Articles | Volume 16, issue 3
https://doi.org/10.5194/essd-16-1395-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-1395-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Mar 2024
Data description paper |
| 15 Mar 2024
| 15 Mar 2024
Systematically tracking the hourly progression of large wildfires using GOES satellite observations
Department of Earth System Science, University of California, Irvine, Irvine, CA, USA
James T. Randerson
Department of Earth System Science, University of California, Irvine, Irvine, CA, USA
Yang Chen
Department of Earth System Science, University of California, Irvine, Irvine, CA, USA
Douglas C. Morton
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Elizabeth B. Wiggins
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Padhraic Smyth
Department of Computer Science, University of California, Irvine, Irvine, CA, USA
Efi Foufoula-Georgiou
Department of Earth System Science, University of California, Irvine, Irvine, CA, USA
Roy Nadler
Google, Mountain View, CA, USA
Omer Nevo
Google, Mountain View, CA, USA
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Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev., 18, 4103–4117, https://doi.org/10.5194/gmd-18-4103-2025, https://doi.org/10.5194/gmd-18-4103-2025, 2025
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This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Jason A. Miech, Joshua P. DiGangi, Glenn S. Diskin, Yonghoon Choi, Richard H. Moore, Luke D. Ziemba, Francesca Gallo, Carolyn E. Jordan, Michael A. Shook, Elizabeth B. Wiggins, Edward L. Winstead, Sayantee Roy, Young Ro Lee, Katherine Ball, John D. Crounse, Paul Wennberg, Felix Piel, Stefan Swift, Wojciech Wojnowski, and Armin Wisthaler
EGUsphere, https://doi.org/10.5194/egusphere-2025-2602, https://doi.org/10.5194/egusphere-2025-2602, 2025
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Biomass burning is a significant source of greenhouse gases and airborne pollutants in Asia. Airborne measurements of greenhouse gas enhancement ratios, trace gases, and particle scattering were used to identify air masses impacted by biomass burning over several Asian countries during March and April of 2024. Further analysis using atmospheric transport models and satellite hotspot products was performed to understand the transport history of biomass burning impacted airmasses over Thailand.
Jan-Lukas Tirpitz, Santo Fedele Colosimo, Nathaniel Brockway, Robert Spurr, Matt Christi, Samuel Hall, Kirk Ullmann, Johnathan Hair, Taylor Shingler, Rodney Weber, Jack Dibb, Richard Moore, Elizabeth Wiggins, Vijay Natraj, Nicolas Theys, and Jochen Stutz
Atmos. Chem. Phys., 25, 1989–2015, https://doi.org/10.5194/acp-25-1989-2025, https://doi.org/10.5194/acp-25-1989-2025, 2025
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We combine plume composition data from the 2019 NASA FIREX-AQ campaign with state-of-the-art radiative transfer modeling techniques to calculate distributions of actinic flux and photolysis frequencies in a wildfire plume. Excellent agreement of the model and observations demonstrates the applicability of this approach to constrain photochemistry in such plumes. We identify limiting factors for the modeling accuracy and discuss spatial and spectral features of the distributions.
Joanne V. Hall, Fernanda Argueta, Maria Zubkova, Yang Chen, James T. Randerson, and Louis Giglio
Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, https://doi.org/10.5194/essd-16-867-2024, 2024
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Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
Yang Chen, Joanne Hall, Dave van Wees, Niels Andela, Stijn Hantson, Louis Giglio, Guido R. van der Werf, Douglas C. Morton, and James T. Randerson
Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, https://doi.org/10.5194/essd-15-5227-2023, 2023
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Using multiple sets of remotely sensed data, we created a dataset of monthly global burned area from 1997 to 2020. The estimated annual global burned area is 774 million hectares, significantly higher than previous estimates. Burned area declined by 1.21% per year due to extensive fire loss in savanna, grassland, and cropland ecosystems. This study enhances our understanding of the impact of fire on the carbon cycle and climate system, and may improve the predictions of future fire changes.
