Articles | Volume 15, issue 22
https://doi.org/10.5194/gmd-15-8411-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-8411-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| Highlight paper
| 
21 Nov 2022
Model description paper | Highlight paper |
| 21 Nov 2022
| 21 Nov 2022
Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)
Department of Earth Sciences, Vrije Universiteit, Amsterdam, 1081 HV,
the Netherlands
Guido R. van der Werf
CORRESPONDING AUTHOR
Department of Earth Sciences, Vrije Universiteit, Amsterdam, 1081 HV,
the Netherlands
James T. Randerson
Department of Earth System Science, University of California, Irvine,
CA 92697, USA
Brendan M. Rogers
Woodwell Climate Research Center, Falmouth, MA 02540, USA
Yang Chen
Department of Earth System Science, University of California, Irvine,
CA 92697, USA
Sander Veraverbeke
Department of Earth Sciences, Vrije Universiteit, Amsterdam, 1081 HV,
the Netherlands
Louis Giglio
Department of Geographical Sciences, University of Maryland, College
Park, MD 20742, USA
Douglas C. Morton
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD 20771, USA
Related authors
Douglas I. Kelley, Chantelle Burton, Francesca Di Giuseppe, Matthew W. Jones, Maria L. F. Barbosa, Esther Brambleby, Joe R. McNorton, Zhongwei Liu, Anna S. I. Bradley, Katie Blackford, Eleanor Burke, Andrew Ciavarella, Enza Di Tomaso, Jonathan Eden, Igor José M. Ferreira, Lukas Fiedler, Andrew J. Hartley, Theodore R. Keeping, Seppe Lampe, Anna Lombardi, Guilherme Mataveli, Yuquan Qu, Patrícia S. Silva, Fiona R. Spuler, Carmen B. Steinmann, Miguel Ángel Torres-Vázquez, Renata Veiga, Dave van Wees, Jakob B. Wessel, Emily Wright, Bibiana Bilbao, Mathieu Bourbonnais, Gao Cong, Carlos M. Di Bella, Kebonye Dintwe, Victoria M. Donovan, Sarah Harris, Elena A. Kukavskaya, Brigitte N’Dri, Cristina Santín, Galia Selaya, Johan Sjöström, John Abatzoglou, Niels Andela, Rachel Carmenta, Emilio Chuvieco, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Meier, Mark Parrington, Mojtaba Sadegh, Jesus San-Miguel-Ayanz, Fernando Sedano, Marco Turco, Guido R. van der Werf, Sander Veraverbeke, Liana O. Anderson, Hamish Clarke, Paulo M. Fernandes, and Crystal A. Kolden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-483, https://doi.org/10.5194/essd-2025-483, 2025
Preprint under review for ESSD
Short summary
Short summary
The second State of Wildfires report examines extreme wildfire events from 2024 to early 2025. It analyses key regional events in Southern California, Northeast Amazonia, Pantanal-Chiquitano, and the Congo Basin, assessing their drivers, predictability, and attributing them to climate change and land use. Seasonal outlooks and decadal projections are provided. Climate change greatly increased the likelihood of these fires, and without strong mitigation, such events will become more frequent.
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
Short summary
Short summary
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.
Roland Vernooij, Tom Eames, Jeremy Russell-Smith, Cameron Yates, Robin Beatty, Jay Evans, Andrew Edwards, Natasha Ribeiro, Martin Wooster, Tercia Strydom, Marcos Vinicius Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, Dave van Wees, and Guido R. Van der Werf
Earth Syst. Dynam., 14, 1039–1064, https://doi.org/10.5194/esd-14-1039-2023, https://doi.org/10.5194/esd-14-1039-2023, 2023
Short summary
Short summary
Savannas account for over half of global landscape fire emissions. Although environmental and fuel conditions affect the ratio of species the fire emits, these dynamics have not been implemented in global models. We measured CO2, CO, CH4, and N2O emission factors (EFs), fuel parameters, and fire severity proxies during 129 individual fires. We identified EF patterns and trained models to estimate EFs of these species based on satellite observations, reducing the estimation error by 60–85 %.
Lilian Vallet, Martin Schwartz, Philippe Ciais, Dave van Wees, Aurelien de Truchis, and Florent Mouillot
Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
Short summary
Short summary
This study analyzes the ecological impact of the 2022 summer fire season in France by using high-resolution satellite data. The total biomass loss was 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests. While Mediterranean forests had a lower biomass loss, there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. This result revisits the distinctiveness of the 2022 fire season.
Elizabeth Quaye, Ben T. Johnson, James M. Haywood, Guido R. van der Werf, Roland Vernooij, Stephen A. Sitch, and Tom Eames
EGUsphere, https://doi.org/10.5194/egusphere-2025-3936, https://doi.org/10.5194/egusphere-2025-3936, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We find aerosol optical depths in a global climate model are overestimated during extreme wildfire events if emissions are scaled up by a factor of two, typically applied to improve simulated aerosol on seasonal–annual timescales. We propose a technique where a variable scaling factor is determined by fuel consumption, improving correlation in five fire-affected areas. We explore the impact of this change on aerosol radiative effects, during extreme events and on broader space and time scales.
Douglas I. Kelley, Chantelle Burton, Francesca Di Giuseppe, Matthew W. Jones, Maria L. F. Barbosa, Esther Brambleby, Joe R. McNorton, Zhongwei Liu, Anna S. I. Bradley, Katie Blackford, Eleanor Burke, Andrew Ciavarella, Enza Di Tomaso, Jonathan Eden, Igor José M. Ferreira, Lukas Fiedler, Andrew J. Hartley, Theodore R. Keeping, Seppe Lampe, Anna Lombardi, Guilherme Mataveli, Yuquan Qu, Patrícia S. Silva, Fiona R. Spuler, Carmen B. Steinmann, Miguel Ángel Torres-Vázquez, Renata Veiga, Dave van Wees, Jakob B. Wessel, Emily Wright, Bibiana Bilbao, Mathieu Bourbonnais, Gao Cong, Carlos M. Di Bella, Kebonye Dintwe, Victoria M. Donovan, Sarah Harris, Elena A. Kukavskaya, Brigitte N’Dri, Cristina Santín, Galia Selaya, Johan Sjöström, John Abatzoglou, Niels Andela, Rachel Carmenta, Emilio Chuvieco, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Meier, Mark Parrington, Mojtaba Sadegh, Jesus San-Miguel-Ayanz, Fernando Sedano, Marco Turco, Guido R. van der Werf, Sander Veraverbeke, Liana O. Anderson, Hamish Clarke, Paulo M. Fernandes, and Crystal A. Kolden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-483, https://doi.org/10.5194/essd-2025-483, 2025
Preprint under review for ESSD
Short summary
Short summary
The second State of Wildfires report examines extreme wildfire events from 2024 to early 2025. It analyses key regional events in Southern California, Northeast Amazonia, Pantanal-Chiquitano, and the Congo Basin, assessing their drivers, predictability, and attributing them to climate change and land use. Seasonal outlooks and decadal projections are provided. Climate change greatly increased the likelihood of these fires, and without strong mitigation, such events will become more frequent.
