Reanalysis on Hail Suppression Weather Prewarning of the "8.21" Rare Hail in Shenyang

[Objective]The research aimed to analyze hail weather during 18：30-19：30 on August 21,2011.[Method]Based on NCEP 6 h reanalysis data,Micaps data and FY-2 satellite cloud image,weather situation field,meteorological element field and satellite cloud image of the hail during 18：30-19：30 on August 21,2011 were reanalyzed.Weather causes of the hail and characteristics of the satellite cloud image were discussed.We summed up how to conduct prewarning analysis of the hail suppression weather from live weather data and numerical forecast products.[Result]In occurrence and development process of the hail weather,cold vortex at 500 hPa was background weather system.850 hPa warm tongue and ground wind shear were essential conditions for forming strong convective hail cloud.Early weather chart was analyzed.It could analyze occurrence reason of the weather from mechanism aspect of the weather system,and issue weather prewarning as early as possible.Numerical forecast products were used to analyze meteorological element field.It could further analyze and accurately predict probability,time and range of the hail occurrence.Infrared satellite cloud image was more accurate for monitoring strong convective hail cloud,which could intuitively predict occurrence of the hail weather.[Conclusion]The research offered some hail suppression prewarning experiences for the future similar hail weather.

Statistical Guidance on Seasonal Forecast of Korean Dust Days over South Korea in the Springtime

This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast （below normal, normal, above normal） which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years （1981-2010）. In this study, we used three kinds of monthly data： the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research （NCEP/NCAR） reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.