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

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:
$15.0万
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
项目状态:
已结题
起止时间:
2023-10-01 至 2024-09-30

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中文摘要
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英文摘要
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.
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