Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2333-2020
© Author(s) 2020. 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-12-2333-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
01 Oct 2020
Data description paper |
| 01 Oct 2020
| 01 Oct 2020
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
Tim G. Reichenau
CORRESPONDING AUTHOR
Institute of Geography, University of Cologne, Cologne, Germany
Wolfgang Korres
Institute of Geography, University of Cologne, Cologne, Germany
Marius Schmidt
Institute of Bio- and Geosciences 3: Agrosphere (IBG-3),
Jülich Research Centre, Jülich, Germany
Alexander Graf
Institute of Bio- and Geosciences 3: Agrosphere (IBG-3),
Jülich Research Centre, Jülich, Germany
Gerhard Welp
Institute of Crop Science and Resource Conservation
(INRES), Soil Science and Soil Ecology, University of Bonn, Bonn, Germany
Nele Meyer
Institute of Crop Science and Resource Conservation
(INRES), Soil Science and Soil Ecology, University of Bonn, Bonn, Germany
Department of Forest Sciences, University of Helsinki, Helsinki,
Finland
Anja Stadler
Institute of Crop Science and Resource Conservation (INRES), Crop
Science, University of Bonn, Bonn, Germany
Cosimo Brogi
Institute of Bio- and Geosciences 3: Agrosphere (IBG-3),
Jülich Research Centre, Jülich, Germany
Karl Schneider
Institute of Geography, University of Cologne, Cologne, Germany
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Anne Klosterhalfen, Alexander Graf, Nicolas Brüggemann, Clemens Drüe, Odilia Esser, María P. González-Dugo, Günther Heinemann, Cor M. J. Jacobs, Matthias Mauder, Arnold F. Moene, Patrizia Ney, Thomas Pütz, Corinna Rebmann, Mario Ramos Rodríguez, Todd M. Scanlon, Marius Schmidt, Rainer Steinbrecher, Christoph K. Thomas, Veronika Valler, Matthias J. Zeeman, and Harry Vereecken
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Biogeosciences, 15, 187–208, https://doi.org/10.5194/bg-15-187-2018, https://doi.org/10.5194/bg-15-187-2018, 2018
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Wei Qu, Heye R. Bogena, Johan A. Huisman, Marius Schmidt, Ralf Kunkel, Ansgar Weuthen, Henning Schiedung, Bernd Schilling, Jürgen Sorg, and Harry Vereecken
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S. Gebler, H.-J. Hendricks Franssen, T. Pütz, H. Post, M. Schmidt, and H. Vereecken
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H. Post, H. J. Hendricks Franssen, A. Graf, M. Schmidt, and H. Vereecken
Biogeosciences, 12, 1205–1221, https://doi.org/10.5194/bg-12-1205-2015, https://doi.org/10.5194/bg-12-1205-2015, 2015
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P. D. Wagner, S. Kumar, and K. Schneider
Hydrol. Earth Syst. Sci., 17, 2233–2246, https://doi.org/10.5194/hess-17-2233-2013, https://doi.org/10.5194/hess-17-2233-2013, 2013
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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.
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.
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
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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.
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.
Nicholas A. Beresford, Sergii Gashchak, Michael D. Wood, and Catherine L. Barnett
Earth Syst. Sci. Data, 15, 911–920, https://doi.org/10.5194/essd-15-911-2023, https://doi.org/10.5194/essd-15-911-2023, 2023
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Camera traps were established in a highly contaminated area of the Chornobyl Exclusion Zone (CEZ) to capture images of mammals. Over 1 year, 14 mammal species were recorded. The number of species observed did not vary with estimated radiation exposure. The data will be of value from the perspectives of effects of radiation on wildlife and also rewilding in this large, abandoned area. They may also have value in future studies investigating impacts of recent Russian military action in the CEZ.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
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This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
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The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Cited articles
Aguilar, E., Auer, I., Brunet, M., Peterson, T. C., and Wieringa, J.:
Guidelines on climate metadata and homogenization, WMO/TD No. 1186, Geneva,
Switzerland, 2003.
