Identification of Snow and Rain at the Surface using Polarimetric Radar

Abstract

The transition from rain to snow at the surface is one of the challenging facts in aviation and road traffic during winter weather condition. Even though numerical weather forecast is able to provide reasonable forecasts, nowcasting applications still suffer from the precise observation of the transition from rain to snow at the surface. The application of dual-polarization radar has shown that fuzzy logic allows classifying hydrometeors in distinct classes. However, some uncertainty exists in the distinction between light rainfall and light snowfall. The knowledge of temperature can help in this situation, but is often not available with the desired quality and for three-dimensional the region of interest. Further uncertainty is caused by the fact that radar does not measure at the surface but at several hundred meters above the surface. For an improved classification of surface precipitation we identify the height of the melting layer first. The height of the melting layer is then included in the fuzzy classification process. This allows a more reliable distinction between rain (below) and snow (above). In the presentation we will show results from this algorithm using the DLR multi-polarization C-band weather radar POLDIRAD including a verification using ground based observations at Munich airport (disdrometer and human METAR observations) as well as measurements with a vertical pointing Doppler micro rain radar.