Articles | Volume 7, issue 3
https://doi.org/10.5194/gmd-7-931-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-7-931-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
20 May 2014
Development and technical paper |
| 20 May 2014
Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts
C. Szczypta
CNRM-GAME, UMR3589 (Météo-France, CNRS), Toulouse, France
now at: CESBIO, UMR 5126 (CNES, CNRS, IRD, UPS), Toulouse, France
J.-C. Calvet
CNRM-GAME, UMR3589 (Météo-France, CNRS), Toulouse, France
F. Maignan
Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA/CNRS/UVSQ – UMR8212, Gif-sur-Yvette, France
W. Dorigo
Department of Geodesy and Geoinformation, Vienna University of Technology, Vienna, Austria
F. Baret
INRA, EMMAH – UMR1114, Avignon, France
Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA/CNRS/UVSQ – UMR8212, Gif-sur-Yvette, France
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Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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En Liu, Yonghua Zhu, Jean-christophe Calvet, Haishen Lü, Bertrand Bonan, Jingyao Zheng, Qiqi Gou, Xiaoyi Wang, Zhenzhou Ding, Haiting Xu, Ying Pan, and Tingxing Chen
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EGUsphere, https://doi.org/10.5194/egusphere-2023-186, https://doi.org/10.5194/egusphere-2023-186, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Yann Quilcaille, Thomas Gasser, Philippe Ciais, and Olivier Boucher
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Matthew Joseph 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, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Juergen 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 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
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Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
EGUsphere, https://doi.org/10.5194/egusphere-2022-1137, https://doi.org/10.5194/egusphere-2022-1137, 2022
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We explored different options for data assimilation (DA) of 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, which were successful at overcoming these problems, and explore alternative solutions.
Thomas Bossy, Thomas Gasser, and Philippe Ciais
Geosci. Model Dev., 15, 8831–8868, https://doi.org/10.5194/gmd-15-8831-2022, https://doi.org/10.5194/gmd-15-8831-2022, 2022
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We developed a new simple climate model designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: calibration using Bayesian inference, the possibility of coupling with integrated assessment models, and the capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model and its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.
Adil Shah, Olivier Laurent, Luc Lienhardt, Grégoire Broquet, Rodrigo Rivera Martinez, Elisa Allegrini, and Philippe Ciais
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-308, https://doi.org/10.5194/amt-2022-308, 2022
Preprint under review for AMT
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Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
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Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
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The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
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To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Elise Potier, Grégoire Broquet, Yilong Wang, Diego Santaren, Antoine Berchet, Isabelle Pison, Julia Marshall, Philippe Ciais, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5261–5288, https://doi.org/10.5194/amt-15-5261-2022, https://doi.org/10.5194/amt-15-5261-2022, 2022
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Atmospheric inversion at local–regional scales over Europe and pseudo-data assimilation are used to evaluate how CO2 and 14CO2 ground-based measurement networks could complement satellite CO2 imagers to monitor fossil fuel (FF) CO2 emissions. This combination significantly improves precision in the FF emission estimates in areas with a dense network but does not strongly support the separation of the FF from the biogenic signals or the spatio-temporal extrapolation of the satellite information.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
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The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Anthony Rey-Pommier, Frédéric Chevallier, Philippe Ciais, Grégoire Broquet, Theodoros Christoudias, Jonilda Kushta, Didier Hauglustaine, and Jean Sciare
Atmos. Chem. Phys., 22, 11505–11527, https://doi.org/10.5194/acp-22-11505-2022, https://doi.org/10.5194/acp-22-11505-2022, 2022
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Emission inventories for air pollutants can be uncertain in developing countries. In order to overcome these uncertainties, we model nitrogen oxide emissions in Egypt using satellite retrievals. We detect a weekly cycle reflecting Egyptian social norms, an annual cycle consistent with electricity consumption and an activity drop due to the COVID-19 pandemic. However, discrepancies with inventories remain high, illustrating the needs for additional data to improve the potential of our method.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Liu, and Jingyun Fang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-264, https://doi.org/10.5194/essd-2022-264, 2022
Revised manuscript accepted for ESSD
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We provide the first long-term (since 1992), high resolution (8.9 km) satellite radar backscatter data set with a C-band (5.3 GHz) signal dynamic for global lands, the C-band Scatterometer (CScat) data set. CScat was created by fusing signals from ERS (1992–2001, C-band), QSCAT (1999–2009, Ku-band, 13.4 GHz), and ASCAT (since 2007, C-band). CScat has been validated against independent ERS-2 signals. It could be used in a variety of studies such as vegetation monitoring and hydrological modeling.
Haicheng Zhang, Ronny Lauerwald, Pierre Regnier, Philippe Ciais, Kristof Van Oost, Victoria Naipal, Bertrand Guenet, and Wenping Yuan
Earth Syst. Dynam., 13, 1119–1144, https://doi.org/10.5194/esd-13-1119-2022, https://doi.org/10.5194/esd-13-1119-2022, 2022
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We present a land surface model which can simulate the complete lateral transfer of sediment and carbon from land to ocean through rivers. Our model captures the water, sediment, and organic carbon discharges in European rivers well. Application of our model in Europe indicates that lateral carbon transfer can strongly change regional land carbon budgets by affecting organic carbon distribution and soil moisture.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
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Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Rodrigo Andres Rivera Martinez, Diego Santaren, Olivier Laurent, Gregoire Broquet, Ford Cropley, Cécile Mallet, Michel Ramonet, Adil Shah, Leonard Rivier, Caroline Bouchet, Catherine Juery, Olivier Duclaux, and Philippe Ciais
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-200, https://doi.org/10.5194/amt-2022-200, 2022
Revised manuscript accepted for AMT
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A network of low cost sensors is a good alternative to improve the detection of fugitive CH4 emissions. In this study, we present the results of 4 tests conducted with 2 types of Figaro sensors, which were assembled on four chambers in a laboratory experiment: a comparison of five models to reconstruct the CH4 signal; a strategy to reduce the training set size; a detection of age effects in the sensors; and a test of the capability to transfer a model between chambers on the same type of sensor.
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, https://doi.org/10.5194/bg-19-2557-2022, 2022
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For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 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.
Irina Melnikova, Olivier Boucher, Patricia Cadule, Katsumasa Tanaka, Thomas Gasser, Tomohiro Hajima, Yann Quilcaille, Hideo Shiogama, Roland Séférian, Kaoru Tachiiri, Nicolas Vuichard, Tokuta Yokohata, and Philippe Ciais
Earth Syst. Dynam., 13, 779–794, https://doi.org/10.5194/esd-13-779-2022, https://doi.org/10.5194/esd-13-779-2022, 2022
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The deployment of bioenergy crops for capturing carbon from the atmosphere facilitates global warming mitigation via generating negative CO2 emissions. Here, we explored the consequences of large-scale energy crops deployment on the land carbon cycle. The land-use change for energy crops leads to carbon emissions and loss of future potential increase in carbon uptake by natural ecosystems. This impact should be taken into account by the modeling teams and accounted for in mitigation policies.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
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A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Céline Gommet, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, Haicheng Zhang, and Pierre Regnier
Earth Syst. Dynam., 13, 393–418, https://doi.org/10.5194/esd-13-393-2022, https://doi.org/10.5194/esd-13-393-2022, 2022
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Dissolved organic carbon (DOC) leaching from soils into river networks is an important component of the land carbon (C) budget, but its spatiotemporal variation is not yet fully constrained. We use a land surface model to simulate the present-day land C budget at the European scale, including leaching of DOC from the soil. We found average leaching of 14.3 Tg C yr−1 (0.6 % of terrestrial net primary production) with seasonal variations. We determine runoff and temperature to be the main drivers.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
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Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Lore T. Verryckt, Sara Vicca, Leandro Van Langenhove, Clément Stahl, Dolores Asensio, Ifigenia Urbina, Romà Ogaya, Joan Llusià, Oriol Grau, Guille Peguero, Albert Gargallo-Garriga, Elodie A. Courtois, Olga Margalef, Miguel Portillo-Estrada, Philippe Ciais, Michael Obersteiner, Lucia Fuchslueger, Laynara F. Lugli, Pere-Roc Fernandez-Garberí, Helena Vallicrosa, Melanie Verlinden, Christian Ranits, Pieter Vermeir, Sabrina Coste, Erik Verbruggen, Laëtitia Bréchet, Jordi Sardans, Jérôme Chave, Josep Peñuelas, and Ivan A. Janssens
Earth Syst. Sci. Data, 14, 5–18, https://doi.org/10.5194/essd-14-5-2022, https://doi.org/10.5194/essd-14-5-2022, 2022
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We provide a comprehensive dataset of vertical profiles of photosynthesis and important leaf traits, including leaf N and P concentrations, from two 3-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N and P, and other leaf nutrients, in photosynthesis in tropical forests.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-337, https://doi.org/10.5194/gmd-2021-337, 2021
Revised manuscript not accepted
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Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
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.
Alex Resovsky, Michel Ramonet, Leonard Rivier, Jerome Tarniewicz, Philippe Ciais, Martin Steinbacher, Ivan Mammarella, Meelis Mölder, Michal Heliasz, Dagmar Kubistin, Matthias Lindauer, Jennifer Müller-Williams, Sebastien Conil, and Richard Engelen
Atmos. Meas. Tech., 14, 6119–6135, https://doi.org/10.5194/amt-14-6119-2021, https://doi.org/10.5194/amt-14-6119-2021, 2021
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We present a technical description of a statistical methodology for extracting synoptic- and seasonal-length anomalies from greenhouse gas time series. The definition of what represents an anomalous signal is somewhat subjective, which we touch on throughout the paper. We show, however, that the method performs reasonably well in extracting portions of time series influenced by significant North Atlantic Oscillation weather episodes and continent-wide terrestrial biospheric aberrations.
Pramod Kumar, Grégoire Broquet, Camille Yver-Kwok, Olivier Laurent, Susan Gichuki, Christopher Caldow, Ford Cropley, Thomas Lauvaux, Michel Ramonet, Guillaume Berthe, Frédéric Martin, Olivier Duclaux, Catherine Juery, Caroline Bouchet, and Philippe Ciais
Atmos. Meas. Tech., 14, 5987–6003, https://doi.org/10.5194/amt-14-5987-2021, https://doi.org/10.5194/amt-14-5987-2021, 2021
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This study presents a simple atmospheric inversion modeling framework for the localization and quantification of unknown CH4 and CO2 emissions from point sources based on near-surface mobile concentration measurements and a Gaussian plume dispersion model. It is applied for the estimate of a series of brief controlled releases of CH4 and CO2 with a wide range of rates during the TOTAL TADI-2018 experiment. Results indicate a ~10 %–40 % average error on the estimate of the release rates.
Yuanyuan Huang, Phillipe Ciais, Maurizio Santoro, David Makowski, Jerome Chave, Dmitry Schepaschenko, Rose Z. Abramoff, Daniel S. Goll, Hui Yang, Ye Chen, Wei Wei, and Shilong Piao
Earth Syst. Sci. Data, 13, 4263–4274, https://doi.org/10.5194/essd-13-4263-2021, https://doi.org/10.5194/essd-13-4263-2021, 2021
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Roots play a key role in our Earth system. Here we combine 10 307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially explicit global high-resolution (~ 1 km) root biomass dataset. In total, 142 ± 25 (95 % CI) Pg of live dry-matter biomass is stored belowground, representing a global average root : shoot biomass ratio of 0.25 ± 0.10.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, and Peng Gong
Geosci. Model Dev., 14, 4573–4592, https://doi.org/10.5194/gmd-14-4573-2021, https://doi.org/10.5194/gmd-14-4573-2021, 2021
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In this study, we implemented the specific morphology, phenology and harvest process of oil palm in the global land surface model ORCHIDEE-MICT. The improved model generally reproduces the same leaf area index, biomass density and life cycle fruit yield as observations. This explicit representation of oil palm in a global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
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Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Elisa Bruni, Bertrand Guenet, Yuanyuan Huang, Hugues Clivot, Iñigo Virto, Roberta Farina, Thomas Kätterer, Philippe Ciais, Manuel Martin, and Claire Chenu
Biogeosciences, 18, 3981–4004, https://doi.org/10.5194/bg-18-3981-2021, https://doi.org/10.5194/bg-18-3981-2021, 2021
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Increasing soil organic carbon (SOC) stocks is beneficial for climate change mitigation and food security. One way to enhance SOC stocks is to increase carbon input to the soil. We estimate the amount of carbon input required to reach a 4 % annual increase in SOC stocks in 14 long-term agricultural experiments around Europe. We found that annual carbon input should increase by 43 % under current temperature conditions, by 54 % for a 1 °C warming scenario and by 120 % for a 5 °C warming scenario.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
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Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Bowen Cao, Le Yu, Victoria Naipal, Philippe Ciais, Wei Li, Yuanyuan Zhao, Wei Wei, Die Chen, Zhuang Liu, and Peng Gong
Earth Syst. Sci. Data, 13, 2437–2456, https://doi.org/10.5194/essd-13-2437-2021, https://doi.org/10.5194/essd-13-2437-2021, 2021
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In this study, the first 30 m resolution terrace map of China was developed through supervised pixel-based classification using multisource, multi-temporal data based on the Google Earth Engine platform. The classification performed well with an overall accuracy of 94 %. The terrace mapping algorithm can be used to map large-scale terraces in other regions globally, and the terrace map will be valuable for studies on soil erosion, carbon cycle, and ecosystem service assessments.
