Articles | Volume 15, issue 3
https://doi.org/10.5194/essd-15-1151-2023
© 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/essd-15-1151-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
16 Mar 2023
Data description paper |
| 16 Mar 2023
| 16 Mar 2023
A global database on holdover time of lightning-ignited wildfires
Department of Agricultural, Forest and Food Sciences (DISAFA),
University of Turin, Grugliasco, Italy
Pedro Álvarez-Álvarez
Department of Organisms and Systems Biology, University of Oviedo,
Mieres, Spain
Marco Conedera
Insubric Ecosystems Research Group, Swiss Federal Institute for Forest,
Snow and Landscape Research (WSL), Cadenazzo, Switzerland
Annalie Dorph
FLARE Wildfire Research, University of Melbourne, Creswick, Australia
Thomas D. Hessilt
Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the
Netherlands
Hugh G. P. Hunt
Johannesburg Lightning Research Laboratory, University of the
Witwatersrand, Johannesburg, South Africa
Renata Libonati
Department of Meteorology, Federal University of Rio de Janeiro, Rio
de Janeiro, Brazil
Lucas S. Menezes
Department of Meteorology, Federal University of Rio de Janeiro, Rio
de Janeiro, Brazil
Mortimer M. Müller
Institute of Silviculture, University of Natural Resources and Life
Sciences (BOKU), Vienna, Austria
Francisco J. Pérez-Invernón
Institute of Astrophysics of Andalusia (IAA-CSIC), Granada, Spain
Gianni B. Pezzatti
Insubric Ecosystems Research Group, Swiss Federal Institute for Forest,
Snow and Landscape Research (WSL), Cadenazzo, Switzerland
Nicolau Pineda
Meteorological Service of Catalonia, Barcelona, Spain
Rebecca C. Scholten
Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the
Netherlands
Sander Veraverbeke
Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the
Netherlands
B. Mike Wotton
Canadian Forest Service, Sault Ste. Marie, Canada
Davide Ascoli
Department of Agricultural, Forest and Food Sciences (DISAFA),
University of Turin, Grugliasco, Italy
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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
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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.
Francisco J. Pérez-Invernón, Francisco J. Gordillo-Vázquez, Heidi Huntrieser, Patrick Jöckel, and Eric J. Bucsela
Atmos. Chem. Phys., 25, 5557–5575, https://doi.org/10.5194/acp-25-5557-2025, https://doi.org/10.5194/acp-25-5557-2025, 2025
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Lightning plays a significant role in tropospheric chemistry by producing substantial amounts of nitrogen oxides. According to recent estimates, thunderstorms that produce a higher lightning frequency rate also produce less nitrogen oxide per flash. We implemented the dependency of nitrogen oxide production per flash on lightning flash frequency in a chemical atmospheric model.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
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
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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.
Sergio Soler, Francisco J. Gordillo-Vázquez, Francisco J. Pérez-Invernón, Patrick Jöckel, Torsten Neubert, Olivier Chanrion, Victor Reglero, and Nikolai Østgaard
Atmos. Chem. Phys., 24, 10225–10243, https://doi.org/10.5194/acp-24-10225-2024, https://doi.org/10.5194/acp-24-10225-2024, 2024
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Sudden local ozone (O3) enhancements have been reported in different regions of the world since the 1970s. While the hot channel of lightning strokes directly produce significant amounts of nitrogen oxide, no direct emission of O3 is expected. Corona discharges in convective active regions could explain local O3 increases, which remains unexplained. We present the first mathematical functions that relate the global annual frequency of in-cloud coronas with four sets of meteorological variables.
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
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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.
Francisco J. Pérez-Invernón, Francisco J. Gordillo-Vázquez, Alejandro Malagón-Romero, and Patrick Jöckel
Atmos. Chem. Phys., 24, 3577–3592, https://doi.org/10.5194/acp-24-3577-2024, https://doi.org/10.5194/acp-24-3577-2024, 2024
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Sprites are electrical discharges that occur in the upper atmosphere. Recent modelling and observational data suggest that they may have a measurable impact on atmospheric chemistry. We incorporate both the occurrence rate of sprites and their production of chemical species into a chemistry–climate model. While our results indicate that sprites have a minimal global influence on atmospheric chemistry, they underscore their noteworthy importance at a regional scale.
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
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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
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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.
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
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The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
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
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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.
Annalie Dorph, Erica Marshall, Kate A. Parkins, and Trent D. Penman
Nat. Hazards Earth Syst. Sci., 22, 3487–3499, https://doi.org/10.5194/nhess-22-3487-2022, https://doi.org/10.5194/nhess-22-3487-2022, 2022
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Wildfire spatial patterns are determined by fire ignition sources and vegetation fuel moisture. Fire ignitions can be mediated by humans (owing to proximity to human infrastructure) or caused by lightning (owing to fuel moisture, average annual rainfall and local weather). When moisture in dead vegetation is below 20 % the probability of a wildfire increases. The results of this research enable accurate spatial mapping of ignition probability to aid fire suppression efforts and future research.
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.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Thilo Erbertseder, Diego Loyola, Pieter Valks, Song Liu, Dale J. Allen, Kenneth E. Pickering, Eric J. Bucsela, Patrick Jöckel, Jos van Geffen, Henk Eskes, Sergio Soler, Francisco J. Gordillo-Vázquez, and Jeff Lapierre
Atmos. Meas. Tech., 15, 3329–3351, https://doi.org/10.5194/amt-15-3329-2022, https://doi.org/10.5194/amt-15-3329-2022, 2022
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Lightning, one of the major sources of nitrogen oxides in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. In this work, we contribute to improving the estimation of lightning-produced nitrogen oxides in the Ebro Valley and the Pyrenees by using two different TROPOMI products and comparing the results.