Ahrends, H., Haseneder-Lind, R., Schween, J., Crewell, S., Stadler, A., and
Rascher, U.: Diurnal Dynamics of Wheat Evapotranspiration Derived from
Ground-Based Thermal Imagery, Remote Sens., 6, 9775–9801,
https://doi.org/10.3390/rs6109775, 2014.
Ali, M., Montzka, C., Stadler, A., Menz, G., Thonfeld, F., and Vereecken, H.:
Estimation and Validation of RapidEye-Based Time-Series of Leaf Area Index
for Winter Wheat in the Rur Catchment (Germany), Remote Sens., 7,
2808–2831, https://doi.org/10.3390/rs70302808, 2015.
Auer, I., Böhm, R., Jurković, A., Orlik, A., Potzmann, R.,
Schöner, W., Ungersböck, M., Brunetti, M., Nanni, T., Maugeri, M.,
Briffa, K., Jones, P., Efthymiadis, D., Mestre, O., Moisselin, J.-M.,
Begert, M., Brazdil, R., Bochnicek, O., Cegnar, T., Gajić-Čapka, M.,
Zaninović, K., Majstorović, Ž., Szalai, S., Szentimrey, T., and
Mercalli, L.: A new instrumental precipitation dataset for the greater
alpine region for the period 1800–2002: Precipitation Dataset: European
Greater Alpine Region, Int. J. Climatol., 25, 139–166,
https://doi.org/10.1002/joc.1135, 2005.
Beaulieu, C., Seidou, O., Ouarda, T. B. M. J., Zhang, X., Boulet, G., and
Yagouti, A.: Intercomparison of homogenization techniques for precipitation
data: Homogenization of Precipitation, Water Resour. Res., 44, W02425,
https://doi.org/10.1029/2006WR005615, 2008.
Beaulieu, C., Seidou, O., Ouarda, T. B. M. J., and Zhang, X.: Intercomparison
of homogenization techniques for precipitation data continued: Comparison of
two recent Bayesian change point models: Homogenization with Bayesian Change
Point, Water Resour. Res., 45, W08410, https://doi.org/10.1029/2008WR007501, 2009.
Beckers, J. M. and Rixen, M.: EOF Calculations and Data Filling from
Incomplete Oceanographic Datasets, J. Atmos. Ocean. Tech., 20,
1839–1856, https://doi.org/10.1175/1520-0426(2003)020<1839:ECADFF>
2.0.CO;2, 2003.
Bogena, H. R.: TERENO: German network of terrestrial environmental
observatories, J. Large-Scale Res. Facil. JLSRF, 2, A52, https://doi.org/10.17815/jlsrf-2-98,
2016.
Bornemann, L., Herbst, M., Welp, G., Vereecken, H., and Amelung, W.: Rock
Fragments Control Size and Saturation of Organic Carbon Pools in
Agricultural Topsoil, Soil Sci. Soc. Am. J., 75, 1898,
https://doi.org/10.2136/sssaj2010.0454, 2011.
Brandsma, T. and Können, G. P.: Application of nearest-neighbor
resampling for homogenizing temperature records on a daily to sub-daily
level, Int. J. Climatol., 26, 75–89, https://doi.org/10.1002/joc.1236, 2006.
Brogi, C., Huisman, J. A., Pätzold, S., von Hebel, C., Weihermüller,
L., Kaufmann, M. S., van der Kruk, J., and Vereecken, H.: Large-scale soil
mapping using multi-configuration EMI and supervised image classification,
Geoderma, 335, 133–148, https://doi.org/10.1016/j.geoderma.2018.08.001, 2019.
Brogi, C., Huisman, J. A., Herbst, M., Weihermüller, L., Klosterhalfen,
A., Montzka, C., Reichenau, T. G., and Vereecken, H.: Simulation of spatial
variability in crop leaf area index and yield using agroecosystem modeling
and geophysics-based quantitative soil information, Vadose Zone J., 19, e20009,
https://doi.org/10.1002/vzj2.20009, 2020.
Busch, S., van der Kruk, J., and Vereecken, H.: Improved Characterization of
Fine-Texture Soils Using On-Ground GPR Full-Waveform Inversion, IEEE T.
