Articles | Volume 19, issue 19
https://doi.org/10.5194/bg-19-4671-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-4671-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Oct 2022
Research article |
| 05 Oct 2022
| 05 Oct 2022
Evaluation of soil carbon simulation in CMIP6 Earth system models
Department of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Laver Building, North Park Road, Exeter, EX4 4QE, UK
Sarah E. Chadburn
Department of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Laver Building, North Park Road, Exeter, EX4 4QE, UK
Eleanor J. Burke
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
Peter M. Cox
Department of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Laver Building, North Park Road, Exeter, EX4 4QE, UK
Related authors
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 21, 2759–2776, https://doi.org/10.5194/bg-21-2759-2024, https://doi.org/10.5194/bg-21-2759-2024, 2024
Short summary
Short summary
Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meeting Paris Agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils in the land response is highlighted.
Camilla Therese Mathison, Eleanor Burke, Eszter Kovacs, Gregory Munday, Chris Huntingford, Chris Jones, Chris Smith, Norman Steinert, Andy Wiltshire, Laila Gohar, and Rebecca Varney
EGUsphere, https://doi.org/10.5194/egusphere-2023-2932, https://doi.org/10.5194/egusphere-2023-2932, 2024
Short summary
Short summary
We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emission scenarios and rapidly provide regional impacts information. PRIME allows large ensembles to be run on multi-centennial timescales including analysis of many important variables for impacts assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios giving confidence in using PRIME for novel scenarios.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, Simon Jones, Andy J. Wiltshire, and Peter M. Cox
Biogeosciences, 20, 3767–3790, https://doi.org/10.5194/bg-20-3767-2023, https://doi.org/10.5194/bg-20-3767-2023, 2023
Short summary
Short summary
This study evaluates soil carbon projections during the 21st century in CMIP6 Earth system models. In general, we find a reduced spread of changes in global soil carbon in CMIP6 compared to the previous CMIP5 generation. The reduced CMIP6 spread arises from an emergent relationship between soil carbon changes due to change in plant productivity and soil carbon changes due to changes in turnover time. We show that this relationship is consistent with false priming under transient climate change.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Paul David Longden Ritchie, Chris Huntingford, and Peter Cox
EGUsphere, https://doi.org/10.5194/egusphere-2024-3023, https://doi.org/10.5194/egusphere-2024-3023, 2024
Short summary
Short summary
Climate Tipping Points are not instantaneous upon crossing critical thresholds in global warming, as is often assumed. Instead, it is possible to temporarily overshoot a threshold without causing tipping, provided the duration of the overshoot is short. In this Idea, we demonstrate that restricting the time over 1.5 °C would considerably reduce tipping point risks.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
Short summary
Short summary
This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Mark S. Williamson, Peter M. Cox, Chris Huntingford, and Femke J. M. M. Nijsse
Earth Syst. Dynam., 15, 829–852, https://doi.org/10.5194/esd-15-829-2024, https://doi.org/10.5194/esd-15-829-2024, 2024
Short summary
Short summary
Emergent constraints on equilibrium climate sensitivity (ECS) have generally got statistically weaker in the latest set of state-of-the-art climate models (CMIP6) compared to past sets (CMIP5). We look at why this weakening happened for one particular study (Cox et al, 2018) and attribute it to an assumption made in the theory that when corrected for restores there is a stronger relationship between predictor and ECS.
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 21, 2759–2776, https://doi.org/10.5194/bg-21-2759-2024, https://doi.org/10.5194/bg-21-2759-2024, 2024
Short summary
Short summary
Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meeting Paris Agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils in the land response is highlighted.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
Short summary
Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Camilla Therese Mathison, Eleanor Burke, Eszter Kovacs, Gregory Munday, Chris Huntingford, Chris Jones, Chris Smith, Norman Steinert, Andy Wiltshire, Laila Gohar, and Rebecca Varney
EGUsphere, https://doi.org/10.5194/egusphere-2023-2932, https://doi.org/10.5194/egusphere-2023-2932, 2024
Short summary
Short summary
We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emission scenarios and rapidly provide regional impacts information. PRIME allows large ensembles to be run on multi-centennial timescales including analysis of many important variables for impacts assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios giving confidence in using PRIME for novel scenarios.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Mueller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2023-2873, https://doi.org/10.5194/egusphere-2023-2873, 2024
Short summary
Short summary
Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in Northern Europe using ecosystem models, atmospheric inversions and up-scaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions and up-scaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, Simon Jones, Andy J. Wiltshire, and Peter M. Cox
Biogeosciences, 20, 3767–3790, https://doi.org/10.5194/bg-20-3767-2023, https://doi.org/10.5194/bg-20-3767-2023, 2023
Short summary
Short summary
This study evaluates soil carbon projections during the 21st century in CMIP6 Earth system models. In general, we find a reduced spread of changes in global soil carbon in CMIP6 compared to the previous CMIP5 generation. The reduced CMIP6 spread arises from an emergent relationship between soil carbon changes due to change in plant productivity and soil carbon changes due to changes in turnover time. We show that this relationship is consistent with false priming under transient climate change.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
Short summary
Short summary
This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Nina Raoult, Tim Jupp, Ben Booth, and Peter Cox
Earth Syst. Dynam., 14, 723–731, https://doi.org/10.5194/esd-14-723-2023, https://doi.org/10.5194/esd-14-723-2023, 2023
Short summary
Short summary
Climate models are used to predict the impact of climate change. However, poorly constrained parameters used in the physics of the models mean that we simulate a large spread of possible future outcomes. We can use real-world observations to reduce the uncertainty of parameter values, but we do not have observations to reduce the spread of possible future outcomes directly. We present a method for translating the reduction in parameter uncertainty into a reduction in possible model projections.
Paul D. L. Ritchie, Hassan Alkhayuon, Peter M. Cox, and Sebastian Wieczorek
Earth Syst. Dynam., 14, 669–683, https://doi.org/10.5194/esd-14-669-2023, https://doi.org/10.5194/esd-14-669-2023, 2023
Short summary
Short summary
Complex systems can undergo abrupt changes or tipping points when external forcing crosses a critical level and are of increasing concern because of their severe impacts. However, tipping points can also occur when the external forcing changes too quickly without crossing any critical levels, which is very relevant for Earth’s systems and contemporary climate. We give an intuitive explanation of such rate-induced tipping and provide illustrative examples from natural and human systems.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
Short summary
Short summary
Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
Morgan Sparey, Peter Cox, and Mark S. Williamson
Biogeosciences, 20, 451–488, https://doi.org/10.5194/bg-20-451-2023, https://doi.org/10.5194/bg-20-451-2023, 2023
Short summary
Short summary
Accurate climate models are vital for mitigating climate change; however, projections often disagree. Using Köppen–Geiger bioclimate classifications we show that CMIP6 climate models agree well on the fraction of global land surface that will change classification per degree of global warming. We find that 13 % of land will change climate per degree of warming from 1 to 3 K; thus, stabilising warming at 1.5 rather than 2 K would save over 7.5 million square kilometres from bioclimatic change.
Yao Gao, Eleanor J. Burke, Sarah E. Chadburn, Maarit Raivonen, Mika Aurela, Lawrence B. Flanagan, Krzysztof Fortuniak, Elyn Humphreys, Annalea Lohila, Tingting Li, Tiina Markkanen, Olli Nevalainen, Mats B. Nilsson, Włodzimierz Pawlak, Aki Tsuruta, Huiyi Yang, and Tuula Aalto
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-229, https://doi.org/10.5194/bg-2022-229, 2022
Manuscript not accepted for further review
Short summary
Short summary
We coupled a process-based peatland CH4 emission model HIMMELI with a state-of-art land surface model JULES. The performance of the coupled model was evaluated at six northern wetland sites. The coupled model is considered to be more appropriate in simulating wetland CH4 emission. In order to improve the simulated CH4 emission, the model requires better representation of the peat soil carbon and hydrologic processes in JULES and the methane production and transportation processes in HIMMELI.