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.
Rui Guo, Jiaoyue Wang, Longfei Bing, Dan Tong, Philippe Ciais, Steven J. Davis, Robbie M. Andrew, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 13, 1791–1805, https://doi.org/10.5194/essd-13-1791-2021, https://doi.org/10.5194/essd-13-1791-2021, 2021
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Using a life-cycle approach, we estimated the CO2 process emission and uptake of cement materials produced and consumed from 1930 to 2019; ~21 Gt of CO2, about 55 % of the total process emission, had been abated through cement carbonation. China contributed the greatest to the cumulative uptake, with more than 6 Gt (~30 % of the world total), while ~59 %, or more than 12 Gt, of the total uptake was attributed to mortar. Cement CO2 uptake makes up a considerable part of the human carbon budget.
Wei Min Hao, Matthew C. Reeves, L. Scott Baggett, Yves Balkanski, Philippe Ciais, Bryce L. Nordgren, Alexander Petkov, Rachel E. Corley, Florent Mouillot, Shawn P. Urbanski, and Chao Yue
Biogeosciences, 18, 2559–2572, https://doi.org/10.5194/bg-18-2559-2021, https://doi.org/10.5194/bg-18-2559-2021, 2021
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We examined the trends in the spatial and temporal distribution of the area burned in northern Eurasia from 2002 to 2016. The annual area burned in this region declined by 53 % during the 15-year period under analysis. Grassland fires in Kazakhstan dominated the fire activity, comprising 47 % of the area burned but accounting for 84 % of the decline. A wetter climate and the increase in grazing livestock in Kazakhstan are the major factors contributing to the decline in the area burned.
Yuan Zhang, Olivier Boucher, Philippe Ciais, Laurent Li, and Nicolas Bellouin
Geosci. Model Dev., 14, 2029–2039, https://doi.org/10.5194/gmd-14-2029-2021, https://doi.org/10.5194/gmd-14-2029-2021, 2021
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We investigated different methods to reconstruct spatiotemporal distribution of the fraction of diffuse radiation (Fdf) to qualify the aerosol impacts on GPP using the ORCHIDEE_DF land surface model. We find that climatological-averaging methods which dampen the variability of Fdf can cause significant bias in the modeled diffuse radiation impacts on GPP. Better methods to reconstruct Fdf are recommended.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
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We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Bruno Ringeval, Christoph Müller, Thomas A. M. Pugh, Nathaniel D. Mueller, Philippe Ciais, Christian Folberth, Wenfeng Liu, Philippe Debaeke, and Sylvain Pellerin
Geosci. Model Dev., 14, 1639–1656, https://doi.org/10.5194/gmd-14-1639-2021, https://doi.org/10.5194/gmd-14-1639-2021, 2021
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We assess how and why global gridded crop models (GGCMs) differ in their simulation of potential yield. We build a GCCM emulator based on generic formalism and fit its parameters against aboveground biomass and yield at harvest simulated by eight GGCMs. Despite huge differences between GGCMs, we show that the calibration of a few key parameters allows the emulator to reproduce the GGCM simulations. Our simple but mechanistic model could help to improve the global simulation of potential yield.
Zun Yin, Catherine Ottlé, Philippe Ciais, Feng Zhou, Xuhui Wang, Polcher Jan, Patrice Dumas, Shushi Peng, Laurent Li, Xudong Zhou, Yan Bo, Yi Xi, and Shilong Piao
Hydrol. Earth Syst. Sci., 25, 1133–1150, https://doi.org/10.5194/hess-25-1133-2021, https://doi.org/10.5194/hess-25-1133-2021, 2021
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We improved the irrigation module in a land surface model ORCHIDEE and developed a dam operation model with the aim to investigate how irrigation and dams affect the streamflow fluctuations of the Yellow River. Results show that irrigation mainly reduces the annual river flow. The dam operation, however, mainly affects streamflow variation. By considering two generic operation rules, flood control and base flow guarantee, our dam model can sustainably improve the simulation accuracy.
Diego Santaren, Grégoire Broquet, François-Marie Bréon, Frédéric Chevallier, Denis Siméoni, Bo Zheng, and Philippe Ciais
Atmos. Meas. Tech., 14, 403–433, https://doi.org/10.5194/amt-14-403-2021, https://doi.org/10.5194/amt-14-403-2021, 2021
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Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO2 to monitor anthropogenic emissions from regions, cities and large industrial plants. The analysis, applied to a large ensemble of sources in western Europe, shows a strong dependence of the results on different characteristics of the spaceborne instrument, on the source emission budgets and spreads, and on the wind conditions.
Adam Hastie, Ronny Lauerwald, Philippe Ciais, Fabrice Papa, and Pierre Regnier
Earth Syst. Dynam., 12, 37–62, https://doi.org/10.5194/esd-12-37-2021, https://doi.org/10.5194/esd-12-37-2021, 2021
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We used a model of the Congo Basin to investigate the transfer of carbon (C) from land (vegetation and soils) to inland waters. We estimate that leaching of C to inland waters, emissions of CO2 from the water surface, and the export of C to the coast have all increased over the last century, driven by increasing atmospheric CO2 levels and climate change. We predict that these trends may continue through the 21st century and call for long-term monitoring of these fluxes.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
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.
Yilong Wang, Grégoire Broquet, François-Marie Bréon, Franck Lespinas, Michael Buchwitz, Maximilian Reuter, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, and Philippe Ciais
Geosci. Model Dev., 13, 5813–5831, https://doi.org/10.5194/gmd-13-5813-2020, https://doi.org/10.5194/gmd-13-5813-2020, 2020
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Naomi E. Smith, Rona L. Thompson, Ingrid T. Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton
Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, https://doi.org/10.5194/acp-20-12063-2020, 2020
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The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups. It aims to produce an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period 2006–2015, based on constraints provided by observed CO2 concentrations and using inverse modelling techniques. The use of six different models enables us to investigate the robustness of the results.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
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LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet
Geosci. Model Dev., 13, 3607–3625, https://doi.org/10.5194/gmd-13-3607-2020, https://doi.org/10.5194/gmd-13-3607-2020, 2020
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This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.
Thomas Gasser, Léa Crepin, Yann Quilcaille, Richard A. Houghton, Philippe Ciais, and Michael Obersteiner
Biogeosciences, 17, 4075–4101, https://doi.org/10.5194/bg-17-4075-2020, https://doi.org/10.5194/bg-17-4075-2020, 2020
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We combine several lines of evidence to provide a robust estimate of historical CO2 emissions from land use change. Our novel approach leads to reduced uncertainty and identifies key remaining sources of uncertainty and discrepancy.
We also quantify the carbon removal by natural ecosystems that would have occurred if these ecosystems had not been destroyed (mostly via deforestation). Over the last decade, this foregone carbon sink amounted to about 50 % of the actual emissions.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676, https://doi.org/10.5194/hess-24-3663-2020, https://doi.org/10.5194/hess-24-3663-2020, 2020
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Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Bo Zheng, Frédéric Chevallier, Philippe Ciais, Grégoire Broquet, Yilong Wang, Jinghui Lian, and Yuanhong Zhao
Atmos. Chem. Phys., 20, 8501–8510, https://doi.org/10.5194/acp-20-8501-2020, https://doi.org/10.5194/acp-20-8501-2020, 2020
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The Paris Climate Agreement requires all parties to report CO2 emissions regularly. Given the self-reporting nature of this system, it is critical to evaluate the emission reports with independent observation systems. Here we present the direct observations of city CO2 plumes from space and the quantification of CO2 emissions from these observations over the largest emitter country China. The emissions from 46 hot-spot regions representing 13 % of China's total emissions can be well constrained.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Juraj Balkovic, Philippe Ciais, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, Munir Hoffmann, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Nikolay Khabarov, Marian Koch, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Xuhui Wang, Karina Williams, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 2315–2336, https://doi.org/10.5194/gmd-13-2315-2020, https://doi.org/10.5194/gmd-13-2315-2020, 2020
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Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Crop models, which represent plant biology, are necessary tools for this purpose since they allow representing future climate, farmer choices, and new agricultural geographies. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, under the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to evaluate and improve crop models.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
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We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Ana Maria Roxana Petrescu, Glen P. Peters, Greet Janssens-Maenhout, Philippe Ciais, Francesco N. Tubiello, Giacomo Grassi, Gert-Jan Nabuurs, Adrian Leip, Gema Carmona-Garcia, Wilfried Winiwarter, Lena Höglund-Isaksson, Dirk Günther, Efisio Solazzo, Anja Kiesow, Ana Bastos, Julia Pongratz, Julia E. M. S. Nabel, Giulia Conchedda, Roberto Pilli, Robbie M. Andrew, Mart-Jan Schelhaas, and Albertus J. Dolman
Earth Syst. Sci. Data, 12, 961–1001, https://doi.org/10.5194/essd-12-961-2020, https://doi.org/10.5194/essd-12-961-2020, 2020
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up GHG anthropogenic emissions from agriculture, forestry and other land use (AFOLU) in the EU28. The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models, aiming at reconciling GHG budgets with official country-level UNFCCC inventories. We provide comprehensive emission assessments in support to policy, facilitating real-time verification procedures.
Yidi Xu, Le Yu, Wei Li, Philippe Ciais, Yuqi Cheng, and Peng Gong
Earth Syst. Sci. Data, 12, 847–867, https://doi.org/10.5194/essd-12-847-2020, https://doi.org/10.5194/essd-12-847-2020, 2020
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The first annual oil palm area dataset (AOPD) for Malaysia and Indonesia from 2001 to 2016 was produced by integrating multiple satellite datasets and a change-detection algorithm (BFAST). This dataset reveals that oil palm plantations have expanded from 5.69 to 19.05 M ha in the two countries during the past 16 years. The AOPD is useful in understanding the deforestation process in Southeast Asia and may serve as land-use change inputs in dynamic global vegetation models.
Angelika Xaver, Luca Zappa, Gerhard Rab, Isabella Pfeil, Mariette Vreugdenhil, Drew Hemment, and Wouter Arnoud Dorigo
Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, https://doi.org/10.5194/gi-9-117-2020, 2020
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Soil moisture plays a key role in the hydrological cycle and the climate system. Although soil moisture can be observed by the means of satellites, ground observations are still crucial for evaluating and improving these satellite products. In this study, we investigate the performance of a consumer low-cost soil moisture sensor in the lab and in the field. We demonstrate that this sensor can be used for scientific applications, for example to create a dataset valuable for satellite validation.
Didier G. Leibovici, Shaun Quegan, Edward Comyn-Platt, Garry Hayman, Maria Val Martin, Mathieu Guimberteau, Arsène Druel, Dan Zhu, and Philippe Ciais
Biogeosciences, 17, 1821–1844, https://doi.org/10.5194/bg-17-1821-2020, https://doi.org/10.5194/bg-17-1821-2020, 2020
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Analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, may require land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from. The paper proposes a multivariate spatio-temporal data science method to understand the inherent uncertainties in four LSMs and the variations between them in Nordic areas for the net primary production.
Wei Li, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, Jonathan Doelman, Florian Humpenöder, Anna B. Harper, Taejin Park, David Makowski, Petr Havlik, Michael Obersteiner, Jingmeng Wang, Andreas Krause, and Wenfeng Liu
Earth Syst. Sci. Data, 12, 789–804, https://doi.org/10.5194/essd-12-789-2020, https://doi.org/10.5194/essd-12-789-2020, 2020
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We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
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We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Victoria Naipal, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, and Yilong Wang
Geosci. Model Dev., 13, 1201–1222, https://doi.org/10.5194/gmd-13-1201-2020, https://doi.org/10.5194/gmd-13-1201-2020, 2020
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In this study we present the Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the soil carbon cycle along a cascade of hillslopes, floodplains, and rivers. The model can simulate the removal of soil and carbon from eroding areas and their destination at regional scale. We calibrated and validated the model for the Rhine catchment, and we show that soil erosion is a potential large net carbon sink over the period 1850–2005.
