Articles | Volume 13, issue 2
Earth Syst. Sci. Data, 13, 281–298, 2021
https://doi.org/10.5194/essd-13-281-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 13, 281–298, 2021
https://doi.org/10.5194/essd-13-281-2021
© 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 Feb 2021
Data description paper
| 09 Feb 2021
A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States
Chongya Jiang et al.
Related authors
Chongya Jiang, Kaiyu Guan, Ming Pan, Youngryel Ryu, Bin Peng, and Sibo Wang
Hydrol. Earth Syst. Sci., 24, 1251–1273, https://doi.org/10.5194/hess-24-1251-2020, https://doi.org/10.5194/hess-24-1251-2020, 2020
Short summary
Short summary
Quantifying crop water use at each field every day is challenging because of the complexity of the evapotranspiration (ET) process and the unavailability of data at high spatiotemporal resolutions. We fuse multi-satellite data and employ a sophisticated model to estimate ET at 30 m resolution and a daily interval. With validation against 86 site years of ground truth in the US Corn Belt, we are confident that our ET estimation is accurate and a reliable tool for water resource management.
Licheng Liu, Shaoming Xu, Jinyun Tang, Kaiyu Guan, Timothy J. Griffis, Matthew D. Erickson, Alexander L. Frie, Xiaowei Jia, Taegon Kim, Lee T. Miller, Bin Peng, Shaowei Wu, Yufeng Yang, Wang Zhou, Vipin Kumar, and Zhenong Jin
Geosci. Model Dev., 15, 2839–2858, https://doi.org/10.5194/gmd-15-2839-2022, https://doi.org/10.5194/gmd-15-2839-2022, 2022
Short summary
Short summary
By incorporating the domain knowledge into a machine learning model, KGML-ag overcomes the well-known limitations of process-based models due to insufficient representations and constraints, and unlocks the “black box” of machine learning models. Therefore, KGML-ag can outperform existing approaches on capturing the hot moment and complex dynamics of N2O flux. This study will be a critical reference for the new generation of modeling paradigm for biogeochemistry and other geoscience processes.
Sheng Wang, Monica Garcia, Andreas Ibrom, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 24, 3643–3661, https://doi.org/10.5194/hess-24-3643-2020, https://doi.org/10.5194/hess-24-3643-2020, 2020
Short summary
Short summary
Remote sensing only provides snapshots of rapidly changing land surface variables; this limits its application for water resources and ecosystem management. To obtain continuous estimates of surface temperature, soil moisture, evapotranspiration, and ecosystem productivity, a simple and operational modelling scheme is presented. We demonstrate it with temporally sparse optical and thermal remote sensing data from an unmanned aerial system at a Danish bioenergy plantation eddy covariance site.
Chongya Jiang, Kaiyu Guan, Ming Pan, Youngryel Ryu, Bin Peng, and Sibo Wang
Hydrol. Earth Syst. Sci., 24, 1251–1273, https://doi.org/10.5194/hess-24-1251-2020, https://doi.org/10.5194/hess-24-1251-2020, 2020
Short summary
Short summary
Quantifying crop water use at each field every day is challenging because of the complexity of the evapotranspiration (ET) process and the unavailability of data at high spatiotemporal resolutions. We fuse multi-satellite data and employ a sophisticated model to estimate ET at 30 m resolution and a daily interval. With validation against 86 site years of ground truth in the US Corn Belt, we are confident that our ET estimation is accurate and a reliable tool for water resource management.
Related subject area
Biosphere – Biogeosciences
Global GOSAT, OCO-2, and OCO-3 solar-induced chlorophyll fluorescence datasets
The Reading Palaeofire Database: an expanded global resource to document changes in fire regimes from sedimentary charcoal records
VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing
EcoDes-DK15: high-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set
The ABCflux database: Arctic–boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems
Multi-year, spatially extensive, watershed-scale synoptic stream chemistry and water quality conditions for six permafrost-underlain Arctic watersheds
Vertical profiles of leaf photosynthesis and leaf traits and soil nutrients in two tropical rainforests in French Guiana before and after a 3-year nitrogen and phosphorus addition experiment
Global patterns and drivers of soil total phosphorus concentration
The TROPOSIF global sun-induced fluorescence dataset from the Sentinel-5P TROPOMI mission
Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China
BAWLD-CH4: a comprehensive dataset of methane fluxes from boreal and arctic ecosystems
Mapping global forest age from forest inventories, biomass and climate data
European pollen-based REVEALS land-cover reconstructions for the Holocene: methodology, mapping and potentials
Long-term phenological data set of multi-taxonomic groups, agrarian activities, and abiotic parameters from Latvia, northern Europe
A global map of root biomass across the world's forests
Organic matter cycling along geochemical, geomorphic, and disturbance gradients in forest and cropland of the African Tropics – project TropSOC database version 1.0
Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions
The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations
FLUXNET-CH4: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands
A distributed time-lapse camera network to track vegetation phenology with high temporal detail and at varying scales
Global transpiration data from sap flow measurements: the SAPFLUXNET database
MOSAIC (Modern Ocean Sediment Archive and Inventory of Carbon): a (radio)carbon-centric database for seafloor surficial sediments
Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M)
MOSEV: a global burn severity database from MODIS (2000–2020)
SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0
Gap-free global annual soil moisture: 15 km grids for 1991–2018
Carbon emissions and removals from forests: new estimates, 1990–2020
Standardized flux seasonality metrics: a companion dataset for FLUXNET annual product
LUCAS Copernicus 2018: Earth-observation-relevant in situ data on land cover and use throughout the European Union
The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience
Seabed video and still images from the northern Weddell Sea and the western flanks of the Powell Basin
Production and application of manure nitrogen and phosphorus in the United States since 1860
Synchronized high-resolution bed-level change and biophysical data from 10 marsh–mudflat sites in northwestern Europe
Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020)
A satellite-derived database for stand-replacing windthrow events in boreal forests of European Russia in 1986–2017
Drainage of organic soils and GHG emissions: validation with country data
Element and radionuclide concentrations in soils and wildlife from forests in north-eastern England with a focus on species representative of the ICRP's Reference Animals and Plants
Apparent ecosystem carbon turnover time: uncertainties and robust features
A comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany
Decomposability of soil organic matter over time: the Soil Incubation Database (SIDb, version 1.0) and guidance for incubation procedures
The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
A spatially downscaled sun-induced fluorescence global product for enhanced monitoring of vegetation productivity
Spatial and temporal patterns of global soil heterotrophic respiration in terrestrial ecosystems
Observations of late-winter marine microbial activity in an ice-covered fjord, west Greenland
Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale
A spatially explicit database of wind disturbances in European forests over the period 2000–2018
Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019)
The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA)
A taxonomically harmonized and temporally standardized fossil pollen dataset from Siberia covering the last 40 kyr
A review of biomass equations for China's tree species
Russell Doughty, Thomas P. Kurosu, Nicholas Parazoo, Philipp Köhler, Yujie Wang, Ying Sun, and Christian Frankenberg
Earth Syst. Sci. Data, 14, 1513–1529, https://doi.org/10.5194/essd-14-1513-2022, https://doi.org/10.5194/essd-14-1513-2022, 2022
Short summary
Short summary
We describe and compare solar-induced chlorophyll fluorescence data produced by NASA from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 platforms.