Geosci. Remote, 52, 3947–3958, https://doi.org/10.1109/TGRS.2013.2278297,
2014.
Della-Marta, P. M. and Wanner, H.: A Method of Homogenizing the Extremes and
Mean of Daily Temperature Measurements, J. Clim., 19, 4179–4197,
https://doi.org/10.1175/JCLI3855.1, 2006.
Dengel, S., Graf, A., Grünwald, T., Hehn, M., Kolari, P., Löfvenius,
M. O., Merbold, L., Nicolini, G., and Pavelka, M.: Standardized precipitation
measurements within ICOS: rain, snowfall and snow depth: a review, Int.
Agrophys., 32, 607–617, https://doi.org/10.1515/intag-2017-0046, 2018.
Domonkos, P. and Coll, J.: Homogenisation of temperature and precipitation
time series with ACMANT3: method description and efficiency tests:
Homogenisation of time series with ACMANT3, Int. J. Climatol., 37,
1910–1921, https://doi.org/10.1002/joc.4822, 2017.
Eder, F., Schmidt, M., Damian, T., Träumner, K., and Mauder, M.:
Mesoscale Eddies Affect Near-Surface Turbulent Exchange: Evidence from Lidar
and Tower Measurements, J. Appl. Meteorol. Climatol., 54, 189–206,
https://doi.org/10.1175/JAMC-D-14-0140.1, 2015.
Graf, A.: Gap-filling meteorological variables with Empirical Orthogonal
Functions, Geophys. Res. Abstr.,no. 19, 2017.
Graf, A., Prolingheuer, N., Schickling, A., Schmidt, M., Schneider, K.,
Schüttemeyer, D., Herbst, M., Huisman, J. A., Weihermüller, L.,
Scharnagl, B., Steenpass, C., Harms, R., and Vereecken, H.: Temporal
Downscaling of Soil Carbon Dioxide Efflux Measurements Based on Time-Stable
Spatial Patterns, Vadose Zone J., 10, 239–251, https://doi.org/10.2136/vzj2009.0152,
2011.
Graf, A., Herbst, M., Weihermüller, L., Huisman, J. A., Prolingheuer,
N., Bornemann, L., and Vereecken, H.: Analyzing spatiotemporal variability of
heterotrophic soil respiration at the field scale using orthogonal
functions, Geoderma, 181–182, 91–101, https://doi.org/10.1016/j.geoderma.2012.02.016,
2012.
Heitmann-Weber, B., Mittelstaedt, W., and Fuhr, F.: The degradation of
anilazine and dihydroxy-anilazine at various soil depths of an orthic
luvisol, J. Environ. Sci. Health Pt. B, 29, 247–264,
https://doi.org/10.1080/03601239409372878, 1994.
Hoffmeister, D., Waldhoff, G., Korres, W., Curdt, C., and Bareth, G.: Crop
height variability detection in a single field by multi-temporal terrestrial
laser scanning, Precis. Agric., 17, 296–312,
https://doi.org/10.1007/s11119-015-9420-y, 2016.
IUSS Working Group WRB: World Reference Base for Soil Resources 2014, FAO, Rome, Italy, 2015.
Jakobi, J., Huisman, J. A., Schrön, M., Fiedler, J., Brogi, C.,
Vereecken, H., and Bogena, H. R.: Error Estimation for Soil Moisture
Measurements With Cosmic Ray Neutron Sensing and Implications for Rover
Surveys, Front. Water, 2, 10, https://doi.org/10.3389/frwa.2020.00010, 2020.
Jones, J. W., Antle, J. M., Basso, B., Boote, K. J., Conant, R. T., Foster, I., Godfray,
H. C. J., Herrero, M., Howitt, R. E., Janssen, S., Keating, B. A.,
Munoz-Carpena, R., Porter, C. H., Rosenzweig, C., and Wheeler, T. R.: Toward
a new generation of agricultural system data, models, and knowledge
products: State of agricultural systems science, Agric. Syst., 155,
269–288, https://doi.org/10.1016/j.agsy.2016.09.021, 2017.