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.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Pierre Regnier, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 13, 507–520, https://doi.org/10.5194/gmd-13-507-2020, https://doi.org/10.5194/gmd-13-507-2020, 2020
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In this second part of the study, we performed simulations of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. We compare simulations using this model to existing data sources to show that it is capable of reproducing dissolved carbon fluxes of potentially great importance for the future of the global permafrost.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
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Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Bertrand Bonan, Clément Albergel, Yongjun Zheng, Alina Lavinia Barbu, David Fairbairn, Simon Munier, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, https://doi.org/10.5194/hess-24-325-2020, 2020
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This paper introduces an ensemble square root filter (EnSRF), a deterministic ensemble Kalman filter, for jointly assimilating observations of the surface soil moisture and leaf area index in the Land Data Assimilation System LDAS-Monde. LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (ISBA) land surface model to improve the reanalysis of land surface variables. EnSRF is compared with the simplified extended Kalman filter over the European Mediterranean region.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 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.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, T. Scott Zaccheo, Jeremy Dobler, Michel Ramonet, Johannes Staufer, Diego Santaren, Irène Xueref-Remy, and Philippe Ciais
Atmos. Chem. Phys., 19, 13809–13825, https://doi.org/10.5194/acp-19-13809-2019, https://doi.org/10.5194/acp-19-13809-2019, 2019
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CO2 emissions within urban areas impact nearby and downwind concentrations. A different system, based on bi-wavelength laser measurements, has been deployed over Paris. It samples CO2 concentrations along horizontal lines, between a transceiver and a reflector. In this paper, we analyze the measurements provided by this system, together with the more classical in situ sampling and high-resolution modeling. We focus on the temporal and spatial variability of atmospheric CO2 concentrations.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Bo Zheng, Frederic Chevallier, Yi Yin, Philippe Ciais, Audrey Fortems-Cheiney, Merritt N. Deeter, Robert J. Parker, Yilong Wang, Helen M. Worden, and Yuanhong Zhao
Earth Syst. Sci. Data, 11, 1411–1436, https://doi.org/10.5194/essd-11-1411-2019, https://doi.org/10.5194/essd-11-1411-2019, 2019
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We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide (CO) variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. We identify a declining trend in the global CO budget since 2000, driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.
Bruno Ringeval, Marko Kvakić, Laurent Augusto, Philippe Ciais, Daniel Goll, Nathaniel D. Mueller, Christoph Müller, Thomas Nesme, Nicolas Vuichard, Xuhui Wang, and Sylvain Pellerin
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-298, https://doi.org/10.5194/bg-2019-298, 2019
Preprint withdrawn
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Crossed fertilization additions lead to the definition of nutrient interaction categories. However, the implications of such categories in terms of nutrient interaction modeling are not clear. We developed a theoretical analysis of nitrogen and phosphorus fertilization experiments, then applied it to current estimates of nutrient limitation in cropland. We found that a true co-limitation could affect up to 42 % of the global maize area when using a given formalism of nutrient interaction.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 12, 3503–3521, https://doi.org/10.5194/gmd-12-3503-2019, https://doi.org/10.5194/gmd-12-3503-2019, 2019
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Few Earth system models represent permafrost soil biogeochemistry, contributing to uncertainty in estimating its response and that of the planet to warming. Because the permafrost contains over double the carbon in the present atmosphere, its fate as it is
unlockedby warming is globally significant. One way it can be mobilised is into rivers, the sea, or the atmosphere: a vector previously ignored in climate modelling. We present a model scheme for resolving this vector at a global scale.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Shushi Peng, Gerhard Krinner, Ardalan Tootchi, Agnès Ducharne, and Adam Hastie
Geosci. Model Dev., 12, 2961–2982, https://doi.org/10.5194/gmd-12-2961-2019, https://doi.org/10.5194/gmd-12-2961-2019, 2019
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We present a model that can simulate the dynamics of peatland area extent and the vertical buildup of peat. The model is validated across a range of northern peatland sites and over the Northern Hemisphere (> 30° N). It is able to reproduce the spatial extent of northern peatlands and peat carbon accumulation over the Holocene.
Alexander Gruber, Tracy Scanlon, Robin van der Schalie, Wolfgang Wagner, and Wouter Dorigo
Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, https://doi.org/10.5194/essd-11-717-2019, 2019
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Soil moisture is a key variable in our Earth system. Knowledge of soil moisture and its dynamics across scales is vital for many applications such as the prediction of agricultural yields or irrigation demands, flood and drought monitoring, weather forecasting and climate modelling. To date, the ESA CCI SM products are the only consistent long-term multi-satellite soil moisture data sets available. This paper reviews the evolution of these products and their underlying merging methodology.
Yilong Wang, Philippe Ciais, Grégoire Broquet, François-Marie Bréon, Tomohiro Oda, Franck Lespinas, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, Haoran Xu, Shu Tao, Kevin R. Gurney, Geoffrey Roest, Diego Santaren, and Yongxian Su
Earth Syst. Sci. Data, 11, 687–703, https://doi.org/10.5194/essd-11-687-2019, https://doi.org/10.5194/essd-11-687-2019, 2019
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We address the question of the global characterization of fossil fuel CO2 emission hotspots that may cause coherent XCO2 plumes in space-borne CO2 images, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. For space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 hotspots are identified, covering 72 % of the global emissions. These hotspots define the targets for the purpose of monitoring fossil fuel CO2 emissions from space.
Emmanuel Arzoumanian, Felix R. Vogel, Ana Bastos, Bakhram Gaynullin, Olivier Laurent, Michel Ramonet, and Philippe Ciais
Atmos. Meas. Tech., 12, 2665–2677, https://doi.org/10.5194/amt-12-2665-2019, https://doi.org/10.5194/amt-12-2665-2019, 2019
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We tested commercial lower-cost CO2 sensors in laboratory and field studies to see if they can measure atmospheric CO2 mole fractions with less than 1 ppm bias (with monthly calibration), to allow continuous urban CO2 monitoring.
We find that the sensors' CO2 readings are influenced by temperature, atmospheric pressure and water vapour content, but this can be corrected for by adding sensors (T, p, RH) and carefully calibrating each sensor against a high-precision instrument.
Sibo Zhang, Catherine Meurey, and Jean-Christophe Calvet
Atmos. Chem. Phys., 19, 5005–5020, https://doi.org/10.5194/acp-19-5005-2019, https://doi.org/10.5194/acp-19-5005-2019, 2019
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In situ rain temperature measurements are rare. Soil moisture and soil temperature observations in southern France are used to assess the cooling effects on soils of rainfall events. The rainwater temperature is estimated using observed changes of topsoil volumetric soil moisture and soil temperature in response to the rainfall event. The obtained rain temperature estimates are generally lower than the ambient air temperatures, wet-bulb temperatures, and topsoil temperatures.
Felix R. Vogel, Matthias Frey, Johannes Staufer, Frank Hase, Grégoire Broquet, Irène Xueref-Remy, Frédéric Chevallier, Philippe Ciais, Mahesh Kumar Sha, Pascale Chelin, Pascal Jeseck, Christof Janssen, Yao Té, Jochen Groß, Thomas Blumenstock, Qiansi Tu, and Johannes Orphal
Atmos. Chem. Phys., 19, 3271–3285, https://doi.org/10.5194/acp-19-3271-2019, https://doi.org/10.5194/acp-19-3271-2019, 2019
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Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO2 levels is one key aspect. This study uses atmospheric observations of total column CO2 and compares them to numerical simulations to investigate CO2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions. Our measurements reveal the influence of locally added CO2, which our model is also able to predict.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
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About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Pierre Laurent, Florent Mouillot, Maria Vanesa Moreno, Chao Yue, and Philippe Ciais
Biogeosciences, 16, 275–288, https://doi.org/10.5194/bg-16-275-2019, https://doi.org/10.5194/bg-16-275-2019, 2019
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Fire propagation and fire size are usually considered to be proportional to fire intensity. We used a global database of fire patch size and fire radiative power, used as a proxy of fire intensity, to test this relationship at a global scale. We showed that in some regions fire size tends to saturate when a regional fire intensity threshold is reached. We concluded that increasing landscape fragmentation limits fire propagation and this effect should be accounted for in global fire modules.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
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Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Philippe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, and Edna Rödig
Geosci. Model Dev., 11, 5203–5215, https://doi.org/10.5194/gmd-11-5203-2018, https://doi.org/10.5194/gmd-11-5203-2018, 2018
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We propose a generic approach for a pixel-to-point comparison applicable for evaluation of models and remote-sensing products. We provide statistical measures accounting for the uncertainty in ecosystem variables. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 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.
Haicheng Zhang, Daniel S. Goll, Stefano Manzoni, Philippe Ciais, Bertrand Guenet, and Yuanyuan Huang
Geosci. Model Dev., 11, 4779–4796, https://doi.org/10.5194/gmd-11-4779-2018, https://doi.org/10.5194/gmd-11-4779-2018, 2018
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Carbon use efficiency (CUE) of decomposers depends strongly on the organic matter quality (C : N ratio) and soil nutrient availability rather than a fixed value. A soil biogeochemical model with flexible CUE can better capture the differences in respiration rate of litter with contrasting C : N ratios and under different levels of mineral N availability than the model with fixed CUE, and well represent the effect of varying litter quality (N content) on SOM formation across temporal scales.
Zun Yin, Catherine Ottlé, Philippe Ciais, Matthieu Guimberteau, Xuhui Wang, Dan Zhu, Fabienne Maignan, Shushi Peng, Shilong Piao, Jan Polcher, Feng Zhou, Hyungjun Kim, and other China-Trend-Stream project members
Hydrol. Earth Syst. Sci., 22, 5463–5484, https://doi.org/10.5194/hess-22-5463-2018, https://doi.org/10.5194/hess-22-5463-2018, 2018
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Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3, PGF, CRU-NCEP, and WFDEI. Simulated soil moisture was compared to several datasets to evaluate the ability of ORCHIDEE in reproducing soil moisture dynamics. Results showed that ORCHIDEE soil moisture coincided well with other datasets in wet areas and in non-irrigated areas. It suggested that the ORCHIDEE-MICT was suitable for further hydrological studies in China.
Igor B. Konovalov, Daria A. Lvova, Matthias Beekmann, Hiren Jethva, Eugene F. Mikhailov, Jean-Daniel Paris, Boris D. Belan, Valerii S. Kozlov, Philippe Ciais, and Meinrat O. Andreae
Atmos. Chem. Phys., 18, 14889–14924, https://doi.org/10.5194/acp-18-14889-2018, https://doi.org/10.5194/acp-18-14889-2018, 2018
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A good knowledge of black carbon (BC) emissions from open biomass burning (BB) is an important prerequisite for reliable climate predictions, especially in the Arctic. This paper introduces a method to constrain a regional budget of BB BC emissions using satellite measurements of the absorption and extinction optical depths and evaluates its potential application in a large Siberian region.
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
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We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Chloé Largeron, Gerhard Krinner, Philippe Ciais, and Claire Brutel-Vuilmet
Geosci. Model Dev., 11, 3279–3297, https://doi.org/10.5194/gmd-11-3279-2018, https://doi.org/10.5194/gmd-11-3279-2018, 2018
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Peatlands are widely present in boreal regions and contain large carbon stocks due to their hydrologic properties and high water content. We have enhanced the global land surface model ORCHIDEE by introducing boreal peatlands. These are considered as a new type of vegetation in the model, with specific hydrological properties for peat soil. In this paper, we focus on the representation of the hydrology of northern peatlands and on the evaluation of the hydrological impact of this implementation.
Victoria Naipal, Philippe Ciais, Yilong Wang, Ronny Lauerwald, Bertrand Guenet, and Kristof Van Oost
Biogeosciences, 15, 4459–4480, https://doi.org/10.5194/bg-15-4459-2018, https://doi.org/10.5194/bg-15-4459-2018, 2018
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We seek to better understand the links between soil erosion by rainfall and the global carbon (C) cycle by coupling a soil erosion model to the C cycle of a land surface model. With this modeling approach we evaluate the effects of soil removal on soil C stocks in the presence of climate change and land use change. We find that accelerated soil erosion leads to a potential SOC removal flux of 74 ±18 Pg of C globally over the period AD 1850–2005, with significant impacts on the land C balance.
Emilie Joetzjer, Fabienne Maignan, Jérôme Chave, Daniel Goll, Ben Poulter, Jonathan Barichivich, Isabelle Maréchaux, Sebastiaan Luyssaert, Matthieu Guimberteau, Kim Naudts, Damien Bonal, and Philippe Ciais
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-308, https://doi.org/10.5194/bg-2018-308, 2018
Revised manuscript not accepted
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This study explores the relative contributions of tree demographic, canopy structure and hydraulic processes on the Amazonian carbon and water cycles using large-scale process-based model. Our results imply that explicit coupling of the water and carbon cycles improves the representation of biogeochemical cycles and their spatial variability. Representing the variation in the ecological functioning of Amazonia should be the next step to improve the performance and predictive ability of models.
