Articles | Volume 19, issue 11
https://doi.org/10.5194/bg-19-2805-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-2805-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
08 Jun 2022
Technical note |
| 08 Jun 2022
| 08 Jun 2022
Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set
Sophia Walther
CORRESPONDING AUTHOR
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
Simon Besnard
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
South Pole, Digital Innovation, Fred. Roeskestraat 115, Amsterdam, the Netherlands
Jacob Allen Nelson
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
Tarek Sebastian El-Madany
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
Mirco Migliavacca
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
European Commission, Joint Research Centre, Via Fermi 2749, Ispra (VA), Italy
Ulrich Weber
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
Nuno Carvalhais
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal
Sofia Lorena Ermida
Departamento de Ciências e Engenharia do Ambiente (DCEA), Faculdade de Ciências e Tecnologia (FCT), Universidade Nova de Lisboa, Lisbon, Portugal
Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, Campo Grande Edifício C1, Piso 1, 1749-016 Lisbon, Portugal
Christian Brümmer
Thünen Institute of Climate-Smart Agriculture, Bundesallee 65, Braunschweig, Germany
Frederik Schrader
Thünen Institute of Climate-Smart Agriculture, Bundesallee 65, Braunschweig, Germany
Anatoly Stanislavovich Prokushkin
V.N. Sukachev Institute of Forest of the Siberian Branch of Russian Academy of Sciences – separated department of the KSC SB RAS, Akademgorodok 50/28, Krasnoyarsk, Russia
Alexey Vasilevich Panov
V.N. Sukachev Institute of Forest of the Siberian Branch of Russian Academy of Sciences – separated department of the KSC SB RAS, Akademgorodok 50/28, Krasnoyarsk, Russia
Martin Jung
Department Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, Germany
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Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
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Sinikka J. Paulus, Rene Orth, Sung-Ching Lee, Anke Hildebrandt, Martin Jung, Jacob A. Nelson, Tarek Sebastian El-Madany, Arnaud Carrara, Gerardo Moreno, Matthias Mauder, Jannis Groh, Alexander Graf, Markus Reichstein, and Mirco Migliavacca
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Martin Jung, Jacob Nelson, Mirco Migliavacca, Tarek El-Madany, Dario Papale, Markus Reichstein, Sophia Walther, and Thomas Wutzler
Biogeosciences, 21, 1827–1846, https://doi.org/10.5194/bg-21-1827-2024, https://doi.org/10.5194/bg-21-1827-2024, 2024
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Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Mana Gharun, Ankit Shekhar, Lukas Hörtnagl, Luana Krebs, Nicola Arriga, Mirco Migliavacca, Marilyn Roland, Bert Gielen, Leonardo Montagnani, Enrico Tomelleri, Ladislav Šigut, Matthias Peichl, Peng Zhao, Marius Schmidt, Thomas Grünwald, Mika Korkiakoski, Annalea Lohila, and Nina Buchmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2964, https://doi.org/10.5194/egusphere-2023-2964, 2024
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Effect of winter warming on forest CO2 fluxes has rarely been investigated. We tested the effect of the warm winter in 2020 on the forest CO2 fluxes across 14 sites in Europe and found that in colder sites net ecosystem productivity (NEP) declined during the warm winter, while in the warmer sites NEP increased. Warming leads to increased respiration fluxes but if not translated into a direct warming of the soil might not enhance productivity, if the soil within the rooting zone remains frozen.
Hui Yang, Krzysztof Stereńczak, Zbigniew Karaszewski, and Nuno Carvalhais
EGUsphere, https://doi.org/10.5194/egusphere-2023-2691, https://doi.org/10.5194/egusphere-2023-2691, 2023
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Wood density is crucial for ecological and carbon stock assessment, yet its labor-intensive analysis limits studies across species and spaces. Our study, based on 48,000 samples from Central Europe, reveals that, even without species information, 91% of inter-tree variations can be predicted by vegetation indexes, topography, and soil texture. Importantly, we highlight neglected intra-tree variation, showing substantial variations vertically along the height and radially from the center to bark.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
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We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Richard Nair, Yunpeng Luo, Tarek El-Madany, Victor Rolo, Javier Pacheco-Labrador, Silvia Caldararu, Kendalynn A. Morris, Marion Schrumpf, Arnaud Carrara, Gerardo Moreno, Markus Reichstein, and Mirco Migliavacca
EGUsphere, https://doi.org/10.5194/egusphere-2023-2434, https://doi.org/10.5194/egusphere-2023-2434, 2023
Preprint archived
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We studied a Mediterranean ecosystem to understand carbon uptake efficiency and its controls. These ecosystems face potential nitrogen-phosphorus imbalances due to pollution. Analysing six years of carbon data, we assessed controls at different timeframes. This is crucial for predicting such vulnerable regions. Our findings revealed N limitation on C uptake, not N:P imbalance, and strong influence of water availability. whether drought or wetness promoted net C uptake depended on timescale.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
Short summary
Short summary
Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
A. Elia, M. Pickering, M. Girardello, G. Oton, G. Ceccherini, S. Capobianco, M. Piccardo, G. Forzieri, M. Migliavacca, and A. Cescatti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W7-2023, 41–46, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-41-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-41-2023, 2023
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
Hydrol. Earth Syst. Sci., 27, 1531–1563, https://doi.org/10.5194/hess-27-1531-2023, https://doi.org/10.5194/hess-27-1531-2023, 2023
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We spatially attribute the variance in global terrestrial water storage (TWS) interannual variability (IAV) and its modeling error with two data-driven hydrological models. We find error hotspot regions that show a disproportionately large significance in the global mismatch and the association of the error regions with a smaller-scale lateral convergence of water. Our findings imply that TWS IAV modeling can be efficiently improved by focusing on model representations for the error hotspots.
Sinikka Jasmin Paulus, Tarek Sebastian El-Madany, René Orth, Anke Hildebrandt, Thomas Wutzler, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Olaf Kolle, Markus Reichstein, and Mirco Migliavacca
Hydrol. Earth Syst. Sci., 26, 6263–6287, https://doi.org/10.5194/hess-26-6263-2022, https://doi.org/10.5194/hess-26-6263-2022, 2022
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In this study, we analyze small inputs of water to ecosystems such as fog, dew, and adsorption of vapor. To measure them, we use a scaling system and later test our attribution of different water fluxes to weight changes. We found that they occur frequently during 1 year in a dry summer ecosystem. In each season, a different flux seems dominant, but they all mainly occur during the night. Therefore, they could be important for the biosphere because rain is unevenly distributed over the year.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, Richard Kranenburg, and Christian Brümmer
Biogeosciences, 19, 5287–5311, https://doi.org/10.5194/bg-19-5287-2022, https://doi.org/10.5194/bg-19-5287-2022, 2022
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For the first time, we compared four methods for estimating the annual dry deposition of total reactive nitrogen into a low-polluted forest ecosystem. In our analysis, we used 2.5 years of flux measurements, an in situ modeling approach, a large-scale chemical transport model (CTM), and canopy budget models. Annual nitrogen dry deposition budgets ranged between 4.3 and 6.7 kg N ha−1 a−1, depending on the applied method.
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022, https://doi.org/10.5194/esd-13-1451-2022, 2022
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Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
Xin Yu, René Orth, Markus Reichstein, Michael Bahn, Anne Klosterhalfen, Alexander Knohl, Franziska Koebsch, Mirco Migliavacca, Martina Mund, Jacob A. Nelson, Benjamin D. Stocker, Sophia Walther, and Ana Bastos
Biogeosciences, 19, 4315–4329, https://doi.org/10.5194/bg-19-4315-2022, https://doi.org/10.5194/bg-19-4315-2022, 2022
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Identifying drought legacy effects is challenging because they are superimposed on variability driven by climate conditions in the recovery period. We develop a residual-based approach to quantify legacies on gross primary productivity (GPP) from eddy covariance data. The GPP reduction due to legacy effects is comparable to the concurrent effects at two sites in Germany, which reveals the importance of legacy effects. Our novel methodology can be used to quantify drought legacies elsewhere.
Miguel Nogueira, Alexandra Hurduc, Sofia Ermida, Daniela C. A. Lima, Pedro M. M. Soares, Frederico Johannsen, and Emanuel Dutra
Geosci. Model Dev., 15, 5949–5965, https://doi.org/10.5194/gmd-15-5949-2022, https://doi.org/10.5194/gmd-15-5949-2022, 2022
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We evaluated the quality of the ERA5 reanalysis representation of the urban heat island (UHI) over the city of Paris and performed a set of offline runs using the SURFEX land surface model. They were compared with observations (satellite and in situ). The SURFEX-TEB runs showed the best performance in representing the UHI, reducing its bias significantly. We demonstrate the ability of the SURFEX-TEB framework to simulate urban climate, which is crucial for studying climate change in cities.
Saqr Munassar, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, Michał Gałkowski, Sophia Walther, and Christoph Gerbig
Atmos. Chem. Phys., 22, 7875–7892, https://doi.org/10.5194/acp-22-7875-2022, https://doi.org/10.5194/acp-22-7875-2022, 2022
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The results obtained from ensembles of inversions over 13 years show the largest spread in the a posteriori fluxes over the station set ensemble. Using different prior fluxes in the inversions led to a smaller impact. Drought occurrences in 2018 and 2019 affected CO2 fluxes as seen in net ecosystem exchange estimates. Our study highlights the importance of expanding the atmospheric site network across Europe to better constrain CO2 fluxes in inverse modelling.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109, https://doi.org/10.5194/hess-26-1089-2022, https://doi.org/10.5194/hess-26-1089-2022, 2022
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We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
Christian Brümmer, Jeremy J. Rüffer, Jean-Pierre Delorme, Pascal Wintjen, Frederik Schrader, Burkhard Beudert, Martijn Schaap, and Christof Ammann
Earth Syst. Sci. Data, 14, 743–761, https://doi.org/10.5194/essd-14-743-2022, https://doi.org/10.5194/essd-14-743-2022, 2022
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Field campaigns were carried out to investigate the biosphere–atmosphere exchange of selected reactive nitrogen compounds over different land surfaces using two different analytical devices for ammonia and total reactive nitrogen. The datasets improve our understanding of the temporal variability of surface–atmosphere exchange in different ecosystems, thereby providing validation opportunities for inferential models simulating the exchange of reactive nitrogen.
J. Pacheco-Labrador, U. Weber, X. Ma, M. D. Mahecha, N. Carvalhais, C. Wirth, A. Huth, F. J. Bohn, G. Kraemer, U. Heiden, FunDivEUROPE members, and M. Migliavacca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1-W1-2021, 49–55, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, 2022
Josephin Kroll, Jasper M. C. Denissen, Mirco Migliavacca, Wantong Li, Anke Hildebrandt, and Rene Orth
Biogeosciences, 19, 477–489, https://doi.org/10.5194/bg-19-477-2022, https://doi.org/10.5194/bg-19-477-2022, 2022
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Plant growth relies on having access to energy (solar radiation) and water (soil moisture). This energy and water availability is impacted by weather extremes, like heat waves and droughts, which will occur more frequently in response to climate change. In this context, we analysed global satellite data to detect in which regions extreme plant growth is controlled by energy or water. We find that extreme plant growth is associated with temperature- or soil-moisture-related extremes.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, and Christian Brümmer
Biogeosciences, 19, 389–413, https://doi.org/10.5194/bg-19-389-2022, https://doi.org/10.5194/bg-19-389-2022, 2022
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Fluxes of total reactive nitrogen (∑Nr) over a low polluted forest were analyzed with regard to their temporal dynamics. Mostly deposition was observed with median fluxes ranging from −15 to −5 ng N m−2 s−1, corresponding to a range of deposition velocities from 0.2 to 0.5 cm s−1. While seasonally changing contributions of NH3 and NOx to the ∑Nr signal were found, we estimate an annual total N deposition (dry+wet) of 12.2 and 10.9 kg N ha−1 a−1 in the 2 years of observation.
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
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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.
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
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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.
Yeonuk Kim, Monica Garcia, Laura Morillas, Ulrich Weber, T. Andrew Black, and Mark S. Johnson
Hydrol. Earth Syst. Sci., 25, 5175–5191, https://doi.org/10.5194/hess-25-5175-2021, https://doi.org/10.5194/hess-25-5175-2021, 2021
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Here, we present a novel physically based evaporation model to demonstrate that vertical relative humidity (RH) gradients from the land surface to the atmosphere tend to evolve towards zero due to land–atmosphere equilibration processes. Collapsing RH gradients on daily to yearly timescales indicate an emergent land–atmosphere equilibrium, making it possible to determine evapotranspiration using only meteorological information, independent of land surface conditions and vegetation controls.
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
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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.
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
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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.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
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Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
Oksana Rybchak, Justin du Toit, Jean-Pierre Delorme, Jens-Kristian Jüdt, Kanisios Mukwashi, Christian Thau, Gregor Feig, Mari Bieri, and Christian Brümmer
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-420, https://doi.org/10.5194/bg-2020-420, 2020
Revised manuscript not accepted
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We studied the impacts of livestock grazing on carbon budgets in the semi-arid South African Karoo by comparing two sites under different grazing intensities. The previously overgrazed site, characterised by unpalatable grasses and thus poorly suited as pasture, sequestered more carbon over the four-year measurement period, compared to the lenient-grazed site. The studied ecosystems act as either carbon sinks or sources depending on precipitation.
