Articles | Volume 20, issue 13
https://doi.org/10.5194/bg-20-2785-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-2785-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2023
Research article |
| 14 Jul 2023
| 14 Jul 2023
Burned area and carbon emissions across northwestern boreal North America from 2001–2019
Stefano Potter
CORRESPONDING AUTHOR
Woodwell Climate Research Center, Falmouth, MA 02540, USA
Sol Cooperdock
Woodwell Climate Research Center, Falmouth, MA 02540, USA
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA 90095, USA
Sander Veraverbeke
Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, 1105, the
Netherlands
Xanthe Walker
Center for Ecosystem Science and Society, Northern Arizona University,
Flagstaff, AZ 86011, USA
Michelle C. Mack
Center for Ecosystem Science and Society, Northern Arizona University,
Flagstaff, AZ 86011, USA
Scott J. Goetz
School of Informatics, Computing, and Cyber Systems, Northern Arizona
University, Flagstaff, AZ 86011, USA
Jennifer Baltzer
Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada
Laura Bourgeau-Chavez
Michigan Tech Research Institute, Ann Arbor, MI 48105, USA
Arden Burrell
Woodwell Climate Research Center, Falmouth, MA 02540, USA
Catherine Dieleman
University of Guelph, Guelph, ON N1G 2W1, Canada
Nancy French
Michigan Tech Research Institute, Ann Arbor, MI 48105, USA
Stijn Hantson
Universidad del Rosario, Bogotá, Cundinamarca, 200433, Colombia
Elizabeth E. Hoy
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Global Science & Technology, Inc, Greenbelt, MD 20770, USA
Liza Jenkins
Michigan Tech Research Institute, Ann Arbor, MI 48105, USA
Jill F. Johnstone
Institute of Arctic Biology, University of Alaska Fairbanks,
Fairbanks, AK 99775, USA
Evan S. Kane
12College of Forest Resources and Environmental Sciences, Michigan Tech University, Houghton, MI 49931, USA
Susan M. Natali
Woodwell Climate Research Center, Falmouth, MA 02540, USA
James T. Randerson
Department of Earth System Science, University of California, Irvine, Irvine, CA 92697, USA
Merritt R. Turetsky
Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder CO 80309, USA
Ellen Whitman
Natural Resources Canada, Canadian Forest Service, Northern Forestry
Centre, Edmonton, AB T6H 3S5, Canada
Elizabeth Wiggins
NASA Langley Research Center, Hampton, VA 23666, USA
Brendan M. Rogers
Woodwell Climate Research Center, Falmouth, MA 02540, USA
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Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
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.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
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This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag
EGUsphere, https://doi.org/10.5194/egusphere-2023-1167, https://doi.org/10.5194/egusphere-2023-1167, 2023
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Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Michael Moubarak, Seeta Sistla, Stefano Potter, Susan M. Natali, and Brendan M. Rogers
Biogeosciences, 20, 1537–1557, https://doi.org/10.5194/bg-20-1537-2023, https://doi.org/10.5194/bg-20-1537-2023, 2023
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Tundra wildfires are increasing in frequency and severity with climate change. We show using a combination of field measurements and computational modeling that tundra wildfires result in a positive feedback to climate change by emitting significant amounts of long-lived greenhouse gasses. With these effects, attention to tundra fires is necessary for mitigating climate change.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
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This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
Peter Stimmler, Mathias Goeckede, Bo Elberling, Susan Natali, Peter Kuhry, Nia Perron, Fabrice Lacroix, Gustaf Hugelius, Oliver Sonnentag, Jens Strauss, Christina Minions, Michael Sommer, and Jörg Schaller
Earth Syst. Sci. Data, 15, 1059–1075, https://doi.org/10.5194/essd-15-1059-2023, https://doi.org/10.5194/essd-15-1059-2023, 2023
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Arctic soils store large amounts of carbon and nutrients. The availability of nutrients, such as silicon, calcium, iron, aluminum, phosphorus, and amorphous silica, is crucial to understand future carbon fluxes in the Arctic. Here, we provide, for the first time, a unique dataset of the availability of the abovementioned nutrients for the different soil layers, including the currently frozen permafrost layer. We relate these data to several geographical and geological parameters.
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.
Clement Jean Frédéric Delcourt and Sander Veraverbeke
Biogeosciences, 19, 4499–4520, https://doi.org/10.5194/bg-19-4499-2022, https://doi.org/10.5194/bg-19-4499-2022, 2022
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This study provides new equations that can be used to estimate aboveground tree biomass in larch-dominated forests of northeast Siberia. Applying these equations to 53 forest stands in the Republic of Sakha (Russia) resulted in significantly larger biomass stocks than when using existing equations. The data presented in this work can help refine biomass estimates in Siberian boreal forests. This is essential to assess changes in boreal vegetation and carbon dynamics.
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.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
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.
David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, Theodore J. Bohn, John Connolly, Patrick Crill, Eugénie S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O'Donnell, Frans-Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire Treat, Ruth K. Varner, Tarmo Virtanen, Rebecca K. Warren, and Jennifer D. Watts
Earth Syst. Sci. Data, 13, 5127–5149, https://doi.org/10.5194/essd-13-5127-2021, https://doi.org/10.5194/essd-13-5127-2021, 2021
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Wetlands, lakes, and rivers are important sources of the greenhouse gas methane to the atmosphere. To understand current and future methane emissions from northern regions, we need maps that show the extent and distribution of specific types of wetlands, lakes, and rivers. The Boreal–Arctic Wetland and Lake Dataset (BAWLD) provides maps of five wetland types, seven lake types, and three river types for northern regions and will improve our ability to predict future methane emissions.