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025, https://doi.org/10.5194/essd-17-3599-2025, 2025
Short summary
Short summary
To address the limitations of short time spans in satellite data and spatiotemporal discontinuity in site records, we reconstructed global monthly burned area maps at a 0.5° resolution for 1901–2020 using machine learning models. The global burned area is predicted at 3.46 × 106–4.58 × 106 km² per year, showing a decline from 1901 to 1978, an increase from 1978 to 2008 and a sharper decrease from 2008 to 2020. This dataset provides a benchmark for studies on fire ecology and the carbon cycle.
Tom Eames, Nick Schutgens, Eleftherios Ioannidis, Ivar R. van der Velde, Max J. van Gerrevink, Roland Vernooij, and Guido R. van der Werf
EGUsphere, https://doi.org/10.5194/egusphere-2025-3394, https://doi.org/10.5194/egusphere-2025-3394, 2025
Short summary
Short summary
Prescribed burning is used as a landscape management tool in southern African savannas. By deliberately changing the timing of fires in this region, the climate effect (radiative forcing) of a fire season can be altered. We show that by burning earlier in the dry season a small climate cooling effect can be achieved, similar to that of a 10 % reduction in global commercial aviation emissions. Local effects must be considered before implementing a fire regime shift for climate change mitigation.
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025, https://doi.org/10.5194/gmd-18-3857-2025, 2025
Short summary
Short summary
This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in Arctic soils. By comparing model outputs with data from a black spruce forest in Alaska, we developed a clearer, more efficient method of matching observations. This is a key step towards understanding how Arctic ecosystems may respond to warming and release carbon, helping make future climate predictions more reliable.
Anna C. Talucci, Michael M. Loranty, Jean E. Holloway, Brendan M. Rogers, Heather D. Alexander, Natalie Baillargeon, Jennifer L. Baltzer, Logan T. Berner, Amy Breen, Leya Brodt, Brian Buma, Jacqueline Dean, Clement J. F. Delcourt, Lucas R. Diaz, Catherine M. Dieleman, Thomas A. Douglas, Gerald V. Frost, Benjamin V. Gaglioti, Rebecca E. Hewitt, Teresa Hollingsworth, M. Torre Jorgenson, Mark J. Lara, Rachel A. Loehman, Michelle C. Mack, Kristen L. Manies, Christina Minions, Susan M. Natali, Jonathan A. O'Donnell, David Olefeldt, Alison K. Paulson, Adrian V. Rocha, Lisa B. Saperstein, Tatiana A. Shestakova, Seeta Sistla, Oleg Sizov, Andrey Soromotin, Merritt R. Turetsky, Sander Veraverbeke, and Michelle A. Walvoord
Earth Syst. Sci. Data, 17, 2887–2909, https://doi.org/10.5194/essd-17-2887-2025, https://doi.org/10.5194/essd-17-2887-2025, 2025
Short summary
Short summary
Wildfires have the potential to accelerate permafrost thaw and the associated feedbacks to climate change. We assembled a dataset of permafrost thaw depth measurements from burned and unburned sites contributed by researchers from across the northern high-latitude region. We estimated maximum thaw depth for each measurement, which addresses a key challenge: the ability to assess impacts of wildfire on maximum thaw depth when measurement timing varies.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
Short summary
Short summary
We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Valeria Briones, Hélène Genet, Elchin E. Jafarov, Brendan M. Rogers, Jennifer D. Watts, Anna-Maria Virkkala, Annett Bartsch, Benjamin C. Maglio, Joshua Rady, and Susan M. Natali
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-226, https://doi.org/10.5194/essd-2025-226, 2025
Manuscript not accepted for further review
Short summary
Short summary
Arctic warming is causing permafrost to thaw, affecting ecosystems and climate. Since land cover, especially vegetation, shapes how permafrost responds, accurate maps are crucial. Using machine learning, we combined existing global and regional datasets to create a hybrid detailed 1-km map of Arctic-Boreal land cover, improving the representation of forests, shrubs, and wetlands across the circumpolar.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Lucas R. Diaz, Clement J. F. Delcourt, Moritz Langer, Michael M. Loranty, Brendan M. Rogers, Rebecca C. Scholten, Tatiana A. Shestakova, Anna C. Talucci, Jorien E. Vonk, Sonam Wangchuk, and Sander Veraverbeke
Earth Syst. Dynam., 15, 1459–1482, https://doi.org/10.5194/esd-15-1459-2024, https://doi.org/10.5194/esd-15-1459-2024, 2024
Short summary
Short summary
Our study in eastern Siberia investigated how fires affect permafrost thaw depth in larch forests. We found that fire induces deeper thaw, yet this process was mediated by topography and vegetation. By combining field and satellite data, we estimated summer thaw depth across an entire fire scar. This research provides insights into post-fire permafrost dynamics and the use of satellite data for mapping fire-induced permafrost thaw.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
Short summary
Short summary
This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Surendra Shrestha, Christopher A. Williams, Brendan M. Rogers, John Rogan, and Dominik Kulakowski
Biogeosciences, 21, 2207–2226, https://doi.org/10.5194/bg-21-2207-2024, https://doi.org/10.5194/bg-21-2207-2024, 2024
Short summary
Short summary
Here, we generated chronosequences of leaf area index (LAI) and surface albedo as a function of time since fire to demonstrate the differences in the characteristic trajectories of post-fire biophysical changes among seven forest types and 21 level III ecoregions of the western United States (US) using satellite data from different sources. We also demonstrated how climate played the dominant role in the recovery of LAI and albedo 10 and 20 years after wildfire events in the western US.
Tianjia Liu, James T. Randerson, Yang Chen, Douglas C. Morton, Elizabeth B. Wiggins, Padhraic Smyth, Efi Foufoula-Georgiou, Roy Nadler, and Omer Nevo
Earth Syst. Sci. Data, 16, 1395–1424, https://doi.org/10.5194/essd-16-1395-2024, https://doi.org/10.5194/essd-16-1395-2024, 2024
Short summary
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.
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
Short summary
Short summary
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).
Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold
Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, https://doi.org/10.5194/nhess-24-445-2024, 2024
Short summary
Short summary
With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.
Thomas D. Hessilt, Brendan M. Rogers, Rebecca C. Scholten, Stefano Potter, Thomas A. J. Janssen, and Sander Veraverbeke
Biogeosciences, 21, 109–129, https://doi.org/10.5194/bg-21-109-2024, https://doi.org/10.5194/bg-21-109-2024, 2024
Short summary
Short summary
In boreal North America, snow and frozen ground prevail in winter, while fires occur in summer. Over the last 20 years, the northwestern parts have experienced earlier snow disappearance and more ignitions. This is opposite to the southeastern parts. However, earlier ignitions following earlier snow disappearance timing led to larger fires across the region. Snow disappearance timing may be a good proxy for ignition timing and may also influence important atmospheric conditions related to fires.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of 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
Short summary
Short summary
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.