Xin Lin, Philippe Ciais, Philippe Bousquet, Michel Ramonet, Yi Yin, Yves Balkanski, Anne Cozic, Marc Delmotte, Nikolaos Evangeliou, Nuggehalli K. Indira, Robin Locatelli, Shushi Peng, Shilong Piao, Marielle Saunois, Panangady S. Swathi, Rong Wang, Camille Yver-Kwok, Yogesh K. Tiwari, and Lingxi Zhou
Atmos. Chem. Phys., 18, 9475–9497, https://doi.org/10.5194/acp-18-9475-2018, https://doi.org/10.5194/acp-18-9475-2018, 2018
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We simulate CH4 and CO2 using a zoomed global transport model with a horizontal resolution of ~50 km over South and East Asia, as well as a standard model version for comparison. Model performance is evaluated for both gases and versions at multiple timescales against a new collection of surface stations over this key GHG-emitting region. The evaluation at different timescales and comparisons between gases and model versions have implications for possible model improvements and inversions.
Clement Albergel, Emanuel Dutra, Simon Munier, Jean-Christophe Calvet, Joaquin Munoz-Sabater, Patricia de Rosnay, and Gianpaolo Balsamo
Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, https://doi.org/10.5194/hess-22-3515-2018, 2018
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ECMWF recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 (2010–2016). ERA-5 has important changes relative to ERA-Interim including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis. One of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model.
Wei Li, Chao Yue, Philippe Ciais, Jinfeng Chang, Daniel Goll, Dan Zhu, Shushi Peng, and Albert Jornet-Puig
Geosci. Model Dev., 11, 2249–2272, https://doi.org/10.5194/gmd-11-2249-2018, https://doi.org/10.5194/gmd-11-2249-2018, 2018
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We implemented four major lignocellulosic bioenergy crops in ORCHIDEE. We added new PFTs, did new parameterizations of photosynthesis, carbon allocation, and phenology based on a compilation of field measurements, and added a specific harvest module. The resulting ORCHIDEE-MICT-BIOENERGY model is evaluated at 296 locations where field measurements of harvested biomass are available, and the new model can generally reproduce the global bioenergy crop yield observations.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Ye Huang, Bertrand Guenet, Philippe Ciais, Ivan A. Janssens, Jennifer L. Soong, Yilong Wang, Daniel Goll, Evgenia Blagodatskaya, and Yuanyuan Huang
Geosci. Model Dev., 11, 2111–2138, https://doi.org/10.5194/gmd-11-2111-2018, https://doi.org/10.5194/gmd-11-2111-2018, 2018
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ORCHIMIC is a modeling effort trying to improve the representation of SOC dynamics in Earth system models (ESM). It has a structure that can be easily incorporated into CENTURY-based ESMs. In ORCHIMIC, key microbial dynamics (i.e., enzyme production, enzymatic decomposition and microbial dormancy) are included. The ORCHIMIC model can also reproduce the observed temporal dynamics of respiration and priming effects; thus it is an improved tool for climate projections and SOC response predictions.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
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We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Yilong Wang, Grégoire Broquet, Philippe Ciais, Frédéric Chevallier, Felix Vogel, Lin Wu, Yi Yin, Rong Wang, and Shu Tao
Atmos. Chem. Phys., 18, 4229–4250, https://doi.org/10.5194/acp-18-4229-2018, https://doi.org/10.5194/acp-18-4229-2018, 2018
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This paper assesses the potential of atmospheric 14CO2 observations and a global inversion system to solve for fossil fuel CO2 (FFCO2) emissions in Europe. The estimate of monthly emission budgets is largely improved in high emitting regions. The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO2 emissions.
Abdelhadi El Yazidi, Michel Ramonet, Philippe Ciais, Gregoire Broquet, Isabelle Pison, Amara Abbaris, Dominik Brunner, Sebastien Conil, Marc Delmotte, Francois Gheusi, Frederic Guerin, Lynn Hazan, Nesrine Kachroudi, Giorgos Kouvarakis, Nikolaos Mihalopoulos, Leonard Rivier, and Dominique Serça
Atmos. Meas. Tech., 11, 1599–1614, https://doi.org/10.5194/amt-11-1599-2018, https://doi.org/10.5194/amt-11-1599-2018, 2018
Sibo Zhang, Jean-Christophe Calvet, José Darrozes, Nicolas Roussel, Frédéric Frappart, and Gilles Bouhours
Hydrol. Earth Syst. Sci., 22, 1931–1946, https://doi.org/10.5194/hess-22-1931-2018, https://doi.org/10.5194/hess-22-1931-2018, 2018
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Surface soil moisture was retrieved from a grassland site in southwestern France using the GNSS-IR technique. In order to efficiently limit the impact of perturbing vegetation effects, the grass growth period and the senescence period are treated separately. While the vegetation biomass effect can be corrected for, the litter water interception influences the observations and cannot be easily accounted for.
Marta Camino-Serrano, Bertrand Guenet, Sebastiaan Luyssaert, Philippe Ciais, Vladislav Bastrikov, Bruno De Vos, Bert Gielen, Gerd Gleixner, Albert Jornet-Puig, Klaus Kaiser, Dolly Kothawala, Ronny Lauerwald, Josep Peñuelas, Marion Schrumpf, Sara Vicca, Nicolas Vuichard, David Walmsley, and Ivan A. Janssens
Geosci. Model Dev., 11, 937–957, https://doi.org/10.5194/gmd-11-937-2018, https://doi.org/10.5194/gmd-11-937-2018, 2018
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Global models generally oversimplify the representation of soil organic carbon (SOC), and thus its response to global warming remains uncertain. We present the new soil module ORCHIDEE-SOM, within the global model ORCHIDEE, that refines the representation of SOC dynamics and includes the dissolved organic carbon (DOC) processes. The model is able to reproduce SOC stocks and DOC concentrations in four different ecosystems, opening an opportunity for improved predictions of SOC in global models.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Irène Xueref-Remy, Elsa Dieudonné, Cyrille Vuillemin, Morgan Lopez, Christine Lac, Martina Schmidt, Marc Delmotte, Frédéric Chevallier, François Ravetta, Olivier Perrussel, Philippe Ciais, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, T. Gerard Spain, and Christophe Ampe
Atmos. Chem. Phys., 18, 3335–3362, https://doi.org/10.5194/acp-18-3335-2018, https://doi.org/10.5194/acp-18-3335-2018, 2018
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Urbanized and industrialized areas are the largest source of fossil CO2. This work analyses the atmospheric CO2 variability observed from the first in situ network deployed in the Paris megacity area. Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO2 records.
Chao Yue, Philippe Ciais, and Wei Li
Biogeosciences, 15, 1185–1201, https://doi.org/10.5194/bg-15-1185-2018, https://doi.org/10.5194/bg-15-1185-2018, 2018
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Gross land use change such as shifting cultivation causes carbon emissions because carbon release in cleared forests is larger than absorption in regrowing ones. However, to appropriately account for this process, vegetation models have to represent sub-grid secondary forest dynamics. We found that gross land use emissions can be overestimated if sub-grid secondary forests are neglected in the model. Conversely, rotation lengths of shifting cultivation have a critical role.
Ben Parkes, Dimitri Defrance, Benjamin Sultan, Philippe Ciais, and Xuhui Wang
Earth Syst. Dynam., 9, 119–134, https://doi.org/10.5194/esd-9-119-2018, https://doi.org/10.5194/esd-9-119-2018, 2018
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We present an analysis of three crops in West Africa and their response to short-term climate change in a world where temperatures are 1.5 °C above the preindustrial levels. We show that the number of crop failures for all crops is due to increase in the future climate. We further show the difference in yield change across several West African countries and show that the yields are not expected to increase fast enough to prevent food shortages.
Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner
Earth Syst. Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, https://doi.org/10.5194/essd-10-267-2018, 2018
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In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
Grégoire Broquet, François-Marie Bréon, Emmanuel Renault, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Frédéric Chevallier, Lin Wu, and Philippe Ciais
Atmos. Meas. Tech., 11, 681–708, https://doi.org/10.5194/amt-11-681-2018, https://doi.org/10.5194/amt-11-681-2018, 2018
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This study assesses the potential of space-borne imagery of CO2 atmospheric concentrations for monitoring the emissions from the Paris area. Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO2 emissions for urban areas with CO2 observations from satellites, and calls for more technological innovations in the remote sensing of CO2 and in the models that exploit it.
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.
Chao Yue, Philippe Ciais, Sebastiaan Luyssaert, Wei Li, Matthew J. McGrath, Jinfeng Chang, and Shushi Peng
Geosci. Model Dev., 11, 409–428, https://doi.org/10.5194/gmd-11-409-2018, https://doi.org/10.5194/gmd-11-409-2018, 2018
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Human alteration of land cover has caused CO2 that is stored in forest biomass and soil to be released into the atmosphere and thus contribute to global warming. Global vegetation models that are used to quantify such carbon emissions from land use change traditionally rarely include shifting cultivation and secondary forest age dynamics. In this study, we expanded one vegetation model to include these features. We found that carbon emissions from land use change are estimated to be smaller.
Wei Li, Natasha MacBean, Philippe Ciais, Pierre Defourny, Céline Lamarche, Sophie Bontemps, Richard A. Houghton, and Shushi Peng
Earth Syst. Sci. Data, 10, 219–234, https://doi.org/10.5194/essd-10-219-2018, https://doi.org/10.5194/essd-10-219-2018, 2018
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We evaluated the land cover changes based on plant functional types (PFTs) derived from the newly released annual ESA land cover maps. We addressed the geographical distributions and temporal trends of the translated PFT maps and compared with other datasets commonly used by the land surface model community. Different choices of these datasets for the applications in land surface models are proposed depending on the research purposes.
Matthieu Guimberteau, Dan Zhu, Fabienne Maignan, Ye Huang, Chao Yue, Sarah Dantec-Nédélec, Catherine Ottlé, Albert Jornet-Puig, Ana Bastos, Pierre Laurent, Daniel Goll, Simon Bowring, Jinfeng Chang, Bertrand Guenet, Marwa Tifafi, Shushi Peng, Gerhard Krinner, Agnès Ducharne, Fuxing Wang, Tao Wang, Xuhui Wang, Yilong Wang, Zun Yin, Ronny Lauerwald, Emilie Joetzjer, Chunjing Qiu, Hyungjun Kim, and Philippe Ciais
Geosci. Model Dev., 11, 121–163, https://doi.org/10.5194/gmd-11-121-2018, https://doi.org/10.5194/gmd-11-121-2018, 2018
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Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module.
Fei Lun, Junguo Liu, Philippe Ciais, Thomas Nesme, Jinfeng Chang, Rong Wang, Daniel Goll, Jordi Sardans, Josep Peñuelas, and Michael Obersteiner
Earth Syst. Sci. Data, 10, 1–18, https://doi.org/10.5194/essd-10-1-2018, https://doi.org/10.5194/essd-10-1-2018, 2018
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We quantified in detail the P budgets in agricultural systems and PUE on global, regional, and national scales from 2002 to 2010. Globally, half of the total P inputs into agricultural systems accumulated in agricultural soils, with the rest lost to bodies of water. There are great differences in P budgets and PUE in agricultural systems on global, regional, and national scales. International trade played a significant role in P redistribution and P in fertilizer and food among countries.
Wei Li, Philippe Ciais, Chao Yue, Thomas Gasser, Shushi Peng, and Ana Bastos
Biogeosciences, 15, 91–103, https://doi.org/10.5194/bg-15-91-2018, https://doi.org/10.5194/bg-15-91-2018, 2018
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We compared the biomass recovery curves from a recent field-based study with those used in bookkeeping models and demonstrated the importance of considering gross forest changes rather than net forest changes. We also derived a critical gross-to-net forest area change ratio, beyond which the sign of carbon flux will be reversed. This critical ratio was further applied to the high-resolution satellite data in the Amazon to distinguish the sensitive regions.
Arsène Druel, Philippe Peylin, Gerhard Krinner, Philippe Ciais, Nicolas Viovy, Anna Peregon, Vladislav Bastrikov, Natalya Kosykh, and Nina Mironycheva-Tokareva
Geosci. Model Dev., 10, 4693–4722, https://doi.org/10.5194/gmd-10-4693-2017, https://doi.org/10.5194/gmd-10-4693-2017, 2017
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To improve the simulation of vegetation–climate feedbacks at high latitudes, three new circumpolar vegetation types were added in the ORCHIDEE land surface model: bryophytes (mosses) and lichens, Arctic shrubs, and Arctic grasses. This article is an introduction to the modification of vegetation distribution and physical behaviour, implying for example lower productivity, roughness, and higher winter albedo or freshwater discharge in the Arctic Ocean.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
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Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Chao Yue, Philippe Ciais, Ana Bastos, Frederic Chevallier, Yi Yin, Christian Rödenbeck, and Taejin Park
Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, https://doi.org/10.5194/acp-17-13903-2017, 2017
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The year 2015 appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since 2000 according to satellite observation, but the atmospheric CO2 growth rate is also the highest since 1959. We found that this is due to a only moderate land carbon sink, because high growing-season sink in northern lands has been partly offset by autumn and winter release and the late-year El Niño has led to an abrupt transition to land source in the tropics.
