Canadian and Alaskan wildfire smoke particle properties, their evolution, and controlling factors, from satellite observations

Abstract

Abstract. The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Satellite Multi‐Angle Observations of Wildfire Smoke Plumes During the CalFiDE Field Campaign: Aerosol Plume Heights, Particle Property Evolution, and Aging Timescales

“…Based on a series of pre-and post-launch theoretical sensitivity studies (Kahn et al, 1997(Kahn et al, , 1998(Kahn et al, , 2001Kalashnikova & Kahn, 2006), about three-to-five bins in particle size over the range of about 0.1-2 µm effective radius, two-to-four bins in mid-visible SSA between about 0.7 and 1.0, and spherical versus randomly oriented non-spherical particles can be distinguished under good but not necessarily ideal retrieval conditions. The theoretical sensitivity results have been validated subsequently in both field-campaign case studies and statistical analyses (e.g., Diner et al, 2001;Kahn & Gaitley, 2015;Kahn et al, 2004Kahn et al, , 2009Kahn et al, , 2010, and specifically for wildfire smoke plumes in previous field campaigns where coincident, in situ aerosol measurement were also acquired (Junghenn Junghenn Noyes et al, 2022).…”

“…The pixel size is 1.1 km in all channels except for those of the nadir camera and the eight red‐band off‐nadir views, where the pixel resolution is about 275 m. Terra satellite equator crossing on the day side is in the mid‐late morning at about 10:30 a.m. local time, so the typical diurnal peak of fire activity is missed. However, major fire activity is often observed by MISR for fires at high latitudes, and everywhere for major fires that remain active through the night, making comprehensive, statistically based regional studies of wildfire plume properties and evolution possible (e.g., Gonzalez‐ Alonso et al., 2019; Junghenn Noyes et al., 2022; Val Martin et al., 2018; Zhu et al., 2018).…”

“…A user must outline the plume boundary to capture a region where the aerosol is sufficiently optically thick, so plume contrast features can be matched in the multi‐angle views, and must specify the plume source location and apparent wind direction interactively, on a case‐by‐case basis. As it takes about 7 min for all nine MISR cameras to view a given location on Earth, the proper motion of plume contrast elements over this period is used to derive the wind speed at plume elevation, allowing wind‐corrected plume height to be derived, and the age of aerosol progressively downwind from the source to be estimated (e.g., Junghenn Noyes, Kahn, Limbacher, Sedlechek, et al., 2020, Junghenn Noyes et al., 2022).…”

Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street

“…For example, although the amount of dust raised from a particular desert source region can vary diurnally, seasonally, and interannually, the emitted dust microphysical properties generally remain unchanged (e.g., Reid et al., 2008). Similarly, wildfires consuming the same vegetation types in the same ecosystem and season tend to produce smoke particles having similar properties (e.g., Junghenn Noyes et al., 2022; Reid et al., 2005). This means a program aimed at making the suite of key in situ particle intensive property measurements systematically is at least feasible.…”

“…This complementary exchange of information is illustrated in Figure 1 (red and dark green arrows). Further, despite the qualitative nature of satellite‐based particle‐evolution‐process deductions, the satellite data also offer broad spatial coverage that allows for multi‐year assessment of the dominant particle evolution processes and associated timescales where data quality is adequate (e.g., Junghenn Noyes et al., 2022).…”