Roland Vernooij, Tom Eames, Jeremy Russell-Smith, Cameron Yates, Robin Beatty, Jay Evans, Andrew Edwards, Natasha Ribeiro, Martin Wooster, Tercia Strydom, Marcos Vinicius Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, Dave van Wees, and Guido R. Van der Werf
Earth Syst. Dynam., 14, 1039–1064, https://doi.org/10.5194/esd-14-1039-2023, https://doi.org/10.5194/esd-14-1039-2023, 2023
Short summary
Short summary
Savannas account for over half of global landscape fire emissions. Although environmental and fuel conditions affect the ratio of species the fire emits, these dynamics have not been implemented in global models. We measured CO2, CO, CH4, and N2O emission factors (EFs), fuel parameters, and fire severity proxies during 129 individual fires. We identified EF patterns and trained models to estimate EFs of these species based on satellite observations, reducing the estimation error by 60–85 %.
Lilian Vallet, Martin Schwartz, Philippe Ciais, Dave van Wees, Aurelien de Truchis, and Florent Mouillot
Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
Short summary
Short summary
This study analyzes the ecological impact of the 2022 summer fire season in France by using high-resolution satellite data. The total biomass loss was 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests. While Mediterranean forests had a lower biomass loss, there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. This result revisits the distinctiveness of the 2022 fire season.
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
Short summary
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.
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
Short summary
Short summary
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.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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
Short summary
Short summary
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.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
Short summary
Short summary
Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022, https://doi.org/10.5194/amt-15-4271-2022, 2022
Short summary
Short summary
Landscape fires are a substantial emitter of greenhouse gases and aerosols. Previous studies have indicated savanna emission factors to be highly variable. Improving fire emission estimates, and understanding future climate- and human-induced changes in fire regimes, requires in situ measurements. We present a drone-based method that enables the collection of a large amount of high-quality emission factor measurements that do not have the biases of aircraft or surface measurements.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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
Short summary
Short summary
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.
Roland Vernooij, Ulrike Dusek, Maria Elena Popa, Peng Yao, Anupam Shaikat, Chenxi Qiu, Patrik Winiger, Carina van der Veen, Thomas Callum Eames, Natasha Ribeiro, and Guido R. van der Werf
Atmos. Chem. Phys., 22, 2871–2890, https://doi.org/10.5194/acp-22-2871-2022, https://doi.org/10.5194/acp-22-2871-2022, 2022
Short summary
Short summary
Landscape fires are a major source of greenhouse gases and aerosols, particularly in sub-tropical savannas. Stable carbon isotopes in emissions can be used to trace the contribution of C3 plants (e.g. trees or shrubs) and C4 plants (e.g. savanna grasses) to greenhouse gases and aerosols if the process is well understood. This helps us to link individual vegetation types to emissions, identify biomass burning emissions in the atmosphere, and improve the reconstruction of historic fire regimes.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Roland Vernooij, Marcos Giongo, Marco Assis Borges, Máximo Menezes Costa, Ana Carolina Sena Barradas, and Guido R. van der Werf
Biogeosciences, 18, 1375–1393, https://doi.org/10.5194/bg-18-1375-2021, https://doi.org/10.5194/bg-18-1375-2021, 2021
Short summary
Short summary
We used drones to measure greenhouse gas emission factors from fires in the Brazilian Cerrado. We compared early-dry-season management fires and late-dry-season fires to determine if fire management can be a tool for abating emissions.
Although we found some evidence of increased CO and CH4 emission factors, the seasonal effect was smaller than that found in previous studies. For N2O, the third most important greenhouse gas, we found opposite trends in grass- and shrub-dominated areas.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 21, 597–616, https://doi.org/10.5194/acp-21-597-2021, https://doi.org/10.5194/acp-21-597-2021, 2021
Short summary
Short summary
This paper compares the relative atmospheric enhancements of CO and NO2 measured by the space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in the ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional-scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Cited articles
Abatzoglou, J. T., Williams, A. P., and Barbero, R.: Global Emergence of
Anthropogenic Climate Change in Fire Weather Indices, Geophys. Res. Lett.,
46, 326–336, https://doi.org/10.1029/2018GL080959, 2019.
Andela, N., Morton, D. C., Giglio, L., Chen, Y., van Der Werf, G. R.,
Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S.,
Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R.,
Yue, C., and Randerson, J. T.: A human-driven decline in global burned area,
Science, 356, 1356–1362, https://doi.org/10.1126/science.aal4108, 2017.
Aragão, L. E. O. C., Anderson, L. O., Fonseca, M. G., Rosan, T. M.,
Vedovato, L. B., Wagner, F. H., Silva, C. V. J., Silva Junior, C. H. L.,
Arai, E., Aguiar, A. P., Barlow, J., Berenguer, E., Deeter, M. N.,
Domingues, L. G., Gatti, L., Gloor, M., Malhi, Y., Marengo, J. A., Miller,
J. B., Phillips, O. L., and Saatchi, S.: 21st Century drought-related fires
counteract the decline of Amazon deforestation carbon emissions, Nat.
Commun., 9, 536, https://doi.org/10.1038/s41467-017-02771-y, 2018.
Ballhorn, U., Siegert, F., Mason, M., and Limin, S.: Derivation of burn scar
depths and estimation of carbon emissions with LIDAR in Indonesian
peatlands, P. Natl. Acad. Sci. USA, 106, 21213–21218,
https://doi.org/10.1073/pnas.0906457106, 2009.
Berbery, E. H., Ciappesoni, H. C., and Kalnay, E.: The smoke episode in
Buenos Aires, 15–20 April 2008, Geophys. Res. Lett., 35, L21801,
https://doi.org/10.1029/2008GL035278, 2008.
Brando, P. M., Paolucci, L., Ummenhofer, C. C., Ordway, E. M., Hartmann, H.,
Cattau, M. E., Rattis, L., Medjibe, V., Coe, M. T., and Balch, J.: Droughts,
Wildfires, and Forest Carbon Cycling: A Pantropical Synthesis, Annu. Rev.
Earth Planet. Sci., 47, 555–581,
https://doi.org/10.1146/annurev-earth-082517-010235, 2019.
Canadell, J. G., Meyer, C. P., Cook, G. D., Dowdy, A., Briggs, P. R.,
Knauer, J., Pepler, A., and Haverd, V.: Multi-decadal increase of forest
burned area in Australia is linked to climate change, Nat. Commun., 12,
6921, https://doi.org/10.1038/s41467-021-27225-4, 2021.
Carroll, M., DiMiceli, C., Wooten, M., Hubbard, A., Sohlberg, R., and
Townshend, J.: MOD44W MODIS/Terra Land Water Mask Derived from MODIS and
SRTM L3 Global 250m SIN Grid V006, NASA EOSDIS L. Process. DAAC [data set],
https://doi.org/10.5067/MODIS/MOD44W.006, 2017.