Isobel M. Parry, Paul D. L. Ritchie, and Peter M. Cox
Earth Syst. Dynam., 13, 1667–1675, https://doi.org/10.5194/esd-13-1667-2022, https://doi.org/10.5194/esd-13-1667-2022, 2022
Short summary
Short summary
Despite little evidence of regional Amazon rainforest dieback, many localised abrupt dieback events are observed in the latest state-of-the-art global climate models under anthropogenic climate change. The detected dieback events would still cause severe consequences for local communities and ecosystems. This study suggests that 7 ± 5 % of the northern South America region would experience abrupt downward shifts in vegetation carbon for every degree of global warming past 1.5 °C.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
Short summary
Short summary
In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
Short summary
Short summary
The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, https://doi.org/10.5194/gmd-15-1633-2022, 2022
Short summary
Short summary
We present a new method to include peatlands in an Earth system model (ESM). Peatlands store huge amounts of carbon that accumulates very slowly but that can be rapidly destabilised, emitting greenhouse gases. Our model captures the dynamic nature of peat by simulating the change in surface height and physical properties of the soil as carbon is added or decomposed. Thus, we model, for the first time in an ESM, peat dynamics and its threshold behaviours that can lead to destabilisation.
Thomas Schneider von Deimling, Hanna Lee, Thomas Ingeman-Nielsen, Sebastian Westermann, Vladimir Romanovsky, Scott Lamoureux, Donald A. Walker, Sarah Chadburn, Erin Trochim, Lei Cai, Jan Nitzbon, Stephan Jacobi, and Moritz Langer
The Cryosphere, 15, 2451–2471, https://doi.org/10.5194/tc-15-2451-2021, https://doi.org/10.5194/tc-15-2451-2021, 2021
Short summary
Short summary
Climate warming puts infrastructure built on permafrost at risk of failure. There is a growing need for appropriate model-based risk assessments. Here we present a modelling study and show an exemplary case of how a gravel road in a cold permafrost environment in Alaska might suffer from degrading permafrost under a scenario of intense climate warming. We use this case study to discuss the broader-scale applicability of our model for simulating future Arctic infrastructure failure.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
Short summary
Short summary
We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
Short summary
Short summary
Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Bettina K. Gier, Michael Buchwitz, Maximilian Reuter, Peter M. Cox, Pierre Friedlingstein, and Veronika Eyring
Biogeosciences, 17, 6115–6144, https://doi.org/10.5194/bg-17-6115-2020, https://doi.org/10.5194/bg-17-6115-2020, 2020
Short summary
Short summary
Models from Coupled Model Intercomparison Project (CMIP) phases 5 and 6 are compared to a satellite data product of column-averaged CO2 mole fractions (XCO2). The previously believed discrepancy of the negative trend in seasonal cycle amplitude in the satellite product, which is not seen in in situ data nor in the models, is attributed to a sampling characteristic. Furthermore, CMIP6 models are shown to have made progress in reproducing the observed XCO2 time series compared to CMIP5.
Eleanor J. Burke, Yu Zhang, and Gerhard Krinner
The Cryosphere, 14, 3155–3174, https://doi.org/10.5194/tc-14-3155-2020, https://doi.org/10.5194/tc-14-3155-2020, 2020
Short summary
Short summary
Permafrost will degrade under future climate change. This will have implications locally for the northern high-latitude regions and may well also amplify global climate change. There have been some recent improvements in the ability of earth system models to simulate the permafrost physical state, but further model developments are required. Models project the thawed volume of soil in the top 2 m of permafrost will increase by 10 %–40 % °C−1 of global mean surface air temperature increase.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
Short summary
Short summary
The Robust Ecosystem Demography (RED) model simulates cohorts of vegetation through mass classes. RED establishes a framework for representing demographic changes through competition, growth, and mortality across the size distribution of a forest. The steady state of the model can be solved analytically, enabling initialization. When driven by mean growth rates from a land-surface model, RED is able to fit the observed global vegetation map, giving a map of implicit mortality rates.
Femke J. M. M. Nijsse, Peter M. Cox, and Mark S. Williamson
Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, https://doi.org/10.5194/esd-11-737-2020, 2020
Short summary
Short summary
One of the key questions in climate science is how much more heating we will get for a given rise in carbon dioxide in the atmosphere. A new generation of models showed that this might be more than previously expected. Comparing the new models to observed temperature rise since 1970, we show that there is no need to revise the estimate upwards. Air pollution, whose effect on climate warming is poorly understood, stopped rising, allowing us to better constrain the greenhouse gas signal.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
Short summary
Short summary
Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Jonathan R. Moore, Arthur P. K. Argles, Kai Zhu, Chris Huntingford, and Peter M. Cox
Biogeosciences, 17, 1013–1032, https://doi.org/10.5194/bg-17-1013-2020, https://doi.org/10.5194/bg-17-1013-2020, 2020
Short summary
Short summary
The distribution of tree sizes across Amazonia can be fitted very well (for both trunk diameter and tree mass) by a simple equilibrium model assuming power law growth and size-independent mortality. We find tree growth to mirror some aspects of metabolic scaling theory and that there may be a trade-off between fast-growing, short-lived and longer-lived, slow-growing ones. Our Amazon mortality-to-growth ratio is very similar to US temperate forests, hinting at a universal property for trees.
Christian G. Andresen, David M. Lawrence, Cathy J. Wilson, A. David McGuire, Charles Koven, Kevin Schaefer, Elchin Jafarov, Shushi Peng, Xiaodong Chen, Isabelle Gouttevin, Eleanor Burke, Sarah Chadburn, Duoying Ji, Guangsheng Chen, Daniel Hayes, and Wenxin Zhang
The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, https://doi.org/10.5194/tc-14-445-2020, 2020
Short summary
Short summary
Widely-used land models project near-surface drying of the terrestrial Arctic despite increases in the net water balance driven by climate change. Drying was generally associated with increases of active-layer depth and permafrost thaw in a warming climate. However, models lack important mechanisms such as thermokarst and soil subsidence that will change the hydrological regime and add to the large uncertainty in the future Arctic hydrological state and the associated permafrost carbon feedback.
Karina E. Williams, Anna B. Harper, Chris Huntingford, Lina M. Mercado, Camilla T. Mathison, Pete D. Falloon, Peter M. Cox, and Joon Kim
Geosci. Model Dev., 12, 3207–3240, https://doi.org/10.5194/gmd-12-3207-2019, https://doi.org/10.5194/gmd-12-3207-2019, 2019
Short summary
Short summary
Data from the First ISLSCP Field Experiment, 1987–1989, is used to assess how well the JULES land-surface model simulates water stress in tallgrass prairie vegetation. We find that JULES simulates a decrease in key carbon and water cycle variables during the dry period, as expected, but that it does not capture the shape of the diurnal cycle on these days. These results will be used to inform future model development as part of wider evaluation efforts.
Julia Boike, Jan Nitzbon, Katharina Anders, Mikhail Grigoriev, Dmitry Bolshiyanov, Moritz Langer, Stephan Lange, Niko Bornemann, Anne Morgenstern, Peter Schreiber, Christian Wille, Sarah Chadburn, Isabelle Gouttevin, Eleanor Burke, and Lars Kutzbach
Earth Syst. Sci. Data, 11, 261–299, https://doi.org/10.5194/essd-11-261-2019, https://doi.org/10.5194/essd-11-261-2019, 2019
Short summary
Short summary
Long-term observational data are available from the Samoylov research site in northern Siberia, where meteorological parameters, energy balance, and subsurface observations have been recorded since 1998. This paper presents the temporal data set produced between 2002 and 2017, explaining the instrumentation, calibration, processing, and data quality control. Furthermore, we present a merged dataset of the parameters, which were measured from 1998 onwards.