Stefano Potter, Sol Cooperdock, Sander Veraverbeke, Xanthe Walker, Michelle C. Mack, Scott J. Goetz, Jennifer Baltzer, Laura Bourgeau-Chavez, Arden Burrell, Catherine Dieleman, Nancy French, Stijn Hantson, Elizabeth E. Hoy, Liza Jenkins, Jill F. Johnstone, Evan S. Kane, Susan M. Natali, James T. Randerson, Merritt R. Turetsky, Ellen Whitman, Elizabeth Wiggins, and Brendan M. Rogers
Biogeosciences, 20, 2785–2804, https://doi.org/10.5194/bg-20-2785-2023, https://doi.org/10.5194/bg-20-2785-2023, 2023
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Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m resolution. We estimate 2.37 Mha burned annually between 2001–2019 over the domain, emitting 79.3 Tg C per year, with a mean combustion rate of 3.13 kg C m−2. We found larger-fire years were generally associated with greater mean combustion. The burned-area and combustion datasets described here can be used for local- to continental-scale applications of boreal fire science.
Laura Tomsche, Felix Piel, Tomas Mikoviny, Claus J. Nielsen, Hongyu Guo, Pedro Campuzano-Jost, Benjamin A. Nault, Melinda K. Schueneman, Jose L. Jimenez, Hannah Halliday, Glenn Diskin, Joshua P. DiGangi, John B. Nowak, Elizabeth B. Wiggins, Emily Gargulinski, Amber J. Soja, and Armin Wisthaler
Atmos. Chem. Phys., 23, 2331–2343, https://doi.org/10.5194/acp-23-2331-2023, https://doi.org/10.5194/acp-23-2331-2023, 2023
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Ammonia (NH3) is an important trace gas in the atmosphere and fires are among the poorly investigated sources. During the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) aircraft campaign, we measured gaseous NH3 and particulate ammonium (NH4+) in smoke plumes emitted from 6 wildfires in the Western US and 66 small agricultural fires in the Southeastern US. We herein present a comprehensive set of emission factors of NH3 and NHx, where NHx = NH3 + NH4+.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Francesca Gallo, Kevin J. Sanchez, Bruce E. Anderson, Ryan Bennett, Matthew D. Brown, Ewan C. Crosbie, Chris Hostetler, Carolyn Jordan, Melissa Yang Martin, Claire E. Robinson, Lynn M. Russell, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Elizabeth B. Wiggins, Edward L. Winstead, Armin Wisthaler, Luke D. Ziemba, and Richard H. Moore
Atmos. Chem. Phys., 23, 1465–1490, https://doi.org/10.5194/acp-23-1465-2023, https://doi.org/10.5194/acp-23-1465-2023, 2023
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We integrate in situ ship- and aircraft-based measurements of aerosol, trace gases, and meteorological parameters collected during the NASA North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) field campaigns in the western North Atlantic Ocean region. A comprehensive characterization of the vertical profiles of aerosol properties under different seasonal regimes is provided for improving the understanding of aerosol key processes and aerosol–cloud interactions in marine regions.
Pamela S. Rickly, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Glenn M. Wolfe, Ryan Bennett, Ilann Bourgeois, John D. Crounse, Jack E. Dibb, Joshua P. DiGangi, Glenn S. Diskin, Maximilian Dollner, Emily M. Gargulinski, Samuel R. Hall, Hannah S. Halliday, Thomas F. Hanisco, Reem A. Hannun, Jin Liao, Richard Moore, Benjamin A. Nault, John B. Nowak, Jeff Peischl, Claire E. Robinson, Thomas Ryerson, Kevin J. Sanchez, Manuel Schöberl, Amber J. Soja, Jason M. St. Clair, Kenneth L. Thornhill, Kirk Ullmann, Paul O. Wennberg, Bernadett Weinzierl, Elizabeth B. Wiggins, Edward L. Winstead, and Andrew W. Rollins
Atmos. Chem. Phys., 22, 15603–15620, https://doi.org/10.5194/acp-22-15603-2022, https://doi.org/10.5194/acp-22-15603-2022, 2022
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Biomass burning sulfur dioxide (SO2) emission factors range from 0.27–1.1 g kg-1 C. Biomass burning SO2 can quickly form sulfate and organosulfur, but these pathways are dependent on liquid water content and pH. Hydroxymethanesulfonate (HMS) appears to be directly emitted from some fire sources but is not the sole contributor to the organosulfur signal. It is shown that HMS and organosulfur chemistry may be an important S(IV) reservoir with the fate dependent on the surrounding conditions.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
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We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Ewan Crosbie, Luke D. Ziemba, Michael A. Shook, Claire E. Robinson, Edward L. Winstead, K. Lee Thornhill, Rachel A. Braun, Alexander B. MacDonald, Connor Stahl, Armin Sorooshian, Susan C. van den Heever, Joshua P. DiGangi, Glenn S. Diskin, Sarah Woods, Paola Bañaga, Matthew D. Brown, Francesca Gallo, Miguel Ricardo A. Hilario, Carolyn E. Jordan, Gabrielle R. Leung, Richard H. Moore, Kevin J. Sanchez, Taylor J. Shingler, and Elizabeth B. Wiggins
Atmos. Chem. Phys., 22, 13269–13302, https://doi.org/10.5194/acp-22-13269-2022, https://doi.org/10.5194/acp-22-13269-2022, 2022
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The linkage between cloud droplet and aerosol particle chemical composition was analyzed using samples collected in a polluted tropical marine environment. Variations in the droplet composition were related to physical and dynamical processes in clouds to assess their relative significance across three cases that spanned a range of rainfall amounts. In spite of the pollution, sea salt still remained a major contributor to the droplet composition and was preferentially enhanced in rainwater.
