Articles | Volume 10, issue 3
https://doi.org/10.5194/essd-10-1327-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-1327-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
20 Jul 2018
Review article |
| 20 Jul 2018
| 20 Jul 2018
Upscaled diurnal cycles of land–atmosphere fluxes: a new global half-hourly data product
Max Planck Institute for Biogeochemistry, Jena, Germany
Martin Jung
Max Planck Institute for Biogeochemistry, Jena, Germany
Fabian Gans
Max Planck Institute for Biogeochemistry, Jena, Germany
Miguel D. Mahecha
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
Michael Stifel Center Jena (MSCJ) for Data-Driven & Simulation Science, Jena, Germany
Markus Reichstein
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
Michael Stifel Center Jena (MSCJ) for Data-Driven & Simulation Science, Jena, Germany
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Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
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Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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Biogeosciences, 21, 2051–2085, https://doi.org/10.5194/bg-21-2051-2024, https://doi.org/10.5194/bg-21-2051-2024, 2024
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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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Samuel Upton, Markus Reichstein, Fabian Gans, Wouter Peters, Basil Kraft, and Ana Bastos
Atmos. Chem. Phys., 24, 2555–2582, https://doi.org/10.5194/acp-24-2555-2024, https://doi.org/10.5194/acp-24-2555-2024, 2024
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Data-driven eddy-covariance upscaled estimates of the global land–atmosphere net CO2 exchange (NEE) show important mismatches with regional and global estimates based on atmospheric information. To address this, we create a model with a dual constraint based on bottom-up eddy-covariance data and top-down atmospheric inversion data. Our model overcomes shortcomings of each approach, producing improved NEE estimates from local to global scale, helping to reduce uncertainty in the carbon budget.
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.
Theertha Kariyathan, Ana Bastos, Julia Marshall, Wouter Peters, Pieter Tans, and Markus Reichstein
Atmos. Meas. Tech., 16, 3299–3312, https://doi.org/10.5194/amt-16-3299-2023, https://doi.org/10.5194/amt-16-3299-2023, 2023
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The timing and duration of the carbon uptake period (CUP) are sensitive to the occurrence of major phenological events, which are influenced by recent climate change. This study presents an ensemble-based approach for quantifying the timing and duration of the CUP and their uncertainty when derived from atmospheric CO2 measurements with noise and gaps. The CUP metrics derived with the approach are more robust and have less uncertainty than when estimated with the conventional methods.
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.
Robert Vautard, Geert Jan van Oldenborgh, Rémy Bonnet, Sihan Li, Yoann Robin, Sarah Kew, Sjoukje Philip, Jean-Michel Soubeyroux, Brigitte Dubuisson, Nicolas Viovy, Markus Reichstein, Friederike Otto, and Iñaki Garcia de Cortazar-Atauri
Nat. Hazards Earth Syst. Sci., 23, 1045–1058, https://doi.org/10.5194/nhess-23-1045-2023, https://doi.org/10.5194/nhess-23-1045-2023, 2023
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A deep frost occurred in early April 2021, inducing severe damages in grapevine and fruit trees in France. We found that such extreme frosts occurring after the start of the growing season such as those of April 2021 are currently about 2°C colder [0.5 °C to 3.3 °C] in observations than in preindustrial climate. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change, making the 2021 event 50 % more likely [10 %–110 %].
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.
Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Earth Syst. Dynam., 13, 1505–1533, https://doi.org/10.5194/esd-13-1505-2022, https://doi.org/10.5194/esd-13-1505-2022, 2022
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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.
D. Montero, C. Aybar, M. D. Mahecha, and S. Wieneke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 301–306, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022, 2022
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
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The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614, https://doi.org/10.5194/hess-26-1579-2022, https://doi.org/10.5194/hess-26-1579-2022, 2022
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We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
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.
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
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
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.
Milan Flach, Alexander Brenning, Fabian Gans, Markus Reichstein, Sebastian Sippel, and Miguel D. Mahecha
Biogeosciences, 18, 39–53, https://doi.org/10.5194/bg-18-39-2021, https://doi.org/10.5194/bg-18-39-2021, 2021
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Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. We study the impact of droughts and heatwaves on the uptake of CO2 of different vegetation types at the global scale. We find that agricultural areas are generally strongly affected. Forests instead are not particularly sensitive to the events under scrutiny. This implies different water management strategies of forests but also a lack of sensitivity to remote-sensing-derived vegetation activity.
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.
B. Kraft, M. Jung, M. Körner, and M. Reichstein
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1537–1544, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1537-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1537-2020, 2020
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.
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.
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.
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.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
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The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
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.
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.
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.
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.
Milan Flach, Sebastian Sippel, Fabian Gans, Ana Bastos, Alexander Brenning, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 15, 6067–6085, https://doi.org/10.5194/bg-15-6067-2018, https://doi.org/10.5194/bg-15-6067-2018, 2018
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Northern forests enhanced their productivity during and before the 2010 Russian mega heatwave. We scrutinize this issue with a novel type of multivariate extreme event detection approach. Forests compensate for 54 % of the carbon losses in agricultural ecosystems due to vulnerable conditions in spring and better water management in summer. The findings highlight the importance of forests in mitigating climate change, while not alleviating the consequences of extreme events for food security.
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.
