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Abstract. Wildfire smoke is one of the most significant concerns ofhuman and environmental health, associated with its substantial impacts onair quality, weather, and climate. However, biomass burning emissions andsmoke remain among the largest sources of uncertainties in air qualityforecasts. In this study, we evaluate the smoke emissions and plumeforecasts from 12 state-of-the-art air quality forecasting systemsduring the Williams Flats fire in Washington State, US, August 2019, whichwas intensively observed during the Fire Influence on Regional to GlobalEnvironments and Air Quality (FIREX-AQ) field campaign. Model forecasts withlead times within 1 d are intercompared under the same framework basedon observations from multiple platforms to reveal their performanceregarding fire emissions, aerosol optical depth (AOD), surface PM2.5,plume injection, and surface PM2.5 to AOD ratio. The comparison ofsmoke organic carbon (OC) emissions suggests a large range of daily totalsamong the models, with a factor of 20 to 50. Limited representations of thediurnal patterns and day-to-day variations of emissions highlight the needto incorporate new methodologies to predict the temporal evolution andreduce uncertainty of smoke emission estimates. The evaluation of smoke AOD(sAOD) forecasts suggests overall underpredictions in both the magnitude andsmoke plume area for nearly all models, although the high-resolution modelshave a better representation of the fine-scale structures of smoke plumes.The models driven by fire radiativepower (FRP)-based fire emissions or assimilating satellite AODdata generally outperform the others. Additionally, limitations of thepersistence assumption used when predicting smoke emissions are revealed bysubstantial underpredictions of sAOD on 8 August 2019, mainly over thetransported smoke plumes, owing to the underestimated emissions on7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecastsshow both positive and negative overall biases for these models, with mostmembers presenting more considerable diurnal variations of sPM2.5.Overpredictions of sPM2.5 are found for the models driven by FRP-basedemissions during nighttime, suggesting the necessity to improve verticalemission allocation within and above the planetary boundary layer (PBL).Smoke injection heights are further evaluated using the NASA LangleyResearch Center's Differential Absorption High Spectral Resolution Lidar(DIAL-HSRL) data collected during the flight observations. As the firebecame stronger over 3–8 August, the plume height became deeper, with aday-to-day range of about 2–9 km a.g.l. However, narrower ranges arefound for all models, with a tendency of overpredicting the plume heights forthe shallower injection transects and underpredicting for the days showingdeeper injections. The misrepresented plume injection heights lead toinaccurate vertical plume allocations along the transects corresponding totransported smoke that is 1 d old. Discrepancies in model performance forsurface PM2.5 and AOD are further suggested by the evaluation of theirratio, which cannot be compensated for by solely adjusting the smoke emissionsbut are more attributable to model representations of plume injections,besides other possible factors including the evolution of PBL depths andaerosol optical property assumptions. By consolidating multiple forecastsystems, these results provide strategic insight on pathways to improvesmoke forecasts.
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Smoke‐Driven Changes in Photosynthetically Active Radiation During the U.S. Agricultural Growing Season
Abstract Wildfire smoke is frequently present over the U.S. during the agricultural growing season and will likely increase with climate change. Studies of smoke impacts have largely focused on air quality and human health; however, understanding smoke's impact on photosynthetically active radiation (PAR) is essential for predicting how smoke affects plant growth. We compare surface shortwave irradiance and diffuse fraction (DF) on smoke‐impacted and smoke‐free days from 2006 to 2020 using data from multifilter rotating shadowband radiometers at 10 U.S. Department of Agriculture UV‐B Monitoring and Research Program stations and smoke plume locations from operational satellite products. On average, 20% of growing season days are smoke‐impacted, but smoke prevalence increases over time (r = 0.60,p < 0.05). Smoke presence peaks in the mid to late growing season (i.e., July, August), particularly over the northern Rocky Mountains, Great Plains, and Midwest. We find an increase in the distribution of PAR DF on smoke‐impacted days, with larger increases at lower cloud fractions. On clear‐sky days, daily average PAR DF increases by 10 percentage points when smoke is present. Spectral analysis of clear‐sky days shows smoke increases DF (average: +45%) and decreases total irradiance (average: −6%) across all six wavelengths measured from 368 to 870 nm. Optical depth measurements from ground and satellite observations both indicate that spectral DF increases and total spectral irradiance decreases with increasing smoke plume optical depth. Our analysis provides a foundation for understanding smoke's impact on PAR, which carries implications for agricultural crop productivity under a changing climate.
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- Award ID(s):
- 1828902
- PAR ID:
- 10386641
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 127
- Issue:
- 23
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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