Ye Liu, Yongkang Xue, Glen MacDonald, Peter Cox, and Zhengqiu Zhang
Earth Syst. Dynam., 10, 9–29, https://doi.org/10.5194/esd-10-9-2019, https://doi.org/10.5194/esd-10-9-2019, 2019
Short summary
Short summary
Climate regime shift during the 1980s identified by abrupt change in temperature, precipitation, etc. had a substantial impact on the ecosystem at different scales. Our paper identifies the spatial and temporal characteristics of the effects of climate variability, global warming, and eCO2 on ecosystem trends before and after the shift. We found about 15 % (20 %) of the global land area had enhanced positive trend (trend sign reversed) during the 1980s due to climate regime shift.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
Short summary
Short summary
Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
Short summary
Short summary
Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann
Earth Syst. Sci. Data, 10, 355–390, https://doi.org/10.5194/essd-10-355-2018, https://doi.org/10.5194/essd-10-355-2018, 2018
Short summary
Short summary
A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.
Mahdi Nakhavali, Pierre Friedlingstein, Ronny Lauerwald, Jing Tang, Sarah Chadburn, Marta Camino-Serrano, Bertrand Guenet, Anna Harper, David Walmsley, Matthias Peichl, and Bert Gielen
Geosci. Model Dev., 11, 593–609, https://doi.org/10.5194/gmd-11-593-2018, https://doi.org/10.5194/gmd-11-593-2018, 2018
Short summary
Short summary
In order to provide a better understanding of the Earth's carbon cycle, we need a model that represents the whole continuum from atmosphere to land and into the ocean. In this study we include in JULES a representation of dissolved organic carbon (DOC) processes. Our results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating the terrestrial and aquatic ecosystem.
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
Short summary
Short summary
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.
Sarah E. Chadburn, Gerhard Krinner, Philipp Porada, Annett Bartsch, Christian Beer, Luca Belelli Marchesini, Julia Boike, Altug Ekici, Bo Elberling, Thomas Friborg, Gustaf Hugelius, Margareta Johansson, Peter Kuhry, Lars Kutzbach, Moritz Langer, Magnus Lund, Frans-Jan W. Parmentier, Shushi Peng, Ko Van Huissteden, Tao Wang, Sebastian Westermann, Dan Zhu, and Eleanor J. Burke
Biogeosciences, 14, 5143–5169, https://doi.org/10.5194/bg-14-5143-2017, https://doi.org/10.5194/bg-14-5143-2017, 2017
Short summary
Short summary
Earth system models (ESMs) are our main tools for understanding future climate. The Arctic is important for the future carbon cycle, particularly due to the large carbon stocks in permafrost. We evaluated the performance of the land component of three major ESMs at Arctic tundra sites, focusing on the fluxes and stocks of carbon.
We show that the next steps for model improvement are to better represent vegetation dynamics, to include mosses and to improve below-ground carbon cycle processes.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
Short summary
Short summary
Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
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
Short summary
Short summary
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.
Eleanor J. Burke, Sarah E. Chadburn, and Altug Ekici
Geosci. Model Dev., 10, 959–975, https://doi.org/10.5194/gmd-10-959-2017, https://doi.org/10.5194/gmd-10-959-2017, 2017
Short summary
Short summary
There is a large amount of relatively inert organic carbon locked into permafrost soils. In a warming climate the permafrost will thaw and this organic carbon will become vulnerable to decomposition. This process is not typically included within Earth system models (ESMs). This paper describes the development of a vertically resolved soil organic carbon decomposition model which, in the future, can be included within the UKESM to quantify the response of the climate to permafrost carbon loss.
Nina M. Raoult, Tim E. Jupp, Peter M. Cox, and Catherine M. Luke
Geosci. Model Dev., 9, 2833–2852, https://doi.org/10.5194/gmd-9-2833-2016, https://doi.org/10.5194/gmd-9-2833-2016, 2016
Short summary
Short summary
We present a set of "optimal" parameter values used to describe the influence of vegetation in a numerical climate model, and the software suite that we developed to find it. Observational data from ~ 100 locations were used, and the optimal parameters improve the fit in 90 % of the locations. The new parameter values will allow the climate model to give better predictions, and our software should prove useful in future calibrations.
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
Short summary
Short summary
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.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
Short summary
Short summary
Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
Short summary
Short summary
Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
W. Wang, A. Rinke, J. C. Moore, X. Cui, D. Ji, Q. Li, N. Zhang, C. Wang, S. Zhang, D. M. Lawrence, A. D. McGuire, W. Zhang, C. Delire, C. Koven, K. Saito, A. MacDougall, E. Burke, and B. Decharme
The Cryosphere, 10, 287–306, https://doi.org/10.5194/tc-10-287-2016, https://doi.org/10.5194/tc-10-287-2016, 2016
Short summary
Short summary
We use a model-ensemble approach for simulating permafrost on the Tibetan Plateau. We identify the uncertainties across models (state-of-the-art land surface models) and across methods (most commonly used methods to define permafrost).
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
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
Short summary
Short summary
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.
Z. A. Thomas, F. Kwasniok, C. A. Boulton, P. M. Cox, R. T. Jones, T. M. Lenton, and C. S. M. Turney
Clim. Past, 11, 1621–1633, https://doi.org/10.5194/cp-11-1621-2015, https://doi.org/10.5194/cp-11-1621-2015, 2015
Short summary
Short summary
Using a combination of speleothem records and model simulations of the East Asian Monsoon over the penultimate glacial cycle, we search for early warning signals of past tipping points. We detect a characteristic slower response to perturbations prior to an abrupt monsoon shift at the glacial termination; however, we do not detect these signals in the preceding shifts. Our results have important implications for detecting tipping points in palaeoclimate records outside glacial terminations.
S. Miyazaki, K. Saito, J. Mori, T. Yamazaki, T. Ise, H. Arakida, T. Hajima, Y. Iijima, H. Machiya, T. Sueyoshi, H. Yabuki, E. J. Burke, M. Hosaka, K. Ichii, H. Ikawa, A. Ito, A. Kotani, Y. Matsuura, M. Niwano, T. Nitta, R. O'ishi, T. Ohta, H. Park, T. Sasai, A. Sato, H. Sato, A. Sugimoto, R. Suzuki, K. Tanaka, S. Yamaguchi, and K. Yoshimura
Geosci. Model Dev., 8, 2841–2856, https://doi.org/10.5194/gmd-8-2841-2015, https://doi.org/10.5194/gmd-8-2841-2015, 2015
Short summary
Short summary
The paper provides an overall outlook and the Stage 1 experiment (site simulations) protocol of GTMIP, an open model intercomparison project for terrestrial Arctic, conducted as an activity of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA). Models are driven by 34-year data created with the GRENE-TEA observations at four sites in Finland, Siberia and Alaska, and evaluated for physico-ecological key processes: energy budgets, snow, permafrost, phenology, and carbon budget.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
Short summary
Short summary
In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
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
Short summary
Short summary
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.