Sandy P. Harrison, Roberto Villegas-Diaz, Esmeralda Cruz-Silva, Daniel Gallagher, David Kesner, Paul Lincoln, Yicheng Shen, Luke Sweeney, Daniele Colombaroli, Adam Ali, Chéïma Barhoumi, Yves Bergeron, Tatiana Blyakharchuk, Přemysl Bobek, Richard Bradshaw, Jennifer L. Clear, Sambor Czerwiński, Anne-Laure Daniau, John Dodson, Kevin J. Edwards, Mary E. Edwards, Angelica Feurdean, David Foster, Konrad Gajewski, Mariusz Gałka, Michelle Garneau, Thomas Giesecke, Graciela Gil Romera, Martin P. Girardin, Dana Hoefer, Kangyou Huang, Jun Inoue, Eva Jamrichová, Nauris Jasiunas, Wenying Jiang, Gonzalo Jiménez-Moreno, Monika Karpińska-Kołaczek, Piotr Kołaczek, Niina Kuosmanen, Mariusz Lamentowicz, Martin Lavoie, Fang Li, Jianyong Li, Olga Lisitsyna, José Antonio López-Sáez, Reyes Luelmo-Lautenschlaeger, Gabriel Magnan, Eniko Katalin Magyari, Alekss Maksims, Katarzyna Marcisz, Elena Marinova, Jenn Marlon, Scott Mensing, Joanna Miroslaw-Grabowska, Wyatt Oswald, Sebastián Pérez-Díaz, Ramón Pérez-Obiol, Sanna Piilo, Anneli Poska, Xiaoguang Qin, Cécile C. Remy, Pierre J. H. Richard, Sakari Salonen, Naoko Sasaki, Hieke Schneider, William Shotyk, Migle Stancikaite, Dace Šteinberga, Normunds Stivrins, Hikaru Takahara, Zhihai Tan, Liva Trasune, Charles E. Umbanhowar, Minna Väliranta, Jüri Vassiljev, Xiayun Xiao, Qinghai Xu, Xin Xu, Edyta Zawisza, Yan Zhao, Zheng Zhou, and Jordan Paillard
Earth Syst. Sci. Data, 14, 1109–1124, https://doi.org/10.5194/essd-14-1109-2022, https://doi.org/10.5194/essd-14-1109-2022, 2022
Short summary
Short summary
We provide a new global data set of charcoal preserved in sediments that can be used to examine how fire regimes have changed during past millennia and to investigate what caused these changes. The individual records have been standardised, and new age models have been constructed to allow better comparison across sites. The data set contains 1681 records from 1477 sites worldwide.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
Short summary
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Jakob J. Assmann, Jesper E. Moeslund, Urs A. Treier, and Signe Normand
Earth Syst. Sci. Data, 14, 823–844, https://doi.org/10.5194/essd-14-823-2022, https://doi.org/10.5194/essd-14-823-2022, 2022
Short summary
Short summary
In 2014 and 2015, the Danish government scanned the whole of Denmark using laser scanners on planes. The information can help biologists learn more about Denmark's natural environment. To make it easier to access the outputs from the scan, we divided the country into 10 m x 10 m squares and summed up the information most relevant to biologists for each square. The result is a set of 70 maps describing the three-dimensional architecture of the Danish landscape and vegetation.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
Short summary
Short summary
The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Arial J. Shogren, Jay P. Zarnetske, Benjamin W. Abbott, Samuel Bratsman, Brian Brown, Michael P. Carey, Randy Fulweber, Heather E. Greaves, Emma Haines, Frances Iannucci, Joshua C. Koch, Alexander Medvedeff, Jonathan A. O'Donnell, Leika Patch, Brett A. Poulin, Tanner J. Williamson, and William B. Bowden
Earth Syst. Sci. Data, 14, 95–116, https://doi.org/10.5194/essd-14-95-2022, https://doi.org/10.5194/essd-14-95-2022, 2022
Short summary
Short summary
Rapidly sampling multiple points in an entire river network provides a high-resolution snapshot in time that can reveal where nutrients and carbon are being taken up and released. Here, we describe two such datasets of river network chemistry in six Arctic watersheds in northern Alaska. We describe how these repeated snapshots can be used as an indicator of ecosystem response to climate change and to improve predictions of future release of carbon, nutrient, and other solutes.
Lore T. Verryckt, Sara Vicca, Leandro Van Langenhove, Clément Stahl, Dolores Asensio, Ifigenia Urbina, Romà Ogaya, Joan Llusià, Oriol Grau, Guille Peguero, Albert Gargallo-Garriga, Elodie A. Courtois, Olga Margalef, Miguel Portillo-Estrada, Philippe Ciais, Michael Obersteiner, Lucia Fuchslueger, Laynara F. Lugli, Pere-Roc Fernandez-Garberí, Helena Vallicrosa, Melanie Verlinden, Christian Ranits, Pieter Vermeir, Sabrina Coste, Erik Verbruggen, Laëtitia Bréchet, Jordi Sardans, Jérôme Chave, Josep Peñuelas, and Ivan A. Janssens
Earth Syst. Sci. Data, 14, 5–18, https://doi.org/10.5194/essd-14-5-2022, https://doi.org/10.5194/essd-14-5-2022, 2022
Short summary
Short summary
We provide a comprehensive dataset of vertical profiles of photosynthesis and important leaf traits, including leaf N and P concentrations, from two 3-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N and P, and other leaf nutrients, in photosynthesis in tropical forests.
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Yingping Wang, Julian Helfenstein, Yuanyuan Huang, Kailiang Yu, Zhiqiang Wang, Yongchuan Yang, and Enqing Hou
Earth Syst. Sci. Data, 13, 5831–5846, https://doi.org/10.5194/essd-13-5831-2021, https://doi.org/10.5194/essd-13-5831-2021, 2021
Short summary
Short summary
Our database of globally distributed natural soil total P (STP) concentration showed concentration ranged from 1.4 to 9630.0 (mean 570.0) mg kg−1. Global predictions of STP concentration increased with latitude. Global STP stocks (excluding Antarctica) were estimated to be 26.8 and 62.2 Pg in the topsoil and subsoil, respectively. Our global map of STP concentration can be used to constrain Earth system models representing the P cycle and to inform quantification of global soil P availability.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
Short summary
Short summary
Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Yi-Wei Zhang, Yanpei Guo, Zhiyao Tang, Yuhao Feng, Xinrong Zhu, Wenting Xu, Yongfei Bai, Guoyi Zhou, Zongqiang Xie, and Jingyun Fang
Earth Syst. Sci. Data, 13, 5337–5351, https://doi.org/10.5194/essd-13-5337-2021, https://doi.org/10.5194/essd-13-5337-2021, 2021
Short summary
Short summary
Nitrogen (N) and phosphorus (P) are limiting nutrients for ecosystem productivity. For the first time, we mapped N and P densities of living plants, litter, and soil in forest, shrubland, and grassland ecosystems across China using random forest models based on a dataset of 4868 field sites. Our results depicted the spatial distribution pattern, the total pool, and the allocation among ecosystem components of N and P, which could benefit a more precise prediction of the carbon cycle.
McKenzie A. Kuhn, Ruth K. Varner, David Bastviken, Patrick Crill, Sally MacIntyre, Merritt Turetsky, Katey Walter Anthony, Anthony D. McGuire, and David Olefeldt
Earth Syst. Sci. Data, 13, 5151–5189, https://doi.org/10.5194/essd-13-5151-2021, https://doi.org/10.5194/essd-13-5151-2021, 2021
Short summary
Short summary
Methane (CH4) emissions from the boreal–Arctic region are globally significant, but the current magnitude of annual emissions is not well defined. Here we present a dataset of surface CH4 fluxes from northern wetlands, lakes, and uplands that was built alongside a compatible land cover dataset, sharing the same classifications. We show CH4 fluxes can be split by broad land cover characteristics. The dataset is useful for comparison against new field data and model parameterization or validation.