Kalis, A. J.: Die menschliche Beeinflussung der Vegetationsverhältnisse
auf der Aldenhovener Platte (Rheinland) während der vergangenen 2000
Jahre, in Archäologie in den rheinischen Lößbörden:
Beiträge zur Siedlungsgeschichte im Rheinland, vol. 24,
Rheinland-Verlag, Köln, 1983.
Kersebaum, K. C., Boote, K. J., Jorgenson, J. S., Nendel, C., Bindi, M.,
Frühauf, C., Gaiser, T., Hoogenboom, G., Kollas, C., Olesen, J. E.,
Rötter, R. P., Ruget, F., Thorburn, P. J., Trnka, M., and Wegehenkel, M.:
Analysis and classification of data sets for calibration and validation of
agro-ecosystem models, Environ. Model. Softw., 72, 402–417,
https://doi.org/10.1016/j.envsoft.2015.05.009, 2015.
Klosterhalfen, A., Herbst, M., Weihermüller, L., Graf, A., Schmidt, M.,
Stadler, A., Schneider, K., Subke, J.-A., Huisman, J. A., and Vereecken, H.:
Multi-site calibration and validation of a net ecosystem carbon exchange
model for croplands, Ecol. Model., 363, 137–156,
https://doi.org/10.1016/j.ecolmodel.2017.07.028, 2017.
Korres, W., Koyama, C. N., Fiener, P., and Schneider, K.: Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions, Hydrol. Earth Syst. Sci., 14, 751–764, https://doi.org/10.5194/hess-14-751-2010, 2010.
Korres, W., Reichenau, T. G., and Schneider, K.: Patterns and scaling
properties of surface soil moisture in an agricultural landscape: An
ecohydrological modeling study, J. Hydrol., 498, 89–102, 2013.
Kuglitsch, F. G., Toreti, A., Xoplaki, E., Della-Marta, P. M., Luterbacher,
J., and Wanner, H.: Homogenization of daily maximum temperature series in the
Mediterranean, J. Geophys. Res., 114, D15108, https://doi.org/10.1029/2008JD011606, 2009.
Mauder, M. and Foken, T.: Documentation and Instruction Manual of the
Eddy-Covariance Software Package TK3, Universität Bayreuth, Abt.
Mikrometeorologie, Bayreuth, 2011.
Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H. P.,
Schmidt, M., and Steinbrecher, R.: A strategy for quality and uncertainty
assessment of long-term eddy-covariance measurements, Agr. Forest Meteorol.,
169, 122–135, https://doi.org/10.1016/j.agrformet.2012.09.006, 2013.
Meier, U., Bleiholder, H., Buhr, L., Feller, C., Hack, H., Heß, M.,
Lancashire, P. D., Schnock, U., Stauß, R., van den Boom, T., Weber, E.,
and Zwerger, P.: The BBCH system to coding the phenological growth stages of
plants – history and publications, J. Cultiv. Plants, 61, 41–52,
2009.
Mestre, O., Gruber, C., Prieur, C., Caussinus, H., and Jourdain, S.:
SPLIDHOM: A Method for Homogenization of Daily Temperature Observations, J.
Appl. Meteorol. Climatol., 50, 2343–2358, https://doi.org/10.1175/2011JAMC2641.1,
2011.
Meyer, N., Bornemann, L., Welp, G., Schiedung, H., Herbst, M., and Amelung,
W.: Carbon saturation drives spatial patterns of soil organic matter losses
under long-term bare fallow, Geoderma, 306, 89–98,
https://doi.org/10.1016/j.geoderma.2017.07.004, 2017.
Moore, C. J.: Frequency response corrections for eddy correlation systems, Bound.-Lay. Meteorol., 37, 17–35, https://doi.org/10.1007/BF00122754, 1986.
Nemes, A., Wosten, J. H. M., Lilly, A., and Voshaar, J. H. O.: Evaluation of
different procedures to interpolate particle-size distributions to achieve
compatibility within soil databases, Geoderma, 90, 187–202, 1999.