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
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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.
Miguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F. Trigo, Sofia L. Ermida, João P. A. Martins, and Emanuel Dutra
Geosci. Model Dev., 13, 3975–3993, https://doi.org/10.5194/gmd-13-3975-2020, https://doi.org/10.5194/gmd-13-3975-2020, 2020
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We used earth observations to evaluate and improve the representation of land surface temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX land surface models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction in daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
Daniel E. Pabon-Moreno, Talie Musavi, Mirco Migliavacca, Markus Reichstein, Christine Römermann, and Miguel D. Mahecha
Biogeosciences, 17, 3991–4006, https://doi.org/10.5194/bg-17-3991-2020, https://doi.org/10.5194/bg-17-3991-2020, 2020
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Ecosystem CO2 uptake changes in time depending on climate conditions. In this study, we analyze how different climate variables affect the timing when CO2 uptake is at a maximum (DOYGPPmax). We found that the joint effects of radiation, temperature, and vapor pressure deficit are the most relevant controlling factors of DOYGPPmax and that if they increase, DOYGPPmax will happen earlier. These results help us to better understand how CO2 uptake could be affected by climate change.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Pascal Wintjen, Christof Ammann, Frederik Schrader, and Christian Brümmer
Atmos. Meas. Tech., 13, 2923–2948, https://doi.org/10.5194/amt-13-2923-2020, https://doi.org/10.5194/amt-13-2923-2020, 2020
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With recent technological advances it is now possible to measure the exchange of trace gases between the land surface and the atmosphere. When using the so-called eddy-covariance method, certain corrections need to be applied to account for attenuation in the flux signal. These losses were found to be setup- and site-specific and can be up to 38 % for reactive nitrogen fluxes. We evaluated five different methods and recommend using an empirical version with locally measured cospectra.
Thomas Wutzler, Oscar Perez-Priego, Kendalynn Morris, Tarek S. El-Madany, and Mirco Migliavacca
Geosci. Instrum. Method. Data Syst., 9, 239–254, https://doi.org/10.5194/gi-9-239-2020, https://doi.org/10.5194/gi-9-239-2020, 2020
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Continuous data of soil CO2 efflux can improve model prediction of climate warming, and automated data are becoming increasingly available. However, aggregating chamber-based data to plot scale pose challenges. Therefore, we showed, using 1 year of half-hourly data, how using the lognormal assumption tackles several challenges. We propose that plot-scale SO2 efflux observations should be reported together with lognormally based uncertainties and enter model constraining frameworks at log scale.
René Orth, Georgia Destouni, Martin Jung, and Markus Reichstein
Biogeosciences, 17, 2647–2656, https://doi.org/10.5194/bg-17-2647-2020, https://doi.org/10.5194/bg-17-2647-2020, 2020
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Drought duration is a key control of the large-scale biospheric drought response.
Thereby, the vegetation responds linearly to drought duration at large spatial scales.
The slope of the linear relationship between the vegetation drought response and drought duration is steeper in drier climates.
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
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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.
Barbara Marcolla, Mirco Migliavacca, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 17, 2365–2379, https://doi.org/10.5194/bg-17-2365-2020, https://doi.org/10.5194/bg-17-2365-2020, 2020
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This work investigates the sensitivity of terrestrial CO2 fluxes to climate drivers. We observed that CO2 flux is mostly controlled by temperature during the growing season and by radiation off season. We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia. Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
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Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Javier Pacheco-Labrador, Tarek S. El-Madany, M. Pilar Martin, Rosario Gonzalez-Cascon, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Tiana Hammer, Heiko Moossen, Kathrin Henkel, Olaf Kolle, David Martini, Vicente Burchard, Christiaan van der Tol, Karl Segl, Markus Reichstein, and Mirco Migliavacca
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-501, https://doi.org/10.5194/bg-2019-501, 2020
Revised manuscript not accepted
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The new generation of sensors on-board satellites have the potential to provide richer information about the function of vegetation than before. This information, nowadays missing, is fundamental to improve our understanding and prediction of carbon and water cycles, and therefore to anticipate effects and responses to Climate Change. In this manuscript we propose a method to exploit the data provided by these satellites to successfully obtain this information key to face Climate Change.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Vicente Burchard-Levine, Héctor Nieto, David Riaño, Mirco Migliavacca, Tarek S. El-Madany, Oscar Perez-Priego, Arnaud Carrara, and M. Pilar Martín
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-354, https://doi.org/10.5194/hess-2019-354, 2019
Manuscript not accepted for further review
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Models are increasingly being used to understand surface water fluxes, which are of high use to manage crop irrigation, and to understand the earth system´s response to environmental change. However, often these models have higher uncertainty in complex ecosystems with multiple layers of vegetation. This manuscript adapts and analyzes a well known model to better simulate water fluxes for a savanna-like ecosystem and to understand the influence that vegetation has on their predictions.
Mikhail A. Korets and Anatoly S. Prokushkin
Proc. Int. Cartogr. Assoc., 2, 65, https://doi.org/10.5194/ica-proc-2-65-2019, https://doi.org/10.5194/ica-proc-2-65-2019, 2019
Sven Boese, Martin Jung, Nuno Carvalhais, Adriaan J. Teuling, and Markus Reichstein
Biogeosciences, 16, 2557–2572, https://doi.org/10.5194/bg-16-2557-2019, https://doi.org/10.5194/bg-16-2557-2019, 2019
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This study examines how limited water availability during droughts affects water-use efficiency. This metric describes how much carbon an ecosystem can assimilate for each unit of water lost by transpiration. We test how well different water-use efficiency models can capture the dynamics of transpiration decrease due to increased soil-water limitation. Accounting for the interacting effects of radiation and water limitation is necessary to accurately predict transpiration during these periods.
Richard K. F. Nair, Kendalynn A. Morris, Martin Hertel, Yunpeng Luo, Gerardo Moreno, Markus Reichstein, Marion Schrumpf, and Mirco Migliavacca
Biogeosciences, 16, 1883–1901, https://doi.org/10.5194/bg-16-1883-2019, https://doi.org/10.5194/bg-16-1883-2019, 2019
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We investigated how nutrient availability affects seasonal timing of root growth and death in a Spanish savanna, adapted to a long summer drought. We found that nitrogen (N) additions led to more root biomass but number of roots was higher with N and phosphorus together. These effects were strongly affected by the time of year. In autumn root growth occurred after leaf production. This has implications for how we understand biomass production and carbon uptake in these systems.
Biagio Di Mauro, Roberto Garzonio, Micol Rossini, Gianluca Filippa, Paolo Pogliotti, Marta Galvagno, Umberto Morra di Cella, Mirco Migliavacca, Giovanni Baccolo, Massimiliano Clemenza, Barbara Delmonte, Valter Maggi, Marie Dumont, François Tuzet, Matthieu Lafaysse, Samuel Morin, Edoardo Cremonese, and Roberto Colombo
The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, https://doi.org/10.5194/tc-13-1147-2019, 2019
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The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt. We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event. This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.
Xiaolu Tang, Nuno Carvalhais, Catarina Moura, Bernhard Ahrens, Sujan Koirala, Shaohui Fan, Fengying Guan, Wenjie Zhang, Sicong Gao, Vincenzo Magliulo, Pauline Buysse, Shibin Liu, Guo Chen, Wunian Yang, Zhen Yu, Jingjing Liang, Leilei Shi, Shenyan Pu, and Markus Reichstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-37, https://doi.org/10.5194/bg-2019-37, 2019
Preprint withdrawn
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Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass. This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls. Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.
Boaz Hilman, Jan Muhr, Susan E. Trumbore, Norbert Kunert, Mariah S. Carbone, Päivi Yuval, S. Joseph Wright, Gerardo Moreno, Oscar Pérez-Priego, Mirco Migliavacca, Arnaud Carrara, José M. Grünzweig, Yagil Osem, Tal Weiner, and Alon Angert
Biogeosciences, 16, 177–191, https://doi.org/10.5194/bg-16-177-2019, https://doi.org/10.5194/bg-16-177-2019, 2019
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Combined measurement of CO2 / O2 fluxes in tree stems suggested that on average 41 % of the respired CO2 was not emitted locally to the atmosphere. This finding strengthens the recognition that CO2 efflux from tree stems is not an accurate measure of respiration. The CO2 / O2 fluxes did not vary as expected if CO2 dissolution in the xylem sap was the main driver for the CO2 retention. We suggest the examination of refixation of respired CO2 as a possible mechanism for CO2 retention.
Sophia Walther, Luis Guanter, Birgit Heim, Martin Jung, Gregory Duveiller, Aleksandra Wolanin, and Torsten Sachs
Biogeosciences, 15, 6221–6256, https://doi.org/10.5194/bg-15-6221-2018, https://doi.org/10.5194/bg-15-6221-2018, 2018
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We explored the timing of the peak of the short annual growing season in tundra ecosystems as indicated by an extensive suite of satellite indicators of vegetation productivity. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. Plants also experience growth after optimal conditions for assimilation regarding light and temperature have passed. Our results have implications for the modelling of the circumpolar carbon balance.
Thomas Wutzler, Antje Lucas-Moffat, Mirco Migliavacca, Jürgen Knauer, Kerstin Sickel, Ladislav Šigut, Olaf Menzer, and Markus Reichstein
Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, https://doi.org/10.5194/bg-15-5015-2018, 2018
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Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main source for understanding biosphere–atmosphere interactions. However, there is a need for more usable and extensible tools for post-processing steps of the half-hourly flux data. Therefore, we developed the REddyProc package, providing data filtering, gap filling, and flux partitioning. The extensible functions are compatible with state-of-the-art tools but allow easier integration in extended analysis.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung
Hydrol. Earth Syst. Sci., 22, 4061–4082, https://doi.org/10.5194/hess-22-4061-2018, https://doi.org/10.5194/hess-22-4061-2018, 2018
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In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage. We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis. While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Jacob A. Nelson, Nuno Carvalhais, Mirco Migliavacca, Markus Reichstein, and Martin Jung
Biogeosciences, 15, 2433–2447, https://doi.org/10.5194/bg-15-2433-2018, https://doi.org/10.5194/bg-15-2433-2018, 2018
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Plants have typical daily carbon uptake and water loss cycles. However, these cycles may change under periods of duress, such as water limitation. Here we identify two types of patterns in response to water limitations: a tendency to lose more water in the morning than afternoon and a decoupling of the carbon and water cycles. The findings show differences in responses by trees and grasses and suggest that morning shifts may be more efficient at gaining carbon per unit water used.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
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Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, https://doi.org/10.5194/gmd-11-497-2018, 2018
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Northern peatlands store large amount of soil carbon and are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth was not well predicted but had only small influence on simulated NEE.
Eugene F. Mikhailov, Svetlana Mironova, Gregory Mironov, Sergey Vlasenko, Alexey Panov, Xuguang Chi, David Walter, Samara Carbone, Paulo Artaxo, Martin Heimann, Jost Lavric, Ulrich Pöschl, and Meinrat O. Andreae
Atmos. Chem. Phys., 17, 14365–14392, https://doi.org/10.5194/acp-17-14365-2017, https://doi.org/10.5194/acp-17-14365-2017, 2017
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Iulia Ilie, Peter Dittrich, Nuno Carvalhais, Martin Jung, Andreas Heinemeyer, Mirco Migliavacca, James I. L. Morison, Sebastian Sippel, Jens-Arne Subke, Matthew Wilkinson, and Miguel D. Mahecha
Geosci. Model Dev., 10, 3519–3545, https://doi.org/10.5194/gmd-10-3519-2017, https://doi.org/10.5194/gmd-10-3519-2017, 2017
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Accurate representation of land-atmosphere carbon fluxes is essential for future climate projections, although some of the responses of CO2 fluxes to climate often remain uncertain. The increase in available data allows for new approaches in their modelling. We automatically developed models for ecosystem and soil carbon respiration using a machine learning approach. When compared with established respiration models, we found that they are better in prediction as well as offering new insights.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
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We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017, https://doi.org/10.5194/bg-14-3685-2017, 2017
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Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere. A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. Our primary goal is to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in situ observatories.
Sven Boese, Martin Jung, Nuno Carvalhais, and Markus Reichstein
Biogeosciences, 14, 3015–3026, https://doi.org/10.5194/bg-14-3015-2017, https://doi.org/10.5194/bg-14-3015-2017, 2017
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For plants, the ratio of carbon uptake to water loss by transpiration is usually thought to depend on characteristic properties (their adaption to water scarcity) and the dryness of the atmosphere at any given moment. We show that, on the ecosystem scale, radiation has an independent effect on this ratio that had not been previously considered. When including this variable in models, predictions of transpiration improve considerably.
Christian Brümmer, Bjarne Lyshede, Dirk Lempio, Jean-Pierre Delorme, Jeremy J. Rüffer, Roland Fuß, Antje M. Moffat, Miriam Hurkuck, Andreas Ibrom, Per Ambus, Heinz Flessa, and Werner L. Kutsch
Biogeosciences, 14, 1365–1381, https://doi.org/10.5194/bg-14-1365-2017, https://doi.org/10.5194/bg-14-1365-2017, 2017
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We present a novel chamber design for measuring soil–atmosphere N2O fluxes and compare the performance of a commonly applied gas chromatography (GC) setup with laser-based (QCL) concentration detection. While GC was still a useful method for longer-term investigations, we found that closure times of 10 min and sampling every 5 s is sufficient when using a QCL system. Further, extremely low standard errors (< 2 % of flux value) were observed regardless of linear or exponential flux calculation.