Simon Besnard, Sujan Koirala, Maurizio Santoro, Ulrich Weber, Jacob Nelson, Jonas Gütter, Bruno Herault, Justin Kassi, Anny N'Guessan, Christopher Neigh, Benjamin Poulter, Tao Zhang, and Nuno Carvalhais
Earth Syst. Sci. Data, 13, 4881–4896, https://doi.org/10.5194/essd-13-4881-2021, https://doi.org/10.5194/essd-13-4881-2021, 2021
Short summary
Short summary
Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. Yet, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. In this paper, we introduced a new global distribution of forest age inferred from forest inventory, remote sensing and climate data in support of a better understanding of the global dynamics in the forest water and carbon cycles.
Esther Githumbi, Ralph Fyfe, Marie-Jose Gaillard, Anna-Kari Trondman, Florence Mazier, Anne-Birgitte Nielsen, Anneli Poska, Shinya Sugita, Martin Theuerkauf, Jessie Woodbridge, Julien Azuara, Angelica Feurdean, Roxana Grindean, Vincent Lebreton, Laurent Marquer, Nathalie Nebout-Combourieu, Migle Stancikaite, Ioan Tanţău, Spassimir Tonkov, Lyudmila Shumilovskikh, and the LandClimII Data Contributors
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-269, https://doi.org/10.5194/essd-2021-269, 2021
Revised manuscript accepted for ESSD
Short summary
Short summary
Reconstruction of past land cover is necessary for the study of past climate – land cover interactions and the evaluation of climate models, land use scenarios. We used available pollen data from across Europe covering the last 11700 years in the REVEALS model to calculate percentage cover and associated standard errors for 31 taxa, 12 plant functional types and 3 land-cover types. REVEALS results are reliant on the quality of the input datasets.
Gunta Kalvāne, Andis Kalvāns, and Andris Ģērmanis
Earth Syst. Sci. Data, 13, 4621–4633, https://doi.org/10.5194/essd-13-4621-2021, https://doi.org/10.5194/essd-13-4621-2021, 2021
Short summary
Short summary
A phenological (seasonal occurrences) data set in Latvia, northern Europe, is presented. It includes phenological phases of eight taxonomic groups such as timing of leaf unfolding, bird migration, and leaf senescence as well as weather phenomena and agrarian activities from 1979 to 2018. The data provide direct and compelling evidence of climate change like earlier spring blossom and delayed autumn phases of some migratory birds and plants in recent years.
Yuanyuan Huang, Phillipe Ciais, Maurizio Santoro, David Makowski, Jerome Chave, Dmitry Schepaschenko, Rose Z. Abramoff, Daniel S. Goll, Hui Yang, Ye Chen, Wei Wei, and Shilong Piao
Earth Syst. Sci. Data, 13, 4263–4274, https://doi.org/10.5194/essd-13-4263-2021, https://doi.org/10.5194/essd-13-4263-2021, 2021
Short summary
Short summary
Roots play a key role in our Earth system. Here we combine 10 307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially explicit global high-resolution (~ 1 km) root biomass dataset. In total, 142 ± 25 (95 % CI) Pg of live dry-matter biomass is stored belowground, representing a global average root : shoot biomass ratio of 0.25 ± 0.10.
Sebastian Doetterl, Rodrigue K. Asifiwe, Geert Baert, Fernando Bamba, Marijn Bauters, Pascal Boeckx, Benjamin Bukombe, Georg Cadisch, Matthew Cooper, Landry N. Cizungu, Alison Hoyt, Clovis Kabaseke, Karsten Kalbitz, Laurent Kidinda, Annina Maier, Moritz Mainka, Julia Mayrock, Daniel Muhindo, Basile B. Mujinya, Serge M. Mukotanyi, Leon Nabahungu, Mario Reichenbach, Boris Rewald, Johan Six, Anna Stegmann, Laura Summerauer, Robin Unseld, Bernard Vanlauwe, Kristof Van Oost, Kris Verheyen, Cordula Vogel, Florian Wilken, and Peter Fiener
Earth Syst. Sci. Data, 13, 4133–4153, https://doi.org/10.5194/essd-13-4133-2021, https://doi.org/10.5194/essd-13-4133-2021, 2021
Short summary
Short summary
The African Tropics are hotspots of modern-day land use change and are of great relevance for the global carbon cycle. Here, we present data collected as part of the DFG-funded project TropSOC along topographic, land use, and geochemical gradients in the eastern Congo Basin and the Albertine Rift. Our database contains spatial and temporal data on soil, vegetation, environmental properties, and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d’Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, and Frédéric Chevallier
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-235, https://doi.org/10.5194/essd-2021-235, 2021
Revised manuscript accepted for ESSD
Short summary
Short summary
In support of the Global Stocktake of the Paris Agreement on Climate change, we proposed a method for reconciling the results of atmospheric inversions with results of UNFCCC national inventory reports. Here, based on a new global harmonized database we compiled from the UNFCCC national reports, and a comprehensive framework presented in this study to process the results of inversions, we compared the results of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O).
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data, 13, 3927–3950, https://doi.org/10.5194/essd-13-3927-2021, https://doi.org/10.5194/essd-13-3927-2021, 2021
Short summary
Short summary
Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
Short summary
Short summary
Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Frans-Jan W. Parmentier, Lennart Nilsen, Hans Tømmervik, and Elisabeth J. Cooper
Earth Syst. Sci. Data, 13, 3593–3606, https://doi.org/10.5194/essd-13-3593-2021, https://doi.org/10.5194/essd-13-3593-2021, 2021
Short summary
Short summary
Satellites provide a global overview of Earth's ecosystems, but they have coarse resolutions and low revisit times. Small-scale vegetation patterns and sudden shifts in plant growth can easily be missed. In this paper, we show how to fill these gaps with vegetation indices obtained with ordinary time-lapse cameras deployed across a valley on Svalbard. We show how to adjust for unwanted camera movement and that vegetation indices from ordinary cameras compare well to those used by satellites.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
Short summary
Short summary
Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Tessa Sophia van der Voort, Thomas Michael Blattmann, Muhammed Usman, Daniel Montluçon, Thomas Loeffler, Maria Luisa Tavagna, Nicolas Gruber, and Timothy Ian Eglinton
Earth Syst. Sci. Data, 13, 2135–2146, https://doi.org/10.5194/essd-13-2135-2021, https://doi.org/10.5194/essd-13-2135-2021, 2021
Short summary
Short summary
Ocean sediments form the largest and longest-term storage of organic carbon. Despite their global importance, information on these sediments is often scattered, incomplete or inaccessible. Here we present MOSAIC (Modern Ocean Sediment Archive and Inventory of Carbon, mosaic.ethz.ch), a (radio)carbon-centric database that addresses this information gap. This database provides a platform for assessing the transport, deposition and storage of carbon in ocean surface sediments.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
Short summary
Short summary
The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Esteban Alonso-González and Víctor Fernández-García
Earth Syst. Sci. Data, 13, 1925–1938, https://doi.org/10.5194/essd-13-1925-2021, https://doi.org/10.5194/essd-13-1925-2021, 2021
Short summary
Short summary
We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area products. The database inludes monthly scenes with the dNBR, RdNBR and post-burn NBR spectral indices at 500 m spatial resolution from November 2000 onwards. Moreover, in this work we show that there is a close relationship between the burn severity metrics included in MOSEV and the same ones obtained from Landsat-8.