Nicolau Pineda, Juan Carlos Peña, Xavier Soler, Montse Aran, and Núria Pérez-Zanón
Adv. Sci. Res., 19, 39–49, https://doi.org/10.5194/asr-19-39-2022, https://doi.org/10.5194/asr-19-39-2022, 2022
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Wildfire origins can be related to human activity or to natural phenomena, like lightning. Under favourable environmental conditions, lightning ignitions can develop into a fire. In the present study, we analyse the kind of weather that favours wildfires ignited by lightning in Catalonia. We have found that most fires occur under three types of weather. These results help to improve our understanding of lightning fires and are of great assistance to wildfire management agencies.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Patrick Jöckel, and Francisco J. Gordillo-Vázquez
Geosci. Model Dev., 15, 1545–1565, https://doi.org/10.5194/gmd-15-1545-2022, https://doi.org/10.5194/gmd-15-1545-2022, 2022
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This study reports the first parameterization of long-continuing-current lightning in a climate model. Long-continuing-current lightning is proposed to be the main precursor of lightning-ignited wildfires and sprites, a type of transient luminous event taking place in the mesosphere. This parameterization can significantly contribute to improving the implementation of wildfires in climate models.
Ingrid Vigna, Angelo Besana, Elena Comino, Alessandro Pezzoli, and Davide Ascoli
Abstr. Int. Cartogr. Assoc., 3, 304, https://doi.org/10.5194/ica-abs-3-304-2021, https://doi.org/10.5194/ica-abs-3-304-2021, 2021
Francisco J. Pérez-Invernón, Heidi Huntrieser, Sergio Soler, Francisco J. Gordillo-Vázquez, Nicolau Pineda, Javier Navarro-González, Víctor Reglero, Joan Montanyà, Oscar van der Velde, and Nikos Koutsias
Atmos. Chem. Phys., 21, 17529–17557, https://doi.org/10.5194/acp-21-17529-2021, https://doi.org/10.5194/acp-21-17529-2021, 2021
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Lightning-ignited fires tend to occur in remote areas and can spread significantly before suppression. Long continuing current (LCC) lightning, preferably taking place in dry thunderstorms, is believed to be the main precursor of lightning-ignited fires. We analyze fire databases of lightning-ignited fires in the Mediterranean basin and report the shared meteorological conditions of fire- and LCC-lightning-producing thunderstorms. These results can be useful to improve fire forecasting methods.
Dieter R. Poelman, Wolfgang Schulz, Stephane Pedeboy, Dustin Hill, Marcelo Saba, Hugh Hunt, Lukas Schwalt, Christian Vergeiner, Carlos T. Mata, Carina Schumann, and Tom Warner
Nat. Hazards Earth Syst. Sci., 21, 1909–1919, https://doi.org/10.5194/nhess-21-1909-2021, https://doi.org/10.5194/nhess-21-1909-2021, 2021
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Information about lightning properties is important in order to advance the current understanding of lightning, whereby the characteristics of ground strike points are in particular helpful to improving the risk estimation for lightning protection. High-speed video recordings of 1174 negative downward lightning flashes are taken in different regions around the world and analyzed in terms of flash multiplicity, duration, interstroke intervals and ground strike point properties.
Dieter R. Poelman, Wolfgang Schulz, Stephane Pedeboy, Leandro Z. S. Campos, Michihiro Matsui, Dustin Hill, Marcelo Saba, and Hugh Hunt
Nat. Hazards Earth Syst. Sci., 21, 1921–1933, https://doi.org/10.5194/nhess-21-1921-2021, https://doi.org/10.5194/nhess-21-1921-2021, 2021
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The lightning flash density is a key input parameter for assessing the risk of occurrence of a lightning strike. Flashes tend to have more than one ground termination point on average; therefore the use of ground strike point densities is more appropriate. The aim of this study is to assess the ability of three distinct ground strike point algorithms to correctly determine the observed ground-truth strike points.
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.
Magí Franquesa, Melanie K. Vanderhoof, Dimitris Stavrakoudis, Ioannis Z. Gitas, Ekhi Roteta, Marc Padilla, and Emilio Chuvieco
Earth Syst. Sci. Data, 12, 3229–3246, https://doi.org/10.5194/essd-12-3229-2020, https://doi.org/10.5194/essd-12-3229-2020, 2020
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The article presents a database of reference sites for the validation of burned area products. We have compiled 2661 reference files from different international projects. The paper describes the methods used to generate and standardize the data. The Burned Area Reference Data (BARD) is publicly available and will facilitate the arduous task of validating burned area algorithms.
Alejandro Luque, Francisco José Gordillo-Vázquez, Dongshuai Li, Alejandro Malagón-Romero, Francisco Javier Pérez-Invernón, Anthony Schmalzried, Sergio Soler, Olivier Chanrion, Matthias Heumesser, Torsten Neubert, Víctor Reglero, and Nikolai Østgaard
Geosci. Model Dev., 13, 5549–5566, https://doi.org/10.5194/gmd-13-5549-2020, https://doi.org/10.5194/gmd-13-5549-2020, 2020
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Lightning flashes are often recorded from space-based platforms. Besides being valuable inputs for weather forecasting, these observations also enable research into fundamental questions regarding lightning physics. To exploit them, it is essential to understand how light propagates from a lightning flash to a space-based observation instrument. Here, we present an open-source software tool to model this process that extends on previous work and overcomes some of the existing limitations.