McKenzie A. Kuhn, Ruth K. Varner, David Bastviken, Patrick Crill, Sally MacIntyre, Merritt Turetsky, Katey Walter Anthony, Anthony D. McGuire, and David Olefeldt
Earth Syst. Sci. Data, 13, 5151–5189, https://doi.org/10.5194/essd-13-5151-2021, https://doi.org/10.5194/essd-13-5151-2021, 2021
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Methane (CH4) emissions from the boreal–Arctic region are globally significant, but the current magnitude of annual emissions is not well defined. Here we present a dataset of surface CH4 fluxes from northern wetlands, lakes, and uplands that was built alongside a compatible land cover dataset, sharing the same classifications. We show CH4 fluxes can be split by broad land cover characteristics. The dataset is useful for comparison against new field data and model parameterization or validation.
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.
Leah Birch, Christopher R. Schwalm, Sue Natali, Danica Lombardozzi, Gretchen Keppel-Aleks, Jennifer Watts, Xin Lin, Donatella Zona, Walter Oechel, Torsten Sachs, Thomas Andrew Black, and Brendan M. Rogers
Geosci. Model Dev., 14, 3361–3382, https://doi.org/10.5194/gmd-14-3361-2021, https://doi.org/10.5194/gmd-14-3361-2021, 2021
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The high-latitude landscape or Arctic–boreal zone has been warming rapidly, impacting the carbon balance both regionally and globally. Given the possible global effects of climate change, it is important to have accurate climate model simulations. We assess the simulation of the Arctic–boreal carbon cycle in the Community Land Model (CLM 5.0). We find biases in both the timing and magnitude photosynthesis. We then use observational data to improve the simulation of the carbon cycle.
William R. Wieder, Derek Pierson, Stevan Earl, Kate Lajtha, Sara G. Baer, Ford Ballantyne, Asmeret Asefaw Berhe, Sharon A. Billings, Laurel M. Brigham, Stephany S. Chacon, Jennifer Fraterrigo, Serita D. Frey, Katerina Georgiou, Marie-Anne de Graaff, A. Stuart Grandy, Melannie D. Hartman, Sarah E. Hobbie, Chris Johnson, Jason Kaye, Emily Kyker-Snowman, Marcy E. Litvak, Michelle C. Mack, Avni Malhotra, Jessica A. M. Moore, Knute Nadelhoffer, Craig Rasmussen, Whendee L. Silver, Benjamin N. Sulman, Xanthe Walker, and Samantha Weintraub
Earth Syst. Sci. Data, 13, 1843–1854, https://doi.org/10.5194/essd-13-1843-2021, https://doi.org/10.5194/essd-13-1843-2021, 2021
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Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Here we present the SOils DAta Harmonization database (SoDaH), a flexible database designed to harmonize diverse SOM datasets from multiple research networks.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
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.
Matthew J. Rowlinson, Alexandru Rap, Douglas S. Hamilton, Richard J. Pope, Stijn Hantson, Steve R. Arnold, Jed O. Kaplan, Almut Arneth, Martyn P. Chipperfield, Piers M. Forster, and Lars Nieradzik
Atmos. Chem. Phys., 20, 10937–10951, https://doi.org/10.5194/acp-20-10937-2020, https://doi.org/10.5194/acp-20-10937-2020, 2020
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas which contributes to anthropogenic climate change; however, the effect of human emissions is uncertain because pre-industrial ozone concentrations are not well understood. We use revised inventories of pre-industrial natural emissions to estimate the human contribution to changes in tropospheric ozone. We find that tropospheric ozone radiative forcing is up to 34 % lower when using improved pre-industrial biomass burning and vegetation emissions.
Cited articles
Amiro, B. D., Todd, J. B., Wotton, B. M., Logan, K. A., Flannigan, M. D.,
Stocks, B. J., Mason, J. A., Martell, D. L., and Hirsch, K. G.: Direct
carbon emissions from Canadian forest fires, 1959–1999, Can. J.
Forest Res., 31, 512–525, https://doi.org/10.1139/cjfr-31-3-512, 2001.
Balshi, M. S., Mcguire, A. D., Duffy, P., Flannigan, M., Kicklighter, D. W.,
and Melillo, J.: Vulnerability of carbon storage in North American boreal
forests to wildfires during the 21st century, Glob. Change Biol., 15,
1491–1510, https://doi.org/10.1111/j.1365-2486.2009.01877.x,
2009.
Baltzer, J. L., Day, N. J., Walker, X. J., Greene, D., Mack, M. C., Alexander, H. D., Arseneault, D.,
Barnes, J., Bergeron, Y., Boucher, Y., Bourgeau-Chavez, L., Brown, C. D., Carrière, S., Howard,
B. K., Gauthier, S., Parisien, M.-A., Reid, K. A., Rogers, B. M., Roland, C., Sirous, C., Stehn, S.,
Thompson, D. K., Turetsky, M. R., Veraverbeke, S., Whitman, E., Yang, J., and Johnstone, J. F.: Increasing fire and the decline of fire
adapted black spruce in the boreal forest, P. Natl.
Acad. Sci. USA, 118, e2024872118, https://doi.org/10.1073/pnas.2024872118, 2021.
Beaudoin, A., Bernier, P., Guindon, L., Villemaire, P., Guo, X. J., Stinson,
G., Magnussen, S., and Hall, R. J.: Mapping attributes of Canada's forests
at moderate resolution through kNN and MODIS imagery, Can. J. Forest Res., 44, 521–532,
https://doi.org/10.1139/cjfr-2013-0401, 2014.