William R. Wieder, Derek Pierson, Stevan Earl, Kate Lajtha, Sara G. Baer, Ford Ballantyne, Asmeret Asefaw Berhe, Sharon A. Billings, Laurel M. Brigham, Stephany S. Chacon, Jennifer Fraterrigo, Serita D. Frey, Katerina Georgiou, Marie-Anne de Graaff, A. Stuart Grandy, Melannie D. Hartman, Sarah E. Hobbie, Chris Johnson, Jason Kaye, Emily Kyker-Snowman, Marcy E. Litvak, Michelle C. Mack, Avni Malhotra, Jessica A. M. Moore, Knute Nadelhoffer, Craig Rasmussen, Whendee L. Silver, Benjamin N. Sulman, Xanthe Walker, and Samantha Weintraub
Earth Syst. Sci. Data, 13, 1843–1854, https://doi.org/10.5194/essd-13-1843-2021, https://doi.org/10.5194/essd-13-1843-2021, 2021
Short summary
Short summary
Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Here we present the SOils DAta Harmonization database (SoDaH), a flexible database designed to harmonize diverse SOM datasets from multiple research networks.
Mario Guevara, Michela Taufer, and Rodrigo Vargas
Earth Syst. Sci. Data, 13, 1711–1735, https://doi.org/10.5194/essd-13-1711-2021, https://doi.org/10.5194/essd-13-1711-2021, 2021
Short summary
Short summary
Soil moisture is key for understanding soil–plant–atmosphere interactions. We provide a machine learning approach to increase the spatial resolution of satellite-derived soil moisture information. The outcome is a dataset of gap-free global mean annual soil moisture predictions and associated uncertainty for 28 years (1991–2018) across 15 km grids. This dataset has higher agreement with in situ soil moisture and precipitation measurements. Results show a decline of global annual soil moisture.
Francesco N. Tubiello, Giulia Conchedda, Nathan Wanner, Sandro Federici, Simone Rossi, and Giacomo Grassi
Earth Syst. Sci. Data, 13, 1681–1691, https://doi.org/10.5194/essd-13-1681-2021, https://doi.org/10.5194/essd-13-1681-2021, 2021
Short summary
Short summary
This paper presents the first estimates of forest carbon fluxes (1990–2020) based on the new Global Forest Resources Assessment (FRA) 2020. We document for the first time in the literature forest carbon fluxes for the last decade 2011–2020. Results show that carbon losses from net forest conversion (3.1 billion tonnes of CO2) were counterbalanced by carbon gains on forest land (−3.3 billion tonnes of CO2), resulting in the world's forests acting overall as a small carbon sink in the past decade.
Linqing Yang and Asko Noormets
Earth Syst. Sci. Data, 13, 1461–1475, https://doi.org/10.5194/essd-13-1461-2021, https://doi.org/10.5194/essd-13-1461-2021, 2021
Short summary
Short summary
We present a flux seasonality metrics database (FSMD) depicting a set of standardized metrics of ecosystem biogeochemical fluxes of CO2, water, and energy, including transition dates, phase lengths, and rates of change with uncertainty estimates. FSMD allows assessment of spatial and temporal patterns in developmental dynamics, validation of novel aspects of phenology product, and process models. It is calculated from FLUXNET2015 data product and will be updated with new FLUXNET data releases.
Raphaël d'Andrimont, Astrid Verhegghen, Michele Meroni, Guido Lemoine, Peter Strobl, Beatrice Eiselt, Momchil Yordanov, Laura Martinez-Sanchez, and Marijn van der Velde
Earth Syst. Sci. Data, 13, 1119–1133, https://doi.org/10.5194/essd-13-1119-2021, https://doi.org/10.5194/essd-13-1119-2021, 2021
Short summary
Short summary
The Land Use/Cover Area frame Survey (LUCAS) is a regular in situ land cover and land use ground survey exercise that extends over the whole of the European Union. A new LUCAS module specifically tailored to Earth observation was introduced in 2018: the LUCAS Copernicus module. This paper summarizes the LUCAS Copernicus survey and provides the unique resulting data: 58 426 polygons with level-3 land cover (66 specific classes including crop type) and land use (38 classes).
Jeff W. Atkins, Elizabeth Agee, Alexandra Barry, Kyla M. Dahlin, Kalyn Dorheim, Maxim S. Grigri, Lisa T. Haber, Laura J. Hickey, Aaron G. Kamoske, Kayla Mathes, Catherine McGuigan, Evan Paris, Stephanie C. Pennington, Carly Rodriguez, Autym Shafer, Alexey Shiklomanov, Jason Tallant, Christopher M. Gough, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 943–952, https://doi.org/10.5194/essd-13-943-2021, https://doi.org/10.5194/essd-13-943-2021, 2021
Short summary
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.
Autun Purser, Simon Dreutter, Huw Griffiths, Laura Hehemann, Kerstin Jerosch, Axel Nordhausen, Dieter Piepenburg, Claudio Richter, Henning Schröder, and Boris Dorschel
Earth Syst. Sci. Data, 13, 609–615, https://doi.org/10.5194/essd-13-609-2021, https://doi.org/10.5194/essd-13-609-2021, 2021
Short summary
Short summary
This dataset comprises 26-megapixel seafloor images collected from below ice and steeply sloped regions of the Southern Ocean (the western Weddell Sea; the Powell Basin; and the rapidly shallowing, iceberg-scoured Nachtigaller Shoal). These data were collected with the Ocean Floor Observation and Bathymetry System (OFOBS), an advanced towed camera platform incorporating various sonar devices to aid in hazard avoidance and seafloor mapping, for use in challenging, high-relief seafloor areas.
Zihao Bian, Hanqin Tian, Qichun Yang, Rongting Xu, Shufen Pan, and Bowen Zhang
Earth Syst. Sci. Data, 13, 515–527, https://doi.org/10.5194/essd-13-515-2021, https://doi.org/10.5194/essd-13-515-2021, 2021
Short summary
Short summary
The estimation of manure nutrient production and application is critical for the efficient use of manure nutrients. This study developed four manure nitrogen and phosphorus datasets with high spatial resolution and a long time period (1860–2017) in the US. The datasets can provide useful information for stakeholders and scientists who focus on agriculture, nutrient budget, and biogeochemical cycle.
Zhan Hu, Pim W. J. M. Willemsen, Bas W. Borsje, Chen Wang, Heng Wang, Daphne van der Wal, Zhenchang Zhu, Bas Oteman, Vincent Vuik, Ben Evans, Iris Möller, Jean-Philippe Belliard, Alexander Van Braeckel, Stijn Temmerman, and Tjeerd J. Bouma
Earth Syst. Sci. Data, 13, 405–416, https://doi.org/10.5194/essd-13-405-2021, https://doi.org/10.5194/essd-13-405-2021, 2021
Short summary
Short summary
Erosion and accretion processes govern the ecogeomorphic evolution of intertidal (salt marsh and tidal flat) ecosystems and hence substantially affect their valuable ecosystem services. By applying a novel sensor, we obtained unique high-resolution daily bed-level change datasets from 10 marsh–mudflat sites in northwestern Europe. This dataset has revealed diverse spatial bed-level change patterns over daily to seasonal scales, which are valuable to theoretical and model development.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
Short summary
Short summary
On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Andrey N. Shikhov, Alexander V. Chernokulsky, Igor O. Azhigov, and Anastasia V. Semakina
Earth Syst. Sci. Data, 12, 3489–3513, https://doi.org/10.5194/essd-12-3489-2020, https://doi.org/10.5194/essd-12-3489-2020, 2020
Short summary
Short summary
Severe winds are among the main causes of forest disturbances in Russia. However, compared to other European countries, windthrows in Russian forests remain substantially understudied. In this study, we compiled a new spatial database of stand-replacing (total) windthrows in the forest zone of European Russia for 1986–2017. Windthrows were delineated mainly with Landsat images. The total area of windthrows was estimated to be 2966 km2 (0.19 % of the total forest-covered area).
