ARL Weekly News – March 10, 2023

Recent Activities

AEROMMA Sensor Evaluation

Xinrong Ren, Phil Stratton, and Winston Luke met with Professor Mark Zondlo and his research group at Princeton University on Thursday, March 9. Dr. Zondlo has developed a unique open-path sensor for the sensitive and rapid detection of atmospheric ammonia (NH3), which solves the problem of the extensive surface interactions which plague closed-cell detectors. The purpose of the visit was to better understand the deployment, operation, and maintenance of the sensor and to foster collaborations to deploy it on ARL’s Chevrolet Suburban SUV for this summer’s AEROMMA (Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas) field study.

Ammonia measurements from the Suburban will support Dr. Nebila Lichiheb’s effort to study spatial and temporal variations in ambient atmospheric ammonia concentrations at the Yale Coastal Field Station in Guilford, CT, on the northern edge of Long Island Sound, before, during, and after AEROMMA. Combining measurements of atmospheric ammonia with those of greenhouse gases, ozone, and ozone precursors on the Suburban will also allow the calculation of atmospheric ammonia emission factors (EFs) from vehicular traffic in the NYC and Washington, DC areas. Mobile, on-road sources of ammonia are believed to be more significant than previously thought, and may constitute an important source of this aerosol precursor to the atmosphere.

Installation of the open path atmospheric ammonia sensor.
Mark Zondlo’s open-path sensor for the sensitive and rapid detection of atmospheric ammonia (NH3) to measure atmospheric ammonia.

Mini Conference at NCWCP
Several scientists from ARL’s Atmospheric Sciences and Modeling Division (ASMD) made presentations at an in-person mini-conference in College Park that took place from March 13-16, 2023. This event brought together colleagues at the NOAA Center for Weather and Climate Prediction (NCWCP) and the University of Maryland (UMD) in order to share presentations from recent conferences such as AGU and AMS. This was the first time such an event had occurred and was an opportunity that allowed for a greater sharing of science efforts between organizations including NWS/NCEP, OAR/ARL, NESDIS/STAR, ESSIC/CISESS, and UMD’s Department of Atmospheric and Oceanic Science (AOSC). The ASMD scientists who made presentations on ARL’s work were, Howard Diamond, Alice Crawford, Chris Loughner, Xinrong Ren, and Tianfeng Chai. While all these organizations work in the College Park area, it was a an excellent opportunity for ARL to better interact with our neighbors and to both show the work we do as well as to learn what science the other organizations are involved in.


Published: Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: a comparison of three schemes (Briggs, Freitas, and Sofiev). 

Citation: Li, Y., Tong, D., Ma, S., Freitas, S. R., Ahmadov, R., Sofiev, M., Zhang, X., Kondragunta, S., Kahn, R., Tang, Y., Baker, B., Campbell, P., Saylor, R., Grell, G., and Li, F.: Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: a comparison of three schemes (Briggs, Freitas, and Sofiev), Atmos. Chem. Phys., 23, 3083–3101,, 2023.

Short Summary: Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.

Abstract: Plume height plays a vital role in wildfire smoke dispersion and the subsequent effects on air quality and human health. In this study, we assess the impact of different plume rise schemes on predicting the dispersion of wildfire air pollution and the exceedances of the National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM2.5) during the 2020 western United States wildfire season. Three widely used plume rise schemes (Briggs, 1969; Freitas et al., 2007; Sofiev et al., 2012) are compared within the Community Multiscale Air Quality (CMAQ) modeling framework. The plume heights simulated by these schemes are comparable to the aerosol height observed by the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The performance of the simulations with these schemes varies by fire case and weather conditions. On average, simulations with higher plume injection heights predict lower aerosol optical depth (AOD) and surface PM2.5 concentrations near the source region but higher AOD and PM2.5 in downwind regions due to the faster spread of the smoke plume once ejected. The 2-month mean AOD difference caused by different plume rise schemes is approximately 20 %–30 % near the source regions and 5 %–10 % in the downwind regions. Thick smoke blocks sunlight and suppresses photochemical reactions in areas with high AOD. The surface PM2.5 difference reaches 70 % on the West Coast of the USA, and the difference is lower than 15 % in the downwind regions. Moreover, the plume injection height affects pollution exceedance (>35 µg m−3) predictions. Higher plume heights generally produce larger downwind PM2.5 exceedance areas. The PM2.5 exceedance areas predicted by the three schemes largely overlap, suggesting that all schemes perform similarly during large wildfire events when the predicted concentrations are well above the exceedance threshold. At the edges of the smoke plumes, however, there are noticeable differences in the PM2.5 concentration and predicted PM2.5 exceedance region. For the whole period of study, the difference in the total number of exceedance days could be as large as 20 d in northern California and 4 d in the downwind regions. This disagreement among the PM2.5 exceedance forecasts may affect key decision-making regarding early warning of extreme air pollution episodes at local levels during large wildfire events.