A. Ekici, S. Chadburn, N. Chaudhary, L. H. Hajdu, A. Marmy, S. Peng, J. Boike, E. Burke, A. D. Friend, C. Hauck, G. Krinner, M. Langer, P. A. Miller, and C. Beer
The Cryosphere, 9, 1343–1361, https://doi.org/10.5194/tc-9-1343-2015, https://doi.org/10.5194/tc-9-1343-2015, 2015
Short summary
Short summary
This paper compares the performance of different land models in estimating soil thermal regimes at distinct cold region landscape types. Comparing models with different processes reveal the importance of surface insulation (snow/moss layer) and soil internal processes (heat/water transfer). The importance of model processes also depend on site conditions such as high/low snow cover, dry/wet soil types.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
Short summary
Short summary
Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
Related subject area
Earth System Science/Response to Global Change: Climate Change
Responses of field-grown maize to different soil types, water regimes, and contrasting vapor pressure deficit
Effect of the 2022 summer drought across forest types in Europe
Effect of terrestrial nutrient limitation on the estimation of the remaining carbon budget
Projected changes in forest fire season, the number of fires, and burnt area in Fennoscandia by 2100
New ozone–nitrogen model shows early senescence onset is the primary cause of ozone-induced reduction in grain quality of wheat
Ocean alkalinity enhancement approaches and the predictability of runaway precipitation processes: results of an experimental study to determine critical alkalinity ranges for safe and sustainable application scenarios
Variations of polyphenols and carbohydrates of Emiliania huxleyi grown under simulated ocean acidification conditions
Modelling the nutritional implications of ozone on wheat protein and amino acids
Global and regional hydrological impacts of global forest expansion
The biological and preformed carbon pumps in perpetually slower and warmer oceans
The Effectiveness of Agricultural Carbon Dioxide Removal using the University of Victoria Earth System Climate Model
Toward more robust NPP projections in the North Atlantic Ocean
The Southern Ocean as the climate's freight train – driving ongoing global warming under zero-emission scenarios with ACCESS-ESM1.5
Review and syntheses: Ocean alkalinity enhancement and carbon dioxide removal through coastal enhanced silicate weathering with olivine
Mapping the future afforestation distribution of China constrained by a national afforestation plan and climate change
Southern Ocean phytoplankton under climate change: a shifting balance of bottom-up and top-down control
Coherency and time lag analyses between MODIS vegetation indices and climate across forests and grasslands in the European temperate zone
Direct foliar phosphorus uptake from wildfire ash
Unifying framework for assessing sensitivity for marine calcifiers to ocean alkalinity enhancement identifies winners, losers and biological thresholds – importance of caution with precautionary principle
The effect of forest cover changes on the regional climate conditions in Europe during the period 1986–2015
Carbon cycle feedbacks in an idealized simulation and a scenario simulation of negative emissions in CMIP6 Earth system models
Divergent responses of evergreen needle-leaf forests in Europe to the 2020 warm winter
Spatiotemporal heterogeneity in the increase in ocean acidity extremes in the northeastern Pacific
Particle fluxes by subtropical pelagic communities under ocean alkalinity enhancement
Anthropogenic climate change drives non-stationary phytoplankton internal variability
The response of wildfire regimes to Last Glacial Maximum carbon dioxide and climate
Simulated responses of soil carbon to climate change in CMIP6 Earth system models: the role of false priming
Alkalinity biases in CMIP6 Earth system models and implications for simulated CO2 drawdown via artificial alkalinity enhancement
Experiments of the efficacy of tree ring blue intensity as a climate proxy in central and western China
Burned area and carbon emissions across northwestern boreal North America from 2001–2019
Quantifying land carbon cycle feedbacks under negative CO2 emissions
The potential of an increased deciduous forest fraction to mitigate the effects of heat extremes in Europe
Ideas and perspectives: Alleviation of functional limitations by soil organisms is key to climate feedbacks from arctic soils
A comparison of the climate and carbon cycle effects of carbon removal by afforestation and an equivalent reduction in fossil fuel emissions
Stability of alkalinity in ocean alkalinity enhancement (OAE) approaches – consequences for durability of CO2 storage
Ideas and perspectives: Land–ocean connectivity through groundwater
Bioclimatic change as a function of global warming from CMIP6 climate projections
Reconciling different approaches to quantifying land surface temperature impacts of afforestation using satellite observations
Drivers of intermodel uncertainty in land carbon sink projections
Reviews and syntheses: A framework to observe, understand and project ecosystem response to environmental change in the East Antarctic Southern Ocean
Acidification impacts and acclimation potential of Caribbean benthic foraminifera assemblages in naturally discharging low-pH water
Monitoring vegetation condition using microwave remote sensing: the standardized vegetation optical depth index (SVODI)
Diazotrophy as a key driver of the response of marine net primary productivity to climate change
Impact of negative and positive CO2 emissions on global warming metrics using an ensemble of Earth system model simulations
Acidification, deoxygenation, and nutrient and biomass declines in a warming Mediterranean Sea
Ocean alkalinity enhancement – avoiding runaway CaCO3 precipitation during quick and hydrated lime dissolution
Assessment of the impacts of biological nitrogen fixation structural uncertainty in CMIP6 earth system models
Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil
The European forest carbon budget under future climate conditions and current management practices
The influence of mesoscale climate drivers on hypoxia in a fjord-like deep coastal inlet and its potential implications regarding climate change: examining a decade of water quality data
Thuy Huu Nguyen, Thomas Gaiser, Jan Vanderborght, Andrea Schnepf, Felix Bauer, Anja Klotzsche, Lena Lärm, Hubert Hüging, and Frank Ewert
Biogeosciences, 21, 5495–5515, https://doi.org/10.5194/bg-21-5495-2024, https://doi.org/10.5194/bg-21-5495-2024, 2024
Short summary
Short summary
Leaf water potential was at certain thresholds, depending on soil type, water treatment, and weather conditions. In rainfed plots, the lower water availability in the stony soil resulted in fewer roots with a higher root tissue conductance than the silty soil. In the silty soil, higher stress in the rainfed soil led to more roots with a lower root tissue conductance than in the irrigated plot. Crop responses to water stress can be opposite, depending on soil water conditions that are compared.
Mana Gharun, Ankit Shekhar, Jingfeng Xiao, Xing Li, and Nina Buchmann
Biogeosciences, 21, 5481–5494, https://doi.org/10.5194/bg-21-5481-2024, https://doi.org/10.5194/bg-21-5481-2024, 2024
Short summary
Short summary
In 2022, Europe's forests faced unprecedented dry conditions. Our study aimed to understand how different forest types respond to extreme drought. Using meteorological data and satellite imagery, we compared 2022 with two previous extreme years, 2003 and 2018. Despite less severe drought in 2022, forests showed a 30 % greater decline in photosynthesis compared to 2018 and 60 % more than 2003. This suggests an alarming level of vulnerability of forests across Europe to more frequent droughts.
Makcim L. De Sisto and Andrew H. MacDougall
Biogeosciences, 21, 4853–4873, https://doi.org/10.5194/bg-21-4853-2024, https://doi.org/10.5194/bg-21-4853-2024, 2024
Short summary
Short summary
The remaining carbon budget (RCB) represents the allowable future CO2 emissions before a temperature target is reached. Understanding the uncertainty in the RCB is critical for effective climate regulation and policy-making. One major source of uncertainty is the representation of the carbon cycle in Earth system models. We assessed how nutrient limitation affects the estimation of the RCB. We found a reduction in the estimated RCB when nutrient limitation is taken into account.
Outi Kinnunen, Leif Backman, Juha Aalto, Tuula Aalto, and Tiina Markkanen
Biogeosciences, 21, 4739–4763, https://doi.org/10.5194/bg-21-4739-2024, https://doi.org/10.5194/bg-21-4739-2024, 2024
Short summary
Short summary
Climate change is expected to increase the risk of forest fires. Ecosystem process model simulations are used to project changes in fire occurrence in Fennoscandia under six climate projections. The findings suggest a longer fire season, more fires, and an increase in burnt area towards the end of the century.