Giulia Conchedda and Francesco N. Tubiello
Earth Syst. Sci. Data, 12, 3113–3137, https://doi.org/10.5194/essd-12-3113-2020, https://doi.org/10.5194/essd-12-3113-2020, 2020
Short summary
Short summary
This paper describes the FAO methodology used to globally assess areas of drained organic soils and peatlands due to agriculture over the period 1990–2019. We overlay geospatial information of soil type, land cover, agro-climatic zones, livestock distribution and IPCC coefficients, then aggregate it at national level for over 200 countries and territories. Results are compared to inventory data reported to UNFCCC, showing good agreement between the FAO estimates and country data.
Catherine L. Barnett, Nicholas A. Beresford, Michael D. Wood, Maria Izquierdo, Lee A. Walker, and Ross Fawkes
Earth Syst. Sci. Data, 12, 3021–3038, https://doi.org/10.5194/essd-12-3021-2020, https://doi.org/10.5194/essd-12-3021-2020, 2020
Short summary
Short summary
This paper describes data from a study conducted in 2015–2016 to sample terrestrial wildlife, soil and water from two forests in north-eastern England. Sampling was targeted towards species representative of the International Commission on Radiological Protection’s (ICRP) terrestrial Reference Animals and Plants (RAPs): Wild Grass, Pine Tree, Earthworm, Bee, Rat, Deer and Frog. The dataset comprises stable-element and radionuclide activity concentrations.
Naixin Fan, Sujan Koirala, Markus Reichstein, Martin Thurner, Valerio Avitabile, Maurizio Santoro, Bernhard Ahrens, Ulrich Weber, and Nuno Carvalhais
Earth Syst. Sci. Data, 12, 2517–2536, https://doi.org/10.5194/essd-12-2517-2020, https://doi.org/10.5194/essd-12-2517-2020, 2020
Short summary
Short summary
The turnover time of terrestrial carbon (τ) controls the global carbon cycle–climate feedback. In this study, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback.
Tim G. Reichenau, Wolfgang Korres, Marius Schmidt, Alexander Graf, Gerhard Welp, Nele Meyer, Anja Stadler, Cosimo Brogi, and Karl Schneider
Earth Syst. Sci. Data, 12, 2333–2364, https://doi.org/10.5194/essd-12-2333-2020, https://doi.org/10.5194/essd-12-2333-2020, 2020
Christina Schädel, Jeffrey Beem-Miller, Mina Aziz Rad, Susan E. Crow, Caitlin E. Hicks Pries, Jessica Ernakovich, Alison M. Hoyt, Alain Plante, Shane Stoner, Claire C. Treat, and Carlos A. Sierra
Earth Syst. Sci. Data, 12, 1511–1524, https://doi.org/10.5194/essd-12-1511-2020, https://doi.org/10.5194/essd-12-1511-2020, 2020
Short summary
Short summary
Carbon loss to the atmosphere via microbial decomposition is often assessed by laboratory soil incubation studies that measure greenhouse gases released from soils under controlled conditions. Here, we introduce the Soil Incubation Database (SIDb) version 1.0, a compilation of time series data from incubations, structured into a new, publicly available, open-access database of carbon dioxide and methane flux. We also provide guidance for database entry and the required variables.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
Short summary
Short summary
Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Gregory Duveiller, Federico Filipponi, Sophia Walther, Philipp Köhler, Christian Frankenberg, Luis Guanter, and Alessandro Cescatti
Earth Syst. Sci. Data, 12, 1101–1116, https://doi.org/10.5194/essd-12-1101-2020, https://doi.org/10.5194/essd-12-1101-2020, 2020
Short summary
Short summary
Sun-induced chlorophyll fluorescence is a valuable indicator of vegetation productivity, but our capacity to measure it from space using satellite remote techniques has been hampered by a lack of spatial detail. Based on prior knowledge of how ecosystems should respond to growing conditions in some modelling along with ancillary satellite observations, we provide here a new enhanced dataset with higher spatial resolution that better represents the spatial patterns of vegetation growth over land.
Xiaolu Tang, Shaohui Fan, Manyi Du, Wenjie Zhang, Sicong Gao, Shibin Liu, Guo Chen, Zhen Yu, and Wunian Yang
Earth Syst. Sci. Data, 12, 1037–1051, https://doi.org/10.5194/essd-12-1037-2020, https://doi.org/10.5194/essd-12-1037-2020, 2020
Short summary
Short summary
Global soil heterotrophic respiration (RH) was modelled using Random Forest by linking published observations and globally gridded environmental variables. Globally, RH increased from 55.8 to 58.3 Pg C a−1 with an increasing trend of 0.036 ± 0.007 Pg C a−2 and an annual mean RH of 57.2 ± 0.6 Pg C a−1 over 1980–2016. The developed RH dataset has great potential to serve as a benchmark to constrain global vegetation models.
David Chandler and Shona Mackie
Earth Syst. Sci. Data, 12, 897–906, https://doi.org/10.5194/essd-12-897-2020, https://doi.org/10.5194/essd-12-897-2020, 2020
Short summary
Short summary
The activity of microorganisms at the bottom of the marine food chain has rarely been measured under sea ice in winter. We present the first observations of Arctic winter microbial activity under sea ice in a west Greenland fjord. By measuring changes in the oxygen concentration of seawater under the ice, we found low but significant levels of activity, suggesting these microbial communities may constitute an important part of the winter marine ecosystem.
Wei Li, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, Jonathan Doelman, Florian Humpenöder, Anna B. Harper, Taejin Park, David Makowski, Petr Havlik, Michael Obersteiner, Jingmeng Wang, Andreas Krause, and Wenfeng Liu
Earth Syst. Sci. Data, 12, 789–804, https://doi.org/10.5194/essd-12-789-2020, https://doi.org/10.5194/essd-12-789-2020, 2020
Short summary
Short summary
We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.
Giovanni Forzieri, Matteo Pecchi, Marco Girardello, Achille Mauri, Marcus Klaus, Christo Nikolov, Marius Rüetschi, Barry Gardiner, Julián Tomaštík, David Small, Constantin Nistor, Donatas Jonikavicius, Jonathan Spinoni, Luc Feyen, Francesca Giannetti, Rinaldo Comino, Alessandro Wolynski, Francesco Pirotti, Fabio Maistrelli, Ionut Savulescu, Stéphanie Wurpillot-Lucas, Stefan Karlsson, Karolina Zieba-Kulawik, Paulina Strejczek-Jazwinska, Martin Mokroš, Stefan Franz, Lukas Krejci, Ionel Haidu, Mats Nilsson, Piotr Wezyk, Filippo Catani, Yi-Ying Chen, Sebastiaan Luyssaert, Gherardo Chirici, Alessandro Cescatti, and Pieter S. A. Beck
Earth Syst. Sci. Data, 12, 257–276, https://doi.org/10.5194/essd-12-257-2020, https://doi.org/10.5194/essd-12-257-2020, 2020
Short summary
Short summary
Strong winds may uproot and break trees and represent a risk for forests. Despite the importance of this natural disturbance and possible intensification in view of climate change, spatial information about wind-related impacts is currently missing on a pan-European scale. We present a new database of wind disturbances in European forests comprised of more than 80 000 records over the period 2000–2018. Our database is a unique spatial source for the study of forest disturbances at large scales.