Frederik Schrader, Christian Brümmer, Chris R. Flechard, Roy J. Wichink Kruit, Margreet C. van Zanten, Undine Zöll, Arjan Hensen, and Jan Willem Erisman
Atmos. Chem. Phys., 16, 13417–13430, https://doi.org/10.5194/acp-16-13417-2016, https://doi.org/10.5194/acp-16-13417-2016, 2016
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We found a systematic mismatch of modeled and measured NH3 fluxes using two state-of-the-art dry deposition models and data from five sites in Europe. Results of our analysis indicate a too large minimum non-stomatal resistance and too strong temperature response in the parameterization of a unidirectional surface–atmosphere exchange scheme, as well as room for improvement on the emission potential parameterization of a bidirectional model, both directly impacting predicted NH3 exchange fluxes.
Undine Zöll, Christian Brümmer, Frederik Schrader, Christof Ammann, Andreas Ibrom, Christophe R. Flechard, David D. Nelson, Mark Zahniser, and Werner L. Kutsch
Atmos. Chem. Phys., 16, 11283–11299, https://doi.org/10.5194/acp-16-11283-2016, https://doi.org/10.5194/acp-16-11283-2016, 2016
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Accurate quantification of atmospheric ammonia concentration and exchange fluxes with the land surface has been a major metrological challenge. We demonstrate the applicability of a novel laser device to identify concentration and flux patterns over a peatland ecosystem influenced by nearby agricultural practices. Results help to strengthen air quality monitoring networks, lead to better understanding of ecosystem functionality and improve parameterizations in air chemistry and transport models.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
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We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
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How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
B. Di Mauro, F. Fava, P. Frattini, A. Camia, R. Colombo, and M. Migliavacca
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npgd-2-1553-2015, https://doi.org/10.5194/npgd-2-1553-2015, 2015
Preprint withdrawn
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In this paper, we analyse the probability distribution of wildfires burned area at European scale. We evaluate the performance of a land surface model using power law scaling as a benchmark. Our analysis suggests that only high latitude biomes are described by a power law distribution, and we relate this feature with the less impact of antrhopogenic activity. The benchmarking analysis showed that some refinements are needed in the model structure for reproducing emerging properties of wildfires
O. Perez-Priego, J. Guan, M. Rossini, F. Fava, T. Wutzler, G. Moreno, N. Carvalhais, A. Carrara, O. Kolle, T. Julitta, M. Schrumpf, M. Reichstein, and M. Migliavacca
Biogeosciences, 12, 6351–6367, https://doi.org/10.5194/bg-12-6351-2015, https://doi.org/10.5194/bg-12-6351-2015, 2015
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Sun-induced chlorophyll fluorescence and photochemical reflectance index revealed controls of climate and nutrient availability on photosynthesis (gross primary production, GPP). Meteo-driven models (MMs) were unable to describe nutrient-induced effects on GPP. Important implications can be derived from these results, and uncertainties in the prediction of global GPP still remain when MMs do not account for plant nutrient availability.
L. Wingate, J. Ogée, E. Cremonese, G. Filippa, T. Mizunuma, M. Migliavacca, C. Moisy, M. Wilkinson, C. Moureaux, G. Wohlfahrt, A. Hammerle, L. Hörtnagl, C. Gimeno, A. Porcar-Castell, M. Galvagno, T. Nakaji, J. Morison, O. Kolle, A. Knohl, W. Kutsch, P. Kolari, E. Nikinmaa, A. Ibrom, B. Gielen, W. Eugster, M. Balzarolo, D. Papale, K. Klumpp, B. Köstner, T. Grünwald, R. Joffre, J.-M. Ourcival, M. Hellstrom, A. Lindroth, C. George, B. Longdoz, B. Genty, J. Levula, B. Heinesch, M. Sprintsin, D. Yakir, T. Manise, D. Guyon, H. Ahrends, A. Plaza-Aguilar, J. H. Guan, and J. Grace
Biogeosciences, 12, 5995–6015, https://doi.org/10.5194/bg-12-5995-2015, https://doi.org/10.5194/bg-12-5995-2015, 2015
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The timing of plant development stages and their response to climate and management were investigated using a network of digital cameras installed across different European ecosystems. Using the relative red, green and blue content of images we showed that the green signal could be used to estimate the length of the growing season in broadleaf forests. We also developed a model that predicted the seasonal variations of camera RGB signals and how they relate to leaf pigment content and area well.
M. Hannes, U. Wollschläger, F. Schrader, W. Durner, S. Gebler, T. Pütz, J. Fank, G. von Unold, and H.-J. Vogel
Hydrol. Earth Syst. Sci., 19, 3405–3418, https://doi.org/10.5194/hess-19-3405-2015, https://doi.org/10.5194/hess-19-3405-2015, 2015
S. Hashimoto, N. Carvalhais, A. Ito, M. Migliavacca, K. Nishina, and M. Reichstein
Biogeosciences, 12, 4121–4132, https://doi.org/10.5194/bg-12-4121-2015, https://doi.org/10.5194/bg-12-4121-2015, 2015
A. C. Spessa, R. D. Field, F. Pappenberger, A. Langner, S. Englhart, U. Weber, T. Stockdale, F. Siegert, J. W. Kaiser, and J. Moore
Nat. Hazards Earth Syst. Sci., 15, 429–442, https://doi.org/10.5194/nhess-15-429-2015, https://doi.org/10.5194/nhess-15-429-2015, 2015
M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, and K. Thonicke
Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, https://doi.org/10.5194/bg-11-7025-2014, 2014
S. Vicca, M. Bahn, M. Estiarte, E. E. van Loon, R. Vargas, G. Alberti, P. Ambus, M. A. Arain, C. Beier, L. P. Bentley, W. Borken, N. Buchmann, S. L. Collins, G. de Dato, J. S. Dukes, C. Escolar, P. Fay, G. Guidolotti, P. J. Hanson, A. Kahmen, G. Kröel-Dulay, T. Ladreiter-Knauss, K. S. Larsen, E. Lellei-Kovacs, E. Lebrija-Trejos, F. T. Maestre, S. Marhan, M. Marshall, P. Meir, Y. Miao, J. Muhr, P. A. Niklaus, R. Ogaya, J. Peñuelas, C. Poll, L. E. Rustad, K. Savage, A. Schindlbacher, I. K. Schmidt, A. R. Smith, E. D. Sotta, V. Suseela, A. Tietema, N. van Gestel, O. van Straaten, S. Wan, U. Weber, and I. A. Janssens
Biogeosciences, 11, 2991–3013, https://doi.org/10.5194/bg-11-2991-2014, https://doi.org/10.5194/bg-11-2991-2014, 2014
W. Knorr, T. Kaminski, A. Arneth, and U. Weber
Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, https://doi.org/10.5194/bg-11-1085-2014, 2014
X. Chi, J. Winderlich, J.-C. Mayer, A. V. Panov, M. Heimann, W. Birmili, J. Heintzenberg, Y. Cheng, and M. O. Andreae
Atmos. Chem. Phys., 13, 12271–12298, https://doi.org/10.5194/acp-13-12271-2013, https://doi.org/10.5194/acp-13-12271-2013, 2013
B. Badawy, C. Rödenbeck, M. Reichstein, N. Carvalhais, and M. Heimann
Biogeosciences, 10, 6485–6508, https://doi.org/10.5194/bg-10-6485-2013, https://doi.org/10.5194/bg-10-6485-2013, 2013
Related subject area
Biogeochemistry: Land
Cropland expansion drives vegetation greenness decline in Southeast Asia
How to measure the efficiency of bioenergy crops compared to forestation
Implications of climate and litter quality for simulations of litterbag decomposition at high latitudes
Soil carbon-concentration and carbon-climate feedbacks in CMIP6 Earth system models
Monitoring the impact of forest changes on carbon uptake with solar-induced fluorescence measurements from GOME-2A and TROPOMI for an Australian and Chinese case study
Technical note: Flagging inconsistencies in flux tower data
Relevance of near-surface soil moisture vs. terrestrial water storage for global vegetation functioning
Comparison of shortwave radiation dynamics between boreal forest and open peatland pairs in southern and northern Finland
High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra
Long-term additions of ammonium nitrate to montane forest ecosystems may cause limited soil acidification, even in the presence of soil carbonate
Leaf carbon and nitrogen stoichiometric variation along environmental gradients
Gross primary productivity and the predictability of CO2: more uncertainty in what we predict than how well we predict it
Scale variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using model–data fusion
Seasonal controls override forest harvesting effects on the composition of dissolved organic matter mobilized from boreal forest soil organic horizons
Carbon cycle extremes accelerate weakening of the land carbon sink in the late 21st century
Estimating oil-palm Si storage, Si return to soils, and Si losses through harvest in smallholder oil-palm plantations of Sumatra, Indonesia
Assessing the sensitivity of multi-frequency passive microwave vegetation optical depth to vegetation properties
Seasonal variation of mercury concentration of ancient olive groves of Lebanon
Soil organic matter diagenetic state informs boreal forest ecosystem feedbacks to climate change
Upscaling dryland carbon and water fluxes with artificial neural networks of optical, thermal, and microwave satellite remote sensing
Sun-induced fluorescence as a proxy for primary productivity across vegetation types and climates
Changing sub-Arctic tundra vegetation upon permafrost degradation: impact on foliar mineral element cycling
Land Management Contributes significantly to observed Vegetation Browning in Syria during 2001–2018
MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas
Assessing the representation of the Australian carbon cycle in global vegetation models
Assessing the response of soil carbon in Australia to changing inputs and climate using a consistent modelling framework
Reviews and syntheses: Ongoing and emerging opportunities to improve environmental science using observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites
First pan-Arctic assessment of dissolved organic carbon in lakes of the permafrost region
The impact of wildfire on biogeochemical fluxes and water quality in boreal catchments
Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño
Subalpine grassland productivity increased with warmer and drier conditions, but not with higher N deposition, in an altitudinal transplantation experiment
Reviews and syntheses: Impacts of plant-silica–herbivore interactions on terrestrial biogeochemical cycling
Implementation of nitrogen cycle in the CLASSIC land model
Combined effects of ozone and drought stress on the emission of biogenic volatile organic compounds from Quercus robur L.
A bottom-up quantification of foliar mercury uptake fluxes across Europe
Lagged effects regulate the inter-annual variability of the tropical carbon balance
Spatial variations in terrestrial net ecosystem productivity and its local indicators
Nitrogen cycling in CMIP6 land surface models: progress and limitations
Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest
Sensitivity of 21st century simulated ecosystem indicators to model parameters, prescribed climate drivers, RCP scenarios and forest management actions for two Finnish boreal forest sites
Summarizing the state of the terrestrial biosphere in few dimensions
Patterns and trends of the dominant environmental controls of net biome productivity
Localized basal area affects soil respiration temperature sensitivity in a coastal deciduous forest
Dissolved organic carbon mobilized from organic horizons of mature and harvested black spruce plots in a mesic boreal region
Ideas and perspectives: Proposed best practices for collaboration at cross-disciplinary observatories
Effects of leaf length and development stage on the triple oxygen isotope signature of grass leaf water and phytoliths: insights for a proxy of continental atmospheric humidity
Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models
Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar
Theoretical uncertainties for global satellite-derived burned area estimates
Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model
Ruiying Zhao, Xiangzhong Luo, Yuheng Yang, Luri Nurlaila Syahid, Chi Chen, and Janice Ser Huay Lee
Biogeosciences, 21, 5393–5406, https://doi.org/10.5194/bg-21-5393-2024, https://doi.org/10.5194/bg-21-5393-2024, 2024
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Southeast Asia has been a global hot spot of land-use change over the past 50 years. Meanwhile, it also hosts some of the most carbon-dense and diverse ecosystems in the world. Here, we explore the impact of land-use change, along with other environmental factors, on the ecosystem in Southeast Asia. We find that elevated CO2 imposed a positive impact on vegetation greenness, but the positive impact was largely offset by intensive land-use changes in the region, particularly cropland expansion.
Sabine Egerer, Stefanie Falk, Dorothea Mayer, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Biogeosciences, 21, 5005–5025, https://doi.org/10.5194/bg-21-5005-2024, https://doi.org/10.5194/bg-21-5005-2024, 2024
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Using a state-of-the-art land model, we find that bioenergy plants can store carbon more efficiently than forests over long periods in the soil, in geological reservoirs, or by substituting fossil-fuel-based energy. Planting forests is more suitable for reaching climate targets by 2050. The carbon removal potential depends also on local environmental conditions. These considerations have important implications for climate policy, spatial planning, nature conservation, and agriculture.
Elin Ristorp Aas, Inge Althuizen, Hui Tang, Sonya Geange, Eva Lieungh, Vigdis Vandvik, and Terje Koren Berntsen
Biogeosciences, 21, 3789–3817, https://doi.org/10.5194/bg-21-3789-2024, https://doi.org/10.5194/bg-21-3789-2024, 2024
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We used a soil model to replicate two litterbag decomposition experiments to examine the implications of climate, litter quality, and soil microclimate representation. We found that macroclimate was more important than litter quality for modeled mass loss. By comparing different representations of soil temperature and moisture we found that using observed data did not improve model results. We discuss causes for this and suggest possible improvements to both the model and experimental design.
