, but managing such a huge amount of data is a demanding task for an artificial neural network. The method described here uses statistical analysis to reduce the amount of data and find an appropriate input vector. Based on this analysis, radar measurements (pixels) representing areas requiring approximately the same time to dewater are grouped.

No abstract

This paper presents a novel metamaterial structure which achieves high performance in terms of loss, power handling and size reduction compared to traditional waveguides. The design procedure and considerations have been elaborated for additive manufacturing of the structure. The filter chosen to implement was a 4th-order filter with four poles; 400 MHz bandwidth and a return loss of better than 15 dB, at the center frequency of 18.5 GHz.

Abstract. Polarimetric radar variables of rainfall events, like differential reflectivity Z DR , or specific differential phase K DP , are better suited for estimating rain rate R than just the reflectivity factor for horizontally polarized waves, Z H . A variety of physical and empirical approaches exist to estimate the rain rate from polarimetric radar observables. The relationships vary over a wide range with the location and the weather conditions.In this study, the polarimetric radar variables were simulated for S-, C-and X-band wavelengths in order to establish radar rainfall estimators for the alpine region of the form R(K DP ), R(Z H , Z DR ), and R(K DP , Z DR ). For the simulation drop size distributions of hundreds of 1-minute-rain episodes were obtained from 2D-Video-Distrometer measurements in the mountains of Styria, Austria. The sensitivity of the polarimetric variables to temperature is investigated, as well as the influence of different rain drop shape models -including recently published ones -on radar rainfall estimators. Finally it is shown how the polarimetric radar variables change with the elevation angle of the radar antenna.

The presence of vegetation in the radio path significantly attenuates centimeter and millimeter radio waves. The attenuation depends on the type of vegetation, its density, the season, and the frequency. Attenuation models exist for the horizontal path through vegetation and the slant foliage path through roadside trees. In this study, slant foliage paths through roadside woodland are investigated. This letter presents results for the slant path attenuation loss at 5.2-GHz C-band frequency at three elevation angles (20 , 40 , and 60 ) and three types of vegetation (spruce, pine, and deciduous woodland). Differences between horizontal and slant path results are discussed, and cumulative distribution statistics of the attenuation in the various vegetation types are given.Index Terms-Attenuation in vegetation, C-band, excess loss, satellite communications, slant foliage path.