I. C.F. Amaral, R. S. Libonati, and A. C. P. A. Palmeira
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 505–508, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-505-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-505-2020, 2020
P. S. Silva, J. A. Rodrigues, F. L. M. Santos, A. A. Pereira, J. Nogueira, C. C. DaCamara, and R. Libonati
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 135–140, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-135-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-135-2020, 2020
Jordi Figueras i Ventura, Nicolau Pineda, Nikola Besic, Jacopo Grazioli, Alessandro Hering, Oscar A. van der Velde, David Romero, Antonio Sunjerga, Amirhossein Mostajabi, Mohammad Azadifar, Marcos Rubinstein, Joan Montanyà, Urs Germann, and Farhad Rachidi
Atmos. Meas. Tech., 12, 5573–5591, https://doi.org/10.5194/amt-12-5573-2019, https://doi.org/10.5194/amt-12-5573-2019, 2019
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This paper presents an analysis of the lightning production of convective cells. Polarimetric weather radar data were used to identify and characterize the convective cells while lightning was detected using the EUCLID network and a lightning mapping array deployed during the summer of 2017 in the northeastern part of Switzerland. In it we show that there is a good correlation between the height of the rimed-particle column and the intensity of the lightning activity in the convective cell.
C. Müller-Tautges, A. Eichler, M. Schwikowski, G. B. Pezzatti, M. Conedera, and T. Hoffmann
Atmos. Chem. Phys., 16, 1029–1043, https://doi.org/10.5194/acp-16-1029-2016, https://doi.org/10.5194/acp-16-1029-2016, 2016
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The paper focuses on the determination and interpretation of historic records of organic compounds in an ice core from Grenzgletscher in the southern Swiss Alps, covering the time period from 1942 to 1993. The resulting long-term records of organic species were found to be influenced by the forest fire history in southern Switzerland, anthropogenic emissions, as well as changing mineral dust transport to the drilling site.
S. Veraverbeke, B. M. Rogers, and J. T. Randerson
Biogeosciences, 12, 3579–3601, https://doi.org/10.5194/bg-12-3579-2015, https://doi.org/10.5194/bg-12-3579-2015, 2015
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We developed a statistical model of daily carbon consumption by fire for Alaska at 450m resolution between 2001 and 2012. We used field measurements from black spruce forests in Alaska to build nonlinear multiplicative models predicting carbon consumption by fire in response to environmental variables. Our analysis highlights the importance of accounting for the spatial heterogeneity within fuels and consumption when extrapolating emissions in space and time.
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Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100
A remote-sensing-based dataset to characterize the ecosystem functioning and functional diversity in the Biosphere Reserve of the Sierra Nevada (southeastern Spain)
A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
Mammals in the Chornobyl Exclusion Zone's Red Forest: a motion-activated camera trap study
Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years
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
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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.
Tianjing Ren and Andong Cai
Earth Syst. Sci. Data, 17, 2873–2885, https://doi.org/10.5194/essd-17-2873-2025, https://doi.org/10.5194/essd-17-2873-2025, 2025
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This study compiles a global database of soil dissolved organic carbon (DOC) concentrations, a key factor in soil health and climate change. Using machine learning, it identifies the most influential factors affecting soil DOC levels and maps global DOC patterns. The findings help guide soil management and climate strategies, with the dataset available for further research.
Emma Rehn, Haidee Cadd, Scott Mooney, Tim J. Cohen, Henry Munack, Alexandru T. Codilean, Matthew Adeleye, Kristen K. Beck, Mark Constantine IV, Chris Gouramanis, Johanna M. Hanson, Penelope J. Jones, A. Peter Kershaw, Lydia Mackenzie, Maame Maisie, Michela Mariani, Kia Matley, David McWethy, Keely Mills, Patrick Moss, Nicholas R. Patton, Cassandra Rowe, Janelle Stevenson, John Tibby, and Janet Wilmshurst
Earth Syst. Sci. Data, 17, 2681–2692, https://doi.org/10.5194/essd-17-2681-2025, https://doi.org/10.5194/essd-17-2681-2025, 2025
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This paper presents SahulCHAR, a new collection of palaeofire (ancient fire) records from Australia, New Guinea, and New Zealand. SahulCHAR version 1 contains 687 records of sedimentary charcoal or black carbon, including digitized data, records from existing databases, and original author-submitted data. SahulCHAR is a much-needed update to past charcoal compilations that will also provide greater representation of records from this region in future global syntheses to understand past fire.
Judith Vogt, Martijn M. T. A. Pallandt, Luana S. Basso, Abdullah Bolek, Kseniia Ivanova, Mark Schlutow, Gerardo Celis, McKenzie Kuhn, Marguerite Mauritz, Edward A. G. Schuur, Kyle Arndt, Anna-Maria Virkkala, Isabel Wargowsky, and Mathias Göckede
Earth Syst. Sci. Data, 17, 2553–2573, https://doi.org/10.5194/essd-17-2553-2025, https://doi.org/10.5194/essd-17-2553-2025, 2025
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We present a meta-dataset of greenhouse gas observations in the Arctic and boreal regions, including information on sites where greenhouse gases have been measured using different measurement techniques. We provide a novel repository of metadata to facilitate synthesis efforts for regions undergoing rapid environmental change. The meta-dataset shows where measurements are missing and will be updated as new measurements are published.