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 21, 2759–2776, https://doi.org/10.5194/bg-21-2759-2024, https://doi.org/10.5194/bg-21-2759-2024, 2024
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Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meeting Paris Agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils in the land response is highlighted.
Juliëtte C. S. Anema, Klaas Folkert Boersma, Piet Stammes, Gerbrand Koren, William Woodgate, Philipp Köhler, Christian Frankenberg, and Jacqui Stol
Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
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To keep the Paris agreement goals within reach, negative emissions are necessary. They can be achieved with mitigation techniques, such as reforestation, which remove CO2 from the atmosphere. While governments have pinned their hopes on them, there is not yet a good set of tools to objectively determine whether negative emissions do what they promise. Here we show how satellite measurements of plant fluorescence are useful in detecting carbon uptake due to reforestation and vegetation regrowth.
Martin Jung, Jacob Nelson, Mirco Migliavacca, Tarek El-Madany, Dario Papale, Markus Reichstein, Sophia Walther, and Thomas Wutzler
Biogeosciences, 21, 1827–1846, https://doi.org/10.5194/bg-21-1827-2024, https://doi.org/10.5194/bg-21-1827-2024, 2024
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We present a methodology to detect inconsistencies in perhaps the most important data source for measurements of ecosystem–atmosphere carbon, water, and energy fluxes. We expect that the derived consistency flags will be relevant for data users and will help in improving our understanding of and our ability to model ecosystem–climate interactions.
Prajwal Khanal, Anne J. Hoek Van Dijke, Timo Schaffhauser, Wantong Li, Sinikka J. Paulus, Chunhui Zhan, and René Orth
Biogeosciences, 21, 1533–1547, https://doi.org/10.5194/bg-21-1533-2024, https://doi.org/10.5194/bg-21-1533-2024, 2024
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Water availability is essential for vegetation functioning, but the depth of vegetation water uptake is largely unknown due to sparse ground measurements. This study correlates vegetation growth with soil moisture availability globally to infer vegetation water uptake depth using only satellite-based data. We find that the vegetation water uptake depth varies across climate regimes and vegetation types and also changes during dry months at a global scale.
Otso Peräkylä, Erkka Rinne, Ekaterina Ezhova, Anna Lintunen, Annalea Lohila, Juho Aalto, Mika Aurela, Pasi Kolari, and Markku Kulmala
EGUsphere, https://doi.org/10.5194/egusphere-2024-712, https://doi.org/10.5194/egusphere-2024-712, 2024
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Forests are seen as beneficial for climate. Yet, in areas with snow, trees break up the white snow surface, and absorb more sunlight than open areas. This has a warming effect, negating some of the climate benefit of trees. We studied two pairs of an open peatland and a forest in Finland. We found that the later the snow melts, the larger the difference in absorbed sunlight between forests and peatlands. This has implications for the future, as snow cover duration is affected by global warming.
Anna-Maria Virkkala, Pekka Niittynen, Julia Kemppinen, Maija E. Marushchak, Carolina Voigt, Geert Hensgens, Johanna Kerttula, Konsta Happonen, Vilna Tyystjärvi, Christina Biasi, Jenni Hultman, Janne Rinne, and Miska Luoto
Biogeosciences, 21, 335–355, https://doi.org/10.5194/bg-21-335-2024, https://doi.org/10.5194/bg-21-335-2024, 2024
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Arctic greenhouse gas (GHG) fluxes of CO2, CH4, and N2O are important for climate feedbacks. We combined extensive in situ measurements and remote sensing data to develop machine-learning models to predict GHG fluxes at a 2 m resolution across a tundra landscape. The analysis revealed that the system was a net GHG sink and showed widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale.
Thomas Baer, Gerhard Furrer, Stephan Zimmermann, and Patrick Schleppi
Biogeosciences, 20, 4577–4589, https://doi.org/10.5194/bg-20-4577-2023, https://doi.org/10.5194/bg-20-4577-2023, 2023
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Nitrogen (N) deposition to forest ecosystems is a matter of concern because it affects their nutrient status and makes their soil acidic. We observed an ongoing acidification in a montane forest in central Switzerland even if the subsoil of this site contains carbonates and is thus well buffered. We experimentally added N to simulate a higher pollution, and this increased the acidification. After 25 years of study, however, we can see the first signs of recovery, also under higher N deposition.
Huiying Xu, Han Wang, Iain Colin Prentice, and Sandy P. Harrison
Biogeosciences, 20, 4511–4525, https://doi.org/10.5194/bg-20-4511-2023, https://doi.org/10.5194/bg-20-4511-2023, 2023
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Leaf carbon (C) and nitrogen (N) are crucial elements in leaf construction and physiological processes. This study reconciled the roles of phylogeny, species identity, and climate in stoichiometric traits at individual and community levels. The variations in community-level leaf N and C : N ratio were captured by optimality-based models using climate data. Our results provide an approach to improve the representation of leaf stoichiometry in vegetation models to better couple N with C cycling.
István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
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Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Keri L. Bowering, Kate A. Edwards, and Susan E. Ziegler
Biogeosciences, 20, 2189–2206, https://doi.org/10.5194/bg-20-2189-2023, https://doi.org/10.5194/bg-20-2189-2023, 2023
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Dissolved organic matter (DOM) mobilized from surface soils is a source of carbon (C) for deeper mineral horizons but also a mechanism of C loss. Composition of DOM mobilized in boreal forests varied more by season than as a result of forest harvesting. Results suggest reduced snowmelt and increased fall precipitation enhance DOM properties promoting mineral soil C stores. These findings, coupled with hydrology, can inform on soil C fate and boreal forest C balance in response to climate change.
Bharat Sharma, Jitendra Kumar, Auroop R. Ganguly, and Forrest M. Hoffman
Biogeosciences, 20, 1829–1841, https://doi.org/10.5194/bg-20-1829-2023, https://doi.org/10.5194/bg-20-1829-2023, 2023
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Rising atmospheric carbon dioxide increases vegetation growth and causes more heatwaves and droughts. The impact of such climate extremes is detrimental to terrestrial carbon uptake capacity. We found that due to overall climate warming, about 88 % of the world's regions towards the end of 2100 will show anomalous losses in net biospheric productivity (NBP) rather than gains. More than 50 % of all negative NBP extremes were driven by the compound effect of dry, hot, and fire conditions.
Britta Greenshields, Barbara von der Lühe, Felix Schwarz, Harold J. Hughes, Aiyen Tjoa, Martyna Kotowska, Fabian Brambach, and Daniela Sauer
Biogeosciences, 20, 1259–1276, https://doi.org/10.5194/bg-20-1259-2023, https://doi.org/10.5194/bg-20-1259-2023, 2023
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Silicon (Si) can have multiple beneficial effects on crops such as oil palms. In this study, we quantified Si concentrations in various parts of an oil palm (leaflets, rachises, fruit-bunch parts) to derive Si storage estimates for the total above-ground biomass of an oil palm and 1 ha of an oil-palm plantation. We proposed a Si balance by identifying Si return (via palm fronds) and losses (via harvest) in the system and recommend management measures that enhance Si cycling.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Nagham Tabaja, David Amouroux, Lamis Chalak, François Fourel, Emmanuel Tessier, Ihab Jomaa, Milad El Riachy, and Ilham Bentaleb
Biogeosciences, 20, 619–633, https://doi.org/10.5194/bg-20-619-2023, https://doi.org/10.5194/bg-20-619-2023, 2023
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This study investigates the seasonality of the mercury (Hg) concentration of olive trees. Hg concentrations of foliage, stems, soil surface, and litter were analyzed on a monthly basis in ancient olive trees growing in two groves in Lebanon. Our study draws an adequate baseline for the eastern Mediterranean and for the region with similar climatic inventories on Hg vegetation uptake in addition to being a baseline for new studies on olive trees in the Mediterranean.
Allison N. Myers-Pigg, Karl Kaiser, Ronald Benner, and Susan E. Ziegler
Biogeosciences, 20, 489–503, https://doi.org/10.5194/bg-20-489-2023, https://doi.org/10.5194/bg-20-489-2023, 2023
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Boreal forests, historically a global sink for atmospheric CO2, store carbon in vast soil reservoirs. To predict how such stores will respond to climate warming we need to understand climate–ecosystem feedbacks. We find boreal forest soil carbon stores are maintained through enhanced nitrogen cycling with climate warming, providing direct evidence for a key feedback. Further application of the approach demonstrated here will improve our understanding of the limits of climate–ecosystem feedbacks.
Matthew P. Dannenberg, Mallory L. Barnes, William K. Smith, Miriam R. Johnston, Susan K. Meerdink, Xian Wang, Russell L. Scott, and Joel A. Biederman
Biogeosciences, 20, 383–404, https://doi.org/10.5194/bg-20-383-2023, https://doi.org/10.5194/bg-20-383-2023, 2023
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Earth's drylands provide ecosystem services to many people and will likely be strongly affected by climate change, but it is quite challenging to monitor the productivity and water use of dryland plants with satellites. We developed and tested an approach for estimating dryland vegetation activity using machine learning to combine information from multiple satellite sensors. Our approach excelled at estimating photosynthesis and water use largely due to the inclusion of satellite soil moisture.
Mark Pickering, Alessandro Cescatti, and Gregory Duveiller
Biogeosciences, 19, 4833–4864, https://doi.org/10.5194/bg-19-4833-2022, https://doi.org/10.5194/bg-19-4833-2022, 2022
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This study explores two of the most recent products in carbon productivity estimation, FLUXCOM gross primary productivity (GPP), calculated by upscaling local measurements of CO2 exchange, and remotely sensed sun-induced chlorophyll a fluorescence (SIF). High-resolution SIF data are valuable in demonstrating similarity in the SIF–GPP relationship between vegetation covers, provide an independent probe of the FLUXCOM GPP model and demonstrate the response of SIF to meteorological fluctuations.
Elisabeth Mauclet, Yannick Agnan, Catherine Hirst, Arthur Monhonval, Benoît Pereira, Aubry Vandeuren, Maëlle Villani, Justin Ledman, Meghan Taylor, Briana L. Jasinski, Edward A. G. Schuur, and Sophie Opfergelt
Biogeosciences, 19, 2333–2351, https://doi.org/10.5194/bg-19-2333-2022, https://doi.org/10.5194/bg-19-2333-2022, 2022
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Arctic warming and permafrost degradation largely affect tundra vegetation. Wetter lowlands show an increase in sedges, whereas drier uplands favor shrub expansion. Here, we demonstrate that the difference in the foliar elemental composition of typical tundra vegetation species controls the change in local foliar elemental stock and potential mineral element cycling through litter production upon a shift in tundra vegetation.
Tiexi Chen, Renjie Guo, Qingyun Yan, Xin Chen, Shengjie Zhou, Chuanzhuang Liang, Xueqiong Wei, and Han Dolman
Biogeosciences, 19, 1515–1525, https://doi.org/10.5194/bg-19-1515-2022, https://doi.org/10.5194/bg-19-1515-2022, 2022
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Currently people are very concerned about vegetation changes and their driving factors, including natural and anthropogenic drivers. In this study, a general browning trend is found in Syria during 2001–2018, indicated by the vegetation index. We found that land management caused by social unrest is the main cause of this browning phenomenon. The mechanism initially reported here highlights the importance of land management impacts at the regional scale.
Rahayu Adzhar, Douglas I. Kelley, Ning Dong, Charles George, Mireia Torello Raventos, Elmar Veenendaal, Ted R. Feldpausch, Oliver L. Phillips, Simon L. Lewis, Bonaventure Sonké, Herman Taedoumg, Beatriz Schwantes Marimon, Tomas Domingues, Luzmila Arroyo, Gloria Djagbletey, Gustavo Saiz, and France Gerard
Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, https://doi.org/10.5194/bg-19-1377-2022, 2022
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The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
Biogeosciences, 18, 5185–5202, https://doi.org/10.5194/bg-18-5185-2021, https://doi.org/10.5194/bg-18-5185-2021, 2021
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We performed Roth C simulations across Australia and assessed the response of soil carbon to changing inputs and future climate change using a consistent modelling framework. Site-specific initialisation of the C pools with measurements of the C fractions is essential for accurate simulations of soil organic C stocks and composition at a large scale. With further warming, Australian soils will become more vulnerable to C loss: natural environments > native grazing > cropping > modified grazing.
Anam M. Khan, Paul C. Stoy, James T. Douglas, Martha Anderson, George Diak, Jason A. Otkin, Christopher Hain, Elizabeth M. Rehbein, and Joel McCorkel
Biogeosciences, 18, 4117–4141, https://doi.org/10.5194/bg-18-4117-2021, https://doi.org/10.5194/bg-18-4117-2021, 2021
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Remote sensing has played an important role in the study of land surface processes. Geostationary satellites, such as the GOES-R series, can observe the Earth every 5–15 min, providing us with more observations than widely used polar-orbiting satellites. Here, we outline current efforts utilizing geostationary observations in environmental science and look towards the future of GOES observations in the carbon cycle, ecosystem disturbance, and other areas of application in environmental science.