Carter, T. S., Heald, C. L., Jimenez, J. L., Campuzano-Jost, P., Kondo, Y., Moteki, N., Schwarz, J. P., Wiedinmyer, C., Darmenov, A. S., da Silva, A. M., and Kaiser, J. W.: How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, 2020.
Carvalho, J. A., Santos, J. M., Santos, J. C., and Leitao, M. M.: A Tropical
Rain-Forest Clearing Experiment By Biomass Burning in the Manaus Region,
Atmos. Environ., 29, 2301–2309, https://doi.org/10.1016/1352-2310(95)00094-F, 1995.
Carvalho Jr., J. A., Amaral, S. S., Costa, M. A. M., Soares Neto, T. G.,
Veras, C. A. G., Costa, F. S., van Leeuwen, T. T., Krieger Filho, G. C.,
Tourigny, E., Forti, M. C., Fostier, A. H., Siqueira, M. B., Santos, J. C.,
Lima, B. A., Cascão, P., Ortega, G., and Frade Jr., E. F.: CO2 and CO
emission rates from three forest fire controlled experiments in Western
Amazonia, Atmos. Environ., 135, 73–83, https://doi.org/10.1016/j.atmosenv.2016.03.043,
2016.
Cattau, M. E., Wessman, C., Mahood, A., and Balch, J. K.: Anthropogenic and
lightning-started fires are becoming larger and more frequent over a longer
season length in the U.S.A., Glob. Ecol. Biogeogr., 29, 668–681,
https://doi.org/10.1111/geb.13058, 2020.
Cianciaruso, M. V., Aurélio da Silva, I., and Batalha, M. A.: Aboveground
biomass of functional groups in the ground layer of savannas under different
fire frequencies, Aust. J. Bot., 58, 169–174, https://doi.org/10.1071/BT09136, 2010.
Clark, K. L., Skowronski, N., and Gallagher, M.: Fire Management and Carbon
Sequestration in Pine Barren Forests, J. Sustain. For., 34, 125–146,
https://doi.org/10.1080/10549811.2014.973607, 2015.
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A., and Hansen, M. C.:
Classifying drivers of global forest loss, Science, 361, 1108–1111,
https://doi.org/10.1126/science.aau3445, 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. Chang. Biol., 26,
6062–6079, https://doi.org/10.1111/gcb.15158, 2020a.
Dieleman, C. M., Rogers, B. M., Veraverbeke, S., Johnstone, J. F., Laflamme,
J., Gelhorn, L., Solvik, K., Walker, X. J., Mack, M. C., and Turetsky, M. R.:
ABoVE: Characterization of Burned and Unburned Boreal Forest Stands, SK,
Canada, 2016, ORNL DAAC, Oak Ridge, Tennessee, USA,
https://doi.org/10.3334/ORNLDAAC/1740, 2020b.
Dimiceli, C., Carroll, M., Sohlberg, R., Kim, D. H., Kelly, M., and
Townshend, J. R. G.: MOD44B MODIS/Terra Vegetation Continuous Fields Yearly
L3 Global 250m SIN Grid V006, NASA EOSDIS L. Process. DAAC [data set],
https://doi.org/10.5067/MODIS/MOD44B.006, 2015.
Duncanson, L.,
Kellner, J. R.,
Armston, J.,
Dubayah, R.,
Minor, D. M.,
Hancock, S.,
Healey, S. P.,
Patterson, P. L.,
Saarela, S.,
Marselis, S.,
Silva, C. E.,
Bruening, J.,
Goetz, S. J.,
Tang, H.,
Hofton, M.,
Blair, B.,
Luthcke, S.,
Fatoyinbo, L.,
Abernethy, K.,
Alonso, A.,
Andersen, H.-E.,
Aplin, P.,
Baker, T. R.,
Barbier, N.,
Bastin, J. F.,
Biber, P.,
Boeckx, P.,
Bogaert, J.,
Boschetti, L.,
Boucher, P. B.,
Boyd, D. S.,
Burslem, D. F. R. P.,
Calvo-Rodriguez, S.,
Chave, J.,
Chazdon, R. L.,
Clark, D. B.,
Clark, D. A.,
Cohen, W. B.,
Coomes, D. A.,
Corona, P.,
Cushman, K. C.,
Cutler, M. E. J.,
Dalling, J. W.,
Dalponte, M.,
Dash, J.,
De-Miguel, S.,
Deng, S.,
Ellis, P. W.,
Erasmus, B.,
Fekety, P. A.,
Fernandez-Landa, A.,
Ferraz, A.,
Fischer, R.,
Fisher, A. G.,
García-Abril, A.,
Gobakken, T.,
Hacker, J. M.,
Heurich, M.,
Hill, R. A.,
Hopkinson, C.,
Huang, H.,
Hubbell, S. P.,
Hudak, A. T.,
Huth, A.,
Imbach, B.,
Jeffery, K. J.,
Katoh, M.,
Kearsley, E.,
Kenfack, D.,
Kljun, N.,
Knapp, N.,
Král, K.,
Krůček, M.,
Labrière, N.,
Lewis, S. L.,
Longo, M.,
Lucas, R. M.,
Main, R.,
Manzanera, J. A.,
Martínez, R. V.,
Mathieu, R.,
Memiaghe, H.,
Meyer, V.,
Mendoza, A. M.,
Monerris, A.,
Montesano, P.,
Morsdorf, F.,
Næsset, E.,
Naidoo, L.,
Nilus, R.,
O’Brien, M.,
Orwig, D. A.,
Papathanassiou, K.,
Parker, G.,
Philipson, C.,
Phillips, O. L.,
Pisek, J.,
Poulsen, J. R.,
Pretzsch, H.,
Rüdiger, C.,
Saatchi, S.,
Sanchez-Azofeifa, A.,
Sanchez-Lopez, N.,
Scholes, R.,
Silva, C. A.,
Simard, M.,
Skidmore, A.,
Stereńczak, K.,
Tanase, M.,
Torresan, C.,
Valbuena, R.,
Verbeeck, H.,
Vrska, T.,
Wessels, K.,
White, J. C.,
White, L. J. T.,
Zahabu, E., and
Zgraggen, C.: Aboveground biomass density models for NASA's Global
Ecosystem Dynamics Investigation (GEDI) lidar mission, Remote Sens.
Environ., 270, 112845, https://doi.org/10.1016/j.rse.2021.112845, 2022.
Eames, T., Russell-Smith, J., Yates, C., Edwards, A., Vernooij, R., Ribeiro,
N., Steinbruch, F., and van der Werf, G. R.: Instantaneous Pre-Fire Biomass
and Fuel Load Measurements from Multi-Spectral UAS Mapping in Southern
African Savannas, Fire, 4, 2, https://doi.org/10.3390/fire4010002, 2021.