Beck, P. S. A., Goetz, S. J., Mack, M. C., Alexander, H. D., Jin, Y.,
Randerson, J. T., and Loranty, M. M.: The impacts and implications of an
intensifying fire regime on Alaskan boreal forest composition and albedo,
Glob. Change Biol., 17, 2853–2866, https://doi.org/10.1111/j.1365-2486.2011.02412.x, 2011.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing
area model of basin hydrology, Hydrol. Sci. B., 24,
43–69, https://doi.org/10.1080/02626667909491834, 1979.
Boby, L. A., Schuur, E. A. G., Mack, M. C., Verbyla, D., and Johnstone, J.
F.: Quantifying fire severity, carbon, and nitrogen emissions in Alaska's
boreal forest, Ecol. Appl., 20, 1633–1647, https://doi.org/10.1890/08-2295.1, 2010.
Bonan, G. B. and Shugart, H. H.: Environmental Factors and Ecological
Processes in Boreal Forests, Annu. Rev. Ecol. Syst., 20,
1–28, 1989.
Bond-Lamberty, B., Peckham, S. D., Ahl, D. E., and Gower, S. T.: Fire as the
dominant driver of central Canadian boreal forest carbon balance, Nature,
450, 89–92, https://doi.org/10.1038/nature06272, 2007.
Boulanger, Y., Parisien, M.-A., and Wang, X.: Model-specification
uncertainty in future area burned by wildfires in Canada, Int.
J. Wildland Fire, 27, 164–175, https://doi.org/10.1071/WF17123, 2018.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Burns, P. J., Massey, R. M., Shean, D., Husby, E. B., and Goetz, S. G.: NASA ABoVE 10m Composite Digital
Elevation Model, Arctic Data Center [data set], https://doi.org/10.18739/A2057CT8Q, 2023.
Chawla, N. V., Bowyer, K. W., Hall, L. O., and Kegelmeyer, W. P.: SMOTE:
Synthetic Minority Over-sampling Technique, J. Artif.
Intell. Res., 16, 321–357, https://doi.org/10.1613/jair.953, 2002.
Chen, D., Loboda, T. V., and Hall, J. V.: A systematic evaluation of
influence of image selection process on remote sensing-based burn severity
indices in North American boreal forest and tundra ecosystems, ISPRS J. Photogramm., 159, 63–77, https://doi.org/10.1016/j.isprsjprs.2019.11.011, 2020.
Chen, D., Fu, C., Hall, J. V., Hoy, E. E., and Loboda, T. V.:
Spatio-temporal patterns of optimal Landsat data for burn severity index
calculations: Implications for high northern latitudes wildfire research,
Remote Sens. Environ., 258, 112393, https://doi.org/10.1016/j.rse.2021.112393, 2021.
Daly, C., Gibson, W., Taylor, G., Johnson, G., and Pasteris, P.: A
knowledge-based approach to the statistical mapping of climate, Clim.
Res., 22, 99–113, https://doi.org/10.3354/cr022099, 2002.
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor,
G. H., Curtis, J., and Pasteris, P. P.: Physiographically sensitive mapping
of climatological temperature and precipitation across the conterminous
United States, Int. J. Climatol., 28, 2031–2064, https://doi.org/10.1002/joc.1688, 2008.
de Groot, W.J., Landry, R., Kurz, W. A., Anderson, K. R., Englefield, P., Fraser, R. H., Hall, R. J.,
Banfield, E., Raymond, D. A., Decker, V., Lynham, T. J., and Pritchard, J. M.: Estimating direct carbon emissions from Canadian wildland
fires, Int. J. Wildland Fire, 16, 593–606, https://doi.org/10.1071/WF06150, 2007.
de Groot, W. J., Pritchard, J. M. P. M., and Lynham, T. J. L. J.: Forest
floor fuel consumption and carbon emissions in Canadian boreal forest fires,
Can. J. Forest Res., 39, 367–382, https://doi.org/10.1139/X08-192, 2009.
Di Giuseppe, F., Rémy, S., Pappenberger, F., and Wetterhall, F.: Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations, Atmos. Chem. Phys., 18, 5359–5370, https://doi.org/10.5194/acp-18-5359-2018, 2018.
Dieleman, C. M., Rogers, B. M., Potter, S., Veraverbeke, S., Johnstone, J.
F., Laflamme, J., Solvik, K., Walker, X. J., Mack, M. C., and Turetsky, M.
R.: Wildfire combustion and carbon stocks in the southern Canadian boreal
forest: Implications for a warming world, Glob. Change Biol., 26,
6062–6079, https://doi.org/10.1111/gcb.15158, 2020.
Epp, H. and Lanoville, R.: Satellite data and geographic information
systems for fire and resource management in the Canadian arctic, Geocarto
Int., 11, 97–103, https://doi.org/10.1080/10106049609354537, 1996.
Fick, S. E. and Hijmans, R. J.: WorldClim 2: New 1-km spatial resolution
climate surfaces for global land areas, Int. J.
Climatol., 37, 4302–4315, https://doi.org/10.1002/joc.5086, 2017.
Field, R. D., Spessa, A. C., Aziz, N. A., Camia, A., Cantin, A., Carr, R., de Groot, W. J., Dowdy, A. J., Flannigan, M. D., Manomaiphiboon, K., Pappenberger, F., Tanpipat, V., and Wang, X.: Development of a Global Fire Weather Database, Nat. Hazards Earth Syst. Sci., 15, 1407–1423, https://doi.org/10.5194/nhess-15-1407-2015, 2015.
