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

2023年8月8日开始的狂风肆虐的野火摧毁了毛伊岛拉海纳社区的大部分地区，并造成数百人与烟雾有关的伤亡。野火排放的烟雾可通过其传播在广泛的时间和空间尺度上对空气质量和气候产生不利影响。然而，准确地描述野火羽流的垂直分布仍然是具有挑战性的，这导致了烟雾传输模拟中的巨大不确定性。到目前为止，还没有一种仅基于观测的方法来有效地捕捉快速变化的烟雾传输模式。因此，从观测的角度全面刻画烟雾传输和野火烟羽的垂直分布，将极大地促进对野火烟雾传输模式(如移动方向、距离和影响区域)的基本了解，同时通过直接解决影响其模拟的关键过程之一来改进烟雾传输模拟。鉴于气候变化下的野火活动日益增多，这项研究将减轻野火烟雾对财产和人类生活日益严重的破坏性影响。该项目还将帮助开发一个接近实时的烟雾运动预报系统，并促进一个预警框架，以便在野火烟雾到来之前向当地居民发出警报。通过检查与2023年毛伊岛野火相关的密集烟雾排放和快速烟雾运动，该项目将利用卫星观测和数值模拟，对烟雾传输模式和野火羽流垂直分布对烟雾传输的影响进行系统评估。关键的科学问题包括：1)2023年毛伊岛野火的烟雾传输模式和野火羽流垂直分布的具体特征和时间变化？2)野火羽流的垂直分布如何影响烟雾传输模式？具体地说，该项目将利用高频地球同步卫星测量，利用先进的计算机视觉技术，即光流分析，来描述2023年毛伊岛野火期间的烟雾传输，然后根据地球同步卫星得出的火灾辐射功率的日循环来估计野火羽流上升，以确定羽流的垂直分布。模拟敏感性研究将使用WRF-Chem模式进行，以评估烟羽垂直分布如何影响烟雾传输。最后，模型模拟将与基于观测的分析进行验证，以识别和协调它们之间可能存在的差异，并获得对烟雾传输模式的更准确描述。这项研究实际上代表了首次尝试仅使用观测来量化烟雾传输。来自观测的证据将用于约束和评估2023年毛伊岛野火事件期间烟雾传输的模型模拟，并通过在模型中更好地表示野火羽流上升过程来改进模拟模拟。该奖项反映了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。

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.