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.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
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LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Ronny Lauerwald, Pierre Regnier, Marta Camino-Serrano, Bertrand Guenet, Matthieu Guimberteau, Agnès Ducharne, Jan Polcher, and Philippe Ciais
Geosci. Model Dev., 10, 3821–3859, https://doi.org/10.5194/gmd-10-3821-2017, https://doi.org/10.5194/gmd-10-3821-2017, 2017
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ORCHILEAK is a new branch of the terrestrial ecosystem model ORCHIDEE that represents dissolved organic carbon (DOC) production from canopy and soils, DOC and CO2 leaching from soils to streams, DOC decomposition, and CO2 evasion to the atmosphere during its lateral transport in rivers, as well as exchange with the soil carbon and litter stocks on floodplains and in swamps. We parameterized and validated ORCHILEAK for the Amazon basin.
Daniel S. Goll, Nicolas Vuichard, Fabienne Maignan, Albert Jornet-Puig, Jordi Sardans, Aurelie Violette, Shushi Peng, Yan Sun, Marko Kvakic, Matthieu Guimberteau, Bertrand Guenet, Soenke Zaehle, Josep Penuelas, Ivan Janssens, and Philippe Ciais
Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, https://doi.org/10.5194/gmd-10-3745-2017, 2017
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We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition. However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.
Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4861–4878, https://doi.org/10.5194/hess-21-4861-2017, https://doi.org/10.5194/hess-21-4861-2017, 2017
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Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.
Sibo Zhang, Nicolas Roussel, Karen Boniface, Minh Cuong Ha, Frédéric Frappart, José Darrozes, Frédéric Baup, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4767–4784, https://doi.org/10.5194/hess-21-4767-2017, https://doi.org/10.5194/hess-21-4767-2017, 2017
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GNSS SNR data were obtained from an intensively cultivated wheat field in southwestern France. The data were used to retrieve soil moisture and vegetation characteristics during the growing period of wheat. Vegetation growth broke up the constant height assumption used in soil moisture retrieval algorithms. Soil moisture could not be retrieved after wheat tillering. A new algorithm based on a wavelet analysis was implemented and used to retrieve vegetation height.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
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.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
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This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Ana Bastos, Anna Peregon, Érico A. Gani, Sergey Khudyaev, Chao Yue, Wei Li, Célia Gouveia, and Philippe Ciais
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-267, https://doi.org/10.5194/bg-2017-267, 2017
Revised manuscript not accepted
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The ice-core record indicates a stabilization of atmospheric CO2 in the 1940s, which is not captured by the state-of-the-art reconstructions of CO2 sources and sinks.
The 1940s where marked by major socio-economic disruptions due to war. At the same time, very strong warming was registered in the high-latitudes. Here we evaluate the contributions of these two factors to a possible increase in the terrestrial sink not captured in other datasets, using the Former Soviet Union as a case study.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Eleanor J. Burke, Altug Ekici, Ye Huang, Sarah E. Chadburn, Chris Huntingford, Philippe Ciais, Pierre Friedlingstein, Shushi Peng, and Gerhard Krinner
Biogeosciences, 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, https://doi.org/10.5194/bg-14-3051-2017, 2017
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There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.
Sabina Assan, Alexia Baudic, Ali Guemri, Philippe Ciais, Valerie Gros, and Felix R. Vogel
Atmos. Meas. Tech., 10, 2077–2091, https://doi.org/10.5194/amt-10-2077-2017, https://doi.org/10.5194/amt-10-2077-2017, 2017
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This study is dedicated to improving measurement methods when using a Cavity Ring Down Spectroscopy instrument to measure methane at sites with elevated ethane concentrations such as Oil and Gas sites. The research was undertaken after measurements of natural gas samples suggested biased δ13CH4 results. Two instruments were extensively tested to characterize the cross sensitivities to ethane and δ13CH4 and propose corrections. Results indicate that it is imperative to account for the biases.
Daniel S. Goll, Alexander J. Winkler, Thomas Raddatz, Ning Dong, Ian Colin Prentice, Philippe Ciais, and Victor Brovkin
Geosci. Model Dev., 10, 2009–2030, https://doi.org/10.5194/gmd-10-2009-2017, https://doi.org/10.5194/gmd-10-2009-2017, 2017
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The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate. In the model JSBACH carbon–nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect. The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
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Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
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Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
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This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Thomas Gasser, Glen P. Peters, Jan S. Fuglestvedt, William J. Collins, Drew T. Shindell, and Philippe Ciais
Earth Syst. Dynam., 8, 235–253, https://doi.org/10.5194/esd-8-235-2017, https://doi.org/10.5194/esd-8-235-2017, 2017
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Emission metrics such as GWP or GTP are used to put non-CO2 species on a
CO2-equivalentscale. In the fifth IPCC report the metrics are inconsistent, as the climate–carbon feedback is included only for CO2 but not for non-CO2 species. Here, we simulate a new impulse response function for the feedback, and we use it to correct the metrics. For instance, 1 g of CH4 is equivalent to 31 g of CO2 (instead of 28 g) following the corrected GWP100 metric. It is 34 g if other factors are also updated.
Christoph Müller, Joshua Elliott, James Chryssanthacopoulos, Almut Arneth, Juraj Balkovic, Philippe Ciais, Delphine Deryng, Christian Folberth, Michael Glotter, Steven Hoek, Toshichika Iizumi, Roberto C. Izaurralde, Curtis Jones, Nikolay Khabarov, Peter Lawrence, Wenfeng Liu, Stefan Olin, Thomas A. M. Pugh, Deepak K. Ray, Ashwan Reddy, Cynthia Rosenzweig, Alex C. Ruane, Gen Sakurai, Erwin Schmid, Rastislav Skalsky, Carol X. Song, Xuhui Wang, Allard de Wit, and Hong Yang
Geosci. Model Dev., 10, 1403–1422, https://doi.org/10.5194/gmd-10-1403-2017, https://doi.org/10.5194/gmd-10-1403-2017, 2017
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Crop models are increasingly used in climate change impact research and integrated assessments. For the Agricultural Model Intercomparison and Improvement Project (AgMIP), 14 global gridded crop models (GGCMs) have supplied crop yield simulations (1980–2010) for maize, wheat, rice and soybean. We evaluate the performance of these models against observational data at global, national and grid cell level. We propose an open-access benchmark system against which future model versions can be tested.
Yi Yin, Frederic Chevallier, Philippe Ciais, Gregoire Broquet, Anne Cozic, Sophie Szopa, and Yilong Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-166, https://doi.org/10.5194/acp-2017-166, 2017
Revised manuscript not accepted
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CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere (MOPITT) satellite retrievals and surface in-situ measurements. Here, we assess how well a global CTM fits a large variety of independent CO observations before and after assimilating MOPITTv6 retrievals to optimise CO sources/sink and discuss potential sources of errors and their implications for global CO modelling studies.
Matthieu Guimberteau, Philippe Ciais, Agnès Ducharne, Juan Pablo Boisier, Ana Paula Dutra Aguiar, Hester Biemans, Hannes De Deurwaerder, David Galbraith, Bart Kruijt, Fanny Langerwisch, German Poveda, Anja Rammig, Daniel Andres Rodriguez, Graciela Tejada, Kirsten Thonicke, Celso Von Randow, Rita C. S. Von Randow, Ke Zhang, and Hans Verbeeck
Hydrol. Earth Syst. Sci., 21, 1455–1475, https://doi.org/10.5194/hess-21-1455-2017, https://doi.org/10.5194/hess-21-1455-2017, 2017
Thomas Gasser, Philippe Ciais, Olivier Boucher, Yann Quilcaille, Maxime Tortora, Laurent Bopp, and Didier Hauglustaine
Geosci. Model Dev., 10, 271–319, https://doi.org/10.5194/gmd-10-271-2017, https://doi.org/10.5194/gmd-10-271-2017, 2017
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Simple models of the Earth system are useful, especially because of their high computing efficiency. This work describes the OSCAR model: a new simple Earth system model calibrated on state-of-the-art complex models. It will add to the pool of the few simple models currently used by the community, and it will therefore improve the robustness of future studies. Its source code is available upon request.
Christian Folberth, Joshua Elliott, Christoph Müller, Juraj Balkovic, James Chryssanthacopoulos, Roberto C. Izaurralde, Curtis D. Jones, Nikolay Khabarov, Wenfeng Liu, Ashwan Reddy, Erwin Schmid, Rastislav Skalský, Hong Yang, Almut Arneth, Philippe Ciais, Delphine Deryng, Peter J. Lawrence, Stefan Olin, Thomas A. M. Pugh, Alex C. Ruane, and Xuhui Wang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-527, https://doi.org/10.5194/bg-2016-527, 2016
Manuscript not accepted for further review
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Global crop models differ in numerous aspects such as algorithms, parameterization, input data, and management assumptions. This study compares five global crop model frameworks, all based on the same field-scale model, to identify differences induced by the latter three. Results indicate that foremost nutrient supply, soil handling, and crop management induce substantial differences in crop yield estimates whereas crop cultivars primarily result in scaling of yield levels.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Jean-Christophe Calvet, Noureddine Fritz, Christine Berne, Bruno Piguet, William Maurel, and Catherine Meurey
SOIL, 2, 615–629, https://doi.org/10.5194/soil-2-615-2016, https://doi.org/10.5194/soil-2-615-2016, 2016
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Soil thermal conductivity in wet conditions can be retrieved together with the soil quartz content using a reverse modelling technique based on sub-hourly soil temperature observations at three depths below the soil surface.
A pedotransfer function is proposed for quartz, for the considered region in France.
Gravels have a major impact on soil thermal conductivity, and omitting the soil organic matter information tends to enhance this impact.
Johannes Staufer, Grégoire Broquet, François-Marie Bréon, Vincent Puygrenier, Frédéric Chevallier, Irène Xueref-Rémy, Elsa Dieudonné, Morgan Lopez, Martina Schmidt, Michel Ramonet, Olivier Perrussel, Christine Lac, Lin Wu, and Philippe Ciais
Atmos. Chem. Phys., 16, 14703–14726, https://doi.org/10.5194/acp-16-14703-2016, https://doi.org/10.5194/acp-16-14703-2016, 2016
Shushi Peng, Shilong Piao, Philippe Bousquet, Philippe Ciais, Bengang Li, Xin Lin, Shu Tao, Zhiping Wang, Yuan Zhang, and Feng Zhou
Atmos. Chem. Phys., 16, 14545–14562, https://doi.org/10.5194/acp-16-14545-2016, https://doi.org/10.5194/acp-16-14545-2016, 2016
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Methane is an important greenhouse gas, which accounts for about 20 % of the warming induced by long-lived greenhouse gases since 1750. Anthropogenic methane emissions from China may have been growing rapidly in the past decades because of increased coal mining and fast growing livestock. A good long-term methane emissions dataset is still lacking. Here, we produced a detailed bottom-up inventory of anthropogenic methane emissions from the eight major source sectors in China during 1980–2010.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Igor B. Konovalov, Evgeny V. Berezin, Philippe Ciais, Grégoire Broquet, Ruslan V. Zhuravlev, and Greet Janssens-Maenhout
Atmos. Chem. Phys., 16, 13509–13540, https://doi.org/10.5194/acp-16-13509-2016, https://doi.org/10.5194/acp-16-13509-2016, 2016
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The knowledge of CO2 emissions from fossil-fuel (FF) burning is of paramount importance both for climate prediction and mitigation policy purposes. The paper introduces a method to indirectly constrain a regional budget of FF CO2 emissions by using satellite measurements of "proxy" chemical species and evaluates its potential in application to a western European region.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
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Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
Marta Camino-Serrano, Elisabeth Graf Pannatier, Sara Vicca, Sebastiaan Luyssaert, Mathieu Jonard, Philippe Ciais, Bertrand Guenet, Bert Gielen, Josep Peñuelas, Jordi Sardans, Peter Waldner, Sophia Etzold, Guia Cecchini, Nicholas Clarke, Zoran Galić, Laure Gandois, Karin Hansen, Jim Johnson, Uwe Klinck, Zora Lachmanová, Antti-Jussi Lindroos, Henning Meesenburg, Tiina M. Nieminen, Tanja G. M. Sanders, Kasia Sawicka, Walter Seidling, Anne Thimonier, Elena Vanguelova, Arne Verstraeten, Lars Vesterdal, and Ivan A. Janssens
Biogeosciences, 13, 5567–5585, https://doi.org/10.5194/bg-13-5567-2016, https://doi.org/10.5194/bg-13-5567-2016, 2016
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We investigated the long-term trends of dissolved organic carbon (DOC) in soil solution and the drivers of changes in over 100 forest monitoring plots across Europe. An overall increasing trend was detected in the organic layers, but no overall trend was found in the mineral horizons. There are strong interactions between controls acting at local and regional scales. Our findings are relevant for researchers focusing on the link between terrestrial and aquatic ecosystems and for C-cycle models.