Jo Cook, Clare Brewster, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, Håkan Pleijel, and Lisa Emberson
Biogeosciences, 21, 4809–4835, https://doi.org/10.5194/bg-21-4809-2024, https://doi.org/10.5194/bg-21-4809-2024, 2024
Short summary
Short summary
At ground level, the air pollutant ozone (O3) damages wheat yield and quality. We modified the DO3SE-Crop model to simulate O3 effects on wheat quality and identified onset of leaf death as the key process affecting wheat quality upon O3 exposure. This aligns with expectations, as the onset of leaf death aids nutrient transfer from leaves to grains. Breeders should prioritize wheat varieties resistant to protein loss from delayed leaf death, to maintain yield and quality under O3 exposure.
Niels Suitner, Giulia Faucher, Carl Lim, Julieta Schneider, Charly A. Moras, Ulf Riebesell, and Jens Hartmann
Biogeosciences, 21, 4587–4604, https://doi.org/10.5194/bg-21-4587-2024, https://doi.org/10.5194/bg-21-4587-2024, 2024
Short summary
Short summary
Recent studies described the precipitation of carbonates as a result of alkalinity enhancement in seawater, which could adversely affect the carbon sequestration potential of ocean alkalinity enhancement (OAE) approaches. By conducting experiments in natural seawater, this study observed uniform patterns during the triggered runaway carbonate precipitation, which allow the prediction of safe and efficient local application levels of OAE scenarios.
Milagros Rico, Paula Santiago-Díaz, Guillermo Samperio-Ramos, Melchor González-Dávila, and Juana Magdalena Santana-Casiano
Biogeosciences, 21, 4381–4394, https://doi.org/10.5194/bg-21-4381-2024, https://doi.org/10.5194/bg-21-4381-2024, 2024
Short summary
Short summary
Changes in pH generate stress conditions, either because high pH drastically decreases the availability of trace metals such as Fe(II), a restrictive element for primary productivity, or because reactive oxygen species are increased with low pH. The metabolic functions and composition of microalgae can be affected. These modifications in metabolites are potential factors leading to readjustments in phytoplankton community structure and diversity and possible alteration in marine ecosystems.
Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2968, https://doi.org/10.5194/egusphere-2024-2968, 2024
Short summary
Short summary
Ozone (O3) pollution reduces wheat yields and quality in India, affecting amino acids essential for nutrition, like lysine and methionine. Here, we improve the DO3SE-CropN model to simulate wheat’s protective processes against O3 and their impact on protein and amino acid concentrations. While the model captures O3-induced yield losses, it underestimates amino acid reductions. Further research is needed to refine the model, enabling future risk assessments of O3's impact on yields and nutrition.
James A. King, James Weber, Peter Lawrence, Stephanie Roe, Abigail L. S. Swann, and Maria Val Martin
Biogeosciences, 21, 3883–3902, https://doi.org/10.5194/bg-21-3883-2024, https://doi.org/10.5194/bg-21-3883-2024, 2024
Short summary
Short summary
Tackling climate change by adding, restoring, or enhancing forests is gaining global support. However, it is important to investigate the broader implications of this. We used a computer model of the Earth to investigate a future where tree cover expanded as much as possible. We found that some tropical areas were cooler because of trees pumping water into the atmosphere, but this also led to soil and rivers drying. This is important because it might be harder to maintain forests as a result.
Benoît Pasquier, Mark Holzer, and Matthew A. Chamberlain
Biogeosciences, 21, 3373–3400, https://doi.org/10.5194/bg-21-3373-2024, https://doi.org/10.5194/bg-21-3373-2024, 2024
Short summary
Short summary
How do perpetually slower and warmer oceans sequester carbon? Compared to the preindustrial state, we find that biological productivity declines despite warming-stimulated growth because of a lower nutrient supply from depth. This throttles the biological carbon pump, which still sequesters more carbon because it takes longer to return to the surface. The deep ocean is isolated from the surface, allowing more carbon from the atmosphere to pass through the ocean without contributing to biology.
Rebecca Chloe Evans and H. Damon Matthews
EGUsphere, https://doi.org/10.5194/egusphere-2024-1810, https://doi.org/10.5194/egusphere-2024-1810, 2024
Short summary
Short summary
To mitigate our impact on the climate, research suggests that we will need to both drastically reduce emissions and perform carbon dioxide removal (CDR). We simulated future climates under three emissions scenarios, in which we removed some carbon from the air and put it into agricultural soil at varying rates. We found that agricultural CDR is much more effective at reducing global temperatures if done in a low emissions scenario and at a high rate, and it becomes less effective with time.
Stéphane Doléac, Marina Lévy, Roy El Hourany, and Laurent Bopp
EGUsphere, https://doi.org/10.5194/egusphere-2024-1820, https://doi.org/10.5194/egusphere-2024-1820, 2024
Short summary
Short summary
Phytoplankton net primary production (NPP) is influenced by many processes, and their representation varies across Earth-system models. This leads to differing projections for NPP's future under climate change, especially in the North Atlantic. To address this, we identified and assessed the processes controlling NPP in each model. This assessment helped us select the most reliable models, significantly improving NPP projections in the region.
Matthew A. Chamberlain, Tilo Ziehn, and Rachel M. Law
Biogeosciences, 21, 3053–3073, https://doi.org/10.5194/bg-21-3053-2024, https://doi.org/10.5194/bg-21-3053-2024, 2024
Short summary
Short summary
This paper explores the climate processes that drive increasing global average temperatures in zero-emission commitment (ZEC) simulations despite decreasing atmospheric CO2. ACCESS-ESM1.5 shows the Southern Ocean to continue to warm locally in all ZEC simulations. In ZEC simulations that start after the emission of more than 1000 Pg of carbon, the influence of the Southern Ocean increases the global temperature.
Luna J. J. Geerts, Astrid Hylén, and Filip J. R. Meysman
EGUsphere, https://doi.org/10.5194/egusphere-2024-1824, https://doi.org/10.5194/egusphere-2024-1824, 2024
Short summary
Short summary
Coastal enhanced silicate weathering (CESW) with olivine is a promising method for capturing CO2 from the atmosphere, yet studies in field conditions are lacking. We bridge the gap between theoretical studies and the real-world environment by estimating the predictability of CESW parameters and identifying aspects to consider when applying CESW. A major source of uncertainty is the lack of experimental studies with sediment, which can heavily influence the speed and efficiency of CO2 drawdown.
Shuaifeng Song, Xuezhen Zhang, and Xiaodong Yan
Biogeosciences, 21, 2839–2858, https://doi.org/10.5194/bg-21-2839-2024, https://doi.org/10.5194/bg-21-2839-2024, 2024
Short summary
Short summary
We mapped the distribution of future potential afforestation regions based on future high-resolution climate data and climate–vegetation models. After considering the national afforestation policy and climate change, we found that the future potential afforestation region was mainly located around and to the east of the Hu Line. This study provides a dataset for exploring the effects of future afforestation.
Tianfei Xue, Jens Terhaar, A. E. Friederike Prowe, Thomas L. Frölicher, Andreas Oschlies, and Ivy Frenger
Biogeosciences, 21, 2473–2491, https://doi.org/10.5194/bg-21-2473-2024, https://doi.org/10.5194/bg-21-2473-2024, 2024
Short summary
Short summary
Phytoplankton play a crucial role in marine ecosystems. However, climate change's impact on phytoplankton biomass remains uncertain, particularly in the Southern Ocean. In this region, phytoplankton biomass within the water column is likely to remain stable in response to climate change, as supported by models. This stability arises from a shallower mixed layer, favoring phytoplankton growth but also increasing zooplankton grazing due to phytoplankton concentration near the surface.
Kinga Kulesza and Agata Hościło
Biogeosciences, 21, 2509–2527, https://doi.org/10.5194/bg-21-2509-2024, https://doi.org/10.5194/bg-21-2509-2024, 2024
Short summary
Short summary
We present coherence and time lags in spectral response of three vegetation types in the European temperate zone to the influencing meteorological factors and teleconnection indices for the period 2002–2022. Vegetation condition in broadleaved forest, coniferous forest and pastures was measured with MODIS NDVI and EVI, and the coherence between NDVI and EVI and meteorological elements was described using the methods of wavelet coherence and Pearson’s linear correlation with time lag.