Lydia Stolpmann, Caroline Coch, Anne Morgenstern, Julia Boike, Michael Fritz, Ulrike Herzschuh, Kathleen Stoof-Leichsenring, Yury Dvornikov, Birgit Heim, Josefine Lenz, Amy Larsen, Katey Walter Anthony, Benjamin Jones, Karen Frey, and Guido Grosse
Biogeosciences, 18, 3917–3936, https://doi.org/10.5194/bg-18-3917-2021, https://doi.org/10.5194/bg-18-3917-2021, 2021
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Our new database summarizes DOC concentrations of 2167 water samples from 1833 lakes in permafrost regions across the Arctic to provide insights into linkages between DOC and environment. We found increasing lake DOC concentration with decreasing permafrost extent and higher DOC concentrations in boreal permafrost sites compared to tundra sites. Our study shows that DOC concentration depends on the environmental properties of a lake, especially permafrost extent, ecoregion, and vegetation.
Gustaf Granath, Christopher D. Evans, Joachim Strengbom, Jens Fölster, Achim Grelle, Johan Strömqvist, and Stephan J. Köhler
Biogeosciences, 18, 3243–3261, https://doi.org/10.5194/bg-18-3243-2021, https://doi.org/10.5194/bg-18-3243-2021, 2021
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We measured element losses and impacts on water quality following a wildfire in Sweden. We observed the largest carbon and nitrogen losses during the fire and a strong pulse of elements 1–3 months after the fire that showed a fast (weeks) and a slow (months) release from the catchments. Total carbon export through water did not increase post-fire. Overall, we observed a rapid recovery of the biogeochemical cycling of elements within 3 years but still an annual net release of carbon dioxide.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, and Benjamin Smith
Biogeosciences, 18, 2181–2203, https://doi.org/10.5194/bg-18-2181-2021, https://doi.org/10.5194/bg-18-2181-2021, 2021
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The El Niño–Southern Oscillation (ENSO) describes changes in the sea surface temperature patterns of the Pacific Ocean. This influences the global weather, impacting vegetation on land. There are two types of El Niño: central Pacific (CP) and eastern Pacific (EP). In this study, we explored the long-term impacts on the carbon balance on land linked to the two El Niño types. Using a dynamic vegetation model, we simulated what would happen if only either CP or EP El Niño events had occurred.
Matthias Volk, Matthias Suter, Anne-Lena Wahl, and Seraina Bassin
Biogeosciences, 18, 2075–2090, https://doi.org/10.5194/bg-18-2075-2021, https://doi.org/10.5194/bg-18-2075-2021, 2021
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Grassland ecosystem services like forage production and greenhouse gas storage in the soil depend on plant growth.
In an experiment in the mountains with warming treatments, we found that despite dwindling soil water content, the grassland growth increased with up to +1.3 °C warming (annual mean) compared to present temperatures. Even at +2.4 °C the growth was still larger than at the reference site.
This suggests that plant growth will increase due to global warming in the near future.
Bernice C. Hwang and Daniel B. Metcalfe
Biogeosciences, 18, 1259–1268, https://doi.org/10.5194/bg-18-1259-2021, https://doi.org/10.5194/bg-18-1259-2021, 2021
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Despite growing recognition of herbivores as important ecosystem engineers, many major gaps remain in our understanding of how silicon and herbivory interact to shape biogeochemical processes. We highlight the need for more research particularly in natural settings as well as on the potential effects of herbivory on terrestrial silicon cycling to understand potentially critical animal–plant–soil feedbacks.
Ali Asaadi and Vivek K. Arora
Biogeosciences, 18, 669–706, https://doi.org/10.5194/bg-18-669-2021, https://doi.org/10.5194/bg-18-669-2021, 2021
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More than a quarter of the current anthropogenic CO2 emissions are taken up by land, reducing the atmospheric CO2 growth rate. This is because of the CO2 fertilization effect which benefits 80 % of global vegetation. However, if nitrogen and phosphorus nutrients cannot keep up with increasing atmospheric CO2, the magnitude of this terrestrial ecosystem service may reduce in future. This paper implements nitrogen constraints on photosynthesis in a model to understand the mechanisms involved.
Arianna Peron, Lisa Kaser, Anne Charlott Fitzky, Martin Graus, Heidi Halbwirth, Jürgen Greiner, Georg Wohlfahrt, Boris Rewald, Hans Sandén, and Thomas Karl
Biogeosciences, 18, 535–556, https://doi.org/10.5194/bg-18-535-2021, https://doi.org/10.5194/bg-18-535-2021, 2021
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Drought events are expected to become more frequent with climate change. Along with these events atmospheric ozone is also expected to increase. Both can stress plants. Here we investigate to what extent these factors modulate the emission of volatile organic compounds (VOCs) from oak plants. We find an antagonistic effect between drought stress and ozone, impacting the emission of different BVOCs, which is indirectly controlled by stomatal opening, allowing plants to control their water budget.
Lena Wohlgemuth, Stefan Osterwalder, Carl Joseph, Ansgar Kahmen, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 17, 6441–6456, https://doi.org/10.5194/bg-17-6441-2020, https://doi.org/10.5194/bg-17-6441-2020, 2020
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Mercury uptake by trees from the air represents an important but poorly quantified pathway in the global mercury cycle. We determined mercury uptake fluxes by leaves and needles at 10 European forests which were 4 times larger than mercury deposition via rainfall. The amount of mercury taken up by leaves and needles depends on their age and growing height on the tree. Scaling up our measurements to the forest area of Europe, we estimate that each year 20 t of mercury is taken up by trees.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
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Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Rui Cheng, Troy S. Magney, Debsunder Dutta, David R. Bowling, Barry A. Logan, Sean P. Burns, Peter D. Blanken, Katja Grossmann, Sophia Lopez, Andrew D. Richardson, Jochen Stutz, and Christian Frankenberg
Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, https://doi.org/10.5194/bg-17-4523-2020, 2020
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We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
Jarmo Mäkelä, Francesco Minunno, Tuula Aalto, Annikki Mäkelä, Tiina Markkanen, and Mikko Peltoniemi
Biogeosciences, 17, 2681–2700, https://doi.org/10.5194/bg-17-2681-2020, https://doi.org/10.5194/bg-17-2681-2020, 2020
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We assess the relative magnitude of uncertainty sources on ecosystem indicators of the 21st century climate change on two boreal forest sites. In addition to RCP and climate model uncertainties, we included the overlooked model parameter uncertainty and management actions in our analysis. Management was the dominant uncertainty factor for the more verdant southern site, followed by RCP, climate and parameter uncertainties. The uncertainties were estimated with canonical correlation analysis.
Guido Kraemer, Gustau Camps-Valls, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 17, 2397–2424, https://doi.org/10.5194/bg-17-2397-2020, https://doi.org/10.5194/bg-17-2397-2020, 2020
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To closely monitor the state of our planet, we require systems that can monitor
the observation of many different properties at the same time. We create
indicators that resemble the behavior of many different simultaneous
observations. We apply the method to create indicators representing the
Earth's biosphere. The indicators show a productivity gradient and a water
gradient. The resulting indicators can detect a large number of changes and
extremes in the Earth system.
Barbara Marcolla, Mirco Migliavacca, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 17, 2365–2379, https://doi.org/10.5194/bg-17-2365-2020, https://doi.org/10.5194/bg-17-2365-2020, 2020
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This work investigates the sensitivity of terrestrial CO2 fluxes to climate drivers. We observed that CO2 flux is mostly controlled by temperature during the growing season and by radiation off season. We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia. Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.
Stephanie C. Pennington, Nate G. McDowell, J. Patrick Megonigal, James C. Stegen, and Ben Bond-Lamberty
Biogeosciences, 17, 771–780, https://doi.org/10.5194/bg-17-771-2020, https://doi.org/10.5194/bg-17-771-2020, 2020
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Soil respiration (Rs) is the flow of CO2 from the soil surface to the atmosphere and is one of the largest carbon fluxes on land. This study examined the effect of local basal area (tree area) on Rs in a coastal forest in eastern Maryland, USA. Rs measurements were taken as well as distance from soil collar, diameter, and species of each tree within a 15 m radius. We found that trees within 5 m of our sampling points had a positive effect on how sensitive soil respiration was to temperature.
Keri L. Bowering, Kate A. Edwards, Karen Prestegaard, Xinbiao Zhu, and Susan E. Ziegler
Biogeosciences, 17, 581–595, https://doi.org/10.5194/bg-17-581-2020, https://doi.org/10.5194/bg-17-581-2020, 2020
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We examined the effects of season and tree harvesting on the flow of water and the organic carbon (OC) it carries from boreal forest soils. We found that more OC was lost from the harvested forest because more precipitation reached the soil surface but that during periods of flushing in autumn and snowmelt a limit on the amount of water-extractable OC is reached. These results contribute to an increased understanding of carbon loss from boreal forest soils.
Jason Philip Kaye, Susan L. Brantley, Jennifer Zan Williams, and the SSHCZO team
Biogeosciences, 16, 4661–4669, https://doi.org/10.5194/bg-16-4661-2019, https://doi.org/10.5194/bg-16-4661-2019, 2019
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Interdisciplinary teams can only capitalize on innovative ideas if members work well together through collegial and efficient use of field sites, instrumentation, samples, data, and model code. Thus, biogeoscience teams may benefit from developing a set of best practices for collaboration. We present one such example from a the Susquehanna Shale Hills critical zone observatory. Many of the themes from our example are universal, and they offer insights useful to other biogeoscience teams.
Anne Alexandre, Elizabeth Webb, Amaelle Landais, Clément Piel, Sébastien Devidal, Corinne Sonzogni, Martine Couapel, Jean-Charles Mazur, Monique Pierre, Frédéric Prié, Christine Vallet-Coulomb, Clément Outrequin, and Jacques Roy
Biogeosciences, 16, 4613–4625, https://doi.org/10.5194/bg-16-4613-2019, https://doi.org/10.5194/bg-16-4613-2019, 2019
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This calibration study shows that despite isotope heterogeneity along grass leaves, the triple oxygen isotope composition of bulk leaf phytoliths can be estimated from the Craig and Gordon model, a mixing equation and a mean leaf water–phytolith fractionation exponent (lambda) of 0.521. The results strengthen the reliability of the 17O–excess of phytoliths to be used as a proxy of atmospheric relative humidity and open tracks for its use as an imprint of leaf water 17O–excess.
Lina Teckentrup, Sandy P. Harrison, Stijn Hantson, Angelika Heil, Joe R. Melton, Matthew Forrest, Fang Li, Chao Yue, Almut Arneth, Thomas Hickler, Stephen Sitch, and Gitta Lasslop
Biogeosciences, 16, 3883–3910, https://doi.org/10.5194/bg-16-3883-2019, https://doi.org/10.5194/bg-16-3883-2019, 2019
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This study compares simulated burned area of seven global vegetation models provided by the Fire Model Intercomparison Project (FireMIP) since 1900. We investigate the influence of five forcing factors: atmospheric CO2, population density, land–use change, lightning and climate.
We find that the anthropogenic factors lead to the largest spread between models. Trends due to climate are mostly not significant but climate strongly influences the inter-annual variability of burned area.
Marcos A. S. Scaranello, Michael Keller, Marcos Longo, Maiza N. dos-Santos, Veronika Leitold, Douglas C. Morton, Ekena R. Pinagé, and Fernando Del Bon Espírito-Santo
Biogeosciences, 16, 3457–3474, https://doi.org/10.5194/bg-16-3457-2019, https://doi.org/10.5194/bg-16-3457-2019, 2019
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The coarse dead wood component of the tropical forest carbon pool is rarely measured. For the first time, we developed models for predicting coarse dead wood in Amazonian forests by using airborne laser scanning data. Our models produced site-based estimates similar to independent field estimates found in the literature. Our study provides an approach for estimating coarse dead wood pools from remotely sensed data and mapping those pools over large scales in intact and degraded forests.
James Brennan, Jose L. Gómez-Dans, Mathias Disney, and Philip Lewis
Biogeosciences, 16, 3147–3164, https://doi.org/10.5194/bg-16-3147-2019, https://doi.org/10.5194/bg-16-3147-2019, 2019
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We estimate the uncertainties associated with three global satellite-derived burned area estimates. The method provides unique uncertainties for the three estimates at the global scale for 2001–2013. We find uncertainties of 4 %–5.5 % in global burned area and uncertainties of 8 %–10 % in the frequently burning regions of Africa and Australia.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, https://doi.org/10.5194/bg-16-3069-2019, 2019
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This study presents an estimate of global terrestrial photosynthesis. We make use of satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and estimate photosynthetic carbon uptake. This new framework incorporates nonlinear, process-based understanding of the link between fluorescence and photosynthesis, an advance on past approaches. This will aid in the utility of fluorescence to quantify terrestrial carbon cycle feedbacks.