FAO: Global ecological zones for forest reporting: 2010 update, Forest
Resources Assessment Working Paper 179,
https://data.apps.fao.org/map/catalog/srv/eng/catalog.search#/metadata/2fb209d0-fd34-4e5e-a3d8-a13c241eb61b (last
access: 15 November 2022), 2012.
access: 15 November 2022), 2012.
Field, C. B., Randerson, J. T., and Malmström, C. M.: Global net primary
production: Combining ecology and remote sensing, Remote Sens. Environ.,
51, 74–88, https://doi.org/10.1016/0034-4257(94)00066-V, 1995.
Friedl, M. and Sulla-Menashe, D.: MCD12Q1 MODIS/Terra+Aqua Land Cover Type
Yearly L3 Global 500m SIN Grid V006, NASA EOSDIS L. Process.
DAAC [data set], https://doi.org/10.5067/MODIS/MCD12Q1.006, 2019.
Gaveau, D. L. A., Descals, A., Salim, M. A., Sheil, D., and Sloan, S.: Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning, Earth Syst. Sci. Data, 13, 5353–5368, https://doi.org/10.5194/essd-13-5353-2021, 2021.
Giglio, L., Schroeder, W., and Justice, C. O.: The collection 6 MODIS active
fire detection algorithm and fire products, Remote Sens. Environ., 178,
31–41, https://doi.org/10.1016/j.rse.2016.02.054, 2016.
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.
Girardin, C. A. J., Malhi, Y., Aragão, L. E. O. C., Mamani, M., Huaraca
Huasco, W., Durand, L., Feeley, K. J., Rapp, J., Silva-Espejo, J. E.,
Silman, M., Salinas, N., and Whittaker, R. J.: Net primary productivity
allocation and cycling of carbon along a tropical forest elevational
transect in the Peruvian Andes, Glob. Chang. Biol., 16, 3176–3192,
https://doi.org/10.1111/j.1365-2486.2010.02235.x, 2010.
Glushkov, I., Zhuravleva, I., McCarty, J. L., Komarova, A., Drozdovsky, A.,
Drozdovskaya, M., Lupachik, V., Yaroshenko, A., Stehman, S. V., and
Prishchepov, A. V.: Spring fires in Russia: results from participatory burned
area mapping with Sentinel-2 imagery, Environ. Res. Lett., 16, 125005,
https://doi.org/10.1088/1748-9326/ac3287, 2021.
Goulden, M. L. and Bales, R. C.: California forest die-off linked to
multi-year deep soil drying in 2012–2015 drought, Nat. Geosci., 12,
632–637, https://doi.org/10.1038/s41561-019-0388-5, 2019.
Gumbricht, T., Román-Cuesta, R.M., Verchot, L.V., Herold, M., Wittmann, F., Householder, E., Herold, N., and Murdiyarso, D.: An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor, Global Change Biol., 23, 3581–3599, https://doi.org/10.1111/gcb.13689, 2017.
Gutierrez, A. A., Hantson, S., Langenbrunner, B., Chen, B., Jin, Y.,
Goulden, M. L., and Randerson, J. T.: Wildfire response to changing daily
temperature extremes in California's Sierra Nevada, Sci. Adv., 7,
eabe6417, https://doi.org/10.1126/sciadv.abe6417, 2022.
Hall, J. V, Loboda, T. V, Giglio, L., and McCarty, G. W.: A MODIS-based
burned area assessment for Russian croplands: Mapping requirements and
challenges, Remote Sens. Environ., 184, 506–521,
https://doi.org/10.1016/j.rse.2016.07.022, 2016.
Hansen, M. C., Potapov, P. V, Moore, R., Hancher, M., Turubanova, S. A.,
Tyukavina, A., Thau, D., Stehman, S. V, Goetz, S. J., Loveland, T. R.,
Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., and Townshend, J. R.
G.: High-Resolution Global Maps of 21st-Century Forest Cover Change,
Science, 342, 850–853, https://doi.org/10.1126/science.1244693, 2013.
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.
Hawbaker, T. J., Vanderhoof, M. K., Schmidt, G. L., Beal, Y.-J., Picotte, J.
J., Takacs, J. D., Falgout, J. T., and Dwyer, J. L.: The Landsat Burned Area
algorithm and products for the conterminous United States, Remote Sens.
Environ., 244, 111801, https://doi.org/10.1016/j.rse.2020.111801, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I.,
Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5
monthly averaged data on single levels from 1979 to present, Copernicus
Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.f17050d7, 2019.
Hirano, T., Kusin, K., Limin, S., and Osaki, M.: Carbon dioxide emissions
through oxidative peat decomposition on a burnt tropical peatland, Glob.
Chang. Biol., 20, 555–565, https://doi.org/10.1111/gcb.12296, 2014.
Hugelius, G., Tarnocai, C., Broll, G., Canadell, J. G., Kuhry, P., and Swanson, D. K.: The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions, Earth Syst. Sci. Data, 5, 3–13, https://doi.org/10.5194/essd-5-3-2013, 2013.
Ivanova, G. A., Kukavskaya, E. A., Ivanov, V. A., Conard, S. G., and McRae,
D. J.: Fuel characteristics, loads and consumption in Scots pine forests of
central Siberia, J. For. Res., 31, 2507–2524,
https://doi.org/10.1007/s11676-019-01038-0, 2019.
Janjić, T., Bormann, N., Bocquet, M., Carton, J. A., Cohn, S. E., Dance,
S. L., Losa, S. N., Nichols, N. K., Potthast, R., Waller, J. A., and Weston,
P.: On the representation error in data assimilation, Q. J. Roy. Meteor.
Soc., 144, 1257–1278, https://doi.org/10.1002/qj.3130, 2018.
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012.
Kauffman, J. B., Cummings, D. L., Ward, D. E., and Babbitt, R.: Fire in the
Brazilian Amazon: 1. Biomass, nutrient pools, and losses in slashed primary
forests, Oecologia, 104, 397–408, https://doi.org/10.1007/BF00341336, 1995.
Kelley, D. I., Bistinas, I., Whitley, R., Burton, C., Marthews, T. R., and
Dong, N.: How contemporary bioclimatic and human controls change global fire
regimes, Nat. Clim. Chang., 9, 690–696, https://doi.org/10.1038/s41558-019-0540-7,
2019.
Konecny, K., Ballhorn, U., Navratil, P., Jubanski, J., Page, S. E., Tansey,
K., Hooijer, A., Vernimmen, R., and Siegert, F.: Variable carbon losses from
recurrent fires in drained tropical peatlands, Glob. Chang. Biol., 22,
1469–1480, https://doi.org/10.1111/gcb.13186, 2016.
Krylov, A., McCarty, J. L., Potapov, P., Loboda, T., Tyukavina, A.,
Turubanova, S., and Hansen, M. C.: Remote sensing estimates of
stand-replacement fires in Russia, 2002–2011, Environ. Res. Lett., 9,
105007, https://doi.org/10.1088/1748-9326/9/10/105007, 2014.
