Articles | Volume 13, issue 3
https://doi.org/10.5194/essd-13-943-2021
© Author(s) 2021. 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-13-943-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
09 Mar 2021
Data description paper |
| 09 Mar 2021
| 09 Mar 2021
The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience
Jeff W. Atkins
CORRESPONDING AUTHOR
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Elizabeth Agee
Environmental Sciences Division and Climate Change Science Institute,
Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Alexandra Barry
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Kyla M. Dahlin
Department of Geography, Environment, and Spatial Sciences, Michigan
State University, East Lansing, MI 48824, USA
Kalyn Dorheim
Joint Global Change Research Institute at the University of Maryland,
Pacific Northwest National Laboratory, College Park, MD 20740, USA
Maxim S. Grigri
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Lisa T. Haber
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Laura J. Hickey
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Aaron G. Kamoske
Department of Geography, Environment, and Spatial Sciences, Michigan
State University, East Lansing, MI 48824, USA
Kayla Mathes
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Catherine McGuigan
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Evan Paris
Vassar College, Poughkeepsie, NY 12604, USA
Stephanie C. Pennington
Joint Global Change Research Institute at the University of Maryland,
Pacific Northwest National Laboratory, College Park, MD 20740, USA
Carly Rodriguez
Western Colorado University, Gunnison, CO 81231, USA
Autym Shafer
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Alexey Shiklomanov
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Jason Tallant
University of Michigan Biological Station, Pellston, MI 49769, USA
Christopher M. Gough
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Ben Bond-Lamberty
Joint Global Change Research Institute at the University of Maryland,
Pacific Northwest National Laboratory, College Park, MD 20740, USA
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Junyan Ding, Nate McDowell, Vanessa Bailey, Nate Conroy, Donnie J. Day, Yilin Fang, Kenneth M. Kemner, Matthew L. Kirwan, Charlie D. Koven, Matthew Kovach, Patrick Megonigal, Kendalynn A. Morris, Teri O’Meara, Stephanie C. Pennington, Roberta B. Peixoto, Peter Thornton, Mike Weintraub, Peter Regier, Leticia Sandoval, Fausto Machado-Silva, Alice Stearns, Nick Ward, and Stephanie J. Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2025-1544, https://doi.org/10.5194/egusphere-2025-1544, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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We used a vegetation model to study why coastal forests are dying due to rising water levels and what happens to the ecosystem when marshes take over. We found that tree death is mainly caused by water-damaged roots, leading to major changes in the environment, such as reduced water use and carbon storage. Our study helps explain how coastal ecosystems are shifting and offers new ideas to explore in future field research.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Abigail Snyder, Noah Prime, Claudia Tebaldi, and Kalyn Dorheim
Earth Syst. Dynam., 15, 1301–1318, https://doi.org/10.5194/esd-15-1301-2024, https://doi.org/10.5194/esd-15-1301-2024, 2024
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From running climate models to using their outputs to identify impacts, modeling the integrated human–Earth system is expensive. This work presents a method to identify a smaller subset of models from the full set that preserves the uncertainty characteristics of the full set. This results in a smaller number of runs that an impact modeler can use to assess how uncertainty propagates from the Earth to the human system, while still capturing the range of outcomes provided by climate models.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Danica L. Lombardozzi, William R. Wieder, Negin Sobhani, Gordon B. Bonan, David Durden, Dawn Lenz, Michael SanClements, Samantha Weintraub-Leff, Edward Ayres, Christopher R. Florian, Kyla Dahlin, Sanjiv Kumar, Abigail L. S. Swann, Claire M. Zarakas, Charles Vardeman, and Valerio Pascucci
Geosci. Model Dev., 16, 5979–6000, https://doi.org/10.5194/gmd-16-5979-2023, https://doi.org/10.5194/gmd-16-5979-2023, 2023
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We present a novel cyberinfrastructure system that uses National Ecological Observatory Network measurements to run Community Terrestrial System Model point simulations in a containerized system. The simple interface and tutorials expand access to data and models used in Earth system research by removing technical barriers and facilitating research, educational opportunities, and community engagement. The NCAR–NEON system enables convergence of climate and ecological sciences.
