RAPID: Characterizing and Understanding Smoke Transport in 2023 Hawaii Wildfire Event Using Geostationary Satellite Observations and Numerical Modeling

RAPID：利用对地静止卫星观测和数值模拟描述和理解 2023 年夏威夷野火事件中的烟雾输送

• 批准号: 2345272
• 负责人: Yun Lin
• 金额: $ 15万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2345272&HistoricalAwards=false
• 关键词: RAPID; Characterizing; Understanding; Smoke; Transport

The raging, wind-whipped wildfires starting on August 8, 2023, destroyed much of the Lahaina community of the Island Maui and caused hundreds of deaths and injuries associated with smoke. Smoke emitted from wildfires can exert adverse effects on air quality and climate over a broad range of temporal and spatial scales through its transport. However, accurately characterizing vertical distribution of wildfire plumes is still challenging, leading to large uncertainties in smoke transport simulations. To date, there has not been an observation alone-based method to efficiently capture the fast-changing patterns of smoke transport. Therefore, a comprehensive characterization of smoke transport and wildfire plume vertical distributions from observational perspective will greatly advance the fundamental understanding of wildfire smoke transport pattern like moving direction, distance, and affected area, and at same time, improve smoke transport simulations by directly addressing one of the key processes that impacts its modeling. This research will mitigate the increasingly devastating impacts of wildfire smoke on properties and human lives, given increasing wildfire activities under climate change. The project will also help to develop a near real-time forecast system on smoke movement and facilitate a warning framework to alert local residents in advance of the arrival of wildfire smoke.By examining the intensive smoke emissions and rapid smoke movement associated with the 2023 Maui wildfires, this project will provide a systematic assessment of smoke transport patterns and of wildfire plume vertical distributions impacts on smoke transport, utilizing satellite observations and numerical modeling. The key scientific questions include 1) What are the specific characteristics and temporal variations of smoke transport pattern and wildfire plume vertical distributions in the 2023 Maui wildfires? 2) How do the vertical distributions of wildfire plume affect the smoke transport pattern? Specifically, this project will employ high-frequency geostationary satellite measurements to characterize the smoke transport during the 2023 Maui wildfires using an advance computer vision technique, i.e., optical flow analysis, and then estimate wildfire plume rise based on the diurnal cycles of fire radiative power derived by geostationary satellite to characterize the plume vertical distributions. The modeling sensitivity studies will be performed using the WRF-Chem model to evaluate how the plume vertical distribution affects smoke transport. Finally, the model simulations will be validated against the observation-based analysis to identify and reconcile the possible discrepancies between them and gain a more precise description of smoke transport patterns. This research actually represents the first-time attempt to quantify smoke transport using observations exclusively. Evidence from observations will be used to constrain and evaluate model simulations on smoke transport during the 2023 Maui wildfire event, and improve the modeling simulations by better representing wildfire plume rising process in the model.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.

从2023年8月8日开始，狂暴的狂风野火摧毁了毛伊岛的大部分拉海纳社区，并造成了数百次与烟有关的死亡和伤害。野火从野火发出的烟雾会对空气质量和气候产生不利影响，并通过其运输范围广泛的时间和空间尺度。但是，准确地表征野火羽流的垂直分布仍然具有挑战性，导致烟雾传输模拟中的大量不确定性。迄今为止，还没有一种基于观察的方法来有效捕获烟雾传输的快速变化模式。因此，从观察性的角度对烟雾传输和野火羽状垂直分布的全面表征将大大提高对野火烟雾传输模式（如移动方向，距离和受影响区域）的基本理解，并同时通过直接解决影响其建模的关键过程来改善烟雾传输模拟。鉴于气候变化下的野火活动，这项研究将减轻野火烟雾对财产和人类生命的毁灭性影响。该项目还将有助于开发有关烟气流动的近乎实时预测系统，并促进警告框架，以提醒当地居民在野火烟雾到来之前提醒当地居民。通过检查与2023 Maui Wildfires相关的密集烟雾排放和快速烟雾运动，该项目将对烟雾的烟雾和烟雾的烟雾进行系统的烟雾评估，并在野生烟雾中进行烟雾的影响，并影响野生烟雾，并影响野生烟雾，并影响野生型烟雾，造成野生烟雾，U型野外烟雾，U型野生动物的影响，U型野生烟雾，U型野生动物，U型野外烟雾，U。建模。关键科学问题包括1）2023年毛伊岛野火中烟雾传输模式和野火羽流垂直分布的特定特征和时间变化是什么？ 2）野火羽流的垂直分布如何影响烟雾传输模式？具体而言，该项目将采用高频地理卫星卫星测量测量，以在2023年的2023年毛伊岛野火期间使用预先计算机视觉技术（即光流分析）进行烟雾传输，然后估算基于地理位置式静止卫星的燃烧动力的昼夜循环的野外羽流升高，以表征底漆的分配。建模灵敏度研究将使用WRF-Chem模型进行，以评估羽流分布如何影响烟雾传输。最后，将对基于观察的分析进行验证，以识别和调和它们之间可能存在的差异并获得对烟雾传输模式的更精确描述。这项研究实际上代表了仅使用观测值量化烟雾传输的首次尝试。观察结果的证据将用于限制和评估2023年毛伊岛野火事件期间烟雾传输的模型模拟，并通过更好地代表模型中的野火羽流过程来改善建模模拟。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和广泛的影响来评估NSF的法定任务。