摘要
1灾害天气监测1.19基于贝叶斯方法的冰大小识别研究冰電大小直接影响到产生灾害的程度,针对冰電大小识别的需求,基于济南和青岛两部S波段双偏振雷达探测的冰统计信息建立数据集,获取小冰、大冰、特大冰電的雷达水平反射率因子(Z)、差分反射率(ZpR)和相关系数(CC)的概率分布,构建基于贝叶斯方法的冰大小识别模型(HSDM),然后应用两个超级单体暴过程进行验证。研究表明:(1)模型识别结果与实况吻合,识别的冰電大小也符合不同尺寸冰散射特性、偏振参量特征及超级单体電暴动力与微物理特性的分析。(2)冰大小的水平分布特征与垂直分布特征符合超级单体暴降水粒子筛选机制及冰生长机制。
1 Severe weather monitoring technology 1.1 Classification of cloud phases using combined ground-based polarization lidar and millimeter cloud radar observations over the Tibetan Plateau The distributions of cloud phases play an important role in infuencing the weather and climate system.The characteristics of clouds above the Tibetan Plateau(TP)can profoundly affect regional and global atmospheric circulation.To research the distributions of cloud phases in the TP region,a retrieval algorithm was developed based on the combination of polarization lidar and millimeter cloud radar measurements and applied to the data from a comprehensive field campaign on the central TP in the summer of 2014.