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.
Milan Flach, Fabian Gans, Alexander Brenning, Joachim Denzler, Markus Reichstein, Erik Rodner, Sebastian Bathiany, Paul Bodesheim, Yanira Guanche, Sebastian Sippel, and Miguel D. Mahecha
Earth Syst. Dynam., 8, 677–696, https://doi.org/10.5194/esd-8-677-2017, https://doi.org/10.5194/esd-8-677-2017, 2017
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Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community. The Earth system is highly multivariate. We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing. We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches. The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided.
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.
Sebastian Sippel, Jakob Zscheischler, Miguel D. Mahecha, Rene Orth, Markus Reichstein, Martha Vogel, and Sonia I. Seneviratne
Earth Syst. Dynam., 8, 387–403, https://doi.org/10.5194/esd-8-387-2017, https://doi.org/10.5194/esd-8-387-2017, 2017
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The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and (2) refines the model ensemble using a land–atmosphere coupling diagnostic as constraint. Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season
moisture-limitedclimate regimes in midlatitude regions. This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
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The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Ráduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale
Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, https://doi.org/10.5194/bg-13-4291-2016, 2016
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We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) and energy exchanges between land ecosystems and atmosphere. Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes. The results were good for all the ecosystems, with limitations to the ones in the extreme environments (cold, hot) or less represented in the training data (tropics).
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
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The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
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We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
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.
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. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
X. Wu, F. Babst, P. Ciais, D. Frank, M. Reichstein, M. Wattenbach, C. Zang, and M. D. Mahecha
Biogeosciences, 11, 3057–3068, https://doi.org/10.5194/bg-11-3057-2014, https://doi.org/10.5194/bg-11-3057-2014, 2014
J. Zscheischler, M. Reichstein, S. Harmeling, A. Rammig, E. Tomelleri, and M. D. Mahecha
Biogeosciences, 11, 2909–2924, https://doi.org/10.5194/bg-11-2909-2014, https://doi.org/10.5194/bg-11-2909-2014, 2014
B. Ahrens, M. Reichstein, W. Borken, J. Muhr, S. E. Trumbore, and T. Wutzler
Biogeosciences, 11, 2147–2168, https://doi.org/10.5194/bg-11-2147-2014, https://doi.org/10.5194/bg-11-2147-2014, 2014
J. v. Buttlar, J. Zscheischler, and M. D. Mahecha
Nonlin. Processes Geophys., 21, 203–215, https://doi.org/10.5194/npg-21-203-2014, https://doi.org/10.5194/npg-21-203-2014, 2014
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
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
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
M. C. Braakhekke, T. Wutzler, C. Beer, J. Kattge, M. Schrumpf, B. Ahrens, I. Schöning, M. R. Hoosbeek, B. Kruijt, P. Kabat, and M. Reichstein
Biogeosciences, 10, 399–420, https://doi.org/10.5194/bg-10-399-2013, https://doi.org/10.5194/bg-10-399-2013, 2013
G. Lasslop, M. Migliavacca, G. Bohrer, M. Reichstein, M. Bahn, A. Ibrom, C. Jacobs, P. Kolari, D. Papale, T. Vesala, G. Wohlfahrt, and A. Cescatti
Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, https://doi.org/10.5194/bg-9-5243-2012, 2012
Related subject area
Data, Algorithms, and Models
Improved maps of surface water bodies, large dams, reservoirs, and lakes in China
The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation
A high-resolution inland surface water body dataset for the tundra and boreal forests of North America
A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan
HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand
A dataset of microphysical cloud parameters, retrieved from Fourier-transform infrared (FTIR) emission spectra measured in Arctic summer 2017
A global long-term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network
First SMOS Sea Surface Salinity dedicated products over the Baltic Sea
HomogWS-se: a century-long homogenized dataset of near-surface wind speed observations since 1925 rescued in Sweden
Mapping long-term and high-resolution global gridded photosynthetically active radiation using the ISCCP H-series cloud product and reanalysis data
Description of the China global Merged Surface Temperature version 2.0
TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning
Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations
Multi-site, multi-crop measurements in the soil–vegetation–atmosphere continuum: a comprehensive dataset from two climatically contrasting regions in southwestern Germany for the period 2009–2018
Full-coverage 1 km daily ambient PM2.5 and O3 concentrations of China in 2005–2017 based on a multi-variable random forest model
Median bed-material sediment particle size across rivers in the contiguous US
A flux tower dataset tailored for land model evaluation
A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018
A harmonized global land evaporation dataset from model-based products covering 1980–2017
Estimating population and urban areas at risk of coastal hazards, 1990–2015: how data choices matter
Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017
GRQA: Global River Water Quality Archive
A 1 km global cropland dataset from 10 000 BCE to 2100 CE
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables
SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach
Nitrogen deposition in the UK at 1 km resolution from 1990 to 2017
ERA5-Land: a state-of-the-art global reanalysis dataset for land applications
An all-sky 1 km daily land surface air temperature product over mainland China for 2003–2019 from MODIS and ancillary data
100 years of lake evolution over the Qinghai–Tibet Plateau
The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019
Coastal complexity of the Antarctic continent
UAV-based very high resolution point cloud, digital surface model and orthomosaic of the Chã das Caldeiras lava fields (Fogo, Cabo Verde)
AQ-Bench: a benchmark dataset for machine learning on global air quality metrics
Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018
A new merged dataset for analyzing clouds, precipitation and atmospheric parameters based on ERA5 reanalysis data and the measurements of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner
A new satellite-derived dataset for marine aquaculture areas in China's coastal region
Database of petrophysical properties of the Mid-German Crystalline Rise
Landsat-derived bathymetry of lakes on the Arctic Coastal Plain of northern Alaska
Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China
Hyperspectral-reflectance dataset of dry, wet and submerged marine litter
A climate service for ecologists: sharing pre-processed EURO-CORDEX regional climate scenario data using the eLTER Information System
Crowdsourced air traffic data from the OpenSky Network 2019–2020
A restructured and updated global soil respiration database (SRDB-V5)
The Berkeley Earth Land/Ocean Temperature Record
Dielectric database of organic Arctic soils (DDOAS)
Global Carbon Budget 2020
A global long-term (1981–2000) land surface temperature product for NOAA AVHRR
A coastally improved global dataset of wet tropospheric corrections for satellite altimetry
Xinxin Wang, Xiangming Xiao, Yuanwei Qin, Jinwei Dong, Jihua Wu, and Bo Li
Earth Syst. Sci. Data, 14, 3757–3771, https://doi.org/10.5194/essd-14-3757-2022, https://doi.org/10.5194/essd-14-3757-2022, 2022
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We generated China’s surface water bodies, Large Dams, Reservoirs, and Lakes (China-LDRL) dataset by analyzing all available Landsat imagery in 2019 (19\,338 images) in Google Earth Engine. The dataset provides accurate information on the geographical locations and sizes of surface water bodies, large dams, reservoirs, and lakes in China. The China-LDRL dataset will contribute to the understanding of water security and water resources management in China.
Jie Chen, Qi Yao, Ziyue Chen, Manchun Li, Zhaozhan Hao, Cheng Liu, Wei Zheng, Miaoqing Xu, Xiao Chen, Jing Yang, Qiancheng Lv, and Bingbo Gao
Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022, https://doi.org/10.5194/essd-14-3489-2022, 2022
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The potential degradation of mainstream global fire products leads to large uncertainty in the effective monitoring of wildfires and their influence. To fill this gap, we produced a Fengyun-3D (FY-3D) global active fire product with a similar spatial and temporal resolution to MODIS fire products, aiming to serve as continuity and a replacement for MODIS fire products. The FY-3D fire product is an ideal tool for global fire monitoring and can be preferably employed for fire monitoring in China.
Yijie Sui, Min Feng, Chunling Wang, and Xin Li
Earth Syst. Sci. Data, 14, 3349–3363, https://doi.org/10.5194/essd-14-3349-2022, https://doi.org/10.5194/essd-14-3349-2022, 2022
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High-latitude water bodies differ greatly in their morphological and topological characteristics related to their formation, type, and vulnerability. In this paper, we present a water body dataset for the North American high latitudes (WBD-NAHL). Nearly 6.5 million water bodies were identified, with approximately 6 million (~90 %) of them smaller than 0.1 km2.
Amy McNally, Jossy Jacob, Kristi Arsenault, Kimberly Slinski, Daniel P. Sarmiento, Andrew Hoell, Shahriar Pervez, James Rowland, Mike Budde, Sujay Kumar, Christa Peters-Lidard, and James P. Verdin
Earth Syst. Sci. Data, 14, 3115–3135, https://doi.org/10.5194/essd-14-3115-2022, https://doi.org/10.5194/essd-14-3115-2022, 2022
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The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams described here generate routine estimates of snow, soil moisture, runoff, and other variables useful for tracking water availability. These data are hosted by NASA and USGS data portals for public use.
Thomas R. Etherington, George L. W. Perry, and Janet M. Wilmshurst
Earth Syst. Sci. Data, 14, 2817–2832, https://doi.org/10.5194/essd-14-2817-2022, https://doi.org/10.5194/essd-14-2817-2022, 2022
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Long time series of temperature and rainfall grids are fundamental to understanding how these variables affects environmental or ecological patterns and processes. We present a History of Open Temperature and Rainfall with Uncertainty in New Zealand (HOTRUNZ) that is an open-access dataset that provides monthly 1 km resolution grids of rainfall and mean, minimum, and maximum daily temperatures with associated uncertainties for New Zealand from 1910 to 2019.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Earth Syst. Sci. Data, 14, 2767–2784, https://doi.org/10.5194/essd-14-2767-2022, https://doi.org/10.5194/essd-14-2767-2022, 2022
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We present a dataset of cloud optical depths, effective radii and water paths from optically thin clouds observed in the Arctic around Svalbard. The data have been retrieved from infrared spectral radiance measured using a Fourier-transform infrared (FTIR) spectrometer. Besides a description of the measurements and retrieval technique, the data are put into context with results of corresponding measurements from microwave radiometer, lidar and cloud radar.