Cited articles
Badgley, G., Field, C. B., and Berry, J. A.: Canopy near-infrared reflectance and terrestrial photosynthesis, Sc. Adv.,
3, https://doi.org/10.1126/sciadv.1602244, 2017. a
Baldocchi, D.: Breathing of the terrestrial biosphere: lessons learned from a
global network of carbon dioxide flux measurement systems, Austr. J. Bot., 56, 1–26, https://doi.org/10.1071/BT07151, 2008. a, b
Baldocchi, D., Chu, H., and Reichstein, M.: Inter-annual variability of net and
gross ecosystem carbon fluxes: A review, Agr. Forest Meteorol.,
249, 520–533, https://doi.org/10.1016/j.agrformet.2017.05.015, 2018. a
Baldocchi, D. D.: How eddy covariance flux measurements have contributed to our
understanding of Glob. Change Biol., Glob. Change Biol., 26, 242–260,
https://doi.org/10.1111/gcb.14807, 2020. a
Bao, S., Wutzler, T., Koirala, S., Cuntz, M., Ibrom, A., Besnard, S., Walther,
S., Šigut, L., Moreno, A., Weber, U., Wohlfahrt, G., Cleverly, J.,
Migliavacca, M., Woodgate, W., Merbold, L., Veenendaal, E., and Carvalhais,
N.: Environment-sensitivity functions for gross primary productivity in light
use efficiency models, Agr. Forest Meteorol., 312, 108708,
https://doi.org/10.1016/j.agrformet.2021.108708, 2022. a
Beck, P. S. A., Jönsson, P., Høgda, K., Karlsen, S. R., Eklundh, L., and
Skidmore, A. K.: A ground-validated NDVI dataset for monitoring vegetation
dynamics and mapping phenology in Fennoscandia and the Kola peninsula,
Int. J. Remote Sens., 28, 4311–4330,
https://doi.org/10.1080/01431160701241936, 2007. a, b
Besnard, S., Carvalhais, N., Arain, M. A., Black, A., de Bruin, S., Buchmann,
N., Cescatti, A., Chen, J., Clevers, J. G. P. W., Desai, A. R., Gough, C. M.,
Havrankova, K., Herold, M., Hörtnagl, L., Jung, M., Knohl, A., Kruijt, B.,
Krupkova, L., Law, B. E., Lindroth, A., Noormets, A., Roupsard, O.,
Steinbrecher, R., Varlagin, A., Vincke, C., and Reichstein, M.: Quantifying
the effect of forest age in annual net forest carbon balance, Environ.
Res. Lett., 13, 124018, https://doi.org/10.1088/1748-9326/aaeaeb, 2018. a
Bessenbacher, V., Seneviratne, S. I., and Gudmundsson, L.: CLIMFILL: A Framework for Intelligently Gap-filling Earth Observations, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-164, in review, 2021. a
Camps-Valls, G., Campos-Taberner, M., Moreno-Martínez, Á., Walther,
S., Duveiller, G., Cescatti, A., Mahecha, M. D., Muñoz-Marí, J.,
García-Haro, F. J., Guanter, L., Jung, M., Gamon, J. A., Reichstein, M.,
and Running, S. W.: A unified vegetation index for quantifying the
terrestrial biosphere, Sc. Adv., 7, https://doi.org/10.1126/sciadv.abc7447,
2021. a
Cescatti, A., Marcolla, B., Santhana Vannan, S. K., Pan, J. Y., Román,
M. O., Yang, X., Ciais, P., Cook, R. B., Law, B. E., Matteucci, G.,
Migliavacca, M., Moors, E., Richardson, A. D., Seufert, G., and Schaaf,
C. B.: Intercomparison of MODIS albedo retrievals and in situ measurements
across the global FLUXNET network, Remote Sens. Environ., 121,
323–334, https://doi.org/10.1016/j.rse.2012.02.019, 2012. a
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn,
M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D.,
Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G.,
Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai,
A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough,
C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H.,
Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law,
B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K.,
Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E.,
Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell,
E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens,
E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood,
J. D., and Zona, D.: Representativeness of Eddy-Covariance flux footprints
for areas surrounding AmeriFlux sites, Agr. Forest Meteorol.,
301/302, 108350, https://doi.org/10.1016/j.agrformet.2021.108350,
2021. a, b, c
Crosson, W. L., Al-Hamdan, M. Z., Hemmings, S. N., and Wade, G. M.: A daily
merged MODIS Aqua–Terra land surface temperature data set for the
conterminous United States, Remote Sens. Environ., 119, 315–324,
https://doi.org/10.1016/j.rse.2011.12.019, 2012. a, b
Dumitrescu, A., Brabec, M., and Cheval, S.: Statistical Gap-Filling of SEVIRI
Land Surface Temperature, Remote Sens., 12, 1423, https://doi.org/10.3390/rs12091423, 2020. a, b
Duveiller, G., Camps-Valls, G., Ceccherini, G., and Cescatti, A.: Spatial
homogeneity from temporal stability: Exploiting the combined hyper-frequent
revisit of Terra and Aqua to guide Earth System Science, Remote Sens.
Environ., 261, 112496, https://doi.org/10.1016/j.rse.2021.112496,
2021. a
El-Madany, T. S., Reichstein, M., Perez-Priego, O., Carrara, A., Moreno, G.,
Pilar MartÃn, M., Pacheco-Labrador, J., Wohlfahrt, G., Nieto, H., Weber,
U., Kolle, O., Luo, Y.-P., Carvalhais, N., and Migliavacca, M.: Drivers of
spatio-temporal variability of carbon dioxide and energy fluxes in a
Mediterranean savanna ecosystem, Agr. Forest Meteorol., 262,
258–278, https://doi.org/10.1016/j.agrformet.2018.07.010, 2018. a
Ermida, S. L., Trigo, I. F., DaCamara, C. C., Gättsche, F. M., Olesen, F. S.,
and Hulley, G.: Validation of remotely sensed surface temperature over an oak
woodland landscape – The problem of viewing and illumination geometries,
Remote Sens. Environ., 148, 16–27,
https://doi.org/10.1016/j.rse.2014.03.016, 2014. a
Ermida, S. L., Trigo, I. F., DaCamara, C. C., and Pires, A. C.: A Methodology
to Simulate LST Directional Effects Based on Parametric Models and Landscape
Properties, Remote Sens., 10, 114, https://doi.org/10.3390/rs10071114, 2018. a, b, c, d
Ermida, S. L., Trigo, I. F., DaCamara, C. C., Jiménez, C., and Prigent, C.:
Quantifying the Clear-Sky Bias of Satellite Land Surface Temperature Using
Microwave-Based Estimates, J. Geophys. Res.-Atmos., 124,
844–857, https://doi.org/10.1029/2018JD029354, 2019. a
Falge, E., Baldocchi, D., Olson, R., Anthoni, P., Aubinet, M., Bernhofer, C.,
Burba, G., Ceulemans, R., Clement, R., Dolman, H., Granier, A., Gross, P.,
Grünwald, T., Hollinger, D., Jensen, N.-O., Katul, G., Keronen, P.,
Kowalski, A., Ta Lai, C., Law, B. E., Meyers, T., Moncrieff, J., Moors, E.,
William Munger, J., Pilegaard, K.,Üllar Rannik, Rebmann, C., Suyker, A.,
Tenhunen, J., Tu, K., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: Gap
filling strategies for long term energy flux data sets, Agr. Forest Meteorol., 107, 71–77,
https://doi.org/10.1016/S0168-1923(00)00235-5, 2001. a
Foga, S., Scaramuzza, P. L., Guo, S., Zhu, Z., Dilley, R. D., Beckmann, T.,
Schmidt, G. L., Dwyer, J. L., Hughes, M. J., and Laue, B.: Cloud detection
algorithm comparison and validation for operational Landsat data products,
Remote Sens. Environ., 194, 379–390,
https://doi.org/10.1016/j.rse.2017.03.026, 2017. a
Gamon, J. A.: Reviews and Syntheses: optical sampling of the flux tower
footprint, Biogeosciences, 12, 4509–4523, https://doi.org/10.5194/bg-12-4509-2015,
2015. a
Gao, B.-C.: NDWI – A normalized difference water index for remote sensing of
vegetation liquid water from space, Remote Sens. Environ., 58,
257–266, https://doi.org/10.1016/S0034-4257(96)00067-3, 1996. a, b, c
Ghafarian Malamiri, H. R., Rousta, I., Olafsson, H., Zare, H., and Zhang, H.:
Gap-Filling of MODIS Time Series Land Surface Temperature (LST) Products
Using Singular Spectrum Analysis (SSA), Atmosphere, 9, 334,
https://doi.org/10.3390/atmos9090334, 2018. a, b
Gitelson, A. A.: Wide Dynamic Range Vegetation Index for Remote Quantification
of Biophysical Characteristics of Vegetation, J. Plant Physiol.,
161, 165–173, https://doi.org/10.1078/0176-1617-01176, 2004. a
Gonsamo, A., Chen, J. M., and D'Odorico, P.: Deriving land surface phenology
indicators from CO2 eddy covariance measurements, Ecol. Indic., 29,
203–207, https://doi.org/10.1016/j.ecolind.2012.12.026, 2013. a
Guillevic, P. C., Bork-Unkelbach, A., Göttsche, F. M., Hulley, G.,
Gastellu-Etchegorry, J.-P., Olesen, F. S., and Privette, J. L.: Directional
Viewing Effects on Satellite Land Surface Temperature Products Over Sparse
Vegetation Canopies – A Multisensor Analysis, IEEE Geosci. Remote
Sens. Lett., 10, 1464–1468, https://doi.org/10.1109/LGRS.2013.2260319, 2013. a
Huete, A., Didan, K., Miura, T., Rodriguez, E., Gao, X., and Ferreira, L.:
Overview of the radiometric and biophysical performance of the MODIS
vegetation indices, Remote Sens. Environ., 83, 195–213, 2002. a
ICOS Ecosystem Thematic Centre and Gebesee: Drought-2018 ecosystem eddy
covariance flux product from Gebesee, ICOS Ecosystem Thematic Centre and Gebesee [data set], https://doi.org/10.18160/ZK18-3YW3, 2019. a
Joiner, J., Yoshida, Y., Zhang, Y., Duveiller, G., Jung, M., Lyapustin, A.,
Wang, Y., and Tucker, C. J.: Estimation of Terrestrial Global Gross Primary
Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux
Data, Remote Sens., 10, 1346, https://doi.org/10.3390/rs10091346, 2018. a
Jonsson, P. and Eklundh, L.: Seasonality extraction by function fitting to
time-series of satellite sensor data, IEEE Trans. Geosci.
