Title

Evaluating Wildfire Smoke Transport Within a Coupled Fire-Atmosphere Model Using a High-Density Observation Network for an Episodic Smoke Event Along Utah's Wasatch Front

Publication Date

10-27-2020

Document Type

Article

Department

Meteorology and Climate Science

Publication Title

Journal of Geophysical Research: Atmospheres

Volume

125

Issue

20

DOI

10.1029/2020JD032712

Abstract

One of the primary challenges associated with evaluating smoke models is the availability of observations. The limited density of traditional air quality monitoring networks makes evaluating wildfire smoke transport challenging, particularly over regions where smoke plumes exhibit significant spatiotemporal variability. In this study, we analyzed smoke dispersion for the 2018 Pole Creek and Bald Mountain Fires, which were located in central Utah. Smoke simulations were generated using a coupled fire-atmosphere model, which simultaneously renders fire growth, fire emissions, plume rise, smoke dispersion, and fire-atmosphere interactions. Smoke simulations were evaluated using PM2.5 observations from publicly accessible fixed sites and a semicontinuously running mobile platform. Calibrated measurements of PM2.5 made by low-cost sensors from the Air Quality and yoU (AQ&U) network were within 10% of values reported at nearby air quality sites that used Federal Equivalent Methods. Furthermore, results from this study show that low-cost sensor networks and mobile measurements are useful for characterizing smoke plumes while also serving as an invaluable data set for evaluating smoke transport models. Finally, coupled fire-atmosphere model simulations were able to capture the spatiotemporal variability of wildfire smoke in complex terrain for an isolated smoke event caused by local fires. Results here suggest that resolving local drainage flow could be critical for simulating smoke transport in regions of significant topographic relief.

Funding Number

1646408

Funding Sponsor

National Science Foundation

Keywords

air quality, atmospheric modeling, low-cost air quality sensors, mobile measurements, mountain meteorology, wildfire smoke

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