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机构地区:[1]武汉中心气象台,武汉430074 [2]武汉暴雨研究所,武汉430074
出 处:《气象学报》2003年第5期628-635,共8页Acta Meteorologica Sinica
基 金:中国气象局<预报逐级指导>课题
摘 要:文中详细分析了 1982~ 1998年发生在湖北省的冰雹过程 ,这些冰雹过程被归纳为槽前型和槽后型两类。两类过程的一个共同特点是过程发生前具有极强的位势不稳定。槽前型主要表现在中低空及地面为极强的增湿增暖 ,导致中低空能级升高 ,而中高层是相对干冷的区域或变化不是很大 ,这类过程的触发主要是由于西北槽中有短波槽扰动凌驾于不稳定区之上 ,一方面加大水平能量锋区 ,另一方面使得垂直不稳定度加大 ,进而触发对流。槽后型主要表现在中高层为极强的干冷平流 ,引起降温降湿 ,而低层有弱的增温增湿 ,这类过程的触发主要是西北气流中横槽转动和小槽沿脊前下滑 ,在中低层加大水平能量锋区 ,促进垂直不稳定能量的释放。因此将水平能量锋区ΔθseH/Δn和垂直不稳定ΔθseH/Δz之和作为冰雹判据 ,辅之以其它条件 ,在日常业务中 ,具有较高的预报准确率。利用研究结果 ,对武汉区域中心数值预报模式MAPS的积云对流参数化方案进行改进 ,即改进积云对流参数化中的稳定度条件。用改进后的MAPS模式对 1999~ 2 0 0 1年 3~ 5月的过程进行试报 ,结果表明 ,该模式对冰雹落区有一定的预报能力。The hailstone occurred in Hubei province from 1982 to 1998 had been dirided analyzed in detail. These cases had been divided into two patterns. The same characters of two patterns were that the potential instability were severe before occurred.There were severe increasing humidity and warm in middle low level and the surface in the front trough pattern, and it resulted in energy level increasing in middle and low level. However, the dry and cold air had no great change in the middle and high level. The trigger of the cases were mainly due to horizontal energy front and vertical instability increasing. There were severe dry and cold advection in the middle and high level in behind trough pattern. It resulted in humidity and warm decreasing. The weak humidity and warm increasing existed in the middle and low level. The trigger of the cases were mainly due to horizontal energy front increasing in middle and low level. It prompted vertical instability energy releasing. The sum of horizontal energy front Δ θ seH /Δ n and vertical instability Δ θ seH /Δ z predicted hailstone region as a criterion. In an ordinary operation, the accuracy of prediction is increased with other conditions. As a result, the cumulus convection parameterization of MAPS model is improved, i.e, the instability condition of cumulus convection parameterization is improved. The cases in March to May from 1999 to 2001 had been forecasted using improvement MAPS model. So it shows that the MAPS model is able to forecast hailstone region.
分 类 号:P456.7[天文地球—大气科学及气象学] P446
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