Claudia Tebaldi, Abigail Snyder, and Kalyn Dorheim
Earth Syst. Dynam., 13, 1557–1609, https://doi.org/10.5194/esd-13-1557-2022, https://doi.org/10.5194/esd-13-1557-2022, 2022
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Impact modelers need many future scenarios to characterize the consequences of climate change. The climate modeling community cannot fully meet this need because of the computational cost of climate models. Emulators have fallen short of providing the entire range of inputs that modern impact models require. Our proposal, STITCHES, meets these demands in a comprehensive way and may thus support a fully integrated impact research effort and save resources for the climate modeling enterprise.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences, 19, 1435–1450, https://doi.org/10.5194/bg-19-1435-2022, https://doi.org/10.5194/bg-19-1435-2022, 2022
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As carbon (C) and greenhouse gas (GHG) research has adopted appropriate technology and approach (AT&A), low-cost instruments, open-source software, and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility, and performance, the integration of low-cost and low-technology, participatory and networking-based research approaches can be AT&A for enhancing C and GHG research in developing countries.
Jinshi Jian, Xuan Du, Juying Jiao, Xiaohua Ren, Karl Auerswald, Ryan Stewart, Zeli Tan, Jianlin Zhao, Daniel L. Evans, Guangju Zhao, Nufang Fang, Wenyi Sun, Chao Yue, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-87, https://doi.org/10.5194/essd-2022-87, 2022
Manuscript not accepted for further review
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Field soil loss and sediment yield due to surface runoff observations were compiled into a database named AWESOME: Archive for Water Erosion and Sediment Outflow MEasurements. Annual soil erosion data from 1985 geographic sites and 75 countries have been compiled into AWESOME. This database aims to be an open framework for the scientific community to share field-based annual soil erosion measurements, enabling better understanding of the spatial and temporal variability of annual soil erosion.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
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We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Dawn L. Woodard, Alexey N. Shiklomanov, Ben Kravitz, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 4751–4767, https://doi.org/10.5194/gmd-14-4751-2021, https://doi.org/10.5194/gmd-14-4751-2021, 2021
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We have added a representation of the permafrost carbon feedback to the simple, open-source global carbon–climate model Hector and calibrated the results to be consistent with historical data and Earth system model projections. Our results closely match previous work, estimating around 0.2 °C of warming from permafrost this century. This capability will be useful to explore uncertainties in this feedback and for coupling with integrated assessment models for policy and economic analysis.
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244, https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
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Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin
Geosci. Model Dev., 14, 2603–2633, https://doi.org/10.5194/gmd-14-2603-2021, https://doi.org/10.5194/gmd-14-2603-2021, 2021
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Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare models against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeastern US.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-85, https://doi.org/10.5194/bg-2021-85, 2021
Manuscript not accepted for further review
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While greenhouse gas (GHG) research has adopted highly advanced technology some have adopted appropriate technology and approach (AT&A) such as low-cost instrument, open source software and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility and performance, integration of low-cost and low-technology, participatory and networking based research approaches can be AT&A for enhancing GHG research in developing countries.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
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Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375, https://doi.org/10.5194/gmd-14-365-2021, https://doi.org/10.5194/gmd-14-365-2021, 2021
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Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
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Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Jinshi Jian, Xuan Du, Ryan D. Stewart, Zeli Tan, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-283, https://doi.org/10.5194/essd-2020-283, 2020
Preprint withdrawn
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Field soil loss due to surface runoff observations were compiled into a global database (SoilErosionDB). The database focuses on three erosion-related metrics – surface runoff, soil erosion, and nutrient leaching – and also records background information. Data from 99 geographic sites and 22 countries around the world have been compiled into SoilErosionDB. SoilErosionDB aims to be a data framework for the scientific community to share field-based soil erosion measurements.
Stephanie C. Pennington, Nate G. McDowell, J. Patrick Megonigal, James C. Stegen, and Ben Bond-Lamberty
Biogeosciences, 17, 771–780, https://doi.org/10.5194/bg-17-771-2020, https://doi.org/10.5194/bg-17-771-2020, 2020
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Soil respiration (Rs) is the flow of CO2 from the soil surface to the atmosphere and is one of the largest carbon fluxes on land. This study examined the effect of local basal area (tree area) on Rs in a coastal forest in eastern Maryland, USA. Rs measurements were taken as well as distance from soil collar, diameter, and species of each tree within a 15 m radius. We found that trees within 5 m of our sampling points had a positive effect on how sensitive soil respiration was to temperature.