Niels H. Batjes, Eloi Ribeiro, and Ad van Oostrum
Earth Syst. Sci. Data, 12, 299–320, https://doi.org/10.5194/essd-12-299-2020, https://doi.org/10.5194/essd-12-299-2020, 2020
Short summary
Short summary
This dataset provides quality-assessed and standardised soil data to support digital soil mapping and environmental applications at broadscale levels. The underpinning soil profiles were shared by a wide range of data providers. Special attention was paid to the standardisation of soil property definitions, analytical method descriptions and property values. We present measures for geographic accuracy and a first approximation for the uncertainty associated with the various analytical methods.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
Short summary
Short summary
Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Xianyong Cao, Fang Tian, Andrei Andreev, Patricia M. Anderson, Anatoly V. Lozhkin, Elena Bezrukova, Jian Ni, Natalia Rudaya, Astrid Stobbe, Mareike Wieczorek, and Ulrike Herzschuh
Earth Syst. Sci. Data, 12, 119–135, https://doi.org/10.5194/essd-12-119-2020, https://doi.org/10.5194/essd-12-119-2020, 2020
Short summary
Short summary
Pollen percentages in spectra cannot be utilized to indicate past plant abundance directly because of the different pollen productivities among plants. In this paper, we applied relative pollen productivity estimates (PPEs) to calibrate plant abundances during the last 40 kyr using pollen counts from 203 pollen spectra in northern Asia. Results indicate the vegetation are generally stable during the Holocene and that climate change is the primary factor.
Yunjian Luo, Xiaoke Wang, Zhiyun Ouyang, Fei Lu, Liguo Feng, and Jun Tao
Earth Syst. Sci. Data, 12, 21–40, https://doi.org/10.5194/essd-12-21-2020, https://doi.org/10.5194/essd-12-21-2020, 2020
Short summary
Short summary
How to accurately estimate tree and forest biomass a concern worldwide. Biomass equations are the most commonly used method. China is one of the most important ecoregions of the world. Here, we develop a tree biomass equation dataset for China via literature retrieval. This dataset consists of 5924 equations for nearly 200 tree species, showing sound geographical, climatic and forest coverage across China. Furthermore, multiple potential avenues for future research are identified.
Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop
evapotranspiration-Guidelines for computing crop water requirements-FAO
Irrigation and drainage paper 56, Italy: Rome, available at:
http://www.fao.org/3/x0490E/x0490e00.htm (last access: 20 January 2021), 1998.
Augustine, J. A., DeLuisi, J. J., and Long, C. N.: SURFRAD – A national
surface radiation budget network for atmospheric research, B. Am.
Meteorol. Soc., 81, 2341–2357, https://doi.org/10.1175/1520-0477(2000)081<2341:SANSRB>2.3.CO;2, 2000.
Bacour, C., Maignan, F., Peylin, P., MacBean, N., Bastrikov, V., Joiner, J.,
Köhler, P., Guanter, L., and Frankenberg, C.: Differences Between OCO-2
and GOME-2 SIF Products From a Model-Data Fusion Perspective, J. Geophys.
Res.-Biogeosci., 124, 3143–3157, https://doi.org/10.1029/2018JG004938, 2019.
Badgley, G., Field, C. B., and Berry, J. A.: Canopy near-infrared reflectance
and terrestrial photosynthesis, Sci. Adv., 3, 1–6,
https://doi.org/10.1126/sciadv.1602244, 2017.
Badgley, G., Anderegg, L. D., Berry, J. A., and Field, C. B.: Terrestrial
Gross Primary Production: Using NIR V to Scale from Site to Globe, Glob.
Chang. Biol., 25, 3731–3740,, https://doi.org/10.1111/gcb.14729, 2019.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein,
A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel,
W., Paw, U. K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S.,
Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: a new tool to study the
temporal and spatial variability of ecosystem-scale carbon dioxide, water
vapor, and energy flux densities, B. Am. Meteorol. Soc., 82,
2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001.
Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E.,
Ackerman, S. A., Heidinger, A. K., and Yang, P.: MODIS cloud-top property
refinements for collection 6, J. Appl. Meteorol. Climatol., 51,
1145–1163, https://doi.org/10.1175/JAMC-D-11-0203.1, 2012.
Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais,
N., Rödenbeck, C., Arain, M. A., Baldocchi, D., and Bonan, G. B.:
Terrestrial gross carbon dioxide uptake: global distribution and covariation
with climate, Science, 329, 834–838, 2010.
Bonan, G.: Climate Change and Terrestrial Ecosystem Modeling, Cambridge
University Press, Cambridge, UK, 354 pp., ISBN 978-1-107-04378-7, 2019.
Borbas, E. E., Seemann, S. W., Kern, A., Moy, L., Li, J., Gumley, L., and
Menzel, W. P.: MODIS atmospheric profile retrieval algorithm theoretical
basis document, Citeseer, available at:
http://modis-atmos.gsfc.nasa.gov/MOD07_L2/atbd.html (last access: January 2021), 2015.
Boryan, C., Yang, Z., Mueller, R., and Craig, M.: Monitoring US agriculture:
The US department of agriculture, national agricultural statistics service,
cropland data layer program, Geocarto Int., 26, 341–358,
https://doi.org/10.1080/10106049.2011.562309, 2011.
Cai, S., Liu, D., Sulla-Menashe, D., and Friedl, M. A.: Enhancing MODIS land
cover product with a spatial-temporal modeling algorithm, Remote Sens.
Environ., 147, 243–255, https://doi.org/10.1016/j.rse.2014.03.012, 2014.
Chabot, B. F. and Hicks, D. J.: The ecology of leaf life spans, Annu. Rev.
Ecol. Syst., 13, 229–259,
https://doi.org/10.1146/annurev.es.13.110182.001305, 1982.
Chang, L., Gao, G., Jin, S., He, X., Xiao, R., and Guo, L.: Calibration and
evaluation of precipitable water vapor from Modis infrared observations at
night, IEEE Trans. Geosci. Remote Sens., 53, 2612–2620,
https://doi.org/10.1109/TGRS.2014.2363089, 2015.
Dechant, B., Ryu, Y., Badgley, G., Zeng, Y., Berry, J. A., Goulas, Y., Li,
Z., Zhang, Q., Kang, M., Li, J., and Moya, I.: Canopy structure explains the
relationship between photosynthesis and sun-induced chlorophyll fluorescence
in crops, EarthArXiv Prepr., https://doi.org/10.31223/OSF.IO/CBXPQ, 2019.
Dechant, B., Ryu, Y., Badgley, G., Zeng, Y., Berry, J. A., Zhang, Y.,
Goulas, Y., Li, Z., Zhang, Q., Kang, M., Li, J., and Moya, I.: Canopy
structure explains the relationship between photosynthesis and sun-induced
chlorophyll fluorescence in crops, Remote Sens. Environ., 241, 111733,
https://doi.org/10.1016/j.rse.2020.111733, 2020.
Franch, B., Vermote, E. F., Roger, J. C., Murphy, E., Becker-reshef, I.,
Justice, C., Claverie, M., Nagol, J., Csiszar, I., Meyer, D., Baret, F.,
Masuoka, E., Wolfe, R., and Devadiga, S.: A 30+ year AVHRR land surface
re?ectance climate data record and its application to wheat yield
monitoring, Remote Sens., 9, 1–14, https://doi.org/10.3390/rs9030296, 2017.
