Surface-Atmosphere Couplings and Convection Processes

表面大气耦合和对流过程

• 批准号: 249561-2012
• 负责人: Hanesiak, John
• 金额: $ 1.97万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570647
• 关键词: Surface; Atmosphere; Couplings; Convection; Processes

Deep convection initiation (DCI), the initial stage of most summer severe weather, is one of the most perplexing and complex issues in meteorology today - the prediction of if, when and where DCI takes place generally has low accuracy. Numerical weather prediction models also have significant difficulties in predicting the timing and location of DCI. Improving predictions of DCI and associated atmospheric conditions will ultimately improve severe weather warnings (mode, severity, location and lead times). These statements apply to both daytime and overnight convection. Given this, the research questions to be addressed in this proposal are: (1) What is the sub-hourly and diurnal evolution of wet-dry vegetation regions, how do they interact and impact DCI? (2) What are the detailed characteristics of lake breezes and how do they impact DCI in Manitoba? (3) What are the characteristics, leading up to and during, warm frontal elevated DCI? (4) What are the implications of (1) - (3) for weather prediction and climate studies? Questions (1) - (4) will be addressed by doing detailed field measurements with recently acquired (and pre-existing) equipment that will provide high-resolution (spatial and temporal) profile measurements of temperature, moisture and wind in three different locations as well as surface mobile transects. The research will be done in collaboration with national and international projects that will share many other datasets (e.g. research radars, aircraft, satellite, other special ground-based remote sensors, and special surface and upper air observations) to address the three questions. The results of this work will offer recommendations for the prediction of DCI over appropriate time scales.

深对流形成（DCI）是大多数夏季灾害性天气的初始阶段，是当今气象学中最令人困惑和复杂的问题之一--预测DCI是否、何时和何地发生通常精度较低。数值天气预报模式在预测DCI的时间和位置方面也有很大的困难。改善DCI和相关大气条件的预测将最终改善恶劣天气警报（模式，严重程度，位置和提前时间）。这些陈述适用于白天和夜间的对流。鉴于此，本提案中要解决的研究问题是： (1)干湿植被区的亚小时和昼夜演变是什么，它们如何相互作用并影响DCI？ (2)湖风的详细特征是什么？它们如何影响马尼托巴的DCI？ (3)在暖锋升高的DCI之前和期间，有什么特征？ (4)（1）-（3）对天气预报和气候研究有什么意义？ 问题（1）-（4）将通过使用最近获得的（和预先存在的）设备进行详细的实地测量来解决，这些设备将提供三个不同地点以及地面移动的断面的温度、湿度和风的高分辨率（空间和时间）剖面测量。这项研究将与国家和国际项目合作进行，这些项目将分享许多其他数据集（例如研究雷达、飞机、卫星、其他特殊地面遥感器以及特殊地面和高空观测），以解决这三个问题。这项工作的结果将在适当的时间尺度上的DCI的预测提供建议。