Evaluation of Alberta Hail Growth Model Using Severe Hail Proximity Soundings from the United States
Evaluation of Alberta Hail Growth Model Using Severe Hail Proximity Soundings from the United States
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使用来自美国的强冰雹邻近探测来评估艾伯塔省冰雹增长模型
DOI：
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发表时间：
2004
期刊：
影响因子：
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通讯作者：
J. Brimelow
中科院分区：
文献类型：
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作者：
Ryan E. Jewell;J. Brimelow
摘要对一个一维冰雹云耦合模式（HAILCAST）进行了试验，以评估其预报冰雹大小的能力。该模型采用合奏的方法时，预测最大冰雹的大小，使用探空作为输入，并可以在几秒钟内运行的业务工作站。该模型最初是在南非开发的，然后在加拿大进行了改进，使用高质量的冰雹验证数据进行校准。在这项研究中，该模型运行在1989年至2004年期间收集的美国本土内的914个修改后的严重冰雹接近探测的空间和季节性差异。然后，将模式输出与每个邻近探测的最大观测冰雹大小进行比较。基本的验证统计数据，表明HAILCAST模型表现出相当大的技能，可以使用的业务恶劣天气预报。
Abstract A one-dimensional, coupled hail and cloud model (HAILCAST) is tested to assess its ability to predict hail size. The model employs an ensemble approach when forecasting maximum hail size, uses a sounding as input, and can be run in seconds on an operational workstation. The model was originally developed in South Africa and then improved upon in Canada, using high quality hail verification data for calibration. In this study, the model was run on a spatially and seasonally diverse set of 914 modified severe hail proximity soundings collected within the contiguous United States between 1989 and 2004. Model output was then compared to the maximum observed hail size for each proximity sounding. Basic verification statistics are presented, showing that the HAILCAST model exhibits considerable skill that can be of use to the operational severe weather forecaster.