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
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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.
Alba Viana-Soto and Cornelius Senf
Earth Syst. Sci. Data, 17, 2373–2404, https://doi.org/10.5194/essd-17-2373-2025, https://doi.org/10.5194/essd-17-2373-2025, 2025
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Europe's forests are undergoing complex changes in response to increasing disturbances driven by climate and land use changes. Here, we present the European Forest Disturbance Atlas, a satellite-based approach for mapping annual forest disturbances across continental Europe from 1985 onwards. Maps provide insights into the year of disturbance occurrence, the actual frequency of disturbances, severity and the underlying causal agent, thus contributing to a future monitoring system envisioned for Europe.
Katharina Jentzsch, Lona van Delden, Matthias Fuchs, and Claire C. Treat
Earth Syst. Sci. Data, 17, 2331–2372, https://doi.org/10.5194/essd-17-2331-2025, https://doi.org/10.5194/essd-17-2331-2025, 2025
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Methane is a greenhouse gas that contributes to global warming, but we do not fully understand how much is released from natural sources like wetlands. To measure methane over large areas, many measurements are needed, often from small chambers that are placed on the ground. However, different researchers use different measurement setups, making it hard to combine data. We surveyed 36 researchers about their methods, summarized the responses, and identified ways to make the data more comparable.
Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh
Earth Syst. Sci. Data, 17, 2007–2033, https://doi.org/10.5194/essd-17-2007-2025, https://doi.org/10.5194/essd-17-2007-2025, 2025
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This study reconstructed vegetation and tree cover in the Northern Hemisphere from a harmonized dataset of pollen counts from sediment and peat cores for the past 14 000 years. A model was applied to correct for differences in pollen production between different plants, and modern remote-sensing forest cover was used to validate the reconstructed tree cover. Accurate data on past vegetation are invaluable for the investigation of vegetation–climate dynamics and the validation of vegetation models.
Simeon Lisovski, Alexandra Runge, Iuliia Shevtsova, Nele Landgraf, Anne Morgenstern, Ronald Reagan Okoth, Matthias Fuchs, Nikolay Lashchinskiy, Carl Stadie, Alison Beamish, Ulrike Herzschuh, Guido Grosse, and Birgit Heim
Earth Syst. Sci. Data, 17, 1707–1730, https://doi.org/10.5194/essd-17-1707-2025, https://doi.org/10.5194/essd-17-1707-2025, 2025
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The Lena Delta is the largest river delta in the Arctic and represents a biodiversity hotspot. Here, we describe multiple field datasets and a detailed habitat classification map for the Lena Delta. We present context and methods of these openly available datasets and show how they can improve our understanding of the rapidly changing Arctic tundra system.
Sijia Li and Hongliang Fang
Earth Syst. Sci. Data, 17, 1347–1366, https://doi.org/10.5194/essd-17-1347-2025, https://doi.org/10.5194/essd-17-1347-2025, 2025
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Leaf inclination angle (LIA) is a vital trait in radiative transfer, rainfall interception, evapotranspiration, photosynthesis, and hydrological processes. However, global LIA knowledge is still lacking. This study generated the first global 500 m LIA products by gap-filling LIA measurement data. The global LIA is 41.47° ± 9.55° and increases with latitude. LIA products could enhance our understanding of global LIA and assist remote sensing retrieval and land surface modeling studies.
Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data, 17, 1329–1346, https://doi.org/10.5194/essd-17-1329-2025, https://doi.org/10.5194/essd-17-1329-2025, 2025
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In this study, carbon flux and auxiliary meteorological data are post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River basin. Overall, 18 sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1513 site months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data, 17, 881–916, https://doi.org/10.5194/essd-17-881-2025, https://doi.org/10.5194/essd-17-881-2025, 2025
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Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in the EU 27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Thomas Dirnböck, Michael Bahn, Eugenio Diaz-Pines, Ika Djukic, Michael Englisch, Karl Gartner, Günther Gollobich, Johannes Ingrisch, Barbara Kitzler, Karl Knaebel, Johannes Kobler, Andreas Maier, Armin Malli, Ivo Offenthaler, Johannes Peterseil, Gisela Pröll, Sarah Venier, Christoph Wohner, Sophie Zechmeister-Boltenstern, Anita Zolles, and Stephan Glatzel
Earth Syst. Sci. Data, 17, 685–702, https://doi.org/10.5194/essd-17-685-2025, https://doi.org/10.5194/essd-17-685-2025, 2025
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Long-term observation sites have been established in six Austrian locations, covering major ecosystem types such as forests, grasslands, and wetlands. The purpose of these observations is to measure baselines for assessing the impacts of extreme climate events on the carbon cycle. The collected datasets include meteorological variables, soil temperature and moisture, carbon dioxide fluxes, and tree stem growth in forests at a resolution of 15–60 min between 2019 and 2021.