Jianglei Xu, Shunlin Liang, and Bo Jiang
Earth Syst. Sci. Data, 14, 2315–2341, https://doi.org/10.5194/essd-14-2315-2022, https://doi.org/10.5194/essd-14-2315-2022, 2022
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Land surface all-wave net radiation (Rn) is a key parameter in many land processes. Current products have drawbacks of coarse resolutions, large uncertainty, and short time spans. A deep learning method was used to obtain global surface Rn. A long-term Rn product was generated from 1981 to 2019 using AVHRR data. The product has the highest accuracy and a reasonable spatiotemporal variation compared to three other products. Our product will play an important role in long-term climate change.
Verónica González-Gambau, Estrella Olmedo, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Justino Martínez, Pekka Alenius, Laura Tuomi, Rafael Catany, Manuel Arias, Carolina Gabarró, Nina Hoareau, Marta Umbert, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 2343–2368, https://doi.org/10.5194/essd-14-2343-2022, https://doi.org/10.5194/essd-14-2343-2022, 2022
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We present the first Soil Moisture and Ocean Salinity Sea Surface Salinity (SSS) dedicated products over the Baltic Sea (ESA Baltic+ Salinity Dynamics). The Baltic+ L3 product covers 9 days in a 0.25° grid. The Baltic+ L4 is derived by merging L3 SSS with sea surface temperature information, giving a daily product in a 0.05° grid. The accuracy of L3 is 0.7–0.8 and 0.4 psu for the L4. Baltic+ products have shown to be useful, covering spatiotemporal data gaps and for validating numerical models.
Chunlüe Zhou, Cesar Azorin-Molina, Erik Engström, Lorenzo Minola, Lennart Wern, Sverker Hellström, Jessika Lönn, and Deliang Chen
Earth Syst. Sci. Data, 14, 2167–2177, https://doi.org/10.5194/essd-14-2167-2022, https://doi.org/10.5194/essd-14-2167-2022, 2022
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To fill the key gap of short availability and inhomogeneity of wind speed (WS) in Sweden, we rescued the early paper records of WS since 1925 and built the first 10-member centennial homogenized WS dataset (HomogWS-se) for community use. An initial WS stilling and recovery before the 1990s was observed, and a strong link with North Atlantic Oscillation was found. HomogWS-se improves our knowledge of uncertainty and causes of historical WS changes.
Wenjun Tang, Jun Qin, Kun Yang, Yaozhi Jiang, and Weihao Pan
Earth Syst. Sci. Data, 14, 2007–2019, https://doi.org/10.5194/essd-14-2007-2022, https://doi.org/10.5194/essd-14-2007-2022, 2022
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Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fields. In this study, we produced a 35-year high-resolution global gridded PAR dataset. Compared with the well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES), our PAR product was found to be a more accurate dataset with higher resolution.
Wenbin Sun, Yang Yang, Liya Chao, Wenjie Dong, Boyin Huang, Phil Jones, and Qingxiang Li
Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, https://doi.org/10.5194/essd-14-1677-2022, 2022
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The new China global Merged Surface Temperature CMST 2.0 is the updated version of CMST-Interim used in the IPCC's AR6. The updated dataset is described in this study, containing three versions: CMST2.0 – Nrec, CMST2.0 – Imax, and CMST2.0 – Imin. The reconstructed datasets significantly improve data coverage, especially in the high latitudes in the Northern Hemisphere, thus increasing the long-term trends at global, hemispheric, and regional scales since 1850.
Rohaifa Khaldi, Domingo Alcaraz-Segura, Emilio Guirado, Yassir Benhammou, Abdellatif El Afia, Francisco Herrera, and Siham Tabik
Earth Syst. Sci. Data, 14, 1377–1411, https://doi.org/10.5194/essd-14-1377-2022, https://doi.org/10.5194/essd-14-1377-2022, 2022
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This dataset with millions of 22-year time series for seven spectral bands was built by merging Terra and Aqua satellite data and annotated for 29 LULC classes by spatial–temporal agreement across 15 global LULC products. The mean F1 score was 96 % at the coarsest classification level and 87 % at the finest one. The dataset is born to develop and evaluate machine learning models to perform global LULC mapping given the disagreement between current global LULC products.
Chuanmin Hu
Earth Syst. Sci. Data, 14, 1183–1192, https://doi.org/10.5194/essd-14-1183-2022, https://doi.org/10.5194/essd-14-1183-2022, 2022
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Using data collected by the Hyperspectral Imager for the Coastal Ocean (HICO) between 2010–2014, hyperspectral reflectance of various floating matters in global oceans and lakes is derived for the spectral range of 400–800 nm. Such reflectance spectra are expected to provide spectral endmembers to differentiate and quantify the floating matters from existing multi-band satellite sensors and future hyperspectral satellite missions such as NASA’s PACE, SBG, and GLIMR missions.