Robert Link, Abigail Snyder, Cary Lynch, Corinne Hartin, Ben Kravitz, and Ben Bond-Lamberty
Geosci. Model Dev., 12, 1477–1489, https://doi.org/10.5194/gmd-12-1477-2019, https://doi.org/10.5194/gmd-12-1477-2019, 2019
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Earth system models (ESMs) produce the highest-quality future climate data available, but they are costly to run, so only a few runs from each model are publicly available. What is needed are emulators that tell us what would have happened, if we had been able to perform as many ESM runs as we might have liked. Much of the existing work on emulators has focused on deterministic projections of average values. Here we present a way to imbue emulators with the variability seen in ESM runs.
Katherine Calvin, Pralit Patel, Leon Clarke, Ghassem Asrar, Ben Bond-Lamberty, Ryna Yiyun Cui, Alan Di Vittorio, Kalyn Dorheim, Jae Edmonds, Corinne Hartin, Mohamad Hejazi, Russell Horowitz, Gokul Iyer, Page Kyle, Sonny Kim, Robert Link, Haewon McJeon, Steven J. Smith, Abigail Snyder, Stephanie Waldhoff, and Marshall Wise
Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, https://doi.org/10.5194/gmd-12-677-2019, 2019
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This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. GCAM examines the future evolution of these systems through the end of the 21st century. It can be used to examine, for example, how changes in population, income, or technology cost might alter crop production, energy demand, or water withdrawals, or how changes in one region’s demand for energy affect energy, water, and land in other regions.
Yannick Le Page, Douglas Morton, Corinne Hartin, Ben Bond-Lamberty, José Miguel Cardoso Pereira, George Hurtt, and Ghassem Asrar
Earth Syst. Dynam., 8, 1237–1246, https://doi.org/10.5194/esd-8-1237-2017, https://doi.org/10.5194/esd-8-1237-2017, 2017
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Fires damage large areas of eastern Amazon forests when ignitions from human activity coincide with droughts, while more humid central and western regions are less affected. Here, we use a fire model to estimate that fire activity could increase by an order of magnitude without climate mitigation. Our results show that avoiding further agricultural expansion can limit fire ignitions but that tackling climate change is essential to insulate the interior Amazon through the 21st century.
Cary Lynch, Corinne Hartin, Min Chen, and Ben Bond-Lamberty
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-405, https://doi.org/10.5194/bg-2017-405, 2017
Revised manuscript has not been submitted
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Heterotrophic respiration (RH) is a large part of the carbon cycle, but it is poorly simulated by climate models. We examine the relationships between RH and key climate variables to understand this uncertainty in observations and from climate models. Compared to observations, models overestimate both the RH trend and climatological relationships. In the future, the relationship between RH and temperature is strong and can be used to explore a wide range of future scenarios.
James C. Stegen, Carolyn G. Anderson, Ben Bond-Lamberty, Alex R. Crump, Xingyuan Chen, and Nancy Hess
Biogeosciences, 14, 4341–4354, https://doi.org/10.5194/bg-14-4341-2017, https://doi.org/10.5194/bg-14-4341-2017, 2017
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CO2 loss from soil to the atmosphere (
soil respiration) is a key ecosystem function, especially in systems with permafrost. We find that soil respiration shows a non-linear threshold at permafrost depths > 140 cm and that the number of large trees governs soil respiration. This suggests that remote sensing could be used to estimate spatial variation in soil respiration and (with knowledge of key thresholds) empirically constrain models that predict ecosystem responses to permafrost thaw.
