The Disdrometer Verification Network (DiVeN): a UK network of laser precipitation instruments
The Disdrometer Verification Network (DiVeN): a UK network of laser precipitation instruments
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DOI：
10.5194/amt-12-5845-2019
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发表时间：
2019-11-08
影响因子：
3.8
通讯作者：
Harrison, Dawn
中科院分区：
文献类型：
--
作者：
Pickering, Ben S.;Neely, Ryan R., III;Harrison, Dawn
从2017年2月开始，在英国各地安装了14台Thies激光降水监测仪（LPM），以创建Disdrometer验证网络（DiVeN）。安装这些仪器是为了核查雷达水凝物分类算法，但对于在科学和业务气象界更广泛地使用也很有价值。每台Thies LPM都能将每一个观测到的水凝物指定到20个直径从>= 0.125到> 8 mm的箱中的一个和22个速度从> 0.0到> 20.0 m s（-1）的箱中的一个。使用经验得出的关系，该仪器将降水分为11个可能的水文气象类之一，以目前的天气代码的形式，与相关的不确定性指标。为了向数据用户提供即时反馈，观测结果以近实时（NRT）方式绘制，并在7分钟内在网站上公开。这里显示的案例表明，Thies LPM在识别雨和雪之间的转换方面表现良好，但由于内部处理，它在检测<$层和原始冰晶（在英国很少发生）方面存在困难。目前的天气代码质量指数被证明有一定的技巧，没有由制造商推荐的补充传感器。总体而言，Thies LPM是探测地表水凝物类型的有用工具，DiVeN提供了英国以前没有观测到的新数据集。
Starting in February 2017, a network of 14 Thies laser precipitation monitors (LPMs) were installed at various locations around the United Kingdom to create the Disdrometer Verification Network (DiVeN). The instruments were installed for verification of radar hydrometeor classification algorithms but are valuable for much wider use in the scientific and operational meteorological community. Every Thies LPM is able to designate each observed hydrometeor into one of 20 diameter bins from >= 0.125 to > 8 mm and one of 22 speed bins from > 0.0 to > 20.0 m s(-1). Using empirically derived relationships, the instrument classifies precipitation into one of 11 possible hydrometeor classes in the form of a present weather code, with an associated indicator of uncertainty. To provide immediate feedback to data users, the observations are plotted in near-real time (NRT) and made publicly available on a website within 7 min. Here we describe the Disdrometer Verification Network and present specific cases from the first year of observations. Cases shown here suggest that the Thies LPM performs well at identifying transitions between rain and snow, but struggles with detection of graupel and pristine ice crystals (which occur infrequently in the United Kingdom) inherently, due to internal processing. The present weather code quality index is shown to have some skill without the supplementary sensors recommended by the manufacturer. Overall the Thies LPM is a useful tool for detecting hydrometeor type at the surface and DiVeN provides a novel dataset not previously observed for the United Kingdom.