Philippe Peylin, Cédric Bacour, Natasha MacBean, Sébastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, Abdou Kane, Fabienne Maignan, Frédéric Chevallier, Philippe Ciais, and Pascal Prunet
Geosci. Model Dev., 9, 3321–3346, https://doi.org/10.5194/gmd-9-3321-2016, https://doi.org/10.5194/gmd-9-3321-2016, 2016
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The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model. The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.
Ana Bastos, Philippe Ciais, Jonathan Barichivich, Laurent Bopp, Victor Brovkin, Thomas Gasser, Shushi Peng, Julia Pongratz, Nicolas Viovy, and Cathy M. Trudinger
Biogeosciences, 13, 4877–4897, https://doi.org/10.5194/bg-13-4877-2016, https://doi.org/10.5194/bg-13-4877-2016, 2016
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The ice-core record shows a stabilisation of atmospheric CO2 in the 1940s, despite continued emissions from fossil fuel burning and land-use change (LUC). We use up-to-date reconstructions of the CO2 sources and sinks over the 20th century to evaluate whether these capture the CO2 plateau and to test the previously proposed hypothesis. Both strong terrestrial sink, possibly due to LUC not fully accounted for in the records, and enhanced oceanic uptake are necessary to explain this stall.
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
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The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Jinfeng Chang, Philippe Ciais, Mario Herrero, Petr Havlik, Matteo Campioli, Xianzhou Zhang, Yongfei Bai, Nicolas Viovy, Joanna Joiner, Xuhui Wang, Shushi Peng, Chao Yue, Shilong Piao, Tao Wang, Didier A. Hauglustaine, Jean-Francois Soussana, Anna Peregon, Natalya Kosykh, and Nina Mironycheva-Tokareva
Biogeosciences, 13, 3757–3776, https://doi.org/10.5194/bg-13-3757-2016, https://doi.org/10.5194/bg-13-3757-2016, 2016
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We derived the global maps of grassland management intensity of 1901–2012, including the minimum area of managed grassland with fraction of mown/grazed part. These maps, to our knowledge for the first time, provide global, time-dependent information for drawing up global estimates of management impact on biomass production and yields and for global vegetation models to enable simulations of carbon stocks and GHG budgets beyond simple tuning of grassland productivities to account for management.
Lin Wu, Grégoire Broquet, Philippe Ciais, Valentin Bellassen, Felix Vogel, Frédéric Chevallier, Irène Xueref-Remy, and Yilong Wang
Atmos. Chem. Phys., 16, 7743–7771, https://doi.org/10.5194/acp-16-7743-2016, https://doi.org/10.5194/acp-16-7743-2016, 2016
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This paper advances atmospheric inversion of city CO2 emissions as follows: (1) illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO2 concentrations; (2) demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification (MRV) of city CO2 emissions; (3) clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO2 emissions.
Khatab Abdalla, Pauline Chivenge, Philippe Ciais, and Vincent Chaplot
Biogeosciences, 13, 3619–3633, https://doi.org/10.5194/bg-13-3619-2016, https://doi.org/10.5194/bg-13-3619-2016, 2016
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Discrepancies exist on the impact of tillage on soil CO2 emissions and on the main soil and environmental controls. Results from a meta-analysis using 174 paired observations comparing CO2 emissions over entire seasons or years from tilled (untilled) soils across different climates, crop types and soil conditions show that on average: (1) tilled soils emit 21 % more CO2 than untilled soils; (2) the difference increase to 29 % in sandy soils from arid climates with low soil organic carbon content.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
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Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
Alex Boon, Grégoire Broquet, Deborah J. Clifford, Frédéric Chevallier, David M. Butterfield, Isabelle Pison, Michel Ramonet, Jean-Daniel Paris, and Philippe Ciais
Atmos. Chem. Phys., 16, 6735–6756, https://doi.org/10.5194/acp-16-6735-2016, https://doi.org/10.5194/acp-16-6735-2016, 2016
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We measured carbon dioxide and methane concentrations at four near-ground sites located in London, 2012. We investigated the potential for using these measurements, alongside numerical modelling, to help us to understand urban greenhouse gas emissions. Low-level sites were highly sensitive to local emissions, which questions our ability to use measurements from near-ground sites in cities in some modelling applications. A gradient approach was found to be beneficial to reduce model–data errors.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
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This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
X. Wu, N. Vuichard, P. Ciais, N. Viovy, N. de Noblet-Ducoudré, X. Wang, V. Magliulo, M. Wattenbach, L. Vitale, P. Di Tommasi, E. J. Moors, W. Jans, J. Elbers, E. Ceschia, T. Tallec, C. Bernhofer, T. Grünwald, C. Moureaux, T. Manise, A. Ligne, P. Cellier, B. Loubet, E. Larmanou, and D. Ripoche
Geosci. Model Dev., 9, 857–873, https://doi.org/10.5194/gmd-9-857-2016, https://doi.org/10.5194/gmd-9-857-2016, 2016
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The response of crops to changing climate and atmospheric CO2 could have large effects on food production, terrestrial carbon, water, energy fluxes and the climate feedbacks. We developed a new process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module into the land surface model ORCHIDEE. Our model has good ability to capture the spatial gradients of crop phenology, carbon and energy-related variables across Europe.
Bertrand Guenet, Fernando Esteban Moyano, Philippe Peylin, Philippe Ciais, and Ivan A Janssens
Geosci. Model Dev., 9, 841–855, https://doi.org/10.5194/gmd-9-841-2016, https://doi.org/10.5194/gmd-9-841-2016, 2016
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We present a simple conceptual model of soil carbon decomposition (PRIM) able to reproduce priming experiments. Parameters were optimized using a Bayesian framework and evaluated against another set of soil incubation. PRIM better fit data than the original, CENTURY-type soil decomposition model. We then compared both models incorporated into the global land biosphere model ORCHIDEE. Both versions reproduced observed decay litter rates, but only ORCHIDEE-PRIM could simulate the observed priming.
C. Yue, P. Ciais, D. Zhu, T. Wang, S. S. Peng, and S. L. Piao
Biogeosciences, 13, 675–690, https://doi.org/10.5194/bg-13-675-2016, https://doi.org/10.5194/bg-13-675-2016, 2016
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The pan-boreal biome (> N45°) removes CO2 from the atmosphere (i.e., it is a carbon sink). Fires can alter this carbon balance because they release CO2 to the atmosphere but also initiate a long-term carbon sink during post-fire vegetation recovery. We found that historical fires of 1850–2009 have a small net sink contribution (~6 %) to the 2000–2009 regional carbon sink, which is a balance between immediate source effect of fires in 2000–2009 and sink effects of those in 1850–1999.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
P. Kountouris, C. Gerbig, K.-U. Totsche, A. J. Dolman, A. G. C. A. Meesters, G. Broquet, F. Maignan, B. Gioli, L. Montagnani, and C. Helfter
Biogeosciences, 12, 7403–7421, https://doi.org/10.5194/bg-12-7403-2015, https://doi.org/10.5194/bg-12-7403-2015, 2015
D. Fairbairn, A. L. Barbu, J.-F. Mahfouf, J.-C. Calvet, and E. Gelati
Hydrol. Earth Syst. Sci., 19, 4811–4830, https://doi.org/10.5194/hess-19-4811-2015, https://doi.org/10.5194/hess-19-4811-2015, 2015
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The ensemble Kalman filter (EnKF) and simplified extended Kalman filter (SEKF) root-zone soil moisture analyses are compared when assimilating in situ surface observations. In the synthetic experiments, the EnKF performs best because it can stochastically capture the errors in the precipitation. The two methods perform similarly in the real experiments. During the summer period, both methods perform poorly as a result of nonlinearities in the land surface model.
N. MacBean, F. Maignan, P. Peylin, C. Bacour, F.-M. Bréon, and P. Ciais
Biogeosciences, 12, 7185–7208, https://doi.org/10.5194/bg-12-7185-2015, https://doi.org/10.5194/bg-12-7185-2015, 2015
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Previous model evaluation studies have shown that terrestrial biosphere models (TBMs) need a better representation of the leaf phenology, but the model deficiency could be related to incorrect model parameters or inaccurate model structure. This paper presents a framework for optimising the parameters of phenology models that are commonly used in TBMs. It further demonstrates that the optimisation can result in changes to trends in vegetation productivity and an improvement in gross C fluxes.
Y. Yin, F. Chevallier, P. Ciais, G. Broquet, A. Fortems-Cheiney, I. Pison, and M. Saunois
Atmos. Chem. Phys., 15, 13433–13451, https://doi.org/10.5194/acp-15-13433-2015, https://doi.org/10.5194/acp-15-13433-2015, 2015
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We studied the global CO concentration decline over the recent decade with a sophisticated atmospheric inversion system assimilating MOPITT CO retrievals, surface methane and surface methyl chloroform in situ measurements. The inversion interprets the CO concentration decline as a 23% decrease in the CO emissions from 2002 to 2011, twice the negative trend estimated by emission inventories. In contrast to bottom-up inventories, we find negative trends over China and South-east Asia.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
N. Kadygrov, G. Broquet, F. Chevallier, L. Rivier, C. Gerbig, and P. Ciais
Atmos. Chem. Phys., 15, 12765–12787, https://doi.org/10.5194/acp-15-12765-2015, https://doi.org/10.5194/acp-15-12765-2015, 2015
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We study the potential of the European Integrated Carbon Observing System (ICOS) atmospheric network for estimating European CO2 ecosystem fluxes. Regional atmospheric inversions with synthetic data are used to derive it in terms of statistical uncertainty. This potential is high in western Europe and future extensions of the network will increase it in eastern Europe. Future improvements of the models underlying the inversion should also significantly decrease uncertainties at high resolution.
S. Garrigues, A. Olioso, D. Carrer, B. Decharme, J.-C. Calvet, E. Martin, S. Moulin, and O. Marloie
Geosci. Model Dev., 8, 3033–3053, https://doi.org/10.5194/gmd-8-3033-2015, https://doi.org/10.5194/gmd-8-3033-2015, 2015
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This paper investigates the impacts of uncertainties in the climate, the vegetation dynamic, the soil properties and the cropland management on the simulation of evapotranspiration from the ISBA-A-gs land surface model over a 12-year Mediterranean crop succession. It mainly shows that errors in the soil parameters and the lack of irrigation in the simulation have the largest influence on evapotranspiration compared to the uncertainties in the climate and the vegetation dynamic.
X. Lin, N. K. Indira, M. Ramonet, M. Delmotte, P. Ciais, B. C. Bhatt, M. V. Reddy, D. Angchuk, S. Balakrishnan, S. Jorphail, T. Dorjai, T. T. Mahey, S. Patnaik, M. Begum, C. Brenninkmeijer, S. Durairaj, R. Kirubagaran, M. Schmidt, P. S. Swathi, N. V. Vinithkumar, C. Yver Kwok, and V. K. Gaur
Atmos. Chem. Phys., 15, 9819–9849, https://doi.org/10.5194/acp-15-9819-2015, https://doi.org/10.5194/acp-15-9819-2015, 2015
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We present 5-year flask measurements (2007–2011) of greenhouse gases (GHGs) at three atmospheric stations in India. The results suggest significant sources of CO2, CH4, N2O, CO, and H2 over S and NE India, while SF6 sources are weak. The seasonal cycles for each species reflect the seasonality of sources/sinks and influences of the Indian monsoon circulations. The data show potential to infer regional patterns of GHG fluxes and atmospheric transport over this under-documented region.
A. I. Stegehuis, R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild
Geosci. Model Dev., 8, 2285–2298, https://doi.org/10.5194/gmd-8-2285-2015, https://doi.org/10.5194/gmd-8-2285-2015, 2015
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Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Geosci. Model Dev., 8, 2263–2283, https://doi.org/10.5194/gmd-8-2263-2015, https://doi.org/10.5194/gmd-8-2263-2015, 2015
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This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.
M. A. Rawlins, A. D. McGuire, J. S. Kimball, P. Dass, D. Lawrence, E. Burke, X. Chen, C. Delire, C. Koven, A. MacDougall, S. Peng, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, P. Ciais, B. Decharme, I. Gouttevin, T. Hajima, D. Ji, G. Krinner, D. P. Lettenmaier, P. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
Biogeosciences, 12, 4385–4405, https://doi.org/10.5194/bg-12-4385-2015, https://doi.org/10.5194/bg-12-4385-2015, 2015
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We used outputs from nine models to better understand land-atmosphere CO2 exchanges across Northern Eurasia over the period 1960-1990. Model estimates were assessed against independent ground and satellite measurements. We find that the models show a weakening of the CO2 sink over time; the models tend to overestimate respiration, causing an underestimate in NEP; the model range in regional NEP is twice the multimodel mean. Residence time for soil carbon decreased, amid a gain in carbon storage.