Nicole A. June, Anna L. Hodshire, Elizabeth B. Wiggins, Edward L. Winstead, Claire E. Robinson, K. Lee Thornhill, Kevin J. Sanchez, Richard H. Moore, Demetrios Pagonis, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Matthew M. Coggon, Jonathan M. Dean-Day, T. Paul Bui, Jeff Peischl, Robert J. Yokelson, Matthew J. Alvarado, Sonia M. Kreidenweis, Shantanu H. Jathar, and Jeffrey R. Pierce
Atmos. Chem. Phys., 22, 12803–12825, https://doi.org/10.5194/acp-22-12803-2022, https://doi.org/10.5194/acp-22-12803-2022, 2022
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The evolution of organic aerosol composition and size is uncertain due to variability within and between smoke plumes. We examine the impact of plume concentration on smoke evolution from smoke plumes sampled by the NASA DC-8 during FIREX-AQ. We find that observed organic aerosol and size distribution changes are correlated to plume aerosol mass concentrations. Additionally, coagulation explains the majority of the observed growth.
Ilann Bourgeois, Jeff Peischl, J. Andrew Neuman, Steven S. Brown, Hannah M. Allen, Pedro Campuzano-Jost, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Jessica B. Gilman, Georgios I. Gkatzelis, Hongyu Guo, Hannah A. Halliday, Thomas F. Hanisco, Christopher D. Holmes, L. Gregory Huey, Jose L. Jimenez, Aaron D. Lamplugh, Young Ro Lee, Jakob Lindaas, Richard H. Moore, Benjamin A. Nault, John B. Nowak, Demetrios Pagonis, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Vanessa Selimovic, Jason M. St. Clair, David Tanner, Krystal T. Vasquez, Patrick R. Veres, Carsten Warneke, Paul O. Wennberg, Rebecca A. Washenfelder, Elizabeth B. Wiggins, Caroline C. Womack, Lu Xu, Kyle J. Zarzana, and Thomas B. Ryerson
Atmos. Meas. Tech., 15, 4901–4930, https://doi.org/10.5194/amt-15-4901-2022, https://doi.org/10.5194/amt-15-4901-2022, 2022
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Understanding fire emission impacts on the atmosphere is key to effective air quality management and requires accurate measurements. We present a comparison of airborne measurements of key atmospheric species in ambient air and in fire smoke. We show that most instruments performed within instrument uncertainties. In some cases, further work is needed to fully characterize instrument performance. Comparing independent measurements using different techniques is important to assess their accuracy.
Linghan Zeng, Jack Dibb, Eric Scheuer, Joseph M. Katich, Joshua P. Schwarz, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Carsten Warneke, Anne E. Perring, Glenn S. Diskin, Joshua P. DiGangi, John B. Nowak, Richard H. Moore, Elizabeth B. Wiggins, Demetrios Pagonis, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Lu Xu, and Rodney J. Weber
Atmos. Chem. Phys., 22, 8009–8036, https://doi.org/10.5194/acp-22-8009-2022, https://doi.org/10.5194/acp-22-8009-2022, 2022
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Wildfires emit aerosol particles containing brown carbon material that affects visibility and global climate and is toxic. Brown carbon is poorly characterized due to measurement limitations, and its evolution in the atmosphere is not well known. We report on aircraft measurements of brown carbon from large wildfires in the western United States. We compare two methods for measuring brown carbon and study the evolution of brown carbon in the smoke as it moved away from the burning regions.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Adam T. Ahern, Frank Erdesz, Nicholas L. Wagner, Charles A. Brock, Ming Lyu, Kyra Slovacek, Richard H. Moore, Elizabeth B. Wiggins, and Daniel M. Murphy
Atmos. Meas. Tech., 15, 1093–1105, https://doi.org/10.5194/amt-15-1093-2022, https://doi.org/10.5194/amt-15-1093-2022, 2022
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Particles in the atmosphere play a significant role in climate change by scattering light back into space, reducing the amount of energy available to be absorbed by greenhouse gases. We built a new instrument to measure what direction light is scattered by particles, e.g., wildfire smoke. This is important because, depending on the angle of the sun, some particles scatter light into space (cooling the planet), but some light is also scattered towards the Earth (not cooling the planet).