Tobias K. D. Weber, Joachim Ingwersen, Petra Högy, Arne Poyda, Hans-Dieter Wizemann, Michael Scott Demyan, Kristina Bohm, Ravshan Eshonkulov, Sebastian Gayler, Pascal Kremer, Moritz Laub, Yvonne Funkiun Nkwain, Christian Troost, Irene Witte, Tim Reichenau, Thomas Berger, Georg Cadisch, Torsten Müller, Andreas Fangmeier, Volker Wulfmeyer, and Thilo Streck
Earth Syst. Sci. Data, 14, 1153–1181, https://doi.org/10.5194/essd-14-1153-2022, https://doi.org/10.5194/essd-14-1153-2022, 2022
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Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
Runmei Ma, Jie Ban, Qing Wang, Yayi Zhang, Yang Yang, Shenshen Li, Wenjiao Shi, Zhen Zhou, Jiawei Zang, and Tiantian Li
Earth Syst. Sci. Data, 14, 943–954, https://doi.org/10.5194/essd-14-943-2022, https://doi.org/10.5194/essd-14-943-2022, 2022
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We constructed multi-variable random forest models based on 10-fold cross-validation and estimated daily PM2.5 and O3 concentration of China in 2005–2017 at a resolution of 1 km. The daily R2 values of PM2.5 and O3 were 0.85 and 0.77. The meteorological variables can significantly affect both PM2.5 and O3 modeling. During 2005–2017, PM2.5 exhibited an overall downward trend, while O3 experienced the opposite. The temporal trend of PM2.5 and O3 had spatial characteristics during the study period.
Guta Wakbulcho Abeshu, Hong-Yi Li, Zhenduo Zhu, Zeli Tan, and L. Ruby Leung
Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
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Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Anna M. Ukkola, Gab Abramowitz, and Martin G. De Kauwe
Earth Syst. Sci. Data, 14, 449–461, https://doi.org/10.5194/essd-14-449-2022, https://doi.org/10.5194/essd-14-449-2022, 2022
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Flux towers provide measurements of water, energy, and carbon fluxes. Flux tower data are invaluable in improving and evaluating land models but are not suited to modelling applications as published. Here we present flux tower data tailored for land modelling, encompassing 170 sites globally. Our dataset resolves several key limitations hindering the use of flux tower data in land modelling, including incomplete forcing variable, data format, and low data quality.
Hui Tao, Kaishan Song, Ge Liu, Qiang Wang, Zhidan Wen, Pierre-Andre Jacinthe, Xiaofeng Xu, Jia Du, Yingxin Shang, Sijia Li, Zongming Wang, Lili Lyu, Junbin Hou, Xiang Wang, Dong Liu, Kun Shi, Baohua Zhang, and Hongtao Duan
Earth Syst. Sci. Data, 14, 79–94, https://doi.org/10.5194/essd-14-79-2022, https://doi.org/10.5194/essd-14-79-2022, 2022
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During 1984–2018, lakes in the Tibetan-Qinghai Plateau had the clearest water (mean 3.32 ± 0.38 m), while those in the northeastern region had the lowest Secchi disk depth (SDD) (mean 0.60 ± 0.09 m). Among the 10 814 lakes with > 10 years of SDD results, 55.4 % and 3.5 % experienced significantly increasing and decreasing trends of SDD, respectively. With the exception of Inner Mongolia–Xinjiang, more than half of lakes in all the other regions exhibited a significant trend of increasing SDD.
Jiao Lu, Guojie Wang, Tiexi Chen, Shijie Li, Daniel Fiifi Tawia Hagan, Giri Kattel, Jian Peng, Tong Jiang, and Buda Su
Earth Syst. Sci. Data, 13, 5879–5898, https://doi.org/10.5194/essd-13-5879-2021, https://doi.org/10.5194/essd-13-5879-2021, 2021
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This study has combined three existing land evaporation (ET) products to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25° to define the global proxy ET with lower uncertainties. The merged product is the best at capturing dynamics over different locations and times among all data sets. The merged product performed well over a range of vegetation cover scenarios and also captured the trend of land evaporation over different areas well.
Kytt MacManus, Deborah Balk, Hasim Engin, Gordon McGranahan, and Rya Inman
Earth Syst. Sci. Data, 13, 5747–5801, https://doi.org/10.5194/essd-13-5747-2021, https://doi.org/10.5194/essd-13-5747-2021, 2021
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New estimates of population and land area by settlement types within low-elevation coastal zones (LECZs) based on four sources of population data, four sources of settlement data and four sources of elevation data for the years 1990, 2000 and 2015. The paper describes the sensitivity of these estimates and discusses the fitness of use guiding user decisions. Data choices impact the number of people estimated within LECZs, but across all sources the LECZs are predominantly urban and growing.
Yanhua Xie, Holly K. Gibbs, and Tyler J. Lark
Earth Syst. Sci. Data, 13, 5689–5710, https://doi.org/10.5194/essd-13-5689-2021, https://doi.org/10.5194/essd-13-5689-2021, 2021
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We created 30 m resolution annual irrigation maps covering the conterminous US for the period of 1997–2017, together with derivative products and ground reference data. The products have several improvements over other data, including field-level details of change and frequency, an annual time step, a collection of ~ 10 000 ground reference locations for the eastern US, and improved mapping accuracy of over 90 %, especially in the east compared to others of 50 % to 80 %.
Holger Virro, Giuseppe Amatulli, Alexander Kmoch, Longzhu Shen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 5483–5507, https://doi.org/10.5194/essd-13-5483-2021, https://doi.org/10.5194/essd-13-5483-2021, 2021
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Water quality modeling is essential for understanding and mitigating water quality deterioration in river networks due to agricultural and industrial pollution. Improving the availability and usability of open data is vital to support global water quality modeling efforts. The GRQA extends the spatial and temporal coverage of previously available water quality data and provides a reproducible workflow for combining multi-source water quality datasets.