Foga, S., Scaramuzza, P. L., Guo, S., Zhu, Z., Dilley, R. D., Beckmann, T.,
Schmidt, G. L., Dwyer, J. L., Hughes, M. J., and Laue, B.: Cloud detection
algorithm comparison and validation for operational Landsat data products, Remote Sens. Environ., 194, 379–390, https://doi.org/10.1016/j.rse.2017.03.026, 2017.
French, N. H. F.: Uncertainty in estimating carbon emissions from boreal forest fires, J.
Geophys. Res., 109, D14S08, https://doi.org/10.1029/2003JD003635, 2004.
French, N. H. F., Kasischke, E. S., and Williams, D. G.: Variability in the
emission of carbon-based trace gases from wildfire in the Alaskan boreal
forest, J. Geophys. Res., 108, 8151, https://doi.org/10.1029/2001JD000480, 2002.
French, N. H. F., Groot, W. J. de, Jenkins, L. K., Rogers, B. M., Alvarado,
E., Amiro, B., Jong, B. de, Goetz, S., Hoy, E., Hyer, E., Keane, R., Law, B.
E., McKenzie, D., McNulty, S. G., Ottmar, R., Pérez-Salicrup, D. R.,
Randerson, J., Robertson, K. M., and Turetsky, M.: Model comparisons for
estimating carbon emissions from North American wildland fire, J.
Geophys. Res.-Biogeo., 116, G00K05, https://doi.org/10.1029/2010JG001469, 2011.
French, N. H. F., McKenzie, D., Erickson, T., Koziol, B., Billmire, M.,
Endsley, K. A., Yager Scheinerman, N. K., Jenkins, L., Miller, M. E.,
Ottmar, R., and Prichard, S.: Modeling Regional-Scale Wildland Fire
Emissions with the Wildland Fire Emissions Information System, Earth
Interact., 18, 1–26, https://doi.org/10.1175/EI-D-14-0002.1, 2014.
French, N. H. F., Jenkins, L. K., Loboda, T. V., Flannigan, M., Jandt, R.,
Bourgeau-Chavez, L. L., and Whitley, M.: Fire in arctic tundra of Alaska:
Past fire activity, future fire potential, and significance for land
management and ecology, Int. J. Wildland Fire, 24, 1045, https://doi.org/10.1071/WF14167, 2015.
Friedl, M. and Sulla-Menashe, D.: MCD12Q1 MODIS/Terra+Aqua Land Cover Type
Yearly L3 Global 500 m SIN Grid V006, NASA EOSDIS Land Processes
DAAC [data set], https://doi.org/10.5067/MODIS/MCD12Q1.006, 2019.
Genet, H., McGuire, A. D., Barrett, K., Breen, A., Euskirchen, E. S.,
Johnstone, J. F., Kasischke, E. S., Melvin, A. M., Bennett, A., Mack, M. C.,
Rupp, T. S., Schuur, A. E. G., Turetsky, M. R., and Yuan, F.: Modeling the
effects of fire severity and climate warming on active layer thickness and
soil carbon storage of black spruce forests across the landscape in interior
Alaska, Environ. Res. Lett., 8, 045016, https://doi.org/10.1088/1748-9326/8/4/045016, 2013.
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., and Justice, C. O.:
The Collection 6 MODIS burned area mapping algorithm and product, Remote
Sens. Environ., 217, 72–85, https://doi.org/10.1016/j.rse.2018.08.005, 2018.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore,
R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, https://doi.org/10.1016/j.rse.2017.06.031, 2017.
Gruber, S.: Derivation and analysis of a high-resolution estimate of global permafrost zonation, The Cryosphere, 6, 221–233, https://doi.org/10.5194/tc-6-221-2012, 2012.
Guindon, L., Bernier, P., Gauthier, S., Stinson, G., Villemaire, P., and
Beaudoin, A.: Missing forest cover gains in boreal forests explained,
Ecosphere, 9, e02094, https://doi.org/10.1002/ecs2.2094,
2018.
Guyon, I., Weston, J., Barnhill, S., and Vapnik, V.: Gene Selection for Cancer
Classification Using Support Vector Machines, Mach. Learn., 46,
389–422, 2002.
Hall, R. J., Skakun, R. S., Metsaranta, J. M., Landry, R., Fraser, R. H.,
Raymond, D., Gartrell, M., Decker, V., Little, J., Hall, R. J., Skakun, R.
S., Metsaranta, J. M., Landry, R., Fraser, R. H., Raymond, D., Gartrell, M.,
Decker, V., and Little, J.: Generating annual estimates of forest fire
disturbance in Canada: The National Burned Area Composite, Int.
J. Wildland Fire, 29, 878–891, https://doi.org/10.1071/WF19201, 2020.
Hanes, C. C., Wang, X., Jain, P., Parisien, M.-A., Little, J. M., and
Flannigan, M. D.: Fire-regime changes in Canada over the last half century,
Can. J. Forest Res., 49, 256–269, https://doi.org/10.1139/cjfr-2018-0293, 2018.
Hantson, S., Arneth, A., Harrison, S. P., Kelley, D. I., Prentice, I. C., Rabin, S. S., Archibald, S., Mouillot, F., Arnold, S. R., Artaxo, P., Bachelet, D., Ciais, P., Forrest, M., Friedlingstein, P., Hickler, T., Kaplan, J. O., Kloster, S., Knorr, W., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Meyn, A., Sitch, S., Spessa, A., van der Werf, G. R., Voulgarakis, A., and Yue, C.: The status and challenge of global fire modelling, Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, 2016.
Hardisky, M. A., Klemas, V., and Smart, R. M.: The influences of soil
salinity, growth form, and leaf moisture on the spectral reflectance of
Spartina alterniflora canopies, Photogramm. Eng. Rem.