Kukavskaya, E. A., Buryak, L. V, Kalenskaya, O. P., and Zarubin, D. S.:
Transformation of the ground cover after surface fires and estimation of
pyrogenic carbon emissions in the dark-coniferous forests of Central
Siberia, Contemp. Probl. Ecol., 10, 62–70,
https://doi.org/10.1134/S1995425517010073, 2017.
Kurz, W. A., Dymond, C. C., Stinson, G., Rampley, G. J., Neilson, E. T.,
Carroll, A. L., Ebata, T., and Safranyik, L.: Mountain pine beetle and forest
carbon feedback to climate change, Nature, 452, 987–990,
https://doi.org/10.1038/nature06777, 2008.
Leal Filho, W., Azeiteiro, U. M., Salvia, A. L., Fritzen, B., and Libonati,
R.: Fire in Paradise: Why the Pantanal is burning, Environ. Sci. Policy,
123, 31–34, https://doi.org/10.1016/j.envsci.2021.05.005, 2021.
Libonati, R., DaCamara, C. C., Peres, L. F., Sander de Carvalho, L. A., and
Garcia, L. C.: Rescue Brazil's burning Pantanal wetlands, Nature, 588,
217–219, https://doi.org/10.1038/d41586-020-03464-1, 2020.
Liu, T., Mickley, L. J., Marlier, M. E., DeFries, R. S., Khan, M. F., Latif,
M. T., and Karambelas, A.: Diagnosing spatial biases and uncertainties in
global fire emissions inventories: Indonesia as regional case study, Remote
Sens. Environ., 237, 111557, https://doi.org/10.1016/j.rse.2019.111557, 2020.
Liu, X., Pei, F., Wen, Y., Li, X., Wang, S., Wu, C., Cai, Y., Wu, J., Chen,
J., Feng, K., Liu, J., Hubacek, K., Davis, S. J., Yuan, W., Yu, L., and Liu,
Z.: Global urban expansion offsets climate-driven increases in terrestrial
net primary productivity, Nat. Commun., 10, 5558,
https://doi.org/10.1038/s41467-019-13462-1, 2019.
Marengo, J. A., Cunha, A. P., Cuartas, L. A., Deusdará Leal, K. R.,
Broedel, E., Seluchi, M. E., Michelin, C. M., De Praga Baião, C. F.,
Chuchón Ângulo, E., Almeida, E. K., Kazmierczak, M. L., Mateus, N.
P. A., Silva, R. C., and Bender, F.: Extreme Drought in the Brazilian
Pantanal in 2019–2020: Characterization, Causes, and Impacts, Front. Water,
3, 639204, https://doi.org/10.3389/frwa.2021.639204, 2021.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C.,
Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M.,
Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield,
T., Yelekçi, O., Yu, R., and Zhou, B. (Eds.): IPCC, 2021: Climate Change 2021:
The Physical Science Basis., in: Contribution of Working Group I to the Sixth
Assessment Report of the Intergovernmental Panel on Climate Change,
Cambridge University Press, https://doi.org/10.1017/9781009157896, 2021.
McLauchlan, K. K., Higuera, P. E., Miesel, J., Rogers, B. M., Schweitzer,
J., Shuman, J. K., Tepley, A. J., Varner, J. M., Veblen, T. T.,
Adalsteinsson, S. A., Balch, J. K., Baker, P., Batllori, E., Bigio, E.,
Brando, P., Cattau, M., Chipman, M. L., Coen, J., Crandall, R., Daniels, L.,
Enright, N., Gross, W. S., Harvey, B. J., Hatten, J. A., Hermann, S.,
Hewitt, R. E., Kobziar, L. N., Landesmann, J. B., Loranty, M. M., Maezumi,
S. Y., Mearns, L., Moritz, M., Myers, J. A., Pausas, J. G., Pellegrini, A.
F. A., Platt, W. J., Roozeboom, J., Safford, H., Santos, F., Scheller, R.
M., Sherriff, R. L., Smith, K. G., Smith, M. D., and Watts, A. C.: Fire as a
fundamental ecological process: Research advances and frontiers, J. Ecol.,
108, 2047–2069, https://doi.org/10.1111/1365-2745.13403, 2020.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Moreno-Ruiz, J. A., García-Lázaro, J. R., Arbelo, M., Riaño,
D., Moreno-Ruiz, J. A., García-Lázaro, J. R., Arbelo, M., and
Riaño, D.: A Comparison of Burned Area Time Series in the Alaskan Boreal
Forests from Different Remote Sensing Products, Forests, 10, 363,
https://doi.org/10.3390/f10050363, 2019.
Mota, B. and Wooster, M. J.: A new top-down approach for directly estimating
biomass burning emissions and fuel consumption rates and totals from
geostationary satellite fire radiative power (FRP), Remote Sens. Environ.,
206, 45–62, https://doi.org/10.1016/j.rse.2017.12.016, 2018.
Mueller, E. V, Skowronski, N., Clark, K., Gallagher, M., Kremens, R.,
Thomas, J. C., El Houssami, M., Filkov, A., Hadden, R. M., Mell, W., and
Simeoni, A.: Utilization of remote sensing techniques for the quantification
of fire behavior in two pine stands, Fire Saf. J., 91, 845–854,
https://doi.org/10.1016/j.firesaf.2017.03.076, 2017.
Muñoz Sabater, J.: ERA5-Land monthly averaged data from 1981 to present.
Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.68d2bb30, 2019.
Myneni, R., Knyazikhin, Y., and Park, T.: MCD15A2H MODIS/Terra + Aqua Leaf
Area Index/FPAR 8-day L4 Global 500 m SIN Grid V006, NASA EOSDIS
L. Process. DAAC [data set], https://doi.org/10.5067/MODIS/MCD15A2H.006, 2015.
Nijmeijer, A., Lauri, P.-É., Harmand, J.-M., and Saj, S.: Carbon dynamics
in cocoa agroforestry systems in Central Cameroon: afforestation of savannah
as a sequestration opportunity, Agrofor. Syst., 93, 851–868,
https://doi.org/10.1007/s10457-017-0182-6, 2019.
Obu, J., Westermann, S., Bartsch, A., Berdnikov, N., Christiansen, H. H.,
Dashtseren, A., Delaloye, R., Elberling, B., Etzelmüller, B., Kholodov,
A., Khomutov, A., Kääb, A., Leibman, M. O., Lewkowicz, A. G., Panda,
S. K., Romanovsky, V., Way, R. G., Westergaard-Nielsen, A., Wu, T., Yamkhin,
J., and Zou, D.: Northern Hemisphere permafrost map based on TTOP modelling
for 2000–2016 at 1 km2 scale, Earth-Sci. Rev., 193, 299–316,
https://doi.org/10.1016/j.earscirev.2019.04.023, 2019.
Ottmar, R. D., Hudak, A. T., Prichard, S. J., Wright, C. S., Restaino, J.