Francesc Montané, Andrew M. Fox, Avelino F. Arellano, Natasha MacBean, M. Ross Alexander, Alex Dye, Daniel A. Bishop, Valerie Trouet, Flurin Babst, Amy E. Hessl, Neil Pederson, Peter D. Blanken, Gil Bohrer, Christopher M. Gough, Marcy E. Litvak, Kimberly A. Novick, Richard P. Phillips, Jeffrey D. Wood, and David J. P. Moore
Geosci. Model Dev., 10, 3499–3517, https://doi.org/10.5194/gmd-10-3499-2017, https://doi.org/10.5194/gmd-10-3499-2017, 2017
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How carbon is allocated to different plant tissues (leaves, stem, and roots) determines carbon residence time and thus remains a central challenge for understanding the global carbon cycle. In this paper, we compared standard and novel carbon allocation schemes in CLM4.5 and evaluated them using eddy covariance wood and leaf biomass. The dynamic scheme based on work by Litton improved model performance, but this was dependent on model assumptions about woody turnover.
Cary Lynch, Corinne Hartin, Ben Bond-Lamberty, and Ben Kravitz
Earth Syst. Sci. Data, 9, 281–292, https://doi.org/10.5194/essd-9-281-2017, https://doi.org/10.5194/essd-9-281-2017, 2017
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Pattern scaling climate model output is a computationally efficient way to produce a large amount of data for purposes of uncertainty quantification. Using a multi-model ensemble we explore pattern scaling methodologies across two future forcing scenarios. We find that the simple least squares approach to pattern scaling produces a close approximation of actual model output, and we use this as a justification for the creation of an open-access pattern library at multiple time increments.
Ben Kravitz, Cary Lynch, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 10, 1889–1902, https://doi.org/10.5194/gmd-10-1889-2017, https://doi.org/10.5194/gmd-10-1889-2017, 2017
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Pattern scaling is a way of approximating regional changes without needing to run a full, complex global climate model. We compare two methods of pattern scaling for precipitation and evaluate which methods is
betterin particular circumstances. We also decompose precipitation into a CO2 portion and a non-CO2 portion. The methodologies discussed in this paper can help provide precipitation fields for other models for a wide variety of scenarios of future climate change.
Ben Bond-Lamberty, A. Peyton Smith, and Vanessa Bailey
Biogeosciences, 13, 6669–6681, https://doi.org/10.5194/bg-13-6669-2016, https://doi.org/10.5194/bg-13-6669-2016, 2016
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We used a laboratory experiment to examine how climate change and permafrost melting might alter soils in high-latitude regions. Soils were subjected to two temperatures and drought, and gas emissions were monitored. Carbon dioxide fluxes were influenced by temperature, water, and soil nitrogen, while methane emissions were much smaller and linked only with nitrogen. This suggests that such soils may be very sensitive to changes in moisture as discontinuous permafrost thaws in interior Alaska.
Corinne A. Hartin, Benjamin Bond-Lamberty, Pralit Patel, and Anupriya Mundra
Biogeosciences, 13, 4329–4342, https://doi.org/10.5194/bg-13-4329-2016, https://doi.org/10.5194/bg-13-4329-2016, 2016
Cary Lynch, Corinne Hartin, Ben Bond-Lamberty, and Ben Kravitz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-170, https://doi.org/10.5194/gmd-2016-170, 2016
Revised manuscript not accepted
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Pattern scaling is used to explore uncertainty in future forcing scenarios and assess local climate sensitivity to global temperature change. This paper examines the two dominant pattern scaling methods using a multi-model ensemble with two future socio-economic storylines. We find that high latitudes show the strongest sensitivity to global temperature change and that the simple least squared regression approach to generation of patterns is a better fit to projected global temperature.
K. M. Dahlin, R. A. Fisher, and P. J. Lawrence
Biogeosciences, 12, 5061–5074, https://doi.org/10.5194/bg-12-5061-2015, https://doi.org/10.5194/bg-12-5061-2015, 2015
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We compared monthly leaf area index (LAI) estimates from the Community Land Model (CLM) in stress/drought deciduous regions of the world to a satellite-derived estimate of LAI. This comparison revealed an issue in the CLM in which leaves begin to grow during the dry season due to unrealistic soil water movement. We introduced a rainfall trigger to the stress deciduous algorithm to address this issue, then showed the impacts of this change on the fire cycle and stored carbon.