S., 49, 77–83, 1983.
Hengl, T., de Jesus, J. M., Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda,
M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X.,
Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A.,
Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and
Kempen, B.: SoilGrids250m: Global gridded soil information based on machine
learning, PLOS ONE, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017.
Hilker, T., Wulder, M. A., Coops, N. C., Linke, J., McDermid, G., Masek, J.
G., Gao, F., and White, J. C.: A new data fusion model for high spatial- and
temporal-resolution mapping of forest disturbance based on Landsat and
MODIS, Remote Sens. Environ., 113, 1613–1627, https://doi.org/10.1016/j.rse.2009.03.007, 2009.
Hoy, E. E., Turetsky, M. R., and Kasischke, E.: More frequent burning
increases vulnerability of Alaskan boreal black spruce forests,
Environ. Res. Lett., 11, 095001, https://doi.org/10.1088/1748-9326/11/9/095001, 2016.
Hudak, A. T., Morgan, P., Bobbitt, M. J., Smith, A. M. S., Lewis, S. A.,
Lentile, L. B., Robichaud, P. R., Clark, J. T., and McKinley, R. A.: The
Relationship of Multispectral Satellite Imagery to Immediate Fire Effects,
Fire Ecol., 3, 64–90, https://doi.org/10.4996/fireecology.0301064, 2007.
Houle, G. P., Kane, E. S., Kasischke, E. S., Gibson, C., and Turetsky, M. R.:
Recovery of Carbon Pools a Decade Following Wildfire in Black Spruce Forests
of Interior Alaska: Effects of Soil Texture and Landscape Position, Can.
J. Forest Res., 48, 1–10, https://doi.org/10.1139/cjfr-2017-0236, 2017.
Hutchinson, M. F.: A new objective method for spatial interpolation of
meteorological variables
from irregular networks applied to the estimation of monthly mean solar
radiation, temperature, precip- itation and windrun, CSIRO Division of Water
Resources Tech. Memo., 89, 95–104, 1989.
Ivanova, G. A., Conard, S. G., Kukavskaya, E. A., and McRae, D. J.: Fire
impact on carbon storage in light conifer forests of the Lower Angara
region, Siberia, Environ. Res. Lett., 6, 045203, https://doi.org/10.1088/1748-9326/6/4/045203, 2011.
Jafarov, E. E., Romanovsky, V. E., Genet, H., McGuire, A. D., and Marchenko,
S. S.: The effects of fire on the thermal stability of permafrost in lowland
and upland black spruce forests of interior Alaska in a changing climate,
Environ. Res. Lett., 8, 035030, https://doi.org/10.1088/1748-9326/8/3/035030, 2013.
Jain, P., Coogan, S. C. P., Subramanian, S. G., Crowley, M., Taylor, S., and
Flannigan, M. D.: A review of machine learning applications in wildfire
science and management, Environ. Rev., 28, 478–505, https://doi.org/10.1139/er-2020-0019, 2020.
Johnstone, J. F., Chapin, F. S., Hollingsworth, T. N., Mack, M. C.,
Romanovsky, V., and Turetsky, M.: Fire, climate change, and forest
resilience in interior AlaskaThis article is one of a selection of papers
from The Dynamics of Change in Alaska's Boreal Forests: Resilience and
Vulnerability in Response to Climate Warming, Can. J. Forest
Res., 40, 1302–1312, https://doi.org/10.1139/X10-061,
2010.
Ju, J. and Masek, J. G.: The vegetation greenness trend in Canada and US
Alaska from 1984–2012 Landsat data, Remote Sens. Environ., 176,
1–16, https://doi.org/10.1016/j.rse.2016.01.001, 2016.
Kasischke, E. S. and Hoy, E. E.: Controls on carbon consumption during
Alaskan wildland fires, Glob. Change Biol., 18, 685–699, https://doi.org/10.1111/j.1365-2486.2011.02573.x, 2012.
Kasischke, E. S., Williams, D., and Barry, D.: Analysis of the patterns of
large fires in the boreal forest region of Alaska, Int. J.
Wildland Fire, 11, 131–144, https://doi.org/10.1071/wf02023, 2002.
Kasischke, E. S., Verbyla, D. L., Rupp, T. S., McGuire, A. D., Murphy, K.
A., Jandt, R., Barnes, J. L., Hoy, E. E., Duffy, P. A., Calef, M., and
Turetsky, M. R.: Alaska's changing fire regime – implications for the
vulnerability of its boreal forestsThis article is one of a selection of
papers from The Dynamics of Change in Alaska's Boreal Forests: Resilience
and Vulnerability in Response to Climate Warming, Can. J. Forest
Res., 40, 1313–1324, https://doi.org/10.1139/X10-098,
2010.
Kauth, R. J. and Thomas, G. S.: The Tasselled Cap – A Graphic Description
of the Spectral-Temporal Development of Agricultural Crops as Seen by
LANDSAT, LARS Symposia, paper 159, 1976.
Key, C. H. and Benson, N. C.: Landscape Assessment: Ground measure of severity, the Composite Burn
Index; and Remote sensing of severity, the Normalized Burn Ratio (Report RMRS-GTR-164-CD: LA 1-51), USGS Publications Warehouse, http://pubs.er.usgs.gov/publication/2002085 (last access: 10 July 2023),
2006.
Knopp, L., Wieland, M., Rättich, M., and Martinis, S.: A Deep Learning
Approach for Burned Area Segmentation with Sentinel-2 Data, Remote Sens.,
12, 2422, https://doi.org/10.3390/rs12152422, 2020.