Friedman, J. H.: Multivariate Adaptive Regression Splines, Ann. Stat.,
19, 1–67, https://doi.org/10.1214/aos/1176347963, 1991.
Gamon, J. A., Huemmrich, K. F., Wong, C. Y. S., Ensminger, I., Garrity, S.,
Hollinger, D. Y., Noormets, A., and Peñuelas, J.: A remotely sensed
pigment index reveals photosynthetic phenology in evergreen conifers, P.
Natl. Acad. Sci., 113, 201606162, https://doi.org/10.1073/pnas.1606162113, 2016.
GCOS: Systematic observation requirements for satellite-based data products
for climate, Supplemental details to the satellite-based component of the
“Implementation Plan for the Global Observing System for Climate in Support
of the UNFCCC,” Reference Number GCOS-154, available at:
http://www.wmo.int/pages/prog/gcos/Publications/gcos-154.pdf (last access: 20 January 2021), 2011.
Goldberger, J., Hinton, G. E., Roweis, S. T., and Salakhutdinov, R. R.: Neighbourhood components analysis, in Advances in neural information processing systems, 513–520, available at: http://www.cs.utoronto.ca/~rsalakhu/papers/ncanips.pdf (last access: 20 January 2021), 2005.
Green, T. R., Kipka, H., David, O., and McMaster, G. S.: Where is the USA
Corn Belt, and how is it changing?, Sci. Total Environ., 618, 1613–1618,
https://doi.org/10.1016/j.scitotenv.2017.09.325, 2018.
Guan, K., Berry, J. A., Zhang, Y., Joiner, J., Guanter, L., Badgley, G., and
Lobell, D. B.: Improving the monitoring of crop productivity using
spaceborne solar-induced fluorescence, Glob. Chang. Biol., 22, 716–726,
https://doi.org/10.1111/gcb.13136, 2016.
Guanter, L., Zhang, Y., Jung, M., Joiner, J., Voigt, M., Berry, J. a,
Frankenberg, C., Huete, A. R., Zarco-Tejada, P., Lee, J.-E., Moran, M. S.,
Ponce-Campos, G., Beer, C., Camps-Valls, G., Buchmann, N., Gianelle, D.,
Klumpp, K., Cescatti, A., Baker, J. M., and Griffis, T. J.: Global and
time-resolved monitoring of crop photosynthesis with chlorophyll
fluorescence, P. Natl. Acad. Sci. USA, 111, E1327-33,
https://doi.org/10.1073/pnas.1320008111, 2014.
Homer, C., Huang, C., Yang, L., Wylie, B., and Coan, M.: Development of a
2001 National Land-Cover Database for the United States, Photogramm. Eng.
Remote Sens., 70, 829–840, https://doi.org/10.14358/PERS.70.7.829, 2004.
Houborg, R. and McCabe, M. F.: High-Resolution NDVI from planet's
constellation of earth observing nano-satellites: A new data source for
precision agriculture, Remote Sens., 8, 768, https://doi.org/10.3390/rs8090768, 2016.
Jiang, C. and Fang, H.: GSV: a general model for hyperspectral soil
reflectance simulation, Int. J. Appl. Earth Obs. Geoinf., 83, 101932,
https://doi.org/10.1016/j.jag.2019.101932, 2019.
Jiang, C. and Guan, K.: SLOPE Daily 250 m CONUS Gross Primary Productivity
(2000–2019), ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1786, 2020.
Jiang, C. and Ryu, Y.: Multi-scale evaluation of global gross primary
productivity and evapotranspiration products derived from Breathing Earth
System Simulator (BESS), Remote Sens. Environ., 186, 528–547,
https://doi.org/10.1016/j.rse.2016.08.030, 2016.
Jiang, C., Guan, K., Pan, M., Ryu, Y., Peng, B., and Wang, S.: BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt, Hydrol. Earth Syst. Sci., 24, 1251–1273, https://doi.org/10.5194/hess-24-1251-2020, 2020.
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S.,
Ahlström, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein,
P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B.,
Raduly, B., Rödenbeck, C., Tramontana, G., Viovy, N., Wang, Y. P.,
Weber, U., Zaehle, S., and Zeng, N.: Compensatory water effects link yearly
global land CO2 sink changes to temperature, Nature, 541, 516–520,
https://doi.org/10.1038/nature20780, 2017.
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Gustau-Camps-Valls,
Papale, D., Schwalm, C., Tramontana, G., and Reichstein, M.: The FLUXCOM
ensemble of global land-atmosphere energy fluxes, Sci. Data, 1–14,
https://doi.org/10.1038/s41597-019-0076-8, 2019.
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Fokke Meirink, J., Devasthale, A., Hanschmann, T., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Schlundt, C., Stein, D., Finkensieper, S., Håkansson, N., and Hollmann, R.: CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data, Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, 2017.
Kimm, H., Guan, K., Jiang, C., Peng, B., Gentry, L. F., Wilkin, S. C., Wang,
S., Cai, Y., Bernacchi, C. J., Peng, J., and Luo, Y.: Deriving
high-spatiotemporal-resolution leaf area index for agroecosystems in the
U.S. Corn Belt using Planet Labs CubeSat and STAIR fusion data, Remote Sens.
Environ., 239, 111615, https://doi.org/10.1016/j.rse.2019.111615, 2020.
Kobrick, M. and Crippen, R.: SRTMGL1: NASA Shuttle Radar Topography Mission
Global 1 arc second V003, NASA EOSDIS L. Process. DAAC, https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL1.003, 2017.
Lark, T. J., Mueller, R. M., Johnson, D. M., and Gibbs, H. K.: Measuring
land-use and land-cover change using the U.S. department of agriculture's
cropland data layer: Cautions and recommendations, Int. J. Appl. Earth Obs.
Geoinf., 62, 224–235, https://doi.org/10.1016/j.jag.2017.06.007, 2017.
Li, W., MacBean, N., Ciais, P., Defourny, P., Lamarche, C., Bontemps, S., Houghton, R. A., and Peng, S.: Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015), Earth Syst. Sci. Data, 10, 219–234, https://doi.org/10.5194/essd-10-219-2018, 2018.
Liaw, A. and Wiener, M.: Classification and regression by randomForest, R
News, 2, 18–22, 2002.
Liu, L., Guan, L., and Liu, X.: Directly estimating diurnal changes in GPP
for C3 and C4 crops using far-red sun-induced chlorophyll fluorescence,
Agr. Forest Meteorol., 232, 1–9, https://doi.org/10.1016/j.agrformet.2016.06.014, 2017.
Luo, Y., Guan, K., and Peng, J.: STAIR: A generic and fully-automated method
to fuse multiple sources of optical satellite data to generate a
high-resolution, daily and cloud-/gap-free surface reflectance product,
Remote Sens. Environ., 214, 87–99, https://doi.org/10.1016/j.rse.2018.04.042,
2018.
Lyapustin, A., Wang, Y., Laszlo, I., Kahn, R., Korkin, S., Remer, L., Levy,
R., and Reid, J. S.: Multiangle implementation of atmospheric correction
(MAIAC): 2. Aerosol algorithm, J. Geophys. Res.-Atmos., 116, D03211,
https://doi.org/10.1029/2010JD014986, 2011.