C., Kennedy, M. C., and Vihnanek, R. E.: Pre-fire and post-fire surface fuel
and cover measurements collected in the south-eastern United States for
model evaluation and development – RxCADRE 2008, 2011 and 2012, Int. J.
Wildl. Fire, 25, 10–24, https://doi.org/10.1071/WF15092, 2016.
Page, S. E. and Hooijer, A.: In the line of fire: The peatlands of Southeast
Asia, Philos. Trans. R. Soc. B, 371, 20150176,
https://doi.org/10.1098/rstb.2015.0176, 2016.
Page, S. E., Siegert, F., Rieley, J. O., Boehm, H. D. V., Jaya, A., and
Limin, S.: The amount of carbon released from peat and forest fires in
Indonesia during 1997, Nature, 420, 61–65, https://doi.org/10.1038/nature01131,
2002.
Page, S. E., Rieley, J. O., and Banks, C. J.: Global and regional importance
of the tropical peatland carbon pool, Glob. Chang. Biol., 17, 798–818,
https://doi.org/10.1111/j.1365-2486.2010.02279.x, 2011.
Poorter, H., Niklas, K. J., Reich, P. B., Oleksyn, J., Poot, P., and Mommer,
L.: Biomass allocation to leaves, stems and roots: meta-analysis of
interspecific variation and environmental control, New Phytol., 193,
30–50, https://doi.org/10.1111/j.1469-8137.2011.03952.x, 2012.
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P.
M., Mooney, H. A., and Klooster, S. A.: Terrestrial ecosystem production: a
process model based on global satellite and surface data, Global Biogeochem.
Cycles, 7, 811–841, https://doi.org/10.1029/93GB02725, 1993.
Ramo, R., Roteta, E., Bistinas, I., van Wees, D., Bastarrika, A., Chuvieco,
E., and van der Werf, G. R.: African burned area and fire carbon emissions
are strongly impacted by small fires undetected by coarse resolution
satellite data, P. Natl. Acad. Sci. USA, 118, e2011160118,
https://doi.org/10.1073/pnas.2011160118, 2021.
Randerson, J. T., Chen, Y., van der Werf, G. R., 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.
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., Huang, H., Boschetti, L., Giglio, L., Yan, L., Zhang, H. H., and
Li, Z.: Landsat-8 and Sentinel-2 burned area mapping – A combined sensor
multi-temporal change detection approach, Remote Sens. Environ., 231,
111254, https://doi.org/10.1016/J.RSE.2019.111254, 2019.
Running, S. and Zhao, M.: MOD17A2HGF MODIS/Terra Gross Primary Productivity
Gap-Filled 8-Day L4 Global 500 m SIN Grid V006, NASA EOSDIS L.
Process. DAAC [data set], https://doi.org/10.5067/MODIS/MOD17A2HGF.006, 2019a.
Running, S. and Zhao, M.: MOD17A3HGF MODIS/Terra Net Primary Production
Gap-Filled Yearly L4 Global 500 m SIN Grid V006, NASA EOSDIS L.
Process. DAAC [data set], https://doi.org/10.5067/MODIS/MOD17A3HGF.006, 2019b.
Russell-Smith, J., Yates, C., Evans, J., and Desailly, M.: Developing a
savanna burning emissions abatement methodology for tussock grasslands in
high rainfall regions of northern Australia, Trop. Grasslands, 2, 175–187,
https://doi.org/10.17138/tgft(2)175-187, 2014.
Russell-Smith, J., Yates, C., Vernooij, R., Eames, T., van der Werf, G. R.,
Ribeiro, N., Edwards, A., Beatty, R., Lekoko, O., Mafoko, J., Monagle, C.,
and Johnston, S.: Opportunities and challenges for savanna burning emissions
abatement in southern Africa, J. Environ. Manage., 288, 112414,
https://doi.org/10.1016/j.jenvman.2021.112414, 2021.
Saharjo, B. H. and Nurhayati, A. D.: Domination and Composition Structure
Change at Hemic Peat Natural Regeneration Following Burning; A Case Study in
Pelalawan, Riau Province, Biodiversitas, J. Biol. Divers., 7, 154–158,
https://doi.org/10.13057/biodiv/d070213, 2006.
Schmidt, I. B., Fidelis, A., Miranda, H. S., and Ticktin, T.: How do the wets
burn? Fire behavior and intensity in wet grasslands in the Brazilian
savanna, Brazilian J. Bot., 40, 167–175, https://doi.org/10.1007/s40415-016-0330-7,
2017.
Seiler, W. and Crutzen, P. J.: Estimates of gross and net fluxes of carbon
between the biosphere and the atmosphere from biomass burning, Clim. Change,
2, 207–247, https://doi.org/10.1007/BF00137988, 1980.
Simpson, J. E., Wooster, M. J., Smith, T. E. L., Trivedi, M., Vernimmen, R.
R. E., Dedi, R., Shakti, M., and Dinata, Y.: Tropical Peatland Burn Depth and
Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne
LiDAR, Remote Sens., 8, 1000, https://doi.org/10.3390/rs8121000, 2016.
Sparks, A. M., Smith, A. M. S., Talhelm, A. F., Kolden, C. A., Yedinak, K.
M., and Johnson, D. M.: Impacts of fire radiative flux on mature Pinus
ponderosa growth and vulnerability to secondary mortality agents, Int. J.
Wildl. Fire, 26, 95–106, https://doi.org/10.1071/WF16139, 2017.
Spawn, S. A., Sullivan, C. C., Lark, T. J., and Gibbs, H. K.: Harmonized
global maps of above and belowground biomass carbon density in the year
2010, Sci. Data, 7, 112, https://doi.org/10.1038/s41597-020-0444-4, 2020.
Stockwell, C. E., Jayarathne, T., Cochrane, M. A., Ryan, K. C., Putra, E. I., Saharjo, B. H., Nurhayati, A. D., Albar, I., Blake, D. R., Simpson, I. J., Stone, E. A., and Yokelson, R. J.: Field measurements of trace gases and aerosols emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Niño, Atmos. Chem. Phys., 16, 11711–11732, https://doi.org/10.5194/acp-16-11711-2016, 2016.
Thomas, J. C., Mueller, E. V, Santamaria, S., Gallagher, M., El Houssami,
M., Filkov, A., Clark, K., Skowronski, N., Hadden, R. M., Mell, W., and
Simeoni, A.: Investigation of firebrand generation from an experimental
fire: Development of a reliable data collection methodology, Fire Saf. J.,
91, 864–871, https://doi.org/10.1016/j.firesaf.2017.04.002, 2017.
Turcios, M. M., Jaramillo, M. M. A., do Vale Jr, J. F., Fearnside, P. M., and
Barbosa, R. I.: Soil charcoal as long-term pyrogenic carbon storage in
Amazonian seasonal forests, Glob. Chang. Biol., 22, 190–197,
https://doi.org/10.1111/gcb.13049, 2016.