Latifovic, R., Homer, C., Ressl, R., Pouliot, D. A.,
Hossian, S., Colditz, R., Olthof, I., Chandra, G., and
Victoria, A.: North American Land Change Monitoring System, in: Remote
Sensing of Land Use and Land Cover: Principles and Applications, CRC Press, 303–324,
https://doi.org/10.1201/b11964-24, 2012.
Li, F., Lawrence, D. M., and Bond-Lamberty, B.: Impact of fire on global
land surface air temperature and energy budget for the 20th century due to
changes within ecosystems, Environ. Res. Lett., 12, 044014, https://doi.org/10.1088/1748-9326/aa6685, 2017.
Loboda, T. V., Chen, D., Hall, J. V., and He, J.: ABoVE: Landsat-derived Burn
Scar dNBR across Alaska and Canada, 1985–2015, ORNL DAAC, Oak Ridge,
Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1564, 2018.
Loboda, T. V., Hoy, E. E., and Carroll, M. L.: ABoVE: Study Domain and Standard
Reference Grids, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1527, 2019.
McGuire, A. D., Anderson, L. G., Christensen, T. R., Dallimore, S., Guo, L.,
Hayes, D. J., Heimann, M., Lorenson, T. D., Macdonald, R. W., and Roulet,
N.: Sensitivity of the Carbon Cycle in the Arctic to Climate Change,
Ecol. Monogr., 79, 523–555, 2009.
Miller, J. D. and Thode, A. E.: Quantifying burn severity in a
heterogeneous landscape with a relative version of the delta Normalized Burn
Ratio (dNBR), Remote Sens. Environ., 109, 66–80, https://doi.org/10.1016/j.rse.2006.12.006, 2007.
Mitchell, T. D. and Jones, P. D.: An improved method of constructing a
database of monthly climate observations and associated high-resolution
grids, Int. J. Climatol., 25, 693–712, https://doi.org/10.1002/joc.1181, 2005.
Natali, S. M., Holdren, J. P., Rogers, B. M., Treharne, R., Duffy, P. B.,
Pomerance, R., and MacDonald, E.: Permafrost carbon feedbacks threaten
global climate goals, P. Natl. Acad. Sci. USA,
118, e2100163118, https://doi.org/10.1073/pnas.2100163118, 2021.
Neigh, C. S. R., Masek, J. G., and Nickeson, J. E.: High-Resolution
Satellite Data Open for Government Research, EOS T. Am.
Geophys. Un., 94, 121–123, https://doi.org/10.1002/2013EO130002, 2013.
Ottmar, R. D., Sandberg, D. V., Riccardi, C. L., and Prichard, S. J.: An
overview of the Fuel Characteristic Classification System – Quantifying, classifying, and
creating fuelbeds for resource planning, Can. J. Forest Res., 37,
2383–2393, https://doi.org/10.1139/X07-077, 2007.
Parks, S., Dillon, G., and Miller, C.: A New Metric for Quantifying Burn
Severity: The Relativized Burn Ratio, Remote Sens., 6, 1827–1844, https://doi.org/10.3390/rs6031827, 2014.
Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution
mapping of global surface water and its long-term changes, Nature,
540, 418–422, https://doi.org/10.1038/nature20584, 2016.
Porter, C., Morin, P., Howat, I., Noh, M., Bates, B., Peterman, K., Keesey,
S., Schlenk, M., Gardiner, J., Tomko, K., Willis, M., Kelleher, C.,
Cloutier, M., Husby, E., Foga, S., Nakamura, H., Platson, M., Wethington,
M., Williamson, C., Bauer, G., Enos, J., Arnold, G., Kramer, W., Becker, P.,
Doshi, A., D'Souza, C., Cummens, P., Laurier, F., and Bojesen, M.:
ArcticDEM, V1, Harvard
Dataverse [data set], https://doi.org/10.7910/DVN/OHHUKH, 2018.
Potter, S., Veraverbeke, S., Walker, X. J., Mack, M. C., Goetz, S. J.,
Baltzer, J. L., Dieleman, C., French, N. H. F., Kane, E. S., Turetsky, M. R., Wiggins, E. B.,
and Rogers, B. M.: ABoVE: Burned Area, Depth, and Combustion for Alaska and
Canada, 2001–2019, ORNL DAAC, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/2063, 2022.
Pouliot, D. and Latifovic, R.: Accuracy assessment of annual land cover
time series derived from change-based updating, Banff, Canada, Institute of
Electrical and Electronics Engineers [data set], https://doi.org/10.1109/Multi-Temp.2013.6866005, 2013.
Pouliot, D., Latifovic, R., Zabcic, N., Guindon, L., and Olthof, I.:
Development and assessment of a 250 m spatial resolution MODIS annual land
cover time series (2000–2011) for the forest region of Canada derived from
change-based updating, Remote Sens. Environ., 140, 731–743, https://doi.org/10.1016/j.rse.2013.10.004, 2014.
Rabin, S. S., Melton, J. R., Lasslop, G., Bachelet, D., Forrest, M., Hantson, S., Kaplan, J. O., Li, F., Mangeon, S., Ward, D. S., Yue, C., Arora, V. K., Hickler, T., Kloster, S., Knorr, W., Nieradzik, L., Spessa, A., Folberth, G. A., Sheehan, T., Voulgarakis, A., Kelley, D. I., Prentice, I. C., Sitch, S., Harrison, S., and Arneth, A.: The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions, Geosci. Model Dev., 10, 1175–1197, https://doi.org/10.5194/gmd-10-1175-2017, 2017.