Ney, P. and Graf, A.: High-Resolution Vertical Profile Measurements for
Carbon Dioxide and Water Vapour Concentrations Within and Above Crop
Canopies, Bound.-Lay. Meteorol., 166, 449–473,
https://doi.org/10.1007/s10546-017-0316-4, 2018.
Prolingheuer, N., Scharnagl, B., Graf, A., Vereecken, H., and Herbst, M.: On
the spatial variation of soil rhizospheric and heterotrophic respiration in
a winter wheat stand, Agr. Forest Meteorol., 195–196, 24–31,
https://doi.org/10.1016/j.agrformet.2014.04.016, 2014.
Pütz, T.: Lysimeterversuche zum Verlagerungsverhalten von
Methabenzthiazuron und gelöstem organischen Kohlenstoff in einer
Parabraunerde, Aufbau von zwei Klimameßstationen und Untersuchungen zur
Validierung des Lysimetersystems, Forschungszentrum Zentralbibliothek,
Jülich, available at:
http://gso.gbv.de/DB=2.1/PPNSET?PPN=152374191 (last access: 7 March 2019), 1993.
R Core Team: R, R Foundation for Statistical Computing, Vienna, Austria,
2017.
Reichenau, T. G., Korres, W., Montzka, C., Fiener, P., Wilken, F., Stadler,
A., Waldhoff, G., and Schneider, K.: Spatial Heterogeneity of Leaf Area Index
(LAI) and Its Temporal Course on Arable Land: Combining Field Measurements,
Remote Sensing and Simulation in a Comprehensive Data Analysis Approach
(CDAA), PLOS ONE, 11, e0158451,
https://doi.org/10.1371/journal.pone.0158451, 2016.
Reichenau, T. G., Korres, W., Schmidt, M., Graf, A., Welp, G., Meyer, N.,
Stadler, A., Brogi, C. and Schneider, K.: 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, https://doi.org/10.5880/TR32DB.39, 2020.
Sakai, T., Iizumi, T., Okada, M., Nishimori, M., Grünwald, T., Prueger,
J., Cescatti, A., Korres, W., Schmidt, M., Carrara, A., Loubet, B., and
Ceschia, E.: Varying applicability of four different satellite-derived soil
moisture products to global gridded crop model evaluation, Int. J. Appl.
Earth Obs. Geoinf., 48, 51–60, https://doi.org/10.1016/j.jag.2015.09.011, 2016.
Schad, P., Krasilnikov, P. V., and Arnold, R.: German Soil Classification, in:
A handbook of soil terminology, correlation and classification, edited by: Krasilnikov, P.
V., Ibáñez Martí, J. J., Arnold, R., and Shoba, S.,
Earthscan, London, Sterling, VA, 122–130, 2009.
Schiedung, H., Bornemann, L., and Welp, G.: Seasonal Variability of Soil
Organic Carbon Fractions Under Arable Land, Pedosphere, 27, 380–386,
https://doi.org/10.1016/S1002-0160(17)60326-6, 2017.
Schmidt, M., Reichenau, T. G., Fiener, P., and Schneider, K.: The carbon
budget of a winter wheat field: An eddy covariance analysis of seasonal and
inter-annual variability, Agr. Forest Meteorol., 165, 114–126,
https://doi.org/10.1016/j.agrformet.2012.05.012, 2012.
Schotanus, P., Nieuwstadt, F. T. M., and De Bruin, H. A. R.: Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes, Bound.-Lay. Meteorol., 26, 81–93, https://doi.org/10.1007/BF00164332, 1983.
Schulz, E.: Influence of site conditions and management on different soil
organic matter (som) pools, Arch. Agron. Soil Sci., 50, 33–47,
https://doi.org/10.1080/03650340310001627577, 2004.
Simmer, C., Thiele-Eich, I., Masbou, M., Amelung, W., Bogena, H., Crewell,
S., Diekkrüger, B., Ewert, F., Hendricks Franssen, H.-J., Huisman, J.