Usup, A., Hashimoto, Y., Takahashi, H., and Hayasaka, H.: Combustion and
thermal characteristics of peat fire in tropical peatland in Central
Kalimantan, Indonesia, Tropics, 14, 1–19, https://doi.org/10.3759/tropics.14.1, 2004.
van der Werf, G. R., Morton, D. C., DeFries, R. S., Giglio, L., Randerson, J. T., Collatz, G. J., and Kasibhatla, P. S.: Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling, Biogeosciences, 6, 235–249, https://doi.org/10.5194/bg-6-235-2009, 2009.
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 Leeuwen, T. T., van der Werf, G. R., Hoffmann, A. A., Detmers, R. G., Rücker, G., French, N. H. F., Archibald, S., Carvalho Jr., J. A., Cook, G. D., de Groot, W. J., Hély, C., Kasischke, E. S., Kloster, S., McCarty, J. L., Pettinari, M. L., Savadogo, P., Alvarado, E. C., Boschetti, L., Manuri, S., Meyer, C. P., Siegert, F., Trollope, L. A., and Trollope, W. S. W.: Biomass burning fuel consumption rates: a field measurement database, Biogeosciences, 11, 7305–7329, https://doi.org/10.5194/bg-11-7305-2014, 2014.
van Marle, M. J. E., van Wees, D., Houghton, R. A., Field, R. D.,
Verbesselt, J., and van der Werf, G. R.: New land-use-change emissions
indicate a declining CO2 airborne fraction, Nature, 603, 450–454,
https://doi.org/10.1038/s41586-021-04376-4, 2022.
van Wees, D. and van der Werf, G. R.: Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED), Geosci. Model Dev., 12, 4681–4703, https://doi.org/10.5194/gmd-12-4681-2019, 2019.
van Wees, D., van der Werf, G. R., Randerson, J. T., Andela, N., Chen, Y.,
and Morton, D. C.: The role of fire in global forest loss dynamics, Glob.
Chang. Biol., 27, 2377–2391, https://doi.org/10.1111/gcb.15591, 2021.
van Wees, D., van der Werf, G. R., Randerson, J. T., Rogers, B. M., Chen, Y., Veraverbeke, S., Giglio, L., and Morton, D. C.: Model data for “Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)”, Zenodo [data set], https://doi.org/10.5281/zenodo.7229674, 2022a.
van Wees, D., van der Werf, G. R., Randerson, J. T., Rogers, B. M., Chen, Y., Veraverbeke, S., Giglio, L., and Morton, D. C.: Field data synthesis accompanying “Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)”, Zenodo [data set], https://doi.org/10.5281/zenodo.6670869, 2022b.
van Wees, D., van der Werf, G. R., Randerson, J. T., Rogers, B. M., Chen, Y., Veraverbeke, S., Giglio, L., and Morton, D. C.: Model code for “Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)”, Zenodo [code], https://doi.org/10.5281/zenodo.7229039, 2022c.
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., Delcourt, C. J. F., Kukavskaya, E., Mack, M., Walker, X.,
Hessilt, T., Rogers, B. M., and Scholten, R. C.: Direct and longer-term
carbon emissions from arctic-boreal fires: A short review of recent
advances, Curr. Opin. Environ. Sci. Heal., 23, 100277,
https://doi.org/10.1016/j.coesh.2021.100277, 2021.
Vernooij, R., Giongo, M., Borges, M. A., Costa, M. M., Barradas, A. C. S., and van der Werf, G. R.: Intraseasonal variability of greenhouse gas emission factors from biomass burning in the Brazilian Cerrado, Biogeosciences, 18, 1375–1393, https://doi.org/10.5194/bg-18-1375-2021, 2021.
Virkkula, A., Levula, J., Pohja, T., Aalto, P. P., Keronen, P., Schobesberger, S., Clements, C. B., Pirjola, L., Kieloaho, A.-J., Kulmala, L., Aaltonen, H., Patokoski, J., Pumpanen, J., Rinne, J., Ruuskanen, T., Pihlatie, M., Manninen, H. E., Aaltonen, V., Junninen, H., Petäjä, T., Backman, J., Dal Maso, M., Nieminen, T., Olsson, T., Grönholm, T., Aalto, J., Virtanen, T. H., Kajos, M., Kerminen, V.-M., Schultz, D. M., Kukkonen, J., Sofiev, M., De Leeuw, G., Bäck, J., Hari, P., and Kulmala, M.: Prescribed burning of logging slash in the boreal forest of Finland: emissions and effects on meteorological quantities and soil properties, Atmos. Chem. Phys., 14, 4473–4502, https://doi.org/10.5194/acp-14-4473-2014, 2014.
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. Chang. 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., 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. Chang., 10, 1130–1136,
https://doi.org/10.1038/s41558-020-00920-8, 2020.
Wang, J. A., Baccini, A., Farina, M., Randerson, J., and Friedl, M. A.:
Disturbance suppresses the aboveground biomass carbon sink in North American
boreal forests, Nat. Clim. Chang., 11, 435–441,
https://doi.org/10.1038/s41558-021-01027-4, 2021.
Williams, A. P., Abatzoglou, J. T., Gershunov, A., Guzman-Morales, J.,
Bishop, D. A., Balch, J. K., and Lettenmaier, D. P.: Observed Impacts of
Anthropogenic Climate Change on Wildfire in California, Earth's Futur.,
7, 892–910, https://doi.org/10.1029/2019EF001210, 2019.
Xu, L., Saatchi, S. S., Yang, Y., Yu, Y., Pongratz, J., Bloom, A. A.,
Bowman, K., Worden, J., Liu, J., Yin, Y., Domke, G., McRoberts, R. E.,
Woodall, C., Nabuurs, G.-J., De-Miguel, S., Keller, M., Harris, N., Maxwell,
S., and Schimel, D.: Changes in global terrestrial live biomass over the 21st
century, Sci. Adv., 7, eabe9829, https://doi.org/10.1126/sciadv.abe9829, 2022.
Zheng, B., Ciais, P., Chevallier, F., Chuvieco, E., Chen, Y., and Yang, H.:
Increasing forest fire emissions despite the decline in global burned area,
Sci. Adv., 7, eabh2646, https://doi.org/10.1126/sciadv.abh2646, 2021.
Zhu, W., Pan, Y., He, H., Yu, D., and Hu, H.: Simulation of maximum light use
efficiency for some typical vegetation types in China, Chinese Sci. Bull.,
51, 457–463, https://doi.org/10.1007/s11434-006-0457-1, 2006.
Executive editor
Fire is a pervasive feature of the Earth system, and a cause of significant carbon emissions. This manuscript presents a higher resolution fire emissions data set than previously available, thereby providing a valuable resource to the scientific community.
Fire is a pervasive feature of the Earth system, and a cause of significant carbon emissions....
Short summary
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.
We present a global fire emission model based on the GFED model framework with a spatial...
