Identifying the Physical Drivers and Radar Signatures of Fire-Generated Tornadic Vortices

野火会产生自己的恶劣天气，包括嵌入野火羽流中的龙卷风和雷暴。这些由火灾产生的极端行为威胁着消防员和公共安全，但人们对此知之甚少，而且往往无法预测。为了填补这一知识空白，研究人员建议通过从天气雷达和卫星数据中确定导致火灾龙卷风和雷暴的常见因素来了解火灾引发的极端天气。该项目还将让公众参与野火科学，例如开发侧重于火灾天气的中学课堂课程，并开展公民科学社交媒体活动，收集从野火羽流中落下的火山灰和碎片的照片。公众收集的众包数据将有助于加深我们对野火羽流的了解，以便更好地记录升空的物质的大小和形状。拟议的工作的动机是数十年来成功地利用雷达和卫星观测发出对流恶劣天气(例如严重雷暴)的救生警告。对于火灾产生的龙卷风涡旋(FGTV)和焦云状云雾(PyroCb)，这些工具显示出非凡的、但尚未完全实现的潜力。为了充分实现这一潜力，需要新的物理和概念模型来解释雷达和卫星对野火环境的观测。为了开发这些模型，调查人员将测试一系列假说，这些假说旨在分离与FGTV开发有关的雷达和卫星观测到的火灾和羽流过程的共同特征。这些假设是基于初步的观测结果，表明产生FGTV的火焰通常表现出：(1)具有嵌入和脱落涡旋的弯曲和分叉羽流，(2)火焰周围气流分裂和反转的不对称性，这有利于一种涡旋旋转感(即气旋和反气旋)，以及(3)在涡旋强化的同时，pyroCb的启动。在分离FGTV火灾的共同属性和观察到的特征时，研究小组的目标是为FGTV形成建立概念模型。这些概念模型将促进拯救生命的警告，并增强对野火利益相关者的决策支持，从而提供直接的社会效益。作为这项提议的一部分，社区参与和教育将包括：(A)社交媒体公民科学运动，将雷达观测与记录野火羽流落下的火山灰的大小和形状的照片记录联系起来；(B)课堂上的中学学习经历和课程，以及基于应用程序的数据收集模块；(C)研究生指导和课程开发；以及(D)面向公众和野火利益攸关方的外联活动。公民科学活动预计每年将覆盖1000名用户，课堂项目每年将达到500名以上的学生。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Wildfires can generate their own severe weather, including tornados and thunderstorms embedded in the wildfire plume. These fire-generated extremes threaten fire-fighter and public safety yet are poorly understood and often unpredicted. To fill this knowledge gap, the investigators propose to understand fire-generated extreme weather by identifying the common factors contributing fire-generated tornados and thunderstorms from weather radar and satellite data. The project will also engage the public in wildfire science such as developing middle-school in-class lessons focused on fire-generated weather and conducting a citizen-science social-media campaign to collect photographs of the ash and debris that “rain” down from wildfire plumes. The crowd-sourced data collected by the public will help improve our understanding of wildfire plumes for better documenting the size and shape of material lofted into the sky.The proposed work is motivated by decades of success in using radar and satellite observations to issue life-saving warnings for convectional severe weather (e.g., severe thunderstorms). For fire-generated tornadic vortices (FGTV) and pyrocumulonimbus (pyroCb) these same tools show remarkable, yet incompletely realized potential. To fully realize this potential, new physical and conceptual models are required for interpreting radar and satellite observations of the wildfire environment. To develop these models, the investigators will test a sequence of hypotheses designed to isolate the common characteristics of radar and satellite observed fire and plume processes linked to the FGTV development. These hypotheses are based on preliminary observations demonstrating FGTV producing fires often exhibit: (1) bent-over and bifurcating plumes with both embedded and shedding vortices, (2) asymmetries in flow splitting and flow reversal around the fire that favor one sense of vortex rotation (i.e., cyclonic vs. anticyclonic), and (3) pyroCb initiation concurrent with vortex intensification. In isolating the common attributes and observed signatures of FGTV fires, the research team aims to produce conceptual models for FGTV formation. These conceptual models will facilitate life-saving warnings and enhance decision support for wildfire stakeholders, thereby providing an immediate societal benefit. Community engagement and education as part of this proposal will include: (a) social-media citizen-science campaign linking radar observations with photographic documentation of size and shape of ash falling from wildfire plumes, (b) in-classroom middle school learning experiences and curriculum coupled with an app-based data collection module, (c) graduate student mentoring and curriculum development, and (d) outreach to the public and wildfire stakeholders. The citizen-science campaign is expected to reach 1000s of users annually, and the in-classroom program upwards of 500 students per year.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.