Severe weather studies using data from the OQ-Net VHF Wind-Profiler Network

使用 OQ-Net VHF Wind-Profiler 网络数据进行恶劣天气研究

• 批准号: 41767-2012
• 负责人: Taylor, Peter
• 金额: $ 1.97万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=507659
• 关键词: Severe; weather; studies; using; data

With CFI and OIF support we (York University, University of Western Ontario and McGill) have now completed the installation of a unique regional scale network of ten VHF wind profilers (the O-QNet) in Ontario and southern Quebec. These are providing a valuable data set of hourly and three-hourly winds from about 400 m to 15 km above the surface. At York, our work has so far focused on issues of performance monitoring and quality control. This raised some initial concerns but these have been addressed and we have full confidence in the reliability and accuracy of the data. We plan to use the data to study spatial variations in winds throughout the troposphere in conjunction with meso-scale (WRF for example) meteorological models. We can also use the data to monitor the performance of operational weather forecast models for wind analyses and predictions and develop a climatology of tropospheric winds. A central theme of the proposed research will be to take advantage of the network to look at spatial features of the wind field. One approach will involve using triangles of three wind profilers, typically about 200 km apart, to estimate vorticity and divergence fields. This can be simply done by assuming linear variations of the velocity components in the horizontal coordinates at each geopotential height. Vorticity and divergence are important diagnostic parameters for synoptic and meso-scale meteorology. Integration of divergence will give an estimate of vertical velocity which can be linked to precipitation and severe weather. The profilers will also measure vertical velocity directly. Vorticity and upper level divergence are key quantities in the identification of conditions liable to spawn tornadoes and other severe summer weather. We will look at any nearby profiler data on all recent occasions where strong and damaging winds have occurred (resulting from tornadoes, sting jets or derechos for example) to investigate wind field structure and to see if timely distribution and use of the profiler data could be an aid in short term forecasting of similar events in the future.

在CFI和OIF的支持下，我们（约克大学、西安大略大学和麦吉尔大学）现在已经在安大略省和魁北克省南部完成了由十个VHF风廓线仪组成的独特区域规模网络（O-QNet）的安装。这些卫星提供了一组有价值的每小时和每三小时的风速数据，范围从距离地面400米到15公里。在约克大学，我们的工作迄今集中在绩效监测和质量控制问题上。这引起了一些最初的担忧，但这些问题已经得到解决，我们对数据的可靠性和准确性充满信心。我们计划利用这些数据，结合中尺度（例如WRF）气象模式，研究整个对流层风的空间变化。我们也可以利用这些数据来监测风分析和预测的业务天气预报模式的表现，并发展对流层风的气候学。所提议的研究的一个中心主题将是利用网络来观察风场的空间特征。一种方法将涉及使用三个风廓线仪的三角形，通常相隔约200公里，来估计涡度和散度场。这可以简单地通过假设在每个位势高度的水平坐标中速度分量的线性变化来完成。涡度和辐散度是天气和中尺度气象学的重要诊断参数。辐散的积分将给出与降水和恶劣天气有关的垂直速度的估计。剖面仪还将直接测量垂直速度。涡度和高空辐散度是识别龙卷风和其他夏季恶劣天气的关键条件。我们将查看最近发生强风和破坏性大风（例如，由龙卷风、刺刺射流或回波引起）的任何附近廓线仪数据，以调查风场结构，并查看及时分发和使用廓线仪数据是否有助于未来类似事件的短期预测。