Published: Evaluation of Aerosol Optical Depth Forecasts from NOAA’s Global Aerosol Forecast Model (GEFS-Aerosols).

Citation: Bhattacharjee, P., Zhang, L., Baker, B., Pan, L., Montuoro, R., Grell, G. and McQueen, J. (2023). Evaluation of Aerosol Optical Depth Forecasts from NOAA’s Global Aerosol Forecast Model (GEFS-Aerosols). Weather and Forecasting 38(2) pp. 225-249. Available at: [Accessed 10 Mar 2023].

The NWS/NCEP recently implemented a new global deterministic aerosol forecast model named the Global Ensemble Forecast Systems Aerosols (GEFS-Aerosols), which is based on the Finite Volume version 3 GFS (FV3GFS). It replaced the operational NOAA Environmental Modeling System (NEMS) GFS Aerosol Component version 2 (NGACv2), which was based on a global spectral model (GSM). GEFS-Aerosols uses aerosol modules from the GOCART previously integrated in the WRF Model with Chemistry (WRF-Chem), FENGSHA dust scheme, and several other updates. In this study, we have extensively evaluated aerosol optical depth (AOD) forecasts from GEFS-Aerosols against various observations over a timespan longer than one year (2019–20). The total AOD improvement (in terms of seasonal mean) in GEFS-Aerosols is about 40% compared to NGACv2 in the fall and winter season of 2019. In terms of aerosol species, the biggest improvement came from the enhanced representation of biomass burning aerosol species as GEFS-Aerosols is able to capture more fire events in southern Africa, South America, and Asia than its predecessor. Dust AODs reproduce the seasonal variation over Africa and the Middle East. We have found that correlation of total AOD over large regions of the globe remains consistent for forecast days 3–5. However, we have found that GEFS-Aerosols generates some systematic positive biases for organic carbon AOD near biomass burning regions and sulfate AOD over prediction over East Asia. The addition of a data assimilation capability to GEFS-Aerosols in the near future is expected to address these biases and provide a positive impact to aerosol forecasts by the model.

Accepted: A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height.

Citation: Yorks, John E., Jun Wang, Matthew J. McGill, Melanie Follette-Cook, Edward P. Nowottnick, Jeffrey S. Reid, Peter R. Colarco, Jianglong Zhang, Olga Kalashnikova, Hongbin Yu, Franco Marenco, Joseph A. Santanello, Tammy M. Weckwerth, Zhanqing Li, James R. Campbell, Ping Yang, Minghui Diao, Vincent Noel, Kerry G. Meyer, James L. Carr, Michael Garay, Kenneth Christian, Angela Bennedetti, Allison M. Ring, Alice Crawford, Michael J. Pavolonis, Valentina Aquila, Jhoon Kim, and Shobha Kondragunta. “A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height”, Bulletin of the American Meteorological Society (published online ahead of print 2023), doi:

Abstract: A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing earth observation satellites to (1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to the Earth’s radiation budget), (2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and (3) characterize smoke and dust emission processes impacting their long-range transport on the sub-seasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in the Earth’s climate system at multiple spatiotemporal scales. Yet, their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multi-angle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol mixing layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.