Xueqin Yang, Qingling Sun, Liusheng Han, Wenping Yuan, Jie Tian, Liyang Liu, Wei Zheng, Mei Wang, Yunpeng Wang, and Xiuzhi Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-64, https://doi.org/10.5194/essd-2025-64, 2025
Revised manuscript accepted for ESSD
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Understanding how leaves absorb carbon from the atmosphere is essential for predicting changes in global forests. Young leaves play a key role in this process, but their efficiency has been difficult to measure at large scales. Using satellite data, we developed a new method to track the seasonal patterns of young leaves’ photosynthetic capacity from 2001 to 2018. Our dataset helps scientists better understand forest growth and how ecosystems respond to climate change.
Masahito Ueyama, Yuta Takao, Hiromi Yazawa, Makiko Tanaka, Hironori Yabuki, Tomo’omi Kumagai, Hiroki Iwata, Md. Abdul Awal, Mingyuan Du, Yoshinobu Harazono, Yoshiaki Hata, Takashi Hirano, Tsutom Hiura, Reiko Ide, Sachinobu Ishida, Mamoru Ishikawa, Kenzo Kitamura, Yuji Kominami, Shujiro Komiya, Ayumi Kotani, Yuta Inoue, Takashi Machimura, Kazuho Matsumoto, Yojiro Matsuura, Yasuko Mizoguchi, Shohei Murayama, Hirohiko Nagano, Taro Nakai, Tatsuro Nakaji, Ko Nakaya, Shinjiro Ohkubo, Takeshi Ohta, Keisuke Ono, Taku M. Saitoh, Ayaka Sakabe, Takanori Shimizu, Seiji Shimoda, Michiaki Sugita, Kentaro Takagi, Yoshiyuki Takahashi, Naoya Takamura, Satoru Takanashi, Takahiro Takimoto, Yukio Yasuda, Qinxue Wang, Jun Asanuma, Hideo Hasegawa, Tetsuya Hiyama, Yoshihiro Iijima, Shigeyuki Ishidoya, Masayuki Itoh, Tomomichi Kato, Hiroaki Kondo, Yoshiko Kosugi, Tomonori Kume, Takahisa Maeda, Trofim Maximov, Ryo Moriwaki, Hiroyuki Muraoka, Roman Petrov, Jun Suzuki, Shingo Taniguchi, and Kazuhito Ichii
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-615, https://doi.org/10.5194/essd-2024-615, 2025
Revised manuscript accepted for ESSD
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The JapanFlux2024 dataset, created through collaboration across Japan and East Asia, includes eddy covariance data from 79 sites spanning 652 site-years (1990–2023). This comprehensive dataset offers valuable insights into energy, water, and CO2 fluxes, supporting research on land-atmosphere interactions and process models. Compatible with FLUXNET, it fosters global collaboration and advances research in environmental science and regional climate dynamics.
Gudeta Weldesemayat Sileshi, Edmundo Barrios, Johannes Lehmann, and Francesco Nicola Tubiello
Earth Syst. Sci. Data, 17, 369–391, https://doi.org/10.5194/essd-17-369-2025, https://doi.org/10.5194/essd-17-369-2025, 2025
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Agricultural, fishery, forestry and agro-processing activities produce large quantities of residues, by-products and waste materials every year. Here, we present a global organic matter database (OMD), the first of its kind, consolidating estimates of residues and by-products potentially available for use in a circular bio-economy. It also provides definitions, typologies and methods to aid consistent classification, estimation and reporting of the various residues and by-products.
Rong Shang, Xudong Lin, Jing M. Chen, Yunjian Liang, Keyan Fang, Mingzhu Xu, Yulin Yan, Weimin Ju, Guirui Yu, Nianpeng He, Li Xu, Liangyun Liu, Jing Li, Wang Li, Jun Zhai, and Zhongmin Hu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-574, https://doi.org/10.5194/essd-2024-574, 2025
Revised manuscript accepted for ESSD
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Forest age is critical for carbon cycle modelling and effective forest management. Existing datasets, however, have low spatial resolutions or limited temporal coverage. This study introduces China's Annual Forest Age Dataset (CAFA), spanning 1986–2022 at 30-m resolution. By tracking forest disturbances, we annually update ages. Validation shows small errors for disturbed forests and larger for undisturbed forests. CAFA can enhance carbon cycle modelling and forest management in China.
Kelly S. Aho, Kaelin M. Cawley, Robert T. Hensley, Robert O. Hall Jr., Walter K. Dodds, and Keli J. Goodman
Earth Syst. Sci. Data, 16, 5563–5578, https://doi.org/10.5194/essd-16-5563-2024, https://doi.org/10.5194/essd-16-5563-2024, 2024
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Gas exchange is fundamental to many biogeochemical processes in streams and depends on the degree of gas saturation and the gas transfer velocity (k). Currently, k is harder to measure than concentration. Here, we present a processing pipeline to estimate k from tracer-gas experiments conducted in 22 streams by the National Ecological Observatory Network. The processed dataset (n = 339) represents the largest compilation of standardized k estimates available.
Yifang Shi and W. Daniel Kissling
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-488, https://doi.org/10.5194/essd-2024-488, 2024
Revised manuscript accepted for ESSD
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We present a new set of multi-temporal LiDAR metrics of ecosystem structure derived from four national ALS surveys of the Netherlands (AHN1–AHN4), capturing vegetation height, cover, and structural variability over the past two decades (1998–2022). Around 70 TB point clouds have been processed to read-to-use raster layers at 10 m resolution (~ 59 GB), enabling a wide use and uptake of ecosystem structure information in biodiversity and habitat monitoring, ecosystem and carbon dynamic modelling.
Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová
Earth Syst. Sci. Data, 16, 5069–5087, https://doi.org/10.5194/essd-16-5069-2024, https://doi.org/10.5194/essd-16-5069-2024, 2024
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Radiative transfer models play a key role in monitoring vegetation using remote sensing data such as satellite or airborne images. The development of these models has been hindered by a lack of comprehensive ground reference data on structural and spectral characteristics of forests. Here, we reported datasets on the structural and spectral properties of temperate, hemiboreal, and boreal European forest stands. We anticipate that these data will have wide use in remote sensing applications.
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
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VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Peiyu Cao, Bo Yi, Franco Bilotto, Carlos Gonzalez Fischer, Mario Herrero, and Chaoqun Lu
Earth Syst. Sci. Data, 16, 4557–4572, https://doi.org/10.5194/essd-16-4557-2024, https://doi.org/10.5194/essd-16-4557-2024, 2024
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This article presents a spatially explicit time series dataset reconstructing crop-specific phosphorus fertilizer application rates, timing, and methods at a 4 km × 4 km resolution in the United States from 1850 to 2022. We comprehensively characterized the spatio-temporal dynamics of P fertilizer management over the last 170 years by considering cross-crop variations. This dataset will greatly contribute to the field of agricultural sustainability assessment and Earth system modeling.
Chad A. Burton, Sami W. Rifai, Luigi J. Renzullo, and Albert I. J. M. Van Dijk
Earth Syst. Sci. Data, 16, 4389–4416, https://doi.org/10.5194/essd-16-4389-2024, https://doi.org/10.5194/essd-16-4389-2024, 2024
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Understanding vegetation response to environmental change requires accurate, long-term data on vegetation condition (VC). We evaluated existing satellite VC datasets over Australia and found them lacking, so we developed a new VC dataset for Australia, AusENDVI. It can be used for studying Australia's changing vegetation dynamics and downstream impacts on the carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
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The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Yishuo Cui, Shouzhi Chen, Yufeng Gong, Mingwei Li, Zitong Jia, Yuyu Zhou, and Yongshuo H. Fu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-225, https://doi.org/10.5194/essd-2024-225, 2024
Revised manuscript accepted for ESSD
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Global changes have significantly altered vegetation phenology, affecting terrestrial carbon cycle. While various remote-sensing-based phenology datasets exist, they often suffer from inconsistencies and uncertainties. To address this, we developed a new phenology dataset spanning 1982 to 2022 using a reliability ensemble averaging method. Validated against ground data, our dataset demonstrates substantially improved accuracy, providing a novel and reliable source for global ecological studies.
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu
Earth Syst. Sci. Data, 16, 2789–2809, https://doi.org/10.5194/essd-16-2789-2024, https://doi.org/10.5194/essd-16-2789-2024, 2024
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To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
Daju Wang, Peiyang Ren, Xiaosheng Xia, Lei Fan, Zhangcai Qin, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data, 16, 2465–2481, https://doi.org/10.5194/essd-16-2465-2024, https://doi.org/10.5194/essd-16-2465-2024, 2024
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This study generated a high-precision dataset, locating forest harvested carbon and quantifying post-harvest wood emissions for various uses. It enhances our understanding of forest harvesting and post-harvest carbon dynamics in China, providing essential data for estimating the forest ecosystem carbon budget and emphasizing wood utilization's impact on carbon emissions.
Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
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This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Kai Yan, Jingrui Wang, Rui Peng, Kai Yang, Xiuzhi Chen, Gaofei Yin, Jinwei Dong, Marie Weiss, Jiabin Pu, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 1601–1622, https://doi.org/10.5194/essd-16-1601-2024, https://doi.org/10.5194/essd-16-1601-2024, 2024
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Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data, 16, 731–742, https://doi.org/10.5194/essd-16-731-2024, https://doi.org/10.5194/essd-16-731-2024, 2024
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Modern and fossil pollen data contain precious information for reconstructing the climate and environment of the past. However, these data are only achieved for single locations with no continuity in space. We present here a systematic atlas of 194 digital maps containing the spatial estimation of contemporary pollen presence over Europe. This dataset constitutes a free and ready-to-use tool to study climate, biodiversity, and environment in time and space.
João Paulo Darela-Filho, Anja Rammig, Katrin Fleischer, Tatiana Reichert, Laynara Figueiredo Lugli, Carlos Alberto Quesada, Luis Carlos Colocho Hurtarte, Mateus Dantas de Paula, and David M. Lapola
Earth Syst. Sci. Data, 16, 715–729, https://doi.org/10.5194/essd-16-715-2024, https://doi.org/10.5194/essd-16-715-2024, 2024
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Phosphorus (P) is crucial for plant growth, and scientists have created models to study how it interacts with carbon cycle in ecosystems. To apply these models, it is important to know the distribution of phosphorus in soil. In this study we estimated the distribution of phosphorus in the Amazon region. The results showed a clear gradient of soil development and P content. These maps can help improve ecosystem models and generate new hypotheses about phosphorus availability in the Amazon.
Mengyao Zhu, Junhu Dai, Huanjiong Wang, Juha M. Alatalo, Wei Liu, Yulong Hao, and Quansheng Ge
Earth Syst. Sci. Data, 16, 277–293, https://doi.org/10.5194/essd-16-277-2024, https://doi.org/10.5194/essd-16-277-2024, 2024
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This study utilized 24,552 in situ phenology observation records from the Chinese Phenology Observation Network to model and map 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020. These phenology maps are the first gridded, independent and reliable phenology data sources for China, offering a high spatial resolution of 0.1° and an average deviation of about 10 days. It contributes to more comprehensive research on plant phenology and climate change.
