Affiliation:
1. Portland Forestry Sciences Laboratory, Pacific Northwest Research Station, United States Department of Agriculture Forest Service, 1220 SW 3rd Ave., Suite 1410, Portland, OR 97204, USA
Abstract
Weather conditions at the time of wildfire front arrival strongly influence fire behavior and effects, yet few methods exist for estimating weather conditions more spatio-temporally resolved than coarse-grain (e.g., 4 km) daily averages. When a fire front advances rapidly and weather conditions are heterogeneous over space and time, greater spatio-temporal precision is required to accurately link fire weather to observed fire effects. To identify the influence of fire weather on fire effects observed across a sample of existing forest inventory plots during a wind-driven megafire event in the US Pacific Northwest, we explored and compared three methods for estimating time of fire arrival and the wind speed at that arrival time for each plot location. Two methods were based on widely used, remotely sensed active fire data products with dissimilar spatial and temporal resolutions. The third and preferred method, Modeled-Weather Interpolated Perimeters (MoWIP), is a new approach that leveraged fine-grained (1.3 km, hourly) wind speed and direction from modeled fire weather to guide interpolation of aerial infrared-detected (IR) operational perimeters, subdividing the time intervals defined by sequential IR perimeters into quartile intervals to enhance temporal resolution of predicted fire arrival times. Our description of these fire arrival “time stamp” methods and discussion of their utility and shortcomings should prove useful to fire scientists, ecologists, land managers, and future analyses seeking to link estimated fire weather and observed fire effects.
Funder
USDA Forest Service PNW Research Station
Station’s Westside Fire Research Initiative
Oak Ridge Institute for Science and Education
ORAU
Subject
Earth and Planetary Sciences (miscellaneous),Safety Research,Environmental Science (miscellaneous),Safety, Risk, Reliability and Quality,Building and Construction,Forestry
Reference25 articles.
1. Constraints on global fire activity vary across a resource gradient;Krawchuk;Ecology,2011
2. Modeling wildfire smoke feedback mechanisms using a coupled fire-atmosphere model with a radiatively active aerosol scheme;Kochanski;J. Geophys. Res. Atmos.,2019
3. Using satellite-derived fire arrival times for coupled wildfire-air quality simulations at regional scales of the 2020 California wildfire season;Lassman;J. Geophys. Res. Atmos.,2023
4. Farguell, A., Mandel, J., Haley, J., Mallia, D.V., Kochanski, A., and Hilburn, K. (2021). Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data. Remote Sens., 13.
5. Satellite-based fire progression mapping: A comprehensive assessment for large fires in northern California;Scaduto;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2020
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献