W. D. Collins, A. P. Craig, J. E. Truesdale, A. V. Di Vittorio, A. D. Jones, B. Bond-Lamberty, K. V. Calvin, J. A. Edmonds, S. H. Kim, A. M. Thomson, P. Patel, Y. Zhou, J. Mao, X. Shi, P. E. Thornton, L. P. Chini, and G. C. Hurtt
Geosci. Model Dev., 8, 2203–2219, https://doi.org/10.5194/gmd-8-2203-2015, https://doi.org/10.5194/gmd-8-2203-2015, 2015
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The integrated Earth system model (iESM) has been developed as a
new tool for projecting the joint human-climate system. The
iESM is based upon coupling an integrated assessment model (IAM)
and an Earth system model (ESM) into a common modeling
infrastructure. By introducing heretofore-omitted
feedbacks between natural and societal drivers in iESM, we can improve
scientific understanding of the human-Earth system
dynamics.
C. A. Hartin, P. Patel, A. Schwarber, R. P. Link, and B. P. Bond-Lamberty
Geosci. Model Dev., 8, 939–955, https://doi.org/10.5194/gmd-8-939-2015, https://doi.org/10.5194/gmd-8-939-2015, 2015
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Simple climate models play an integral role in policy and scientific communities. Hector v1.0 is an open-source, object-oriented, simple global climate carbon-cycle model. Hector reproduces the global historical trends of atmospheric [CO2], radiative forcing, and surface temperatures. Hector simulates all four representative concentration pathways with equivalent rates of change of key variables over time compared to current observations and other models.
B. Bond-Lamberty, J. P. Fisk, J. A. Holm, V. Bailey, G. Bohrer, and C. M. Gough
Biogeosciences, 12, 513–526, https://doi.org/10.5194/bg-12-513-2015, https://doi.org/10.5194/bg-12-513-2015, 2015
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How will aging forests behave as they undergo ecological transitions? Can our models, which support scientific, policy, and management analyses, accurately simulate these transitions? We tested whether three forest ecosystem models could reproduce dynamics observed in an experimentally manipulated forest in northern Michigan, USA. None of the models fully captured the post-disturbance C fluxes observed, raising doubts about their ability to simulate tree death after moderate disturbances.
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
Related subject area
Biogeosciences and biodiversity
LegacyVegetation: Northern Hemisphere reconstruction of past plant cover and total tree cover from pollen archives of the last 14 kyr
A new habitat map of the Lena Delta in Arctic Siberia based on field and remote sensing datasets
Mapping global leaf inclination angle (LIA) based on field measurement data
A post-processed carbon flux dataset for 34 eddy covariance flux sites across the Heihe River basin, China
Century-long reconstruction of gridded phosphorus surplus across Europe (1850–2019)
High-resolution carbon cycling data from 2019 to 2021 measured at six Austrian long-term ecosystem research sites
Remote sensing of young leaf photosynthetic capacity in tropical and subtropical evergreen broadleaved forests
The JapanFlux2024 dataset for eddy covariance observations covering Japan and East Asia from 1990 to 2023
An organic matter database (OMD): consolidating global residue data from agriculture, fisheries, forestry and related industries
China's annual forest age dataset at 30 m spatial resolution from 1986 to 2022
An expert survey on chamber measurement techniques for methane fluxes
Gas exchange velocities (k600), gas exchange rates (K600), and hydraulic geometries for streams and rivers derived from the NEON Reaeration field and lab collection data product (DP1.20190.001)
Permafrost-wildfire interactions: Active layer thickness estimates for paired burned and unburned sites in northern high-latitudes
Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands
The European Forest Disturbance Atlas: a forest disturbance monitoring system using the Landsat archive
ARGO: ARctic greenhouse Gas Observation metadata version 1
A spectral–structural characterization of European temperate, hemiboreal, and boreal forests
VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring
Crop-specific management history of phosphorus fertilizer input (CMH-P) in the croplands of the United States: reconciliation of top-down and bottom-up data sources
Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation index (NDVI) with MODIS NDVI
The SahulCHAR Collection: A Palaeofire Database for Australia, New Guinea, and New Zealand
Global patterns and drivers of soil dissolved organic carbon concentrations
A synthesized field survey database of vegetation and active-layer properties for the Alaskan tundra (1972–2020)
A vegetation phenology dataset by integrating multiple sources using the Reliability Ensemble Averaging method
TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation
Global nitrous oxide budget (1980–2020)
National forest carbon harvesting and allocation dataset for the period 2003 to 2018
Spatial mapping of key plant functional traits in terrestrial ecosystems across China
WetCH4: A Machine Learning-based Upscaling of Methane Fluxes of Northern Wetlands during 2016–2022
HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022
EUPollMap: the European atlas of contemporary pollen distribution maps derived from an integrated Kriging interpolation approach
Reference maps of soil phosphorus for the pan-Amazon region
Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020
Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022
Investigating limnological processes and modern sedimentation at Lake Żabińskie, northeast Poland: a decade-long multi-variable dataset, 2012–2021
Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020
CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization
Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022
CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada
Quantifying exchangeable base cations in permafrost: a reserve of nutrients about to thaw
Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms
The Portuguese Large Wildfire Spread database (PT-FireSprd)
Thirty-meter map of young forest age in China
GRiMeDB: the Global River Methane Database of concentrations and fluxes
A gridded dataset of a leaf-age-dependent leaf area index seasonality product over tropical and subtropical evergreen broadleaved forests
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
A global database on holdover time of lightning-ignited wildfires
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
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.
Katharina Jentzsch, Lona van Delden, Matthias Fuchs, and Claire C. Treat
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-381, https://doi.org/10.5194/essd-2024-381, 2024
Revised manuscript accepted for ESSD
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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.
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.
Anna 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 Discuss., https://doi.org/10.5194/essd-2024-526, https://doi.org/10.5194/essd-2024-526, 2024
Revised manuscript accepted for ESSD
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Wildfires have the potential to accelerate permafrost thaw and the associated feedbacks to climate change. We assembled a data set 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.
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.
Alba Viana-Soto and Cornelius Senf
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-361, https://doi.org/10.5194/essd-2024-361, 2024
Revised manuscript accepted for ESSD
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Europe's forests are undergoing complex changes in response to increasing disturbances driven by climate and land use changes. We present here the European Forest Disturbance Atlas, a satellite-based approach for mapping annual forest disturbances across continental Europe since 1985. 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.
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 Discuss., https://doi.org/10.5194/essd-2024-456, https://doi.org/10.5194/essd-2024-456, 2024
Revised manuscript accepted for ESSD
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We present ARGO, a meta-dataset of greenhouse gas observations in Arctic and boreal regions including information about sites where greenhouse gases were measured across different measurement techniques. This dataset provides a novel repository for metadata to facilitate synthesis efforts for regions experiencing rapid environmental change. The meta-dataset shows where measurements lack and will be updated as new measurements are made public.
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.
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 Mately, David McWethy, Keely Mills, Patrick Moss, Nicholas R. Patton, Cassandra Rowe, Janelle Stevenson, John Tibby, and Janet Wilmshurst
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-328, https://doi.org/10.5194/essd-2024-328, 2024
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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 on past charcoal compilations that will also provide greater representation of records from this region in future global syntheses to understand past fire.
Tianjing Ren and Andong Cai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-343, https://doi.org/10.5194/essd-2024-343, 2024
Revised manuscript accepted for ESSD
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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 patterns. The findings help guide soil management and climate strategies, with the dataset available for further research.
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.
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
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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.
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.
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, Luke D. Schiferl, Clayton Elder, Olli Peltola, Annett Bartsch, Amanda Armstrong, 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 Discuss., https://doi.org/10.5194/essd-2024-84, https://doi.org/10.5194/essd-2024-84, 2024
Revised manuscript accepted for ESSD
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We present daily methane fluxes of northern wetlands at 10-km resolution during 2016–2022 (WetCH4) derived from a novel machine-learning framework with improved accuracy. We estimated an average annual CH4 emissions of 20.8 ±2.1 Tg CH4 yr-1. Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variations coming from West Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
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.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
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This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
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.
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Short summary
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. The data included help to interpret how carbon cycling processes respond over time to disturbance.
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment...
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