Jiabin Pu, Kai Yan, Samapriya Roy, Zaichun Zhu, Miina Rautiainen, Yuri Knyazikhin, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 15–34, https://doi.org/10.5194/essd-16-15-2024, https://doi.org/10.5194/essd-16-15-2024, 2024
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Long-term global LAI/FPAR products provide the fundamental dataset for accessing vegetation dynamics and studying climate change. This study develops a sensor-independent LAI/FPAR climate data record based on the integration of Terra-MODIS/Aqua-MODIS/VIIRS LAI/FPAR standard products and applies advanced gap-filling techniques. The SI LAI/FPAR CDR provides a valuable resource for researchers studying vegetation dynamics and their relationship to climate change in the 21st century.
Wojciech Tylmann, Alicja Bonk, Dariusz Borowiak, Paulina Głowacka, Kamil Nowiński, Joanna Piłczyńska, Agnieszka Szczerba, and Maurycy Żarczyński
Earth Syst. Sci. Data, 15, 5093–5103, https://doi.org/10.5194/essd-15-5093-2023, https://doi.org/10.5194/essd-15-5093-2023, 2023
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We present a dataset from the decade-long monitoring of Lake Żabińskie, a hardwater and eutrophic lake in northeast Poland. The lake contains varved sediments, which form a unique archive of past environmental variability. The monitoring program was designed to capture a pattern of relationships between meteorological conditions, limnological processes, and modern sedimentation and to verify if meteorological and limnological phenomena can be precisely tracked with varves.
Sen Cao, Muyi Li, Zaichun Zhu, Zhe Wang, Junjun Zha, Weiqing Zhao, Zeyu Duanmu, Jiana Chen, Yaoyao Zheng, Yue Chen, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4877–4899, https://doi.org/10.5194/essd-15-4877-2023, https://doi.org/10.5194/essd-15-4877-2023, 2023
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The long-term global leaf area index (LAI) products are critical for characterizing vegetation dynamics under environmental changes. This study presents an updated GIMMS LAI product (GIMMS LAI4g; 1982−2020) based on PKU GIMMS NDVI and massive Landsat LAI samples. With higher accuracy than other LAI products, GIMMS LAI4g removes the effects of orbital drift and sensor degradation in AVHRR data. It has better temporal consistency before and after 2000 and a more reasonable global vegetation trend.
Yanghui Kang, Max Gaber, Maoya Bassiouni, Xinchen Lu, and Trevor Keenan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-337, https://doi.org/10.5194/essd-2023-337, 2023
Revised manuscript accepted for ESSD
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CEDAR-GPP provides spatiotemporally upscaled estimates of Gross Primary Productivity, uniquely incorporating the direct effect of elevated atmospheric CO2 on global photosynthesis. This dataset was produced by upscaling global eddy covariance measurements with multi-source satellite observations and climate data using machine learning. Available at monthly and 0.05° resolution from 1982 to 2020, CEDAR-GPP offers critical insights into ecosystem-climate interaction.
Muyi Li, Sen Cao, Zaichun Zhu, Zhe Wang, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, https://doi.org/10.5194/essd-15-4181-2023, 2023
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Long-term global Normalized Difference Vegetation Index (NDVI) products support the understanding of changes in vegetation under environmental changes. This study generates a consistent global NDVI product (PKU GIMMS NDVI) from 1982–2022 that eliminates the issue of orbital drift and sensor degradation in Advanced Very High Resolution Radiometer (AVHRR) data. More accurate than its predecessor (GIMMS NDVI3g), it shows high temporal consistency with MODIS NDVI in describing vegetation trends.
Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquin, Hasnat Aslam, and Natalia De Leon Gatti
Earth Syst. Sci. Data, 15, 3963–3990, https://doi.org/10.5194/essd-15-3963-2023, https://doi.org/10.5194/essd-15-3963-2023, 2023
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A genomic, phenomic, and climate database for maize phenotype predictability in the US and Canada is introduced. The database encompasses climate from multiple sources and OMICS from the Genomes to Fields initiative (G2F) data from 2014 to 2021, including codes for input data quality and consistency controls. Earth system modelers and breeders can use CLIM4OMICS since it interconnects the climate and biological system sciences. CLIM4OMICS is designed to foster phenotype predictability.
Elisabeth Mauclet, Maëlle Villani, Arthur Monhonval, Catherine Hirst, Edward A. G. Schuur, and Sophie Opfergelt
Earth Syst. Sci. Data, 15, 3891–3904, https://doi.org/10.5194/essd-15-3891-2023, https://doi.org/10.5194/essd-15-3891-2023, 2023
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Permafrost ecosystems are limited in nutrients for vegetation development and constrain the biological activity to the active layer. Upon Arctic warming, permafrost degradation exposes organic and mineral soil material that may directly influence the capacity of the soil to retain key nutrients for vegetation growth and development. Here, we demonstrate that the average total exchangeable nutrient density (Ca, K, Mg, and Na) is more than 2 times higher in the permafrost than in the active layer.