Randerson, J. T., Chen, Y., Werf, G. R. van der, Rogers, B. M., and Morton,
D. C.: Global burned area and biomass burning emissions from small fires,
J. Geophys. Res.-Biogeo., 117, G04012, https://doi.org/10.1029/2012JG002128, 2012.
Raynolds, M. K., Walker, D. A., Balser, A., Bay, C., Campbell, M., Cherosov, M. M., Daniëls, F. J. A.,
Eidesen, P. B., Ermokhina, K. A., Frost, G. V., Jedrzejek, B., Jorgenson, M. T., Kennedy, B. E.,
Kholod, S. S., Lavrinenko, I. A., Lavrinenko, O. V., Magnússon, B., Matveyeva, N. V.,
Metúsalemsson, S., Nilsen, L., and Troeva, E.: A raster version of the
Circumpolar Arctic Vegetation Map (CAVM), Remote Sens. Environ.,
232, 111297, https://doi.org/10.1016/j.rse.2019.111297, 2019.
R Core Team: R: A language and environment for statistical computing, R
Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 1 April 2023), 2021.
Rogers, B. M., Veraverbeke, S., Azzari, G., Czimczik, C. I., Holden, S. R.,
Mouteva, G. O., Sedano, F., Treseder, K. K., and Randerson, J. T.:
Quantifying fire-wide carbon emissions in interior Alaska using field
measurements and Landsat imagery, J. Geophys. Res.-Biogeo., 119, 1608–1629, https://doi.org/10.1002/2014JG002657, 2014.
Rogers, B. M., Soja, A. J., Goulden, M. L., and Randerson, J. T.: Influence
of tree species on continental differences in boreal fires and climate
feedbacks, Nat. Geosci., 8, 228–234, https://doi.org/10.1038/ngeo2352, 2015.
Roy, D. P., Kovalskyy, V., Zhang, H. K., Vermote, E. F., Yan, L., Kumar, S.
S., and Egorov, A.: Characterization of Landsat-7 to Landsat-8 reflective
wavelength and normalized difference vegetation index continuity, Remote
Sens. Environ., 185, 57–70, https://doi.org/10.1016/j.rse.2015.12.024, 2016.
Scholten, R. C., Jandt, R., Miller, E. A., Rogers, B. M., and Veraverbeke,
S.: Overwintering fires in boreal forests, Nature, 593, 399–404, https://doi.org/10.1038/s41586-021-03437-y, 2021.
Schmidt, G., Jenkerson, C. B., Masek, J., Vermote, E., and Gao, F.: Landsat
ecosystem disturbance adaptive processing system (LEDAPS) algorithm
description (Report No. 2013–1057; Open-File Report, p. 27), USGS
Publications Warehouse, https://doi.org/10.3133/ofr20131057,
2013.
Seiler, W. and Crutzen, P. J.: Estimates of gross and net fluxes of carbon
between the biosphere and the atmosphere from biomass burning, Climatic
Change, 2, 207–247, https://doi.org/10.1007/BF00137988,
1980.
Sexton, J. O., Song, X.-P., Feng, M., Noojipady, P., Anand, A., Huang, C.,
Kim, D.-H., Collins, K. M., Channan, S., DiMiceli, C., and Townshend, J. R.:
Global, 30-m resolution continuous fields of tree cover: Landsat-based
rescaling of MODIS vegetation continuous fields with lidar-based estimates
of error, Int. J. Digit. Earth, 6, 427–448, https://doi.org/10.1080/17538947.2013.786146, 2013.
Skakun, R., Whitman, E., Little, J. M., and Parisien, M.-A.: Area burned
adjustments to historical wildland fires in Canada, Environ. Res.
Lett., 16, 064014, https://doi.org/10.1088/1748-9326/abfb2c, 2021.
Stocks, B. J., Mason, J. A., Todd, J. B., Bosch, E. M., Wotton, B. M.,
Amiro, B. D., Flannigan, M. D., Hirsch, K. G., Logan, K. A., Martell, D. L.,
and Skinner, W. R.: Large forest fires in Canada, 1959–1997, J.
Geophys. Res.-Atmos., 107, FFR 5-1–FFR 5-12, https://doi.org/10.1029/2001JD000484, 2003.
Tan, Z., Tieszen, L. L., Zhu, Z., Liu, S., and Howard, S. M.: An estimate of
carbon emissions from 2004 wildfires across Alaskan Yukon River Basin,
Carbon Balance and Management, 2, 12, https://doi.org/10.1186/1750-0680-2-12, 2007.
Tucker, C. J.: Red and photographic infrared linear combinations for
monitoring vegetation, Remote Sens. Environ., 8, 127–150, https://doi.org/10.1016/0034-4257(79)90013-0, 1979.
Turetsky, M. R., Kane, E. S., Harden, J. W., Ottmar, R. D., Manies, K. L.,
Hoy, E., and Kasischke, E. S.: Recent acceleration of biomass burning and
carbon losses in Alaskan forests and peatlands, Nat. Geosci., 4,
27–31, https://doi.org/10.1038/ngeo1027, 2011.
Treharne, R., Rogers, B. M., Gasser, T., MacDonald, E., and Natali, S.:
Identifying Barriers to Estimating Carbon Release From Interacting Feedbacks
in a Warming Arctic, Front. Climate, 3, 716464, https://doi.org/10.3389/fclim.2021.716464, 2022.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
van Wees, D., van der Werf, G. R., Randerson, J. T., Rogers, B. M., Chen, Y., Veraverbeke, S., Giglio, L., and Morton, D. C.: Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED), Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, 2022.
