Enhancing Wildfire and Smoke Forecasting by Integrating Fire Observations: A Comparative Analysis of Methods for Integrating Infrared and Satellite Data Into a Coupled Fire-Atmosphere Model

IF 3.8 2区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Kathleen Clough, Angel Farguell, Jan Mandel, Kyle Hilburn, Adam Kochanski
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Abstract

Accurate forecasts of fire spread and smoke impacts using coupled fire-atmosphere models require advanced methods for fire initialization. This paper proposes and tests three different methods for integrating fire observations. The methods reconstruct the initial fire evolution needed for the atmosphere spin-up at the beginning of the simulation and identify actively burning fire regions. One method is based solely on IR perimeters, while the other two leverage IR perimeters and satellite detections. One uses only the most recent satellite data, while the other contextualized method uses two consecutive satellite detections to identify which sections of the fire perimeter experienced significant growth and which were inactive. This integration method addresses the problem of inaccurate identification of actively burning regions, thus correcting the previously seen overestimated growth in real-time forecasts. This problem is fundamental when forecasting multiday fire incidents, which benefit from updating the state of the fire at the beginning of each forecast. The methods were tested within the WRFx fire forecasting system. The entire real-time forecast for the 2021 Caldor Fire was rerun using the three methods and compared against observations. The analysis of the fire growth, as well as surface PM2.5 concentrations and smoke heights, indicate that the contextual method utilizing both IR perimeters and satellite detections offers significant improvements when compared to the other methods for all variables analyzed, with the most considerable improvement in forecast skill seen in forecasts with 24–48 hr lead time.

结合火灾观测加强野火和烟雾预报:将红外和卫星数据整合到火-大气耦合模型中的方法比较分析
使用耦合火-大气模型准确预测火灾蔓延和烟雾影响需要先进的火灾初始化方法。本文提出并测试了三种不同的火灾观测综合方法。该方法在模拟开始时重建大气自旋上升所需的初始火灾演变,并识别活跃燃烧的火区。一种方法完全基于红外周界,而另外两种方法利用红外周界和卫星探测。一种方法仅使用最新的卫星数据,而另一种情境化方法使用两个连续的卫星探测来确定火灾边界的哪些部分经历了显著的增长,哪些部分不活跃。这种整合方法解决了不准确识别活跃燃烧区域的问题,从而纠正了以前在实时预测中看到的高估增长。在预测多日火灾事件时,这个问题是基本的,这得益于每次预测开始时更新火灾状态。这些方法在WRFx火灾预报系统中进行了测试。使用这三种方法重新运行了2021年卡尔多大火的整个实时预测,并与观测结果进行了比较。对火灾增长、地表PM2.5浓度和烟雾高度的分析表明,与其他方法相比,利用红外周长和卫星探测的上下文方法对所有分析变量都有显著改进,预测技能的显著提高体现在提前24-48小时的预测中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Geophysical Research: Atmospheres
Journal of Geophysical Research: Atmospheres Earth and Planetary Sciences-Geophysics
CiteScore
7.30
自引率
11.40%
发文量
684
期刊介绍: JGR: Atmospheres publishes articles that advance and improve understanding of atmospheric properties and processes, including the interaction of the atmosphere with other components of the Earth system.
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