Anna G. Boegehold, Ashley M. Burtner, Andrew C. Camilleri, Glenn Carter, Paul DenUyl, David Fanslow, Deanna Fyffe Semenyuk, Casey M. Godwin, Duane Gossiaux, Thomas H. Johengen, Holly Kelchner, Christine Kitchens, Lacey A. Mason, Kelly McCabe, Danna Palladino, Dack Stuart, Henry Vanderploeg, and Reagan Errera
Earth Syst. Sci. Data, 15, 3853–3868, https://doi.org/10.5194/essd-15-3853-2023, https://doi.org/10.5194/essd-15-3853-2023, 2023
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Western Lake Erie suffers from cyanobacterial harmful algal blooms (HABs) despite decades of international management efforts. In response, the US National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) created an annual sampling program to detect, monitor, assess, and predict HABs. Here we describe the data collected from this monitoring program from 2012 to 2021.
Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, and Ana C. L. Sá
Earth Syst. Sci. Data, 15, 3791–3818, https://doi.org/10.5194/essd-15-3791-2023, https://doi.org/10.5194/essd-15-3791-2023, 2023
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We reconstructed the spread of 80 large wildfires that burned recently in Portugal and calculated metrics that describe how wildfires behave, such as rate of spread, growth rate, and energy released. We describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. The database will help improve our current knowledge on wildfire behaviour and support better decision making.
Yuelong Xiao, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson
Earth Syst. Sci. Data, 15, 3365–3386, https://doi.org/10.5194/essd-15-3365-2023, https://doi.org/10.5194/essd-15-3365-2023, 2023
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Forest age is closely related to forest production, carbon cycles, and other ecosystem services. Existing stand age products in China derived from remote-sensing images are of a coarse spatial resolution and are not suitable for applications at the regional scale. Here, we mapped young forest ages across China at an unprecedented fine spatial resolution of 30 m. The overall accuracy (OA) of the generated map of young forest stand ages across China was 90.28 %.
Emily H. Stanley, Luke C. Loken, Nora J. Casson, Samantha K. Oliver, Ryan A. Sponseller, Marcus B. Wallin, Liwei Zhang, and Gerard Rocher-Ros
Earth Syst. Sci. Data, 15, 2879–2926, https://doi.org/10.5194/essd-15-2879-2023, https://doi.org/10.5194/essd-15-2879-2023, 2023
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The Global River Methane Database (GRiMeDB) presents CH4 concentrations and fluxes for flowing waters and concurrent measures of CO2, N2O, and several physicochemical variables, plus information about sample locations and methods used to measure gas fluxes. GRiMeDB is intended to increase opportunities to understand variation in fluvial CH4, test hypotheses related to greenhouse gas dynamics, and reduce uncertainty in future estimates of gas emissions from world streams and rivers.
Xueqin Yang, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, Yihua Xiao, Qinghai Song, Yanjun Du, Shengbiao Wu, Lei Fan, Xiaoai Dai, Yunpeng Wang, and Yongxian Su
Earth Syst. Sci. Data, 15, 2601–2622, https://doi.org/10.5194/essd-15-2601-2023, https://doi.org/10.5194/essd-15-2601-2023, 2023
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We developed the first time-mapped, continental-scale gridded dataset of monthly leaf area index (LAI) in three leaf age cohorts (i.e., young, mature, and old) from 2001–2018 data (referred to as Lad-LAI). The seasonality of three LAI cohorts from the new Lad-LAI product agrees well at eight sites with very fine-scale collections of monthly LAI. The proposed satellite-based approaches can provide references for mapping finer spatiotemporal-resolution LAI products with different leaf age cohorts.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data, 15, 2153–2177, https://doi.org/10.5194/essd-15-2153-2023, https://doi.org/10.5194/essd-15-2153-2023, 2023
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We present a new database of four annual fire weather indicators over 1850–2100 and over all land areas. In a 3°C warmer world with respect to preindustrial times, the mean fire weather would increase on average by at least 66% in both intensity and duration and even triple for 1-in-10-year events. The dataset is a freely available resource for fire danger studies and beyond, highlighting that the best course of action would require limiting global warming as much as possible.
Beatriz P. Cazorla, Javier Cabello, Andrés Reyes, Emilio Guirado, Julio Peñas, Antonio J. Pérez-Luque, and Domingo Alcaraz-Segura
Earth Syst. Sci. Data, 15, 1871–1887, https://doi.org/10.5194/essd-15-1871-2023, https://doi.org/10.5194/essd-15-1871-2023, 2023
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This dataset provides scientists, environmental managers, and the public in general with valuable information on the first characterization of ecosystem functional diversity based on primary production developed in the Sierra Nevada (Spain), a biodiversity hotspot in the Mediterranean basin and an exceptional natural laboratory for ecological research within the Long-Term Social-Ecological Research (LTSER) network.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
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We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Nicholas A. Beresford, Sergii Gashchak, Michael D. Wood, and Catherine L. Barnett
Earth Syst. Sci. Data, 15, 911–920, https://doi.org/10.5194/essd-15-911-2023, https://doi.org/10.5194/essd-15-911-2023, 2023
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Camera traps were established in a highly contaminated area of the Chornobyl Exclusion Zone (CEZ) to capture images of mammals. Over 1 year, 14 mammal species were recorded. The number of species observed did not vary with estimated radiation exposure. The data will be of value from the perspectives of effects of radiation on wildlife and also rewilding in this large, abandoned area. They may also have value in future studies investigating impacts of recent Russian military action in the CEZ.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
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This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
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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.
This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover...
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