地球科学与气候变化杂志

抽象的

Evaluation of Two Radar-Based Hail Detection Algorithms

Foroozan Arkian

Radar data were analyzed for severe thunderstorms that produced severe hail across the south west, west and northern plains of the Iran during the 2008-2010. In order to gain insight in the probability of observing hail at a certain location and the seasonal variation thereof, 3 years of upper-air sounding data and synoptic observations of hail have been analyzed. A dataset containing 32 reports of hail include parameters such as freezing level, echo-top, 45 dBZ Reflectivity Max Heights and Vertical Integrated Liquid water (VIL). The height of the freezing level has been calculated from the upper-air sounding data of 12 UTC for each day. In this research, two methods of hail detection have been selected. The first method is based on criterion of the Waldvogel hail algorithm that uses the maximum altitude at which a reflectivity of 45 dBZ is found in relation to the height of the freezing level. The results show that for height difference greater than 5 km, the probability of hail detection (PHD) is 100%. This value depending on warm and cold climate can be varied up to 1 km. The second Method uses Vertical Integrated Liquid (VIL) product of radar. Thresholds for VILbased hail warnings have been calculated 10 mm.