Veraverbeke, S., Rogers, B. M., and Randerson, J. T.: Daily burned area and carbon emissions from boreal fires in Alaska, Biogeosciences, 12, 3579–3601, https://doi.org/10.5194/bg-12-3579-2015, 2015.
Veraverbeke, S., Rogers, B. M., Goulden, M. L., Jandt, R. R., Miller, C. E.,
Wiggins, E. B., and Randerson, J. T.: Lightning as a major driver of recent
large fire years in North American boreal forests, Nat. Clim. Change,
7, 529–534, https://doi.org/10.1038/nclimate3329, 2017.
Vermote, E. and Wolfe, R.: MOD09GA MODIS/Terra Surface Reflectance Daily L2G
Global 1 km and 500 m SIN Grid V006, NASA EOSDIS Land Processes
DAAC [data set], https://doi.org/10.5067/MODIS/MYD09GA.006, 2015a.
Vermote, E. and Wolfe, R.: MOD09GA MODIS/Terra Surface Reflectance Daily L2G
Global 1 km and 500 m SIN Grid V006, NASA EOSDIS Land Processes
DAAC [data set], https://doi.org/10.5067/MODIS/MOD09GA.006, 2015b.
Vermote, E., Justice, C., Claverie, M., and Franch, B.: Preliminary analysis
of the performance of the Landsat 8/OLI land surface reflectance product,
Remote Sens. Environ., 185, 46–56, https://doi.org/10.1016/j.rse.2016.04.008, 2016.
Walker, X. J., Rogers, B. M., Baltzer, J. L., Cumming, S. G., Day, N. J.,
Goetz, S. J., Johnstone, J. F., Schuur, E. A. G., Turetsky, M. R., and Mack,
M. C.: Cross-scale controls on carbon emissions from boreal forest
megafires, Glob. Change Biol., 24, 4251–4265, https://doi.org/10.1111/gcb.14287, 2018.
Walker, X. J., Baltzer, J. L., Cumming, S. G., Day, N. J., Ebert, C., Goetz,
S., Johnstone, J. F., Potter, S., Rogers, B. M., Schuur, E. A. G., Turetsky,
M. R., and Mack, M. C.: Increasing wildfires threaten historic carbon sink
of boreal forest soils, Nature, 572, 520–523, https://doi.org/10.1038/s41586-019-1474-y, 2019.
Walker, X. J., Baltzer, J. L., Bourgeau-Chavez, L. L., Day, N. J., de Groot,
W. J., Dieleman, C., Hoy, E. E., Johnstone, J. F., Kane, E. S., Parisien, M. A.,
Potter, S., Rogers, B. M., Turetsky, M. R., Veraverbeke, S. R., Whitman, E. and
Mack, M. C.: ABoVE: Synthesis of Burned and Unburned Forest Site Data, AK
and Canada, 1983–2016, ORNL DAAC, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1744, 2020a.
Walker, X. J., Rogers, B. M., Veraverbeke, S., Johnstone, J. F., Baltzer, J.
L., Barrett, K., Bourgeau-Chavez, L., Day, N. J., de Groot, W. J., Dieleman,
C. M., Goetz, S., Hoy, E., Jenkins, L. K., Kane, E. S., Parisien, M.-A.,
Potter, S., Schuur, E. A. G., Turetsky, M., Whitman, E., and Mack, M. C.:
Fuel availability not fire weather controls boreal wildfire severity and
carbon emissions, Nat. Clim. Change, 10, 1130–1136, https://doi.org/10.1038/s41558-020-00920-8, 2020b.
Walker, X. J., Baltzer, J. L., Bourgeau-Chavez, L., Day, N. J., Dieleman, C.
M., Johnstone, J. F., Kane, E. S., Rogers, B. M., Turetsky, M. R.,
Veraverbeke, S., and Mack, M. C.: Patterns of Ecosystem Structure and
Wildfire Carbon Combustion Across Six Ecoregions of the North American
Boreal Forest, Frontiers in Forests and Global Change, 3, 87, https://doi.org/10.3389/ffgc.2020.00087, 2020c.
Wang, J. A., Baccini, A., Farina, M., Randerson, J. T., and Friedl, M. A.:
Disturbance suppresses the aboveground carbon sink in North American boreal
forests, Nat. Clim. Change, 11, 435–441, 2021.
Wang, T., Hamann, A., Spittlehouse, D., and Carroll, C.: Locally Downscaled
and Spatially Customizable Climate Data for Historical and Future Periods
for North America, PLOS ONE, 11, e0156720, https://doi.org/10.1371/journal.pone.0156720, 2016.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Wright, M. and Ziegler, A.: ranger: A Fast Implementation of Random Forests for
High Dimensional Data in C
Wolfe, J. A.: Temperature parameters of humid to mesic forests of Eastern
Asia and relation to forests of other regions of the Northern Hemisphere and
Australasia: analysis of temperature data from more than 400 stations in
Eastern Asia (U.S. Geological Survey Professional Paper No. 1106),
Washington, DC, US Dep. Int., https://doi.org/10.3133/pp1106, 1979.
Young, A. M., Higuera, P. E., Duffy, P. A., and Hu, F. S.: Climatic
thresholds shape northern high-latitude fire regimes and imply vulnerability
to future climate change, Ecography, 40, 606–617, https://doi.org/10.1111/ecog.02205, 2017.
Zhao, B., Zhuang, Q., Shurpali, N., Köster, K., Berninger, F., and
Pumpanen, J.: North American boreal forests are a large carbon source due to
wildfires from 1986 to 2016, Sci. Rep., 11, 7723, https://doi.org/10.1038/s41598-021-87343-3, 2021.
Short summary
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.
Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and...
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