A., Kemna, A., Klitzsch, N., Kollet, S., Langensiepen, M., Löhnert, U.,
Rahman, A. S. M. M., Rascher, U., Schneider, K., Schween, J., Shao, Y.,
Shrestha, P., Stiebler, M., Sulis, M., Vanderborght, J., Vereecken, H., van
der Kruk, J., Waldhoff, G., and Zerenner, T.: Monitoring and Modeling the
Terrestrial System from Pores to Catchments, B. Am. Meteorol. Soc.,
96, 1765–1787, https://doi.org/10.1175/BAMS-D-13-00134.1, 2015.
Trewin, B.: A daily homogenized temperature data set for Australia, Int. J.
Climatol., 33, 1510–1529, https://doi.org/10.1002/joc.3530, 2013.
Van Dijk, A., Moene, A. F., and De Bruin, H. A. R.: The principles of surface
flux physics: theory, practice and description of the ECPACK library,
Meteorology and Air Quality Group, Wageningen University, Wageningen,
the Netherlands, 2004.
Venema, V. K. C., Mestre, O., Aguilar, E., Auer, I., Guijarro, J. A., Domonkos, P., Vertacnik, G., Szentimrey, T., Stepanek, P., Zahradnicek, P., Viarre, J., Müller-Westermeier, G., Lakatos, M., Williams, C. N., Menne, M. J., Lindau, R., Rasol, D., Rustemeier, E., Kolokythas, K., Marinova, T., Andresen, L., Acquaotta, F., Fratianni, S., Cheval, S., Klancar, M., Brunetti, M., Gruber, C., Prohom Duran, M., Likso, T., Esteban, P., and Brandsma, T.: Benchmarking homogenization algorithms for monthly data, Clim. Past, 8, 89–115, https://doi.org/10.5194/cp-8-89-2012, 2012.
Vereecken, H., Kollet, S., and Simmer, C.: Patterns in
Soil–Vegetation–Atmosphere Systems: Monitoring, Modeling, and Data
Assimilation, Vadose Zone J., 9, 821–827, https://doi.org/10.2136/vzj2010.0122, 2010.
Vincent, L. A., Zhang, X., Bonsal, B. R., and Hogg, W. D.: Homogenization of
Daily Temperatures over Canada, J. Clim., 15, 1322–1334,
https://doi.org/10.1175/1520-0442(2002)015<1322:HODTOC>2.0.CO;2,
2002.
von Hebel, C., Matveeva, M., Verweij, E., Rademske, P., Kaufmann, M. S.,
Brogi, C., Vereecken, H., Rascher, U., and van der Kruk, J.: Understanding
Soil and Plant Interaction by Combining Ground-Based Quantitative
Electromagnetic Induction and Airborne Hyperspectral Data, Geophys. Res.
Lett., 45, 7571–7579, https://doi.org/10.1029/2018GL078658, 2018.
Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux measurements for density effects due to heat and water vapour transfer, Q. J. Roy. Meteor. Soc., 106, 85–100, https://doi.org/10.1002/qj.49710644707, 1980.
Webster, R.: Regression and functional relations, Eur. J. Soil Sci., 48,
557–566, https://doi.org/10.1111/j.1365-2389.1997.tb00222.x, 1997.
Wieneke, S., Burkart, A., Cendrero-Mateo, M. P., Julitta, T., Rossini, M.,
Schickling, A., Schmidt, M., and Rascher, U.: Linking photosynthesis and
sun-induced fluorescence at sub-daily to seasonal scales, Remote Sens.
Environ., 219, 247–258, https://doi.org/10.1016/j.rse.2018.10.019, 2018.
Wijngaard, J. B., Klein Tank, A. M. G., and Können, G. P.: Homogeneity of
20th century European daily temperature and precipitation series:
Homogeneity of European Climate Series, Int. J. Climatol., 23, 679–692,
https://doi.org/10.1002/joc.906, 2003.
Zeileis, A. and Grothendieck, G.: zoo: S3 Infrastructure for Regular and
Irregular Time Series, J. Stat. Softw., 14, 6, https://doi.org/10.18637/jss.v014.i06,
2005.
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