Bowen Cao, Le Yu, Xuecao Li, Min Chen, Xia Li, Pengyu Hao, and Peng Gong
Earth Syst. Sci. Data, 13, 5403–5421, https://doi.org/10.5194/essd-13-5403-2021, https://doi.org/10.5194/essd-13-5403-2021, 2021
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In the study, the first 1 km global cropland proportion dataset for 10 000 BCE–2100 CE was produced through the harmonization and downscaling framework. The mapping result coincides well with widely used datasets at present. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The dataset will be valuable for long-term simulations and precise analyses. The framework can be extended to specific regions or other land use types.
Diyang Cui, Shunlin Liang, Dongdong Wang, and Zheng Liu
Earth Syst. Sci. Data, 13, 5087–5114, https://doi.org/10.5194/essd-13-5087-2021, https://doi.org/10.5194/essd-13-5087-2021, 2021
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Large portions of the Earth's surface are expected to experience changes in climatic conditions. The rearrangement of climate distributions can lead to serious impacts on ecological and social systems. Major climate zones are distributed in a predictable pattern and are largely defined following the Köppen climate classification. This creates an urgent need to compile a series of Köppen climate classification maps with finer spatial and temporal resolutions and improved accuracy.
Amanda R. Fay, Luke Gregor, Peter Landschützer, Galen A. McKinley, Nicolas Gruber, Marion Gehlen, Yosuke Iida, Goulven G. Laruelle, Christian Rödenbeck, Alizée Roobaert, and Jiye Zeng
Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, https://doi.org/10.5194/essd-13-4693-2021, 2021
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The movement of carbon dioxide from the atmosphere to the ocean is estimated using surface ocean carbon (pCO2) measurements and an equation including variables such as temperature and wind speed; the choices of these variables lead to uncertainties. We introduce the SeaFlux ensemble which provides carbon flux maps calculated in a consistent manner, thus reducing uncertainty by using common choices for wind speed and a set definition of "global" coverage.
Samuel J. Tomlinson, Edward J. Carnell, Anthony J. Dore, and Ulrike Dragosits
Earth Syst. Sci. Data, 13, 4677–4692, https://doi.org/10.5194/essd-13-4677-2021, https://doi.org/10.5194/essd-13-4677-2021, 2021
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Nitrogen (N) may impact the environment in many ways, and estimation of its deposition to the terrestrial surface is of interest. N deposition data have not been generated at a high resolution (1 km × 1 km) over a long time series in the UK before now. This study concludes that N deposition has reduced by ~ 40 % from 1990. The impact of these results allows analysis of environmental impacts at a high spatial and temporal resolution, using a consistent methodology and consistent set of input data.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
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The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Yan Chen, Shunlin Liang, Han Ma, Bing Li, Tao He, and Qian Wang
Earth Syst. Sci. Data, 13, 4241–4261, https://doi.org/10.5194/essd-13-4241-2021, https://doi.org/10.5194/essd-13-4241-2021, 2021
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This study used remotely sensed and assimilated data to estimate all-sky land surface air temperature (Ta) using a machine learning method, and developed an all-sky 1 km daily mean land Ta product for 2003–2019 over mainland China. Validation results demonstrated that this dataset has achieved satisfactory accuracy and high spatial resolution simultaneously, which fills the current dataset gap in this field and plays an important role in studies of climate change and the hydrological cycle.
Guoqing Zhang, Youhua Ran, Wei Wan, Wei Luo, Wenfeng Chen, Fenglin Xu, and Xin Li
Earth Syst. Sci. Data, 13, 3951–3966, https://doi.org/10.5194/essd-13-3951-2021, https://doi.org/10.5194/essd-13-3951-2021, 2021
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Lakes can be effective indicators of climate change, especially over the Qinghai–Tibet Plateau. Here, we provide the most comprehensive lake mapping covering the past 100 years. The new features of this data set are (1) its temporal length, providing the longest period of lake observations from maps, (2) the data set provides a state-of-the-art lake inventory for the Landsat era (from the 1970s to 2020), and (3) it provides the densest lake observations for lakes with areas larger than 1 km2.
Jie Yang and Xin Huang
Earth Syst. Sci. Data, 13, 3907–3925, https://doi.org/10.5194/essd-13-3907-2021, https://doi.org/10.5194/essd-13-3907-2021, 2021
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We produce the 30 m annual China land cover dataset (CLCD), with an accuracy reaching 79.31 %. Trends and patterns of land cover changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and increase in forest (+4.34 %). The CLCD generally reflected the rapid urbanization and a series of ecological projects in China and revealed the anthropogenic implications on LC under the condition of climate change.
Richard Porter-Smith, John McKinlay, Alexander D. Fraser, and Robert A. Massom
Earth Syst. Sci. Data, 13, 3103–3114, https://doi.org/10.5194/essd-13-3103-2021, https://doi.org/10.5194/essd-13-3103-2021, 2021
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This study quantifies the characteristic complexity
signaturesaround the Antarctic outer coastal margin, giving a multiscale estimate of the magnitude and direction of undulation or complexity at each point location along the entire coastline. It has numerous applications for both geophysical and biological studies and will contribute to Antarctic research requiring quantitative information about this important interface.
