Abstract Radar data were analyzed for severe thunderstorms that produced severe hail across the south west, west and northern plains of the Iran (Tehran, Ahvaz and East Khazar radar stations) 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 at Tehran and synoptic observations of hail in the Iran have been analysed. The height of the freezing level has been calculated from the upper-air sounding data of 12 UTC for each day. A dataset containing 32 reports of hail include parameters such as freezing level, echo-top, 45 dBZ Reflectivity Max Heights and Vertical Integrated Liquid (VIL). In this research, two methods with high accuracy of detection hail occurrence and warning threshold have been selected. The performances of these different hail detection methods have been compared using data of 32 selected days with thunderstorms in the Iran during 2008- 2010. The first method (NEXRAD) 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 method of Waldvogel for the detection of hail, uses the maximum altitude at which a reflectivity of 45 dBZ is found (HZ45) in relation to the height of the freezing level (HT0). when the 45 dBZ reflectivity extends to 1.4 km or more above the freezing level, the presence of hail is likely, and the probability of the presence of hail increases with increasing height of this reflectivity core above the freezing level. The method of Waldvogel combines an indicator for the presence of a substantial updraft, the height of the strong reflectivity core (45 dBZ), with that for a large amount of undercooled water and/or ice, the reflectivity core above the freezing level, to detect (developing) hail. In the current NEXRAD hail detection algorithm, the maximum height of the 45 dBZ reflectivity above the freezing level is converted to a probability of hail. A height difference of 1.6 km corresponds to 10% probability of hail and one of 6.0 km to 100% probability of hail (Witt et al., 1998). The results show that for height difference greater than 5 km, the probability of hail detection is 100%. This value depending on warm and cold climate can be varied up to 1 km.The second of hail detection using vertical integrated liquid (VIL Density). Thresholds for VIL-based hail warnings has been calculated 10 kg/m2.