Remote Sens., 40, 1824–1832, https://doi.org/10.1109/TGRS.2002.802519, 2002. a
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., Papale,
D., Schwalm, C., Tramontana, G., and Reichstein, M.: The FLUXCOM ensemble of
global land-atmosphere energy fluxes, Sci. Data, 6, 74,
https://doi.org/10.1038/s41597-019-0076-8, 2019. a
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala,
S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F.,
Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu,
J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M.,
Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch,
S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon
fluxes from eddy covariance sites to globe: synthesis and evaluation of the
FLUXCOM approach, Biogeosciences, 17, 1343–1365,
https://doi.org/10.5194/bg-17-1343-2020, 2020. a
Kandasamy, S., Baret, F., Verger, A., Neveux, P., and Weiss, M.: A comparison
of methods for smoothing and gap filling time series of remote sensing
observations – application to MODIS LAI products, Biogeosciences, 10,
4055–4071, https://doi.org/10.5194/bg-10-4055-2013, 2013. a, b
Kljun, N., Calanca, P., Rotach, M. W., and Schmid, H. P.: A simple
two-dimensional parameterisation for Flux Footprint Prediction (FFP),
Geosci. Model Dev., 8, 3695–3713,
https://doi.org/10.5194/gmd-8-3695-2015, 2015. a
Knauer, J., El-Madany, T. S., Zaehle, S., and Migliavacca, M.: Bigleaf – An R
package for the calculation of physical and physiological ecosystem
properties from eddy covariance data, PLOS ONE, 13, e0214011,
https://doi.org/10.1371/journal.pone.0201114, 2018. a
Li, X., Zhou, Y., Asrar, G. R., and Zhu, Z.: Creating a seamless 1 km resolution
daily land surface temperature dataset for urban and surrounding areas in the
conterminous United States, Remote Sens. Environ., 206, 84–97,
https://doi.org/10.1016/j.rse.2017.12.010, 2018. a, b, c, d
Luo, Y., El-Madany, T. S., Filippa, G., Ma, X., Ahrens, B., Carrara, A.,
Gonzalez-Cascon, R., Cremonese, E., Galvagno, M., Hammer, T. W.,
Pacheco-Labrador, J., MartÃn, M. P., Moreno, G., Perez-Priego, O.,
Reichstein, M., Richardson, A. D., Römermann, C., and Migliavacca, M.: Using
Near-Infrared-Enabled Digital Repeat Photography to Track Structural and
Physiological Phenology in Mediterranean Tree – Grass Ecosystems, Remote
Sens., 10, 1293, https://doi.org/10.3390/rs10081293, 2018. a
Migliavacca, M., Reichstein, M., Richardson, A. D., Mahecha, M. D., Cremonese,
E., Delpierre, N., Galvagno, M., Law, B. E., Wohlfahrt, G., Andrew Black, T.,
Carvalhais, N., Ceccherini, G., Chen, J., Gobron, N., Koffi, E.,
William Munger, J., Perez-Priego, O., Robustelli, M., Tomelleri, E., and
Cescatti, A.: Influence of physiological phenology on the seasonal pattern of
ecosystem respiration in deciduous forests, Glob. Change Biol., 21,
363–376, https://doi.org/10.1111/gcb.12671, 2015. a
Migliavacca, M., El-Madany, T. S., Carrara, A., Reichstein, M., and ICOS
Ecosystem Thematic Centre: Drought – 2018 ecosystem eddy covariance flux
product from Majadas del Tietar North, [data set], https://doi.org/10.18160/FDSD-GVRS, 2020. a
Migliavacca, M., Musavi, T., Mahecha, M. D., Nelson, J. A., Knauer, J.,
Baldocchi, D. D., Perez-Priego, O., Christiansen, R., Peters, J., Anderson,
K., Bahn, M., Black, T. A., Blanken, P. D., Bonal, D., Buchmann, N.,
Caldararu, S., Carrara, A., Carvalhais, N., Cescatti, A., Chen, J., Cleverly,
J., Cremonese, E., Desai, A. R., El-Madany, T., Farella, M. M.,
Fernández-Martínez, M., Filippa, G., Forkel, M., Galvagno, M., Gomarasca,
U., Gough, C., Göckede, M., Ibrom, A., Ikawa, H., Janssens, I., Jung, M.,
Kattge, J., Keenan, T., Knohl, A., Kobayashi, H., Kraemer, G., Law, B. E.,
Liddell, M., Ma, X., Mammarella, I., Martini, D., Macfarlane, C., Matteucci,
G., Montagnani, L., Pabon-Moreno, D., Panigada, C., Papale, D., Pendall, E.,
Penuelas, J., Phillips, R. P., Reich, P. B., Rossini, M., Rotenberg, E.,
Scott, R., Stahl, C., Weber, U., Wohlfahrt, G., Wolf, S., Wright, I., Yakir,
D., Zaehle, S., and Reichstein, M.: The three major axes of terrestrial
ecosystem function, Nature, 598, 468–472, https://doi.org/10.1038/s41586-021-03939-9, 2021. a
Moffat, A. M., Papale, D., Reichstein, M., Hollinger, D., Richardson, A. D.,
Barr, A. G., Beckstein, C., Braswell, B. H., Churkina, G., Desai, A. R.,
Falge, E., Gove, J. H., Heimann, M., Hui, D., Jarvis, A. J., Kattge, J.,
Noormets, A., and Stauch, V. J.: Comprehensive comparison of gap-filling
techniques for eddy covariance net carbon fluxes, Agr. Forest Meteorol., 147, 209–232,
https://doi.org/10.1016/j.agrformet.2007.08.011, 2007. a
Moreno, A., García-Haro, F. J., Martíez, B., and Gilabert, M. A.: Noise
Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local
Regression Filter, Remote Sens., 6, 8238–8260, https://doi.org/10.3390/rs6098238,
2014. a
Moreno-Martínez, A., Izquierdo-Verdiguier, E., Maneta, M. P., Camps-Valls, G.,
Robinson, N., Muñoz-Marí, J., Sedano, F., Clinton, N., and Running, S. W.:
Multispectral high resolution sensor fusion for smoothing and gap-filling in
the cloud, Remote Sens. Environ., 247, 111901,
https://doi.org/10.1016/j.rse.2020.111901, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models
part I – A discussion of principles, Journal of Hydrology, 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970. a, b, c
Nelson, J. A., Pérez-Priego, O., Zhou, S., Poyatos, R., Zhang, Y., Blanken,
P. D., Gimeno, T. E., Wohlfahrt, G., Desai, A. R., Gioli, B., Limousin,
J.-M., Bonal, D., Paul-Limoges, E., Scott, R. L., Varlagin, A., Fuchs, K.,
Montagnani, L., Wolf, S., Delpierre, N., Berveiller, D., Gharun, M.,
Belelli Marchesini, L., Gianelle, D., Šgut, L., Mammarella, I., Siebicke,
L., Andrew Black, T., Knohl, A., Hörtnagl, L., Magliulo, V., Besnard, S.,
Weber, U., Carvalhais, N., Migliavacca, M., Reichstein, M., and Jung, M.:
Ecosystem transpiration and evaporation: Insights from three water flux
partitioning methods across FLUXNET sites, Glob. Change Biol., 26,
6916–6930, https://doi.org/10.1111/gcb.15314, 2020. a
ORNL DAAC: MODIS and VIIRS Land Products Global Subsetting and Visualization
Tool, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1379, 2018. a, b, c, d
Pacheco-Labrador, J., El-Madany, T. S., Martín, M. P., Migliavacca, M.,
Rossini, M., Carrara, A., and Zarco-Tejada, P. J.: Spatio-Temporal
Relationships between Optical Information and Carbon Fluxes in a
Mediterranean Tree-Grass Ecosystem, Remote Sens., 9, 608,
https://doi.org/10.3390/rs9060608, 2017. a
Papale, D.: Ideas and perspectives: enhancing the impact of the FLUXNET network
of eddy covariance sites, Biogeosciences, 17, 5587–5598,
https://doi.org/10.5194/bg-17-5587-2020, 2020. a
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch,
W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.:
Towards a standardized processing of Net Ecosystem Exchange measured with
eddy covariance technique: algorithms and uncertainty estimation,
Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006. a, b, c, d, e, f
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah,
Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M., Isaac, P.,
Polidori, D., Reichstein, M., Ribeca, A., van Ingen, C., Vuichard, N., Zhang,
L., Amiro, B., Ammann, C., Arain, M. A., Ardö, J., Arkebauer, T., Arndt,
S. K., Arriga, N., Aubinet, M., Aurela, M., Baldocchi, D., Barr, A.,
Beamesderfer, E., Marchesini, L. B., Bergeron, O., Beringer, J., Bernhofer,
C., Berveiller, D., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G.,
Boike, J., Bolstad, P. V., Bonal, D., Bonnefond, J.-M., Bowling, D. R.,
Bracho, R., Brodeur, J., Brümmer, C., Buchmann, N., Burban, B., Burns,
S. P., Buysse, P., Cale, P., Cavagna, M., Cellier, P., Chen, S., Chini, I.,
Christensen, T. R., Cleverly, J., Collalti, A., Consalvo, C., Cook, B. D.,
Cook, D., Coursolle, C., Cremonese, E., Curtis, P. S., D'Andrea, E.,
da Rocha, H., Dai, X., Davis, K. J., Cinti, B. D., Grandcourt, A. d., Ligne,
A. D., De Oliveira, R. C., Delpierre, N., Desai, A. R., Di Bella, C. M.,
Tommasi, P. d., Dolman, H., Domingo, F., Dong, G., Dore, S., Duce, P.,
Dufrêe, E., Dunn, A., Dus̆ek, J., Eamus, D., Eichelmann, U., ElKhidir, H.
A. M., Eugster, W., Ewenz, C. M., Ewers, B., Famulari, D., Fares, S.,
Feigenwinter, I., Feitz, A., Fensholt, R., Filippa, G., Fischer, M., Frank,
J., Galvagno, M., Gharun, M., Gianelle, D., Gielen, B., Gioli, B., Gitelson,
A., Goded, I., Goeckede, M., Goldstein, A. H., Gough, C. M., Goulden, M. L.,
Graf, A., Griebel, A., Gruening, C., Grünwald, T., Hammerle, A., Han, S.,
Han, X., Hansen, B. U., Hanson, C., Hatakka, J., He, Y., Hehn, M., Heinesch,
B., Hinko-Najera, N., Hörtnagl, L., Hutley, L., Ibrom, A., Ikawa, H.,
Jackowicz-Korczynski, M., Janous̆, D., Jans, W., Jassal, R., Jiang, S., Kato,
T., Khomik, M., Klatt, J., Knohl, A., Knox, S., Kobayashi, H., Koerber, G.,
Kolle, O., Kosugi, Y., Kotani, A., Kowalski, A., Kruijt, B., Kurbatova, J.,
Kutsch, W. L., Kwon, H., Launiainen, S., Laurila, T., Law, B., Leuning, R.,
Li, Y., Liddell, M., Limousin, J.-M., Lion, M., Liska, A. J., Lohila, A.,
López-Ballesteros, A., López-Blanco, E., Loubet, B., Loustau, D.,
Lucas-Moffat, A., Lüers, J., Ma, S., Macfarlane, C., Magliulo, V., Maier,
R., Mammarella, I., Manca, G., Marcolla, B., Margolis, H. A., Marras, S.,
Massman, W., Mastepanov, M., Matamala, R., Matthes, J. H., Mazzenga, F.,
McCaughey, H., McHugh, I., McMillan, A. M. S., Merbold, L., Meyer, W.,
Meyers, T., Miller, S. D., Minerbi, S., Moderow, U., Monson, R. K.,
Montagnani, L., Moore, C. E., Moors, E., Moreaux, V., Moureaux, C., Munger,
J. W., Nakai, T., Neirynck, J., Nesic, Z., Nicolini, G., Noormets, A.,
Northwood, M., Nosetto, M., Nouvellon, Y., Novick, K., Oechel, W., Olesen,
J. E., Ourcival, J.-M., Papuga, S. A., Parmentier, F.-J., Paul-Limoges, E.,
Pavelka, M., Peichl, M., Pendall, E., Phillips, R. P., Pilegaard, K., Pirk,
N., Posse, G., Powell, T., Prasse, H., Prober, S. M., Rambal, S., Rannik, Ã.,
Raz-Yaseef, N., Rebmann, C., Reed, D., Dios, V. R. d., Restrepo-Coupe, N.,
Reverter, B. R., Roland, M., Sabbatini, S., Sachs, T., Saleska, S. R.,
Sánchez-Cañete, E. P., Sanchez-Mejia, Z. M., Schmid, H. P., Schmidt, M.,
Schneider, K., Schrader, F., Schroder, I., Scott, R. L., Sedlák, P.,
Serrano-Ortíz, P., Shao, C., Shi, P., Shironya, I., Siebicke, L., Šigut,
L., Silberstein, R., Sirca, C., Spano, D., Steinbrecher, R., Stevens, R. M.,
Sturtevant, C., Suyker, A., Tagesson, T., Takanashi, S., Tang, Y., Tapper,
N., Thom, J., Tomassucci, M., Tuovinen, J.-P., Urbanski, S., Valentini, R.,
van der Molen, M., van Gorsel, E., van Huissteden, K., Varlagin, A.,
Verfaillie, J., Vesala, T., Vincke, C., Vitale, D., Vygodskaya, N., Walker,
J. P., Walter-Shea, E., Wang, H., Weber, R., Westermann, S., Wille, C.,
Wofsy, S., Wohlfahrt, G., Wolf, S., Woodgate, W., Li, Y., Zampedri, R.,
Zhang, J., Zhou, G., Zona, D., Agarwal, D., Biraud, S., Torn, M., and Papale,
D.: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy
covariance data, Sci. Data, 7, 1–27, https://doi.org/10.1038/s41597-020-0534-3, 2020. a, b
Rasmussen, M. O., Gottsche, F.-M., Olesen, F.-S., and Sandholt, I.: Directional
Effects on Land Surface Temperature Estimation From Meteosat Second
Generation for Savanna Landscapes, IEEE Trans. Geosci. Remote
Sens., 49, 4458–4468, https://doi.org/10.1109/TGRS.2011.2144604, 2011. a
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier,
P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grünwald, T.,
Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila,
A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M.,
Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G.,
Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of
net ecosystem exchange into assimilation and ecosystem respiration: review
and improved algorithm, Glob. Change Biol., 11, 1424–1439,
https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005. a
Reitz, O., Graf, A., Schmidt, M., Ketzler, G., and Leuchner, M.: Upscaling Net
Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning,
J. Geophys. Res.-Biogeo., 126, e2020JG005814,
https://doi.org/10.1029/2020JG005814, 2021. a
Robinson, N. P., Allred, B. W., Jones, M. O., Moreno, A., Kimball, J. S.,
Naugle, D. E., Erickson, T. A., and Richardson, A. D.: A Dynamic Landsat
Derived Normalized Difference Vegetation Index (NDVI) Product for the
Conterminous United States, Remote Sens., 9, 863, https://doi.org/10.3390/rs9080863, 2017. a, b, c, d, e, f
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. a, b
Roy, D., Kovalskyy, V., Zhang, H., Vermote, E., Yan, L., Kumar, S., and Egorov,
A.: Characterization of Landsat-7 to Landsat-8 reflective wavelength and
normalized difference vegetation index continuity, Remote Sens.