Gonçalo Vieira, Carla Mora, Pedro Pina, Ricardo Ramalho, and Rui Fernandes
Earth Syst. Sci. Data, 13, 3179–3201, https://doi.org/10.5194/essd-13-3179-2021, https://doi.org/10.5194/essd-13-3179-2021, 2021
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Fogo in Cabo Verde is one of the most active ocean island volcanoes on Earth, posing important hazards to local populations and at a regional level. The last eruption occurred from November 2014 to February 2015. A survey of the Chã das Caldeiras area was conducted using a fixed-wing unmanned aerial vehicle. A point cloud, digital surface model and orthomosaic with 10 and 25 cm resolutions are provided, together with the full aerial survey projects and datasets.
Clara Betancourt, Timo Stomberg, Ribana Roscher, Martin G. Schultz, and Scarlet Stadtler
Earth Syst. Sci. Data, 13, 3013–3033, https://doi.org/10.5194/essd-13-3013-2021, https://doi.org/10.5194/essd-13-3013-2021, 2021
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With the AQ-Bench dataset, we contribute to shared data usage and machine learning methods in the field of environmental science. The AQ-Bench dataset contains air quality data and metadata from more than 5500 air quality observation stations all over the world. The dataset offers a low-threshold entrance to machine learning on a real-world environmental dataset. AQ-Bench thus provides a blueprint for environmental benchmark datasets.
Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann
Earth Syst. Sci. Data, 13, 2701–2722, https://doi.org/10.5194/essd-13-2701-2021, https://doi.org/10.5194/essd-13-2701-2021, 2021
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Semi-arid regions depend on the freshwater resources from the rainy seasons as they are crucial for ensuring security for drinking water, food and electricity. Thus, forecasting the conditions for the next season is crucial for proactive water management. We hence present a seasonal forecast product for four semi-arid domains in Iran, Brazil, Sudan/Ethiopia and Ecuador/Peru. It provides a benchmark for seasonal forecasts and, finally, a crucial contribution for improved disaster preparedness.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Lilu Sun and Yunfei Fu
Earth Syst. Sci. Data, 13, 2293–2306, https://doi.org/10.5194/essd-13-2293-2021, https://doi.org/10.5194/essd-13-2293-2021, 2021
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Multi-source dataset use is hampered by use of different spatial and temporal resolutions. We merged Tropical Rainfall Measuring Mission precipitation radar and visible and infrared scanner measurements with ERA5 reanalysis. The statistical results indicate this process has no unacceptable influence on the original data. The merged dataset can help in studying characteristics of and changes in cloud and precipitation systems and provides an opportunity for data analysis and model simulations.
Yongyong Fu, Jinsong Deng, Hongquan Wang, Alexis Comber, Wu Yang, Wenqiang Wu, Shixue You, Yi Lin, and Ke Wang
Earth Syst. Sci. Data, 13, 1829–1842, https://doi.org/10.5194/essd-13-1829-2021, https://doi.org/10.5194/essd-13-1829-2021, 2021
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Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the first time. It was found to cover a total area of ~1100 km2, of which more than 85 % is marine plant culture areas, with 87 % found in four coastal provinces. The results confirm the applicability and effectiveness of deep learning when applied to GF-1 data at the national scale, identifying the detailed spatial distributions and supporting the sustainable management of coastal resources in China.
Sebastian Weinert, Kristian Bär, and Ingo Sass
Earth Syst. Sci. Data, 13, 1441–1459, https://doi.org/10.5194/essd-13-1441-2021, https://doi.org/10.5194/essd-13-1441-2021, 2021
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Physical rock properties are a key element for resource exploration, the interpretation of results from geophysical methods or the parameterization of physical or geological models. Despite the need for physical rock properties, data are still very scarce and often not available for the area of interest. The database presented aims to provide easy access to physical rock properties measured at 224 locations in Bavaria, Hessen, Rhineland-Palatinate and Thuringia (Germany).
Claire E. Simpson, Christopher D. Arp, Yongwei Sheng, Mark L. Carroll, Benjamin M. Jones, and Laurence C. Smith
Earth Syst. Sci. Data, 13, 1135–1150, https://doi.org/10.5194/essd-13-1135-2021, https://doi.org/10.5194/essd-13-1135-2021, 2021
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Sonar depth point measurements collected at 17 lakes on the Arctic Coastal Plain of Alaska are used to train and validate models to map lake bathymetry. These models predict depth from remotely sensed lake color and are able to explain 58.5–97.6 % of depth variability. To calculate water volumes, we integrate this modeled bathymetry with lake surface area. Knowledge of Alaskan lake bathymetries and volumes is crucial to better understanding water storage, energy balance, and ecological habitat.
Fei Feng and Kaicun Wang
Earth Syst. Sci. Data, 13, 907–922, https://doi.org/10.5194/essd-13-907-2021, https://doi.org/10.5194/essd-13-907-2021, 2021
Els Knaeps, Sindy Sterckx, Gert Strackx, Johan Mijnendonckx, Mehrdad Moshtaghi, Shungudzemwoyo P. Garaba, and Dieter Meire
Earth Syst. Sci. Data, 13, 713–730, https://doi.org/10.5194/essd-13-713-2021, https://doi.org/10.5194/essd-13-713-2021, 2021
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This paper describes a dataset consisting of 47 hyperspectral-reflectance measurements of plastic litter samples. The plastic litter samples include virgin and real samples. They were measured in dry conditions, and a selection of the samples were also measured in wet conditions and submerged in a water tank. The dataset can be used to better understand the effect of water absorption on the plastics and develop algorithms to detect and characterize marine plastics.