C. E. Yver Kwok, D. Müller, C. Caldow, B. Lebègue, J. G. Mønster, C. W. Rella, C. Scheutz, M. Schmidt, M. Ramonet, T. Warneke, G. Broquet, and P. Ciais
Atmos. Meas. Tech., 8, 2853–2867, https://doi.org/10.5194/amt-8-2853-2015, https://doi.org/10.5194/amt-8-2853-2015, 2015
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This study presents two methods for estimating methane emissions from a waste water treatment plant (WWTP) along with results from a measurement campaign at a WWTP in Valence, France. We show that the tracer release method is suitable to quantify facility emissions, while the chamber measurements, provide insights into individual processes. We confirm that the open basins are not a major source of CH4 on the WWTP but that the pretreatment and sludge treatment are the main emitters.
K. Frieler, A. Levermann, J. Elliott, J. Heinke, A. Arneth, M. F. P. Bierkens, P. Ciais, D. B. Clark, D. Deryng, P. Döll, P. Falloon, B. Fekete, C. Folberth, A. D. Friend, C. Gellhorn, S. N. Gosling, I. Haddeland, N. Khabarov, M. Lomas, Y. Masaki, K. Nishina, K. Neumann, T. Oki, R. Pavlick, A. C. Ruane, E. Schmid, C. Schmitz, T. Stacke, E. Stehfest, Q. Tang, D. Wisser, V. Huber, F. Piontek, L. Warszawski, J. Schewe, H. Lotze-Campen, and H. J. Schellnhuber
Earth Syst. Dynam., 6, 447–460, https://doi.org/10.5194/esd-6-447-2015, https://doi.org/10.5194/esd-6-447-2015, 2015
S. Garrigues, A. Olioso, J. C. Calvet, E. Martin, S. Lafont, S. Moulin, A. Chanzy, O. Marloie, S. Buis, V. Desfonds, N. Bertrand, and D. Renard
Hydrol. Earth Syst. Sci., 19, 3109–3131, https://doi.org/10.5194/hess-19-3109-2015, https://doi.org/10.5194/hess-19-3109-2015, 2015
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Land surface model simulations of evapotranspiration are assessed over a 12-year Mediterranean crop succession. Evapotranspiration mainly results from soil evaporation when it is simulated over a Mediterranean crop succession. This leads to a high sensitivity to the soil parameters. Errors on soil hydraulic properties can lead to a large bias in cumulative evapotranspiration over a long period of time. Accounting for uncertainties in soil properties is essential for land surface modelling.
K. Nishina, A. Ito, P. Falloon, A. D. Friend, D. J. Beerling, P. Ciais, D. B. Clark, R. Kahana, E. Kato, W. Lucht, M. Lomas, R. Pavlick, S. Schaphoff, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, https://doi.org/10.5194/esd-6-435-2015, 2015
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Our study focused on uncertainties in terrestrial C cycling under newly developed scenarios with CMIP5. This study presents first results for examining relative uncertainties of projected terrestrial C cycling in multiple projection components. Only using our new model inter-comparison project data sets enables us to evaluate various uncertainty sources in projection periods. The information on relative uncertainties is useful for climate science and climate change impact evaluation.
K. Naudts, J. Ryder, M. J. McGrath, J. Otto, Y. Chen, A. Valade, V. Bellasen, G. Berhongaray, G. Bönisch, M. Campioli, J. Ghattas, T. De Groote, V. Haverd, J. Kattge, N. MacBean, F. Maignan, P. Merilä, J. Penuelas, P. Peylin, B. Pinty, H. Pretzsch, E. D. Schulze, D. Solyga, N. Vuichard, Y. Yan, and S. Luyssaert
Geosci. Model Dev., 8, 2035–2065, https://doi.org/10.5194/gmd-8-2035-2015, https://doi.org/10.5194/gmd-8-2035-2015, 2015
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Despite the potential of forest management to mitigate climate change, none of today's predictions of future climate accounts for the impact of forest management. To address this gap in modelling capability, we developed and parametrised a land-surface model to simulate biogeochemical and biophysical effects of forest management. Comparison of model output against data showed an increased model performance in reproducing large-scale spatial patterns and inter-annual variability over Europe.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, D. Carrer, H. Verbeeck, M. De Weirdt, and D. Bonal
Geosci. Model Dev., 8, 1709–1727, https://doi.org/10.5194/gmd-8-1709-2015, https://doi.org/10.5194/gmd-8-1709-2015, 2015
R. Wang, Y. Balkanski, O. Boucher, L. Bopp, A. Chappell, P. Ciais, D. Hauglustaine, J. Peñuelas, and S. Tao
Atmos. Chem. Phys., 15, 6247–6270, https://doi.org/10.5194/acp-15-6247-2015, https://doi.org/10.5194/acp-15-6247-2015, 2015
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This study makes a first attempt to estimate the temporal trend of Fe emissions from anthropogenic and natural combustion sources from 1960 to 2007 and the emissions of Fe from mineral dust based on a recent mineralogical database. The new emission inventory is introduced into a global aerosol model. The simulated total Fe and soluble Fe concentrations in surface air as well as the deposition of total Fe are evaluated by observations over major continental and oceanic regions globally.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, and T. T. van Leeuwen
Geosci. Model Dev., 8, 1321–1338, https://doi.org/10.5194/gmd-8-1321-2015, https://doi.org/10.5194/gmd-8-1321-2015, 2015
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We conducted parallel simulations using a global land surface model, with and without fires being included, respectively. When the anthropogenic land cover change fire is excluded, we find that natural wildfires have reduced the global land carbon uptake by 0.3Pg C per year over 1901-2012. This is equivalent to 20% of the land carbon uptake in a world without fire. This fire-induced reduction in carbon uptake could be partly explained by climate variability, in particular the ENSO events.
F. M. Bréon, G. Broquet, V. Puygrenier, F. Chevallier, I. Xueref-Remy, M. Ramonet, E. Dieudonné, M. Lopez, M. Schmidt, O. Perrussel, and P. Ciais
Atmos. Chem. Phys., 15, 1707–1724, https://doi.org/10.5194/acp-15-1707-2015, https://doi.org/10.5194/acp-15-1707-2015, 2015
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
N. Canal, J.-C. Calvet, B. Decharme, D. Carrer, S. Lafont, and G. Pigeon
Hydrol. Earth Syst. Sci., 18, 4979–4999, https://doi.org/10.5194/hess-18-4979-2014, https://doi.org/10.5194/hess-18-4979-2014, 2014
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Regional French agricultural yield statistics are used to benchmark root water uptake representations in the ISBA-A-gs model. Key model parameters governing the inter-annual variability of the simulated biomass are retrieved. A complex multi-layer soil hydrology model does not outperform a simple bulk root-zone reservoir approach. This could be explained by missing processes/information in the model such as hydraulic redistribution and detailed soil properties.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, R. Fisher, B. Christoffersen, J. C. Calvet, A. C. L. da Costa, L. V. Ferreira, and P. Meir
Geosci. Model Dev., 7, 2933–2950, https://doi.org/10.5194/gmd-7-2933-2014, https://doi.org/10.5194/gmd-7-2933-2014, 2014
M. Van Oijen, J. Balkovi, C. Beer, D. R. Cameron, P. Ciais, W. Cramer, T. Kato, M. Kuhnert, R. Martin, R. Myneni, A. Rammig, S. Rolinski, J.-F. Soussana, K. Thonicke, M. Van der Velde, and L. Xu
Biogeosciences, 11, 6357–6375, https://doi.org/10.5194/bg-11-6357-2014, https://doi.org/10.5194/bg-11-6357-2014, 2014
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We use a new risk analysis method, and six vegetation models, to analyse how climate change may alter drought risks in European ecosystems. The conclusions are (1) drought will pose increasing risks to productivity in the Mediterranean area; (2) this is because severe droughts will become more frequent, not because ecosystems will become more vulnerable; (3) future C sequestration will be at risk because carbon gain in primary productivity will be more affected than carbon loss in respiration.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
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ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
A. Agustí-Panareda, S. Massart, F. Chevallier, S. Boussetta, G. Balsamo, A. Beljaars, P. Ciais, N. M. Deutscher, R. Engelen, L. Jones, R. Kivi, J.-D. Paris, V.-H. Peuch, V. Sherlock, A. T. Vermeulen, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, https://doi.org/10.5194/acp-14-11959-2014, 2014
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This paper presents a new operational CO2 forecast product as part of the Copernicus Atmospheric Services suite of atmospheric composition products, using the state-of-the-art numerical weather prediction model from the European Centre of Medium-Range Weather Forecasts.
The evaluation with independent observations shows that the forecast has skill in predicting the synoptic variability of CO2. The online simulation of CO2 fluxes from vegetation contributes to this skill.
I. B. Konovalov, E. V. Berezin, P. Ciais, G. Broquet, M. Beekmann, J. Hadji-Lazaro, C. Clerbaux, M. O. Andreae, J. W. Kaiser, and E.-D. Schulze
Atmos. Chem. Phys., 14, 10383–10410, https://doi.org/10.5194/acp-14-10383-2014, https://doi.org/10.5194/acp-14-10383-2014, 2014
J. P. Boisier, N. de Noblet-Ducoudré, and P. Ciais
Hydrol. Earth Syst. Sci., 18, 3571–3590, https://doi.org/10.5194/hess-18-3571-2014, https://doi.org/10.5194/hess-18-3571-2014, 2014
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
J. B. Fisher, M. Sikka, W. C. Oechel, D. N. Huntzinger, J. R. Melton, C. D. Koven, A. Ahlström, M. A. Arain, I. Baker, J. M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, D. Hayes, C. Huntingford, A. K. Jain, P. E. Levy, M. R. Lomas, B. Poulter, D. Price, A. K. Sahoo, K. Schaefer, H. Tian, E. Tomelleri, H. Verbeeck, N. Viovy, R. Wania, N. Zeng, and C. E. Miller
Biogeosciences, 11, 4271–4288, https://doi.org/10.5194/bg-11-4271-2014, https://doi.org/10.5194/bg-11-4271-2014, 2014
M. Schmidt, M. Lopez, C. Yver Kwok, C. Messager, M. Ramonet, B. Wastine, C. Vuillemin, F. Truong, B. Gal, E. Parmentier, O. Cloué, and P. Ciais
Atmos. Meas. Tech., 7, 2283–2296, https://doi.org/10.5194/amt-7-2283-2014, https://doi.org/10.5194/amt-7-2283-2014, 2014
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
A. Valade, P. Ciais, N. Vuichard, N. Viovy, A. Caubel, N. Huth, F. Marin, and J.-F. Martiné
Geosci. Model Dev., 7, 1225–1245, https://doi.org/10.5194/gmd-7-1225-2014, https://doi.org/10.5194/gmd-7-1225-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 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
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
S. Turquety, L. Menut, B. Bessagnet, A. Anav, N. Viovy, F. Maignan, and M. Wooster
Geosci. Model Dev., 7, 587–612, https://doi.org/10.5194/gmd-7-587-2014, https://doi.org/10.5194/gmd-7-587-2014, 2014
K. Nishina, A. Ito, D. J. Beerling, P. Cadule, P. Ciais, D. B. Clark, P. Falloon, A. D. Friend, R. Kahana, E. Kato, R. Keribin, W. Lucht, M. Lomas, T. T. Rademacher, R. Pavlick, S. Schaphoff, N. Vuichard, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, https://doi.org/10.5194/esd-5-197-2014, 2014
S. X. Fang, L. X. Zhou, P. P. Tans, P. Ciais, M. Steinbacher, L. Xu, and T. Luan
Atmos. Chem. Phys., 14, 2541–2554, https://doi.org/10.5194/acp-14-2541-2014, https://doi.org/10.5194/acp-14-2541-2014, 2014
M. Parrens, J.-F. Mahfouf, A. L. Barbu, and J.-C. Calvet
Hydrol. Earth Syst. Sci., 18, 673–689, https://doi.org/10.5194/hess-18-673-2014, https://doi.org/10.5194/hess-18-673-2014, 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
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, and S. Lafont
Hydrol. Earth Syst. Sci., 18, 173–192, https://doi.org/10.5194/hess-18-173-2014, https://doi.org/10.5194/hess-18-173-2014, 2014
J. F. Chang, N. Viovy, N. Vuichard, P. Ciais, T. Wang, A. Cozic, R. Lardy, A.-I. Graux, K. Klumpp, R. Martin, and J.-F. Soussana
Geosci. Model Dev., 6, 2165–2181, https://doi.org/10.5194/gmd-6-2165-2013, https://doi.org/10.5194/gmd-6-2165-2013, 2013
B. Guenet, F. E. Moyano, N. Vuichard, G. J. D. Kirk, P. H. Bellamy, S. Zaehle, and P. Ciais
Geosci. Model Dev., 6, 2153–2163, https://doi.org/10.5194/gmd-6-2153-2013, https://doi.org/10.5194/gmd-6-2153-2013, 2013
F. Souty, B. Dorin, T. Brunelle, P. Dumas, and P. Ciais
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-6975-2013, https://doi.org/10.5194/gmdd-6-6975-2013, 2013
Revised manuscript has not been submitted
C. Yue, P. Ciais, S. Luyssaert, P. Cadule, J. Harden, J. Randerson, V. Bellassen, T. Wang, S. L. Piao, B. Poulter, and N. Viovy
Biogeosciences, 10, 8233–8252, https://doi.org/10.5194/bg-10-8233-2013, https://doi.org/10.5194/bg-10-8233-2013, 2013
E. Joetzjer, H. Douville, C. Delire, P. Ciais, B. Decharme, and S. Tyteca
Hydrol. Earth Syst. Sci., 17, 4885–4895, https://doi.org/10.5194/hess-17-4885-2013, https://doi.org/10.5194/hess-17-4885-2013, 2013
C. Ottlé, J. Lescure, F. Maignan, B. Poulter, T. Wang, and N. Delbart
Earth Syst. Sci. Data, 5, 331–348, https://doi.org/10.5194/essd-5-331-2013, https://doi.org/10.5194/essd-5-331-2013, 2013
C. E. Yver-Kwok, D. Müller, C. Caldow, B. Lebegue, J. G. Mønster, C. W. Rella, C. Scheutz, M. Schmidt, M. Ramonet, T. Warneke, G. Broquet, and P. Ciais
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-6-9181-2013, https://doi.org/10.5194/amtd-6-9181-2013, 2013
Revised manuscript not accepted
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
E. V. Berezin, I. B. Konovalov, P. Ciais, A. Richter, S. Tao, G. Janssens-Maenhout, M. Beekmann, and E.-D. Schulze