Environ., 185, 57–70, https://doi.org/10.1016/j.rse.2015.12.024,
2016. a
Schaaf, C. and Wang, Z.: MCD43A2 MODIS/Terra+Aqua BRDF/Albedo Quality Daily L3
Global – 500 m V006, [data set], https://doi.org/10.5067/MODIS/MCD43A2.006,
2015a. a
Schaaf, C. and Wang, Z.: MCD43A4 MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF
Adjusted Ref Daily L3 Global – 500 m V006, [data set],
https://doi.org/10.5067/MODIS/MCD43A4.006, 2015b. a, b
Schmid, H.: Experimental design for flux measurements: matching scales of
observations and fluxes, Agr. Forest Meteorol., 87, 179–200,
https://doi.org/10.1016/S0168-1923(97)00011-7, 1997. a, b
Schmidt, G., Jenkerson, C. B., Masek, J., Vermote, E., and Gao, F.: Landsat
ecosystem disturbance adaptive processing system (LEDAPS) algorithm
description, USGS Publications Warehouse, https://doi.org/10.3133/ofr20131057, 2013. a
Stekhoven, D. J. and Bühlmann, P.: MissForest – non-parametric missing value
imputation for mixed-type data, Bioinformatics, 28, 112–118,
https://doi.org/10.1093/bioinformatics/btr597, 2011. a
Stoy, P. C., Mauder, M., Foken, T., Marcolla, B., Boegh, E., Ibrom, A., Arain,
M. A., Arneth, A., Aurela, M., Bernhofer, C., Cescatti, A., Dellwik, E.,
Duce, P., Gianelle, D., van Gorsel, E., Kiely, G., Knohl, A., Margolis, H.,
McCaughey, H., Merbold, L., Montagnani, L., Papale, D., Reichstein, M.,
Saunders, M., Serrano-Ortiz, P., Sottocornola, M., Spano, D., Vaccari, F.,
and Varlagin, A.: A data-driven analysis of energy balance closure across
FLUXNET research sites: The role of landscape scale heterogeneity,
Agr. Forest Meteorol., 171/172, 137–152,
https://doi.org/10.1016/j.agrformet.2012.11.004, 2013. a
Sun, Q., Wang, Z., Li, Z., Erb, A., and Schaaf, C. B.: Evaluation of the global
MODIS 30 arc-second spatially and temporally complete snow-free land surface
albedo and reflectance anisotropy dataset, Int. J. Appl.
Earth Observ. Geoin., 58, 36–49,
https://doi.org/10.1016/j.jag.2017.01.011, 2017. a, b, c, d, e, f
Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly,
B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L.,
Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon
dioxide and energy fluxes across global FLUXNET sites with regression
algorithms, Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016,
2016. a
Tucker, C. J.: Red and photographic infrared linear combinations for monitoring
vegetation, Remote Sens. Environ., 8, 127–150, 1979. a
Ueyama, M., Ichii, K., Iwata, H., Euskirchen, E., Zona, D., Rocha, A.,
Harazono, Y., Iwama, C., Nakai, T., and Oechel, W.: Upscaling terrestrial
carbon dioxide fluxes in Alaska with satellite remote sensing and support
vector regression, J. Geophys. Res.-Biogeo., 118,
1266–1281, https://doi.org/10.1002/jgrg.20095, 2013. a
van Buttlar, J., Zscheischler, J., and Mahecha, M. D.: An extended approach for spatiotemporal gapfilling: dealing with large and systematic gaps in geoscientific datasets, Nonlin. Processes Geophys., 21, 203–215, https://doi.org/10.5194/npg-21-203-2014, 2014. a, b, c
Verger, A., Baret, F., and Weiss, M.: A multisensor fusion approach to improve
LAI time series, Remote Sens. Environ., 115, 2460–2470,
https://doi.org/10.1016/j.rse.2011.05.006, 2011. a, b, c
Verger, A., Baret, F., Weiss, M., Kandasamy, S., and Vermote, E.: The CACAO
Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in
Satellite Time Series, IEEE Trans. Geosci. Remote Sens.,
51, 1963–1972, https://doi.org/10.1109/TGRS.2012.2228653, 2013. a, b, c, d
Vesala, T., Kljun, N., Rannik, Ã., Rinne, J., Sogachev, A., Markkanen, T.,
Sabelfeld, K., Foken, T., and Leclerc, M.: Flux and concentration footprint
modelling: State of the art, Environ. Pollut., 152, 653–666,
https://doi.org/10.1016/j.envpol.2007.06.070, 2008. a
Vinnikov, K. Y., Yu, Y., Rama Varma Raja, M. K., Tarpley, D., and Goldberg,
M. D.: Diurnal-seasonal and weather-related variations of land surface
temperature observed from geostationary satellites, Geophys. Res.
Lett., 35, https://doi.org/10.1029/2008GL035759, 2008. a
Virkkala, A.-M., Aalto, J., Rogers, B. M., Tagesson, T., Treat, C. C., Natali,
S. M., Watts, J. D., Potter, S., Lehtonen, A., Mauritz, M., Schuur, E. A. G.,
Kochendorfer, J., Zona, D., Oechel, W., Kobayashi, H., Humphreys, E.,
Goeckede, M., Iwata, H., Lafleur, P. M., Euskirchen, E. S., Bokhorst, S.,
Marushchak, M., Martikainen, P. J., Elberling, B., Voigt, C., Biasi, C.,
Sonnentag, O., Parmentier, F.-J. W., Ueyama, M., Celis, G., St.Louis, V. L.,
Emmerton, C. A., Peichl, M., Chi, J., Järveoja, J., Nilsson, M. B.,
Oberbauer, S. F., Torn, M. S., Park, S.-J., Dolman, H., Mammarella, I., Chae,
N., Poyatos, R., López-Blanco, E., Christensen, T. R., Kwon, M. J., Sachs,
T., Holl, D., and Luoto, M.: Statistical upscaling of ecosystem CO2 fluxes
across the terrestrial tundra and boreal domain: Regional patterns and
uncertainties, Glob. Change Biol., 27, 4040–4059,
https://doi.org/10.1111/gcb.15659, 2021. a
Virkkala, A.-M., Natali, S. M., Rogers, B. M., Watts, J. D., Savage, K., Connon, S. J., Mauritz, M., Schuur, E. A. G., Peter, D., Minions, C., Nojeim, J., Commane, R., Emmerton, C. A., Goeckede, M., Helbig, M., Holl, D., Iwata, H., Kobayashi, H., Kolari, P., López-Blanco, E., Marushchak, M. E., Mastepanov, M., Merbold, L., Parmentier, F.-J. W., Peichl, M., Sachs, T., Sonnentag, O., Ueyama, M., Voigt, C., Aurela, M., Boike, J., Celis, G., Chae, N., Christensen, T. R., Bret-Harte, M. S., Dengel, S., Dolman, H., Edgar, C. W., Elberling, B., Euskirchen, E., Grelle, A., Hatakka, J., Humphreys, E., Järveoja, J., Kotani, A., Kutzbach, L., Laurila, T., Lohila, A., Mammarella, I., Matsuura, Y., Meyer, G., Nilsson, M. B., Oberbauer, S. F., Park, S.-J., Petrov, R., Prokushkin, A. S., Schulze, C., St. Louis, V. L., Tuittila, E.-S., Tuovinen, J.-P., Quinton, W., Varlagin, A., Zona, D., and Zyryanov, V. I.: The ABCflux database: Arctic–boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems, Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, 2022. a
Wagle, P., Gowda, P. H., Neel, J. P., Northup, B. K., and Zhou, Y.: Integrating
eddy fluxes and remote sensing products in a rotational grazing native
tallgrass prairie pasture, Sci. Total Environ., 712, 136407,
https://doi.org/10.1016/j.scitotenv.2019.136407, 2020. a
Walther, S., Besnard, S., Nelson, J. A., El-Madany, T. S., Migliavacca, M.,
Weber, U., Ermida, S. L., Brümmer, C., Schrader, F., Prokushkin, A. S.,
Panov, A. V., and Jung, M.: Technical note: A view from space on global flux
towers by MODIS and Landsat: The FluxnetEO dataset (Landsat), [data set],
2021a. a, b, c
Walther, S., Besnard, S., Nelson, J. A., El-Madany, T. S., Migliavacca, M.,
Weber, U., Ermida, S. L., Brümmer, C., Schrader, F., Prokushkin, A. S.,
Panov, A. V., and Jung, M.: Technical note: A view from space on global flux
towers by MODIS and Landsat: The FluxnetEO dataset (MODIS), [data set],
2021b. a, b, c
Wan, Z., Hook, S., and Hulley, G.: MOD11A1 MODIS/Terra Land Surface
Temperature/Emissivity Daily L3 Global 1 km SIN Grid V006, [data set],
https://doi.org/10.5067/MODIS/MOD11A1.006, 2015a. a
Wan, Z., Hook, S., and Hulley, G.: MYD11A1 MODIS/Aqua Land Surface
Temperature/Emissivity Daily L3 Global 1 km SIN Grid V006, [data set],
https://doi.org/10.5067/MODIS/MYD11A1.006, 2015b. a
Wang, G., Garcia, D., Liu, Y., de Jeu, R., and Johannes Dolman, A.: A
three-dimensional gap filling method for large geophysical datasets:
Application to global satellite soil moisture observations, Environ.
Model. Softw., 30, 139–142,
https://doi.org/10.1016/j.envsoft.2011.10.015, 2012. a, b, c
Weiss, D. J., Atkinson, P. M., Bhatt, S., Mappin, B., Hay, S. I., and Gething,
P. W.: An effective approach for gap-filling continental scale remotely
sensed time-series, ISPRS J. Photogramm. Remote Sens., 98,
106–118, https://doi.org/10.1016/j.isprsjprs.2014.10.001, 2014. a, b
Williams, M., Richardson, A. D., Reichstein, M., Stoy, P. C., Peylin, P.,
Verbeeck, H., Carvalhais, N., Jung, M., Hollinger, D. Y., Kattge, J.,
Leuning, R., Luo, Y., Tomelleri, E., Trudinger, C. M., and Wang, Y.-P.:
Improving land surface models with FLUXNET data, Biogeosciences, 6,
1341–1359, https://doi.org/10.5194/bg-6-1341-2009, 2009. a
Wingate, L., Ogée, J., Cremonese, E., Filippa, G., Mizunuma, T., Migliavacca,
M., Moisy, C., Wilkinson, M., Moureaux, C., Wohlfahrt, G., Hammerle, A.,
Hörtnagl, L., Gimeno, C., Porcar-Castell, A., Galvagno, M., Nakaji, T.,
Morison, J., Kolle, O., Knohl, A., Kutsch, W., Kolari, P., Nikinmaa, E.,
Ibrom, A., Gielen, B., Eugster, W., Balzarolo, M., Papale, D., Klumpp, K.,
Köstner, B., Grünwald, T., Joffre, R., Ourcival, J.-M., Hellstrom, M.,
Lindroth, A., George, C., Longdoz, B., Genty, B., Levula, J., Heinesch, B.,
Sprintsin, M., Yakir, D., Manise, T., Guyon, D., Ahrends, H., Plaza-Aguilar,
A., Guan, J. H., and Grace, J.: Interpreting canopy development and
physiology using a European phenology camera network at flux sites,
Biogeosciences, 12, 5995–6015, https://doi.org/10.5194/bg-12-5995-2015, 2015.
a
Wohlfahrt, G., Hammerle, A., Haslwanter, A., Bahn, M., Tappeiner, U., and Cernusca, A.: Seasonal and inter-annual variability of the net ecosystem CO2 exchange of a temperate mountain grassland: Effects of weather and management, J. Geophys. Res.-Atmos., 113, D08110, https://doi.org/10.1029/2007JD009286, 2008. a
Wulder, M. A., Loveland, T. R., Roy, D. P., Crawford, C. J., Masek, J. G.,
Woodcock, C. E., Allen, R. G., Anderson, M. C., Belward, A. S., Cohen, W. B.,
Dwyer, J., Erb, A., Gao, F., Griffiths, P., Helder, D., Hermosilla, T.,
Hipple, J. D., Hostert, P., Hughes, M. J., Huntington, J., Johnson, D. M.,
Kennedy, R., Kilic, A., Li, Z., Lymburner, L., McCorkel, J., Pahlevan, N.,
Scambos, T. A., Schaaf, C., Schott, J. R., Sheng, Y., Storey, J., Vermote,
E., Vogelmann, J., White, J. C., Wynne, R. H., and Zhu, Z.: Current status of
Landsat program, science, and applications, Remote Sens. Environ.,
225, 127–147, https://doi.org/10.1016/j.rse.2019.02.015, 2019. a
Yan, L. and Roy, D. P.: Large-Area Gap Filling of Landsat Reflectance Time
Series by Spectral-Angle-Mapper Based Spatio-Temporal Similarity (SAMSTS),
Remote Sens., 10, 609, https://doi.org/10.3390/rs10040609, 2018. a, b
Zeng, J., Matsunaga, T., Tan, Z.-H., Saigusa, N., Shirai, T., Tang, Y., Peng,
S., and Fukuda, Y.: Global terrestrial carbon fluxes of 1999–2019 estimated
by upscaling eddy covariance data with a random forest, Sci. Data, 7, 1–11,
https://doi.org/10.1038/s41597-020-00653-5, 2020. a
Zhang, J., Shang, R., Rittenhouse, C., Witharana, C., and Zhu, Z.: Evaluating
the impacts of models, data density and irregularity on reconstructing and
forecasting dense Landsat time series, Sci. Remote Sens., 4,
100023, https://doi.org/10.1016/j.srs.2021.100023, 2021. a, b
Zhu, Z. and Woodcock, C. E.: Object-based cloud and cloud shadow detection in
Landsat imagery, Remote Sens. Environ., 118, 83–94,
https://doi.org/10.1016/j.rse.2011.10.028, 2012. a
Zhu, Z., Wang, S., and Woodcock, C. E.: Improvement and expansion of the Fmask
algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and
Sentinel 2 images, Remote Sens. Environ., 159, 269–277,
https://doi.org/10.1016/j.rse.2014.12.014, 2015. a
Short summary
Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Satellite observations help interpret station measurements of local carbon, water, and energy...
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