Kevin J. Sanchez, Bo Zhang, Hongyu Liu, Matthew D. Brown, Ewan C. Crosbie, Francesca Gallo, Johnathan W. Hair, Chris A. Hostetler, Carolyn E. Jordan, Claire E. Robinson, Amy Jo Scarino, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Elizabeth B. Wiggins, Edward L. Winstead, Luke D. Ziemba, Georges Saliba, Savannah L. Lewis, Lynn M. Russell, Patricia K. Quinn, Timothy S. Bates, Jack Porter, Thomas G. Bell, Peter Gaube, Eric S. Saltzman, Michael J. Behrenfeld, and Richard H. Moore
Atmos. Chem. Phys., 22, 2795–2815, https://doi.org/10.5194/acp-22-2795-2022, https://doi.org/10.5194/acp-22-2795-2022, 2022
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Atmospheric particle concentrations impact clouds, which strongly impact the amount of sunlight reflected back into space and the overall climate. Measurements of particles over the ocean are rare and expensive to collect, so models are necessary to fill in the gaps by simulating both particle and clouds. However, some measurements are needed to test the accuracy of the models. Here, we measure changes in particles in different weather conditions, which are ideal for comparison with models.
Sagar K. Tamang, Ardeshir Ebtehaj, Peter Jan van Leeuwen, Gilad Lerman, and Efi Foufoula-Georgiou
Nonlin. Processes Geophys., 29, 77–92, https://doi.org/10.5194/npg-29-77-2022, https://doi.org/10.5194/npg-29-77-2022, 2022
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The outputs from Earth system models are optimally combined with satellite observations to produce accurate forecasts through a process called data assimilation. Many existing data assimilation methodologies have some assumptions regarding the shape of the probability distributions of model output and observations, which results in forecast inaccuracies. In this paper, we test the effectiveness of a newly proposed methodology that relaxes such assumptions about high-dimensional models.
Zachary C. J. Decker, Michael A. Robinson, Kelley C. Barsanti, Ilann Bourgeois, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Frank M. Flocke, Alessandro Franchin, Carley D. Fredrickson, Georgios I. Gkatzelis, Samuel R. Hall, Hannah Halliday, Christopher D. Holmes, L. Gregory Huey, Young Ro Lee, Jakob Lindaas, Ann M. Middlebrook, Denise D. Montzka, Richard Moore, J. Andrew Neuman, John B. Nowak, Brett B. Palm, Jeff Peischl, Felix Piel, Pamela S. Rickly, Andrew W. Rollins, Thomas B. Ryerson, Rebecca H. Schwantes, Kanako Sekimoto, Lee Thornhill, Joel A. Thornton, Geoffrey S. Tyndall, Kirk Ullmann, Paul Van Rooy, Patrick R. Veres, Carsten Warneke, Rebecca A. Washenfelder, Andrew J. Weinheimer, Elizabeth Wiggins, Edward Winstead, Armin Wisthaler, Caroline Womack, and Steven S. Brown
Atmos. Chem. Phys., 21, 16293–16317, https://doi.org/10.5194/acp-21-16293-2021, https://doi.org/10.5194/acp-21-16293-2021, 2021
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To understand air quality impacts from wildfires, we need an accurate picture of how wildfire smoke changes chemically both day and night as sunlight changes the chemistry of smoke. We present a chemical analysis of wildfire smoke as it changes from midday through the night. We use aircraft observations from the FIREX-AQ field campaign with a chemical box model. We find that even under sunlight typical
nighttimechemistry thrives and controls the fate of key smoke plume chemical processes.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Richard H. Moore, Elizabeth B. Wiggins, Adam T. Ahern, Stephen Zimmerman, Lauren Montgomery, Pedro Campuzano Jost, Claire E. Robinson, Luke D. Ziemba, Edward L. Winstead, Bruce E. Anderson, Charles A. Brock, Matthew D. Brown, Gao Chen, Ewan C. Crosbie, Hongyu Guo, Jose L. Jimenez, Carolyn E. Jordan, Ming Lyu, Benjamin A. Nault, Nicholas E. Rothfuss, Kevin J. Sanchez, Melinda Schueneman, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Nicholas L. Wagner, and Jian Wang
Atmos. Meas. Tech., 14, 4517–4542, https://doi.org/10.5194/amt-14-4517-2021, https://doi.org/10.5194/amt-14-4517-2021, 2021
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Atmospheric particles are everywhere and exist in a range of sizes, from a few nanometers to hundreds of microns. Because particle size determines the behavior of chemical and physical processes, accurately measuring particle sizes is an important and integral part of atmospheric field measurements! Here, we discuss the performance of two commonly used particle sizers and how changes in particle composition and optical properties may result in sizing uncertainties, which we quantify.