Magney, T. S., Bowling, D. R., Logan, B., Grossmann, K., Stutz, J., and
Blanken, P.: Mechanistic evidence for tracking the seasonality of
photosynthesis with solar-induced fluorescence, P. Natl. Acad. Sci., 116, 11640–11645, https://doi.org/10.1073/pnas.1900278116, 2019.
Monteith, J. L.: Solar Radiation and Productivity in Tropical Ecosystems, J.
Appl. Ecol., 9, 747, https://doi.org/10.2307/2401901, 1972.
Monteith, J. L. and Moss, C. J.: Climate and the Efficiency of Crop
Production in Britain, Philos. T. Roy. Soc. B Biol. Sci., 281,
277–294, https://doi.org/10.1098/rstb.1977.0140, 1977.
Remer, L. A., Mattoo, S., Levy, R. C., and Munchak, L. A.: MODIS 3 km aerosol product: algorithm and global perspective, Atmos. Meas. Tech., 6, 1829–1844, https://doi.org/10.5194/amt-6-1829-2013, 2013.
Román, M. O., Schaaf, C. B., Woodcock, C. E., Strahler, A. H., Yang, X.,
Braswell, R. H., Curtis, P. S., Davis, K. J., Dragoni, D., Goulden, M. L.,
Gu, L., Hollinger, D. Y., Kolb, T. E., Meyers, T. P., Munger, J. W.,
Privette, J. L., Richardson, A. D., Wilson, T. B., and Wofsy, S. C.: The
MODIS (Collection V005) BRDF/albedo product: Assessment of spatial
representativeness over forested landscapes, Remote Sens. Environ., 113,
2476–2498, https://doi.org/10.1016/j.rse.2009.07.009, 2009.
Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., and
Hashimoto, H.: A continuous satellite-derived measure of global terrestrial
primary production, Bioscience, 54, 547,
https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2, 2004.
Ryu, Y., Berry, J. A., and Baldocchi, D. D.: What is global photosynthesis?
History, uncertainties and opportunities, Remote Sens. Environ.,
223, 95–114, https://doi.org/10.1016/j.rse.2019.01.016,
2019.
Smith, W. K., Biederman, J. A., Scott, R. L., Moore, D. J. P., He, M.,
Kimball, J. S., Yan, D., Hudson, A., Barnes, M. L., MacBean, N., Fox, A. M.,
and Litvak, M. E.: Chlorophyll Fluorescence Better Captures Seasonal and
Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of
Southwestern North America, Geophys. Res. Lett., 45, 748–757,
https://doi.org/10.1002/2017GL075922, 2018.
Tibshirani, R.: Regression Shrinkage and Selection Via the Lasso, J. R.
Stat. Soc. Ser. B, 58, 267–288, https://doi.org/10.1111/j.2517-6161.1996.tb02080.x,
1996.
Turner, A. J., Köhler, P., Magney, T. S., Frankenberg, C., Fung, I., and Cohen, R. C.: A double peak in the seasonality of California's photosynthesis as observed from space, Biogeosciences, 17, 405–422, https://doi.org/10.5194/bg-17-405-2020, 2020.
Vermote, E. F., El Saleous, N. Z., and Justice, C. O.: Atmospheric correction
of MODIS data in the visible to middle infrared: First results, Remote Sens.
Environ., 83, 97–111, https://doi.org/10.1016/S0034-4257(02)00089-5, 2002.
Wu, G., Guan, K., Jiang, C., Peng, B., Kimm, H., Chen, M., Yang, X., Wang,
S., Sukyer, A. E., Bernacchi, C., Moore, C. E., Zeng, Y., Berry, J., and
Cendrero-Mateo, M. P.: Radiance-based NIRv as a proxy for GPP of corn
and soybean, Environ. Res. Lett., 15, 034009, https://doi.org/10.1088/1748-9326/ab65cc, 2019.
Wu, G., Guan, K., Jiang, C., Peng, B., Kimm, H., Chen, M., Yang, X., Wang,
S., Suyker, A. E., Bernacchi, C., Moore, C. E., Zeng, Y., Berry, J., and
Cendrero-Mateo, M. P.: Radiance-based NIRv as a proxy for GPP of corn and
soybean, Environ. Res. Lett., 15, 034009, https://doi.org/10.1088/1748-9326/ab65cc,
2020.
Xiao, J., Chevallier, F., Gomez, C., Guanter, L., Hicke, J. A., Huete, A.
R., Ichii, K., Ni, W., Pang, Y., Rahman, A. F., Sun, G., Yuan, W., Zhang, L.,
and Zhang, X.: Remote sensing of the terrestrial carbon cycle: A review of
advances over 50 years, Remote Sens. Environ., 233, 111383,
https://doi.org/10.1016/j.rse.2019.111383, 2019.
Yan, L. and Roy, D. P.: Conterminous United States crop field size
quantification from multi-temporal Landsat data, Remote Sens. Environ., 172,
67–86, https://doi.org/10.1016/j.rse.2015.10.034, 2016.
Yang, X., Tang, J., Mustard, J. F., Lee, J., Rossini, M., Joiner, J.,
Munger, J. W., Kornfeld, A., and Richardson, A. D.: Solar-induced chlorophyll
fluorescence that correlates with canopy photosynthesis on diurnal and
seasonal scales in a temperate deciduous forest, Geophys. Res. Lett., 42,
2977–2987, https://doi.org/10.1002/2015GL063201, 2015.
Yang, Y., Xiao, P., Feng, X., and Li, H.: Accuracy assessment of seven global
land cover datasets over China, ISPRS J. Photogramm. Remote Sens., 125,
156–173, https://doi.org/10.1016/j.isprsjprs.2017.01.016, 2017.
Yuan, W., Liu, S., Yu, G., Bonnefond, J.-M. M., Chen, J., Davis, K., Desai,
A. R., Goldstein, A. H., Gianelle, D., Rossi, F., Suyker, A. E., and Verma,
S. B.: Global estimates of evapotranspiration and gross primary production
based on MODIS and global meteorology data, Remote Sens. Environ., 114,
1416–1431, https://doi.org/10.1016/j.rse.2010.01.022, 2010.
Zeng, Y., Badgley, G., Dechant, B., Ryu, Y., Chen, M., and Berry, J. A.: A
practical approach for estimating the escape ratio of near-infrared
solar-induced chlorophyll fluorescence, Remote Sens. Environ., 232, 111209, https://doi.org/10.1016/j.rse.2019.05.028, 2019.
Zhang, Y., Xiao, X., Wu, X., Zhou, S., Zhang, G., Qin, Y., and Dong, J.: A
global moderate resolution dataset of gross primary production of vegetation
for 2000–2016, Sci. Data, 4, 170165, https://doi.org/10.1038/sdata.2017.165, 2017.
Zhang, Y., Joiner, J., Gentine, P., and Zhou, S.: Reduced solar-induced
chlorophyll fluorescence from GOME-2 during Amazon drought caused by dataset
artifacts, Glob. Chang. Biol., 24, 2229–2230, https://doi.org/10.1111/gcb.14134,
2018.
Short summary
Photosynthesis, quantified by gross primary production (GPP), is a key Earth system process. To date, there is a lack of a high-spatiotemporal-resolution, real-time and observation-based GPP dataset. This work addresses this gap by developing a SatelLite Only Photosynthesis Estimation (SLOPE) model and generating a new GPP product, which is advanced in spatial and temporal resolutions, instantaneity, and quantitative uncertainty. The dataset will benefit a range of research and applications.
Photosynthesis, quantified by gross primary production (GPP), is a key Earth system process. To...