Susannah Rennie, Klaus Goergen, Christoph Wohner, Sander Apweiler, Johannes Peterseil, and John Watkins
Earth Syst. Sci. Data, 13, 631–644, https://doi.org/10.5194/essd-13-631-2021, https://doi.org/10.5194/essd-13-631-2021, 2021
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This paper describes a pan-European climate service data product intended for ecological researchers. Access to regional climate scenario data will save ecologists time, and, for many, it will allow them to work with data resources that they will not previously have used due to a lack of knowledge and skills to access them. Providing easy access to climate scenario data in this way enhances long-term ecological research, for example in general regional climate change or impact assessments.
Martin Strohmeier, Xavier Olive, Jannis Lübbe, Matthias Schäfer, and Vincent Lenders
Earth Syst. Sci. Data, 13, 357–366, https://doi.org/10.5194/essd-13-357-2021, https://doi.org/10.5194/essd-13-357-2021, 2021
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Flight data have been used widely for research by academic researchers and (supra)national institutions. Example domains range from epidemiology (e.g. examining the spread of COVID-19 via air travel) to economics (e.g. use as proxy for immediate forecasting of the state of a country's economy) and Earth sciences (climatology in particular). Until now, accurate flight data have been available only in small pieces from closed, proprietary sources. This work changes this with a crowdsourced effort.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
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Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Robert A. Rohde and Zeke Hausfather
Earth Syst. Sci. Data, 12, 3469–3479, https://doi.org/10.5194/essd-12-3469-2020, https://doi.org/10.5194/essd-12-3469-2020, 2020
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A global land and ocean temperature record was created by combining the Berkeley Earth monthly land temperature field with a newly interpolated version of the HadSST3 ocean dataset. The resulting dataset covers the period from 1850 to present.
This paper describes the methods used to create that combination and compares the results to other estimates of global temperature and the associated recent climate change, giving similar results.
Igor Savin, Valery Mironov, Konstantin Muzalevskiy, Sergey Fomin, Andrey Karavayskiy, Zdenek Ruzicka, and Yuriy Lukin
Earth Syst. Sci. Data, 12, 3481–3487, https://doi.org/10.5194/essd-12-3481-2020, https://doi.org/10.5194/essd-12-3481-2020, 2020
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This article presents a dielectric database of organic Arctic soils. This database was created based on dielectric measurements of seven samples of organic soils collected in various parts of the Arctic tundra. The created database can serve not only as a source of experimental data for the development of new soil dielectric models for the Arctic tundra but also as a source of training data for artificial intelligence satellite algorithms of soil moisture retrievals based on neural networks.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jin Ma, Ji Zhou, Frank-Michael Göttsche, Shunlin Liang, Shaofei Wang, and Mingsong Li
Earth Syst. Sci. Data, 12, 3247–3268, https://doi.org/10.5194/essd-12-3247-2020, https://doi.org/10.5194/essd-12-3247-2020, 2020
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Land surface temperature is an important parameter in the research of climate change and many land surface processes. This article describes the development and testing of an algorithm for generating a consistent global long-term land surface temperature product from 20 years of NOAA AVHRR radiance data. The preliminary validation results indicate good accuracy of this new long-term product, which has been designed to simplify applications and support the scientific research community.
Clara Lázaro, Maria Joana Fernandes, Telmo Vieira, and Eliana Vieira
Earth Syst. Sci. Data, 12, 3205–3228, https://doi.org/10.5194/essd-12-3205-2020, https://doi.org/10.5194/essd-12-3205-2020, 2020
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In satellite altimetry (SA), the wet tropospheric correction (WTC) accounts for the path delay induced mainly by atmospheric water vapour. In coastal regions, the accuracy of the WTC determined by the on-board radiometer deteriorates. The GPD+ methodology, developed by the University of Porto in the remit of ESA-funded projects, computes improved WTCs for SA. Global enhanced products are generated for all past and operational altimetric missions, forming a relevant dataset for coastal altimetry.
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Arain, M. A. and Restrepo-Coupe, N.: Net ecosystem production in a temperate pine plantation in southeastern Canada, Agr. Forest Meteorol., 128, 223–241, https://doi.org/10.1016/j.agrformet.2004.10.003, 2005.
Arneth, A., Veenendaal, E. M., Best, C., Timmermans, W., Kolle, O., Montagnani, L., and Shibistova, O.: Water use strategies and ecosystem-atmosphere exchange of CO2 in two highly seasonal environments, Biogeosciences, 3, 421–437, https://doi.org/10.5194/bg-3-421-2006, 2006.
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Short summary
We provide continuous half-hourly carbon and energy fluxes for 2001 to 2014 at 0.5° spatial resolution, which allows for analyzing diurnal cycles globally. The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). In addition, we provide a derived product that only contains monthly average diurnal cycles but which also enables us to study the important characteristics of subdaily patterns at a global scale.
We provide continuous half-hourly carbon and energy fluxes for 2001 to 2014 at 0.5° spatial...
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