Improving Understanding of Convection Initiation in Nocturnal Environments During PECAN (Plains Elevated Convection at Night) Using High-Resolution Ensemble Data Assimilation

使用高分辨率集合数据同化提高对 PECAN（夜间平原高对流）期间夜间环境中对流启动的理解

• 批准号: 1541624
• 负责人: Katja Friedrich
• 金额: $ 59.21万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-12-01 至 2020-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541624&HistoricalAwards=false
• 关键词: Improving; Understanding; Convection; Initiation; Nocturnal

Nocturnal thunderstorms in the central United States provide rainfall for productive agricultural regions but also can pose hazards to lives and property through flooding and severe winds. In 2015, NSF funded a large group of scientists to collect data on these nighttime thunderstorms. This award will make use of that data by conducting very small scale numerical modeling studies to determine what initially triggers the thunderstorms, a process known as convective initiation. The research has the potential to improve understanding and modeling of these events, giving forecasters more information about when and where thunderstorms may happen. The award would also contribute to human resource development by funding an early-career researcher, providing an opportunity for an undergraduate student to participate in a research project, and allowing the researcher to develop a seminar course based on the field campaign.The Plains Elevated Convection at Night (known colloquially as PECAN) field campaign was conducted in the Great Plains region in June and July of 2015. The campaign included numerous observational platforms, such as mobile radars, aircraft, vertical profilers and surface instrumentation. In this project the researcher intends to assimilate data from the campaign into an ensemble with nested mesoscale and convection-resolving grids. The primary focus of the research is to accurately reproduce the evolution of the nocturnal mesoscale environment in which convective initiation occurs and to determine which specific small- and large-scale processes result in parcels lifted to their level of free convection. The ensemble data assimilation experiments will employ the WRF-ARW and the Data Assimilation Research Testbed (DART) ensemble analysis software configured as an Ensemble Adjustment Kalman Filter. Fifty ensemble members will be used and the researcher plans to employ a triple nested model grid strategy with the finest grid spacing of 0.4 to 0.6km. In addition to the work on identifying processes triggering nocturnal convection, the researcher will also conduct forecast sensitivity experiments.

美国中部的夜间雷暴为生产性农业地区提供降雨，但也可能通过洪水和巨大的风危害生命和财产。 2015年，NSF资助了一大批科学家，以收集有关这些夜间雷暴的数据。 该奖项将通过进行非常小的数值建模研究来利用这些数据，以确定最初触发雷暴的方法，这是一种称为对流启动的过程。 该研究有可能提高对这些事件的理解和建模，从而为预测者提供有关雷暴可能发生何时何地的更多信息。 该奖项还将通过资助早期职业研究员的资金来为人力资源开发做出贡献，为一名本科生提供了一个研究项目的机会，并允许研究人员根据现场活动开发基于现场运动的研讨会课程。夜间对流越来越高（熟悉地称为Pecan）在6月和2015年7月的“伟大平原”中进行了竞选活动。垂直剖面和表面仪器。 在这个项目中，研究人员打算将活动的数据吸收到与嵌套的中尺度和解决对流的网格的合奏中。 该研究的主要重点是准确地重现对流启动的夜间中尺度环境的演变，并确定哪些特定的小规模和大型过程导致包裹提升到其自由对流水平。 合奏数据同化实验将采用WRF弧和数据同化研究床（DART）集合分析软件，该软件配置为合奏调整Kalman滤波器。 将使用五十个合奏成员，研究人员计划采用三重嵌套模型网格策略，最佳网格间距为0.4至0.6公里。 除了确定触发夜间对流过程的过程的工作外，研究人员还将进行预测灵敏度实验。