Anton Lokshin, Daniel Palchan, and Avner Gross
Biogeosciences, 21, 2355–2365, https://doi.org/10.5194/bg-21-2355-2024, https://doi.org/10.5194/bg-21-2355-2024, 2024
Short summary
Short summary
Ash particles from wildfires are rich in phosphorus (P), a crucial nutrient that constitutes a limiting factor in 43 % of the world's land ecosystems. We hypothesize that wildfire ash could directly contribute to plant nutrition. We find that fire ash application boosts the growth of plants, but the only way plants can uptake P from fire ash is through the foliar uptake pathway and not through the roots. The fertilization impact of fire ash was also maintained under elevated levels of CO2.
Nina Bednaršek, Greg Pelletier, Hanna van de Mortel, Marisol García-Reyes, Richard Feely, and Andrew Dickson
EGUsphere, https://doi.org/10.5194/egusphere-2024-947, https://doi.org/10.5194/egusphere-2024-947, 2024
Short summary
Short summary
The environmental impacts of ocean alkalinity enhancement (OAE) are unknown. A conceptual framework was developed showing 40 % of species to respond positively, 20 % negatively and 40 % with neutral response upon alkalinity addition. Biological thresholds were found between 10 to 500 µmol/kg NaOH addition, emphasizing lab experiments to be conducted at lower dosages. A precautionary approach is warranted to avoid potential risks.
Marcus Breil, Vanessa K. M. Schneider, and Joaquim G. Pinto
Biogeosciences, 21, 811–824, https://doi.org/10.5194/bg-21-811-2024, https://doi.org/10.5194/bg-21-811-2024, 2024
Short summary
Short summary
The general impact of afforestation on the regional climate conditions in Europe during the period 1986–2015 is investigated. For this purpose, a regional climate model simulation is performed, in which afforestation during this period is considered, and results are compared to a simulation in which this is not the case. Results show that afforestation had discernible impacts on the climate change signal in Europe, which may have mitigated the local warming trend, especially in summer in Europe.
Ali Asaadi, Jörg Schwinger, Hanna Lee, Jerry Tjiputra, Vivek Arora, Roland Séférian, Spencer Liddicoat, Tomohiro Hajima, Yeray Santana-Falcón, and Chris D. Jones
Biogeosciences, 21, 411–435, https://doi.org/10.5194/bg-21-411-2024, https://doi.org/10.5194/bg-21-411-2024, 2024
Short summary
Short summary
Carbon cycle feedback metrics are employed to assess phases of positive and negative CO2 emissions. When emissions become negative, we find that the model disagreement in feedback metrics increases more strongly than expected from the assumption that the uncertainties accumulate linearly with time. The geographical patterns of such metrics over land highlight that differences in response between tropical/subtropical and temperate/boreal ecosystems are a major source of model disagreement.
Mana Gharun, Ankit Shekhar, Lukas Hörtnagl, Luana Krebs, Nicola Arriga, Mirco Migliavacca, Marilyn Roland, Bert Gielen, Leonardo Montagnani, Enrico Tomelleri, Ladislav Šigut, Matthias Peichl, Peng Zhao, Marius Schmidt, Thomas Grünwald, Mika Korkiakoski, Annalea Lohila, and Nina Buchmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2964, https://doi.org/10.5194/egusphere-2023-2964, 2024
Short summary
Short summary
Effect of winter warming on forest CO2 fluxes has rarely been investigated. We tested the effect of the warm winter in 2020 on the forest CO2 fluxes across 14 sites in Europe and found that in colder sites net ecosystem productivity (NEP) declined during the warm winter, while in the warmer sites NEP increased. Warming leads to increased respiration fluxes but if not translated into a direct warming of the soil might not enhance productivity, if the soil within the rooting zone remains frozen.
Flora Desmet, Matthias Münnich, and Nicolas Gruber
Biogeosciences, 20, 5151–5175, https://doi.org/10.5194/bg-20-5151-2023, https://doi.org/10.5194/bg-20-5151-2023, 2023
Short summary
Short summary
Ocean acidity extremes in the upper 250 m depth of the northeastern Pacific rapidly increase with atmospheric CO2 rise, which is worrisome for marine organisms that rapidly experience pH levels outside their local environmental conditions. Presented research shows the spatiotemporal heterogeneity in this increase between regions and depths. In particular, the subsurface increase is substantially slowed down by the presence of mesoscale eddies, often not resolved in Earth system models.
Philipp Suessle, Jan Taucher, Silvan Goldenberg, Moritz Baumann, Kristian Spilling, Andrea Noche-Ferreira, Mari Vanharanta, and Ulf Riebesell
EGUsphere, https://doi.org/10.5194/egusphere-2023-2800, https://doi.org/10.5194/egusphere-2023-2800, 2023
Short summary
Short summary
Ocean alkalinity enhancement (OAE) is a negative emission technology which may alter marine communities and the particle export they drive. Here, impacts of carbonate-based OAE on the flux and attenuation of sinking particles in an oligotrophic plankton community are presented. Whilst biological parameters remained unaffected, abiotic carbonate precipitation occurred. Among counteracting OAE’s efficiency, it influenced mineral ballasting and particle sinking velocities, requiring monitoring.
Geneviève W. Elsworth, Nicole S. Lovenduski, Kristen M. Krumhardt, Thomas M. Marchitto, and Sarah Schlunegger
Biogeosciences, 20, 4477–4490, https://doi.org/10.5194/bg-20-4477-2023, https://doi.org/10.5194/bg-20-4477-2023, 2023
Short summary
Short summary
Anthropogenic climate change will influence marine phytoplankton over the coming century. Here, we quantify the influence of anthropogenic climate change on marine phytoplankton internal variability using an Earth system model ensemble and identify a decline in global phytoplankton biomass variance with warming. Our results suggest that climate mitigation efforts that account for marine phytoplankton changes should also consider changes in phytoplankton variance driven by anthropogenic warming.
Olivia Haas, Iain Colin Prentice, and Sandy P. Harrison
Biogeosciences, 20, 3981–3995, https://doi.org/10.5194/bg-20-3981-2023, https://doi.org/10.5194/bg-20-3981-2023, 2023
Short summary
Short summary
We quantify the impact of CO2 and climate on global patterns of burnt area, fire size, and intensity under Last Glacial Maximum (LGM) conditions using three climate scenarios. Climate change alone did not produce the observed LGM reduction in burnt area, but low CO2 did through reducing vegetation productivity. Fire intensity was sensitive to CO2 but strongly affected by changes in atmospheric dryness. Low CO2 caused smaller fires; climate had the opposite effect except in the driest scenario.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, Simon Jones, Andy J. Wiltshire, and Peter M. Cox
Biogeosciences, 20, 3767–3790, https://doi.org/10.5194/bg-20-3767-2023, https://doi.org/10.5194/bg-20-3767-2023, 2023
Short summary
Short summary
This study evaluates soil carbon projections during the 21st century in CMIP6 Earth system models. In general, we find a reduced spread of changes in global soil carbon in CMIP6 compared to the previous CMIP5 generation. The reduced CMIP6 spread arises from an emergent relationship between soil carbon changes due to change in plant productivity and soil carbon changes due to changes in turnover time. We show that this relationship is consistent with false priming under transient climate change.