Elizabeth B. Wiggins, Arlyn Andrews, Colm Sweeney, John B. Miller, Charles E. Miller, Sander Veraverbeke, Roisin Commane, Steven Wofsy, John M. Henderson, and James T. Randerson
Atmos. Chem. Phys., 21, 8557–8574, https://doi.org/10.5194/acp-21-8557-2021, https://doi.org/10.5194/acp-21-8557-2021, 2021
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We analyzed high-resolution trace gas measurements collected from a tower in Alaska during a very active fire season to improve our understanding of trace gas emissions from boreal forest fires. Our results suggest previous studies may have underestimated emissions from smoldering combustion in boreal forest fires.
Demetrios Pagonis, Pedro Campuzano-Jost, Hongyu Guo, Douglas A. Day, Melinda K. Schueneman, Wyatt L. Brown, Benjamin A. Nault, Harald Stark, Kyla Siemens, Alex Laskin, Felix Piel, Laura Tomsche, Armin Wisthaler, Matthew M. Coggon, Georgios I. Gkatzelis, Hannah S. Halliday, Jordan E. Krechmer, Richard H. Moore, David S. Thomson, Carsten Warneke, Elizabeth B. Wiggins, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 1545–1559, https://doi.org/10.5194/amt-14-1545-2021, https://doi.org/10.5194/amt-14-1545-2021, 2021
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We describe the airborne deployment of an extractive electrospray time-of-flight mass spectrometer (EESI-MS). The instrument provides a quantitative 1 Hz measurement of the chemical composition of organic aerosol up to altitudes of
7 km, with single-compound detection limits as low as 50 ng per standard cubic meter.
Kevin J. Sanchez, Bo Zhang, Hongyu Liu, Georges Saliba, Chia-Li Chen, Savannah L. Lewis, Lynn M. Russell, Michael A. Shook, Ewan C. Crosbie, Luke D. Ziemba, Matthew D. Brown, Taylor J. Shingler, Claire E. Robinson, Elizabeth B. Wiggins, Kenneth L. Thornhill, Edward L. Winstead, Carolyn Jordan, Patricia K. Quinn, Timothy S. Bates, Jack Porter, Thomas G. Bell, Eric S. Saltzman, Michael J. Behrenfeld, and Richard H. Moore
Atmos. Chem. Phys., 21, 831–851, https://doi.org/10.5194/acp-21-831-2021, https://doi.org/10.5194/acp-21-831-2021, 2021
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Models describing atmospheric airflow were combined with satellite measurements representative of marine phytoplankton and other meteorological variables. These combined variables were compared to measured aerosol to identify upwind influences on aerosol concentrations. Results indicate that phytoplankton production rates upwind impact the aerosol mass. Also, results suggest that the condensation of mass onto short-lived large sea spray particles may be a significant sink of aerosol mass.
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Short summary
To improve our understanding of extreme wildfire behavior, we use geostationary satellite data to develop the GOFER algorithm and track the hourly fire progression of large wildfires. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery and reveals considerable variability in fire spread rates on diurnal timescales. We create a product of hourly fire perimeters, active-fire lines, and fire spread rates for 28 fires in California.
To improve our understanding of extreme wildfire behavior, we use geostationary satellite data...
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