Atmos. Chem. Phys., 13, 9415–9438, https://doi.org/10.5194/acp-13-9415-2013, https://doi.org/10.5194/acp-13-9415-2013, 2013
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.5194/hess-17-3523-2013, 2013
M. Roland, P. Serrano-Ortiz, A. S. Kowalski, Y. Goddéris, E. P. Sánchez-Cañete, P. Ciais, F. Domingo, S. Cuezva, S. Sanchez-Moral, B. Longdoz, D. Yakir, R. Van Grieken, J. Schott, C. Cardell, and I. A. Janssens
Biogeosciences, 10, 5009–5017, https://doi.org/10.5194/bg-10-5009-2013, https://doi.org/10.5194/bg-10-5009-2013, 2013
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
R. Amri, M. Zribi, Z. Lili-Chabaane, C. Szczypta, J. C. Calvet, and G. Boulet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-8117-2013, https://doi.org/10.5194/hessd-10-8117-2013, 2013
Revised manuscript not accepted
S. Kandasamy, F. Baret, A. Verger, P. Neveux, and M. Weiss
Biogeosciences, 10, 4055–4071, https://doi.org/10.5194/bg-10-4055-2013, https://doi.org/10.5194/bg-10-4055-2013, 2013
T. Gasser and P. Ciais
Earth Syst. Dynam., 4, 171–186, https://doi.org/10.5194/esd-4-171-2013, https://doi.org/10.5194/esd-4-171-2013, 2013
R. Wang, S. Tao, P. Ciais, H. Z. Shen, Y. Huang, H. Chen, G. F. Shen, B. Wang, W. Li, Y. Y. Zhang, Y. Lu, D. Zhu, Y. C. Chen, X. P. Liu, W. T. Wang, X. L. Wang, W. X. Liu, B. G. Li, and S. L. Piao
Atmos. Chem. Phys., 13, 5189–5203, https://doi.org/10.5194/acp-13-5189-2013, https://doi.org/10.5194/acp-13-5189-2013, 2013
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
M. Casado, P. Ortega, V. Masson-Delmotte, C. Risi, D. Swingedouw, V. Daux, D. Genty, F. Maignan, O. Solomina, B. Vinther, N. Viovy, and P. Yiou
Clim. Past, 9, 871–886, https://doi.org/10.5194/cp-9-871-2013, https://doi.org/10.5194/cp-9-871-2013, 2013
M. Ménégoz, G. Krinner, Y. Balkanski, A. Cozic, O. Boucher, and P. Ciais
The Cryosphere, 7, 537–554, https://doi.org/10.5194/tc-7-537-2013, https://doi.org/10.5194/tc-7-537-2013, 2013
J. P. Boisier, N. de Noblet-Ducoudré, and P. Ciais
Biogeosciences, 10, 1501–1516, https://doi.org/10.5194/bg-10-1501-2013, https://doi.org/10.5194/bg-10-1501-2013, 2013
P. K. Patra, J. G. Canadell, R. A. Houghton, S. L. Piao, N.-H. Oh, P. Ciais, K. R. Manjunath, A. Chhabra, T. Wang, T. Bhattacharya, P. Bousquet, J. Hartman, A. Ito, E. Mayorga, Y. Niwa, P. A. Raymond, V. V. S. S. Sarma, and R. Lasco
Biogeosciences, 10, 513–527, https://doi.org/10.5194/bg-10-513-2013, https://doi.org/10.5194/bg-10-513-2013, 2013
B. Ringeval, P. O. Hopcroft, P. J. Valdes, P. Ciais, G. Ramstein, A. J. Dolman, and M. Kageyama
Clim. Past, 9, 149–171, https://doi.org/10.5194/cp-9-149-2013, https://doi.org/10.5194/cp-9-149-2013, 2013
Related subject area
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Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
SIMO v1.0: simplified model of the vertical temperature profile in a small, warm, monomictic lake
Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling
Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation
A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains
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Evaluating the Atibaia River hydrology using JULES6.1
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model ParFlow-CLM (v3.6.0) over Europe
A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector
CLIMFILL v0.9: a framework for intelligently gap filling Earth observations
Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model
Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v2.0.1) for Earth system model coupling
Improved runoff simulations for a highly varying soil depth and complex terrain watershed in the Loess Plateau with the Community Land Model version 5
GSTools v1.3: a toolbox for geostatistical modelling in Python
AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods
Modeling of streamflow in a 30 km long reach spanning 5 years using OpenFOAM 5.x
Tree hydrodynamic modelling of the soil–plant–atmosphere continuum using FETCH3
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
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Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
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This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
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Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
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Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
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A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
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Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
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The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
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A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Kristina Šarović, Melita Burić, and Zvjezdana B. Klaić
Geosci. Model Dev., 15, 8349–8375, https://doi.org/10.5194/gmd-15-8349-2022, https://doi.org/10.5194/gmd-15-8349-2022, 2022
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We develop a simple 1-D model for the prediction of the vertical temperature profiles in small, warm lakes. The model uses routinely measured meteorological variables as well as UVB radiation and yearly mean temperature data. It can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.
Jason A. Clark, Elchin E. Jafarov, Ken D. Tape, Benjamin M. Jones, and Victor Stepanenko
Geosci. Model Dev., 15, 7421–7448, https://doi.org/10.5194/gmd-15-7421-2022, https://doi.org/10.5194/gmd-15-7421-2022, 2022
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Lakes in the Arctic are important reservoirs of heat. Under climate warming scenarios, we expect Arctic lakes to warm the surrounding frozen ground. We simulate water temperatures in three Arctic lakes in northern Alaska over several years. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season and that more heat storage by lakes would enhance thawing of frozen ground.
Danielle S. Grogan, Shan Zuidema, Alex Prusevich, Wilfred M. Wollheim, Stanley Glidden, and Richard B. Lammers
Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, https://doi.org/10.5194/gmd-15-7287-2022, 2022
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This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
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We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Robert Chlumsky, James R. Craig, Simon G. M. Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown, and Rezgar Arabzadeh
Geosci. Model Dev., 15, 7017–7030, https://doi.org/10.5194/gmd-15-7017-2022, https://doi.org/10.5194/gmd-15-7017-2022, 2022
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We introduce the open-source RavenR package, which has been built to support the use of the hydrologic modelling framework Raven. The R package contains many functions that may be useful in each step of the model-building process, including preparing model input files, running the model, and analyzing the outputs. We present six reproducible use cases of the RavenR package for the Liard River basin in Canada to demonstrate how it may be deployed.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
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Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
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This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Ji Li, Daoxian Yuan, Fuxi Zhang, Jiao Liu, and Mingguo Ma
Geosci. Model Dev., 15, 6581–6600, https://doi.org/10.5194/gmd-15-6581-2022, https://doi.org/10.5194/gmd-15-6581-2022, 2022
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A new karst hydrological model (the QMG model) is developed to simulate and predict the floods in karst trough valley basins. Unlike the complex structure and parameters of current karst groundwater models, this model has a simple double-layered structure with few parameters and decreases the demand for modeling data in karst areas. The flood simulation results based on the QMG model of the Qingmuguan karst trough valley basin are satisfactory, indicating the suitability of the model simulation.
Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
Geosci. Model Dev., 15, 6359–6369, https://doi.org/10.5194/gmd-15-6359-2022, https://doi.org/10.5194/gmd-15-6359-2022, 2022
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MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
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Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
Suyeon Choi and Yeonjoo Kim
Geosci. Model Dev., 15, 5967–5985, https://doi.org/10.5194/gmd-15-5967-2022, https://doi.org/10.5194/gmd-15-5967-2022, 2022
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Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
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With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
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Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-173, https://doi.org/10.5194/gmd-2022-173, 2022
Revised manuscript accepted for GMD
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It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in-situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
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Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
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Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Anthony Bernus and Catherine Ottlé
Geosci. Model Dev., 15, 4275–4295, https://doi.org/10.5194/gmd-15-4275-2022, https://doi.org/10.5194/gmd-15-4275-2022, 2022
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The lake model FLake was coupled to the ORCHIDEE land surface model to simulate lake energy balance at global scale with a multi-tile approach. Several simulations were performed with various atmospheric reanalyses and different lake depth parameterizations. The simulated lake surface temperature showed good agreement with observations (RMSEs of the order of 3 °C). We showed the large impact of the atmospheric forcing on lake temperature. We highlighted systematic errors on ice cover phenology.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Jiming Jin, Lei Wang, Jie Yang, Bingcheng Si, and Guo-Yue Niu
Geosci. Model Dev., 15, 3405–3416, https://doi.org/10.5194/gmd-15-3405-2022, https://doi.org/10.5194/gmd-15-3405-2022, 2022
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This study aimed to improve runoff simulations and explore deep soil hydrological processes for a highly varying soil depth and complex terrain watershed in the Loess Plateau, China. The actual soil depths and river channels were incorporated into the model to better simulate the runoff in this watershed. The soil evaporation scheme was modified to better describe the evaporation processes. Our results showed that the model significantly improved the runoff simulations.
Sebastian Müller, Lennart Schüler, Alraune Zech, and Falk Heße
Geosci. Model Dev., 15, 3161–3182, https://doi.org/10.5194/gmd-15-3161-2022, https://doi.org/10.5194/gmd-15-3161-2022, 2022
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The GSTools package provides a Python-based platform for geoostatistical applications. Salient features of GSTools are its random field generation, its kriging capabilities and its versatile covariance model. It is furthermore integrated with other Python packages, like PyKrige, ogs5py or scikit-gstat, and provides interfaces to meshio and PyVista. Four presented workflows showcase the abilities of GSTools.
Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho
Geosci. Model Dev., 15, 3021–3039, https://doi.org/10.5194/gmd-15-3021-2022, https://doi.org/10.5194/gmd-15-3021-2022, 2022
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The field of artificial intelligence has shown promising results in a wide variety of fields including hydrological modeling. However, developing and testing hydrological models with artificial intelligence techniques require expertise from diverse fields. In this study, we developed an open-source framework based upon the python programming language to simplify the process of the development of hydrological models of time series data using machine learning.
Yunxiang Chen, Jie Bao, Yilin Fang, William A. Perkins, Huiying Ren, Xuehang Song, Zhuoran Duan, Zhangshuan Hou, Xiaoliang He, and Timothy D. Scheibe
Geosci. Model Dev., 15, 2917–2947, https://doi.org/10.5194/gmd-15-2917-2022, https://doi.org/10.5194/gmd-15-2917-2022, 2022
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Climate change affects river discharge variations that alter streamflow. By integrating multi-type survey data with a computational fluid dynamics tool, OpenFOAM, we show a workflow that enables accurate and efficient streamflow modeling at 30 km and 5-year scales. The model accuracy for water stage and depth average velocity is −16–9 cm and 0.71–0.83 in terms of mean error and correlation coefficients. This accuracy indicates the model's reliability for evaluating climate impact on rivers.
Marcela Silva, Ashley M. Matheny, Valentijn R. N. Pauwels, Dimetre Triadis, Justine E. Missik, Gil Bohrer, and Edoardo Daly
Geosci. Model Dev., 15, 2619–2634, https://doi.org/10.5194/gmd-15-2619-2022, https://doi.org/10.5194/gmd-15-2619-2022, 2022
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