Claudia Hinrichs, Peter Köhler, Christoph Völker, and Judith Hauck
Biogeosciences, 20, 3717–3735, https://doi.org/10.5194/bg-20-3717-2023, https://doi.org/10.5194/bg-20-3717-2023, 2023
Short summary
Short summary
This study evaluated the alkalinity distribution in 14 climate models and found that most models underestimate alkalinity at the surface and overestimate it in the deeper ocean. It highlights the need for better understanding and quantification of processes driving alkalinity distribution and calcium carbonate dissolution and the importance of accounting for biases in model results when evaluating potential ocean alkalinity enhancement experiments.
Yonghong Zheng, Huanfeng Shen, Rory Abernethy, and Rob Wilson
Biogeosciences, 20, 3481–3490, https://doi.org/10.5194/bg-20-3481-2023, https://doi.org/10.5194/bg-20-3481-2023, 2023
Short summary
Short summary
Investigations in central and western China show that tree ring inverted latewood intensity expresses a strong positive relationship with growing-season temperatures, indicating exciting potential for regions south of 30° N that are traditionally not targeted for temperature reconstructions. Earlywood BI also shows good potential to reconstruct hydroclimate parameters in some humid areas and will enhance ring-width-based hydroclimate reconstructions in the future.
Stefano Potter, Sol Cooperdock, Sander Veraverbeke, Xanthe Walker, Michelle C. Mack, Scott J. Goetz, Jennifer Baltzer, Laura Bourgeau-Chavez, Arden Burrell, Catherine Dieleman, Nancy French, Stijn Hantson, Elizabeth E. Hoy, Liza Jenkins, Jill F. Johnstone, Evan S. Kane, Susan M. Natali, James T. Randerson, Merritt R. Turetsky, Ellen Whitman, Elizabeth Wiggins, and Brendan M. Rogers
Biogeosciences, 20, 2785–2804, https://doi.org/10.5194/bg-20-2785-2023, https://doi.org/10.5194/bg-20-2785-2023, 2023
Short summary
Short summary
Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m resolution. We estimate 2.37 Mha burned annually between 2001–2019 over the domain, emitting 79.3 Tg C per year, with a mean combustion rate of 3.13 kg C m−2. We found larger-fire years were generally associated with greater mean combustion. The burned-area and combustion datasets described here can be used for local- to continental-scale applications of boreal fire science.
V. Rachel Chimuka, Claude-Michel Nzotungicimpaye, and Kirsten Zickfeld
Biogeosciences, 20, 2283–2299, https://doi.org/10.5194/bg-20-2283-2023, https://doi.org/10.5194/bg-20-2283-2023, 2023
Short summary
Short summary
We propose a new method to quantify carbon cycle feedbacks under negative CO2 emissions. Our method isolates the lagged carbon cycle response to preceding positive emissions from the response to negative emissions. Our findings suggest that feedback parameters calculated with the novel approach are larger than those calculated with the conventional approach whereby carbon cycle inertia is not corrected for, with implications for the effectiveness of carbon dioxide removal in reducing CO2 levels.
Marcus Breil, Annabell Weber, and Joaquim G. Pinto
Biogeosciences, 20, 2237–2250, https://doi.org/10.5194/bg-20-2237-2023, https://doi.org/10.5194/bg-20-2237-2023, 2023
Short summary
Short summary
A promising strategy for mitigating burdens of heat extremes in Europe is to replace dark coniferous forests with brighter deciduous forests. The consequence of this would be reduced absorption of solar radiation, which should reduce the intensities of heat periods. In this study, we show that deciduous forests have a certain cooling effect on heat period intensities in Europe. However, the magnitude of the temperature reduction is quite small.
Gesche Blume-Werry, Jonatan Klaminder, Eveline J. Krab, and Sylvain Monteux
Biogeosciences, 20, 1979–1990, https://doi.org/10.5194/bg-20-1979-2023, https://doi.org/10.5194/bg-20-1979-2023, 2023
Short summary
Short summary
Northern soils store a lot of carbon. Most research has focused on how this carbon storage is regulated by cold temperatures. However, it is soil organisms, from minute bacteria to large earthworms, that decompose the organic material. Novel soil organisms from further south could increase decomposition rates more than climate change does and lead to carbon losses. We therefore advocate for including soil organisms when predicting the fate of soil functions in warming northern ecosystems.
Koramanghat Unnikrishnan Jayakrishnan and Govindasamy Bala
Biogeosciences, 20, 1863–1877, https://doi.org/10.5194/bg-20-1863-2023, https://doi.org/10.5194/bg-20-1863-2023, 2023
Short summary
Short summary
Afforestation and reducing fossil fuel emissions are two important mitigation strategies to reduce the amount of global warming. Our work shows that reducing fossil fuel emissions is relatively more effective than afforestation for the same amount of carbon removed from the atmosphere. However, understanding of the processes that govern the biophysical effects of afforestation should be improved before considering our results for climate policy.
Jens Hartmann, Niels Suitner, Carl Lim, Julieta Schneider, Laura Marín-Samper, Javier Arístegui, Phil Renforth, Jan Taucher, and Ulf Riebesell
Biogeosciences, 20, 781–802, https://doi.org/10.5194/bg-20-781-2023, https://doi.org/10.5194/bg-20-781-2023, 2023
Short summary
Short summary
CO2 can be stored in the ocean via increasing alkalinity of ocean water. Alkalinity can be created via dissolution of alkaline materials, like limestone or soda. Presented research studies boundaries for increasing alkalinity in seawater. The best way to increase alkalinity was found using an equilibrated solution, for example as produced from reactors. Adding particles for dissolution into seawater on the other hand produces the risk of losing alkalinity and degassing of CO2 to the atmosphere.
Damian L. Arévalo-Martínez, Amir Haroon, Hermann W. Bange, Ercan Erkul, Marion Jegen, Nils Moosdorf, Jens Schneider von Deimling, Christian Berndt, Michael Ernst Böttcher, Jasper Hoffmann, Volker Liebetrau, Ulf Mallast, Gudrun Massmann, Aaron Micallef, Holly A. Michael, Hendrik Paasche, Wolfgang Rabbel, Isaac Santos, Jan Scholten, Katrin Schwalenberg, Beata Szymczycha, Ariel T. Thomas, Joonas J. Virtasalo, Hannelore Waska, and Bradley A. Weymer
Biogeosciences, 20, 647–662, https://doi.org/10.5194/bg-20-647-2023, https://doi.org/10.5194/bg-20-647-2023, 2023
Short summary
Short summary
Groundwater flows at the land–ocean transition and the extent of freshened groundwater below the seafloor are increasingly relevant in marine sciences, both because they are a highly uncertain term of biogeochemical budgets and due to the emerging interest in the latter as a resource. Here, we discuss our perspectives on future research directions to better understand land–ocean connectivity through groundwater and its potential responses to natural and human-induced environmental changes.
Morgan Sparey, Peter Cox, and Mark S. Williamson
Biogeosciences, 20, 451–488, https://doi.org/10.5194/bg-20-451-2023, https://doi.org/10.5194/bg-20-451-2023, 2023
Short summary
Short summary
Accurate climate models are vital for mitigating climate change; however, projections often disagree. Using Köppen–Geiger bioclimate classifications we show that CMIP6 climate models agree well on the fraction of global land surface that will change classification per degree of global warming. We find that 13 % of land will change climate per degree of warming from 1 to 3 K; thus, stabilising warming at 1.5 rather than 2 K would save over 7.5 million square kilometres from bioclimatic change.
Huanhuan Wang, Chao Yue, and Sebastiaan Luyssaert
Biogeosciences, 20, 75–92, https://doi.org/10.5194/bg-20-75-2023, https://doi.org/10.5194/bg-20-75-2023, 2023
Short summary
Short summary
This study provided a synthesis of three influential methods to quantify afforestation impact on surface temperature. Results showed that actual effect following afforestation was highly dependent on afforestation fraction. When full afforestation is assumed, the actual effect approaches the potential effect. We provided evidence the afforestation faction is a key factor in reconciling different methods and emphasized that it should be considered for surface cooling impacts in policy evaluation.
Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
Biogeosciences, 19, 5435–5448, https://doi.org/10.5194/bg-19-5435-2022, https://doi.org/10.5194/bg-19-5435-2022, 2022
Short summary
Short summary
The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO2 air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.
Julian Gutt, Stefanie Arndt, David Keith Alan Barnes, Horst Bornemann, Thomas Brey, Olaf Eisen, Hauke Flores, Huw Griffiths, Christian Haas, Stefan Hain, Tore Hattermann, Christoph Held, Mario Hoppema, Enrique Isla, Markus Janout, Céline Le Bohec, Heike Link, Felix Christopher Mark, Sebastien Moreau, Scarlett Trimborn, Ilse van Opzeeland, Hans-Otto Pörtner, Fokje Schaafsma, Katharina Teschke, Sandra Tippenhauer, Anton Van de Putte, Mia Wege, Daniel Zitterbart, and Dieter Piepenburg
Biogeosciences, 19, 5313–5342, https://doi.org/10.5194/bg-19-5313-2022, https://doi.org/10.5194/bg-19-5313-2022, 2022
Short summary
Short summary
Long-term ecological observations are key to assess, understand and predict impacts of environmental change on biotas. We present a multidisciplinary framework for such largely lacking investigations in the East Antarctic Southern Ocean, combined with case studies, experimental and modelling work. As climate change is still minor here but is projected to start soon, the timely implementation of this framework provides the unique opportunity to document its ecological impacts from the very onset.
Daniel François, Adina Paytan, Olga Maria Oliveira de Araújo, Ricardo Tadeu Lopes, and Cátia Fernandes Barbosa
Biogeosciences, 19, 5269–5285, https://doi.org/10.5194/bg-19-5269-2022, https://doi.org/10.5194/bg-19-5269-2022, 2022
Short summary
Short summary
Our analysis revealed that under the two most conservative acidification projections foraminifera assemblages did not display considerable changes. However, a significant decrease in species richness was observed when pH decreases to 7.7 pH units, indicating adverse effects under high-acidification scenarios. A micro-CT analysis revealed that calcified tests of Archaias angulatus were of lower density in low pH, suggesting no acclimation capacity for this species.
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
Short summary
Short summary
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.
Laurent Bopp, Olivier Aumont, Lester Kwiatkowski, Corentin Clerc, Léonard Dupont, Christian Ethé, Thomas Gorgues, Roland Séférian, and Alessandro Tagliabue
Biogeosciences, 19, 4267–4285, https://doi.org/10.5194/bg-19-4267-2022, https://doi.org/10.5194/bg-19-4267-2022, 2022
Short summary
Short summary
The impact of anthropogenic climate change on the biological production of phytoplankton in the ocean is a cause for concern because its evolution could affect the response of marine ecosystems to climate change. Here, we identify biological N fixation and its response to future climate change as a key process in shaping the future evolution of marine phytoplankton production. Our results show that further study of how this nitrogen fixation responds to environmental change is essential.
Negar Vakilifard, Richard G. Williams, Philip B. Holden, Katherine Turner, Neil R. Edwards, and David J. Beerling
Biogeosciences, 19, 4249–4265, https://doi.org/10.5194/bg-19-4249-2022, https://doi.org/10.5194/bg-19-4249-2022, 2022
Short summary
Short summary
To remain within the Paris climate agreement, there is an increasing need to develop and implement carbon capture and sequestration techniques. The global climate benefits of implementing negative emission technologies over the next century are assessed using an Earth system model covering a wide range of plausible climate states. In some model realisations, there is continued warming after emissions cease. This continued warming is avoided if negative emissions are incorporated.
Marco Reale, Gianpiero Cossarini, Paolo Lazzari, Tomas Lovato, Giorgio Bolzon, Simona Masina, Cosimo Solidoro, and Stefano Salon
Biogeosciences, 19, 4035–4065, https://doi.org/10.5194/bg-19-4035-2022, https://doi.org/10.5194/bg-19-4035-2022, 2022
Short summary
Short summary
Future projections under the RCP8.5 and RCP4.5 emission scenarios of the Mediterranean Sea biogeochemistry at the end of the 21st century show different levels of decline in nutrients, oxygen and biomasses and an acidification of the water column. The signal intensity is stronger under RCP8.5 and in the eastern Mediterranean. Under RCP4.5, after the second half of the 21st century, biogeochemical variables show a recovery of the values observed at the beginning of the investigated period.
Charly A. Moras, Lennart T. Bach, Tyler Cyronak, Renaud Joannes-Boyau, and Kai G. Schulz
Biogeosciences, 19, 3537–3557, https://doi.org/10.5194/bg-19-3537-2022, https://doi.org/10.5194/bg-19-3537-2022, 2022
Short summary
Short summary
This research presents the first laboratory results of quick and hydrated lime dissolution in natural seawater. These two minerals are of great interest for ocean alkalinity enhancement, a strategy aiming to decrease atmospheric CO2 concentrations. Following the dissolution of these minerals, we identified several hurdles and presented ways to avoid them or completely negate them. Finally, we proceeded to various simulations in today’s oceans to implement the strategy at its highest potential.
Taraka Davies-Barnard, Sönke Zaehle, and Pierre Friedlingstein
Biogeosciences, 19, 3491–3503, https://doi.org/10.5194/bg-19-3491-2022, https://doi.org/10.5194/bg-19-3491-2022, 2022
Short summary
Short summary
Biological nitrogen fixation is the largest natural input of new nitrogen onto land. Earth system models mainly represent global total terrestrial biological nitrogen fixation within observational uncertainties but overestimate tropical fixation. The model range of increase in biological nitrogen fixation in the SSP3-7.0 scenario is 3 % to 87 %. While biological nitrogen fixation is a key source of new nitrogen, its predictive power for net primary productivity in models is limited.
Niel Verbrigghe, Niki I. W. Leblans, Bjarni D. Sigurdsson, Sara Vicca, Chao Fang, Lucia Fuchslueger, Jennifer L. Soong, James T. Weedon, Christopher Poeplau, Cristina Ariza-Carricondo, Michael Bahn, Bertrand Guenet, Per Gundersen, Gunnhildur E. Gunnarsdóttir, Thomas Kätterer, Zhanfeng Liu, Marja Maljanen, Sara Marañón-Jiménez, Kathiravan Meeran, Edda S. Oddsdóttir, Ivika Ostonen, Josep Peñuelas, Andreas Richter, Jordi Sardans, Páll Sigurðsson, Margaret S. Torn, Peter M. Van Bodegom, Erik Verbruggen, Tom W. N. Walker, Håkan Wallander, and Ivan A. Janssens
Biogeosciences, 19, 3381–3393, https://doi.org/10.5194/bg-19-3381-2022, https://doi.org/10.5194/bg-19-3381-2022, 2022
Short summary
Short summary
In subarctic grassland on a geothermal warming gradient, we found large reductions in topsoil carbon stocks, with carbon stocks linearly declining with warming intensity. Most importantly, however, we observed that soil carbon stocks stabilised within 5 years of warming and remained unaffected by warming thereafter, even after > 50 years of warming. Moreover, in contrast to the large topsoil carbon losses, subsoil carbon stocks remained unaffected after > 50 years of soil warming.
Roberto Pilli, Ramdane Alkama, Alessandro Cescatti, Werner A. Kurz, and Giacomo Grassi
Biogeosciences, 19, 3263–3284, https://doi.org/10.5194/bg-19-3263-2022, https://doi.org/10.5194/bg-19-3263-2022, 2022
Short summary
Short summary
To become carbon neutral by 2050, the European Union (EU27) forest C sink should increase to −450 Mt CO2 yr-1. Our study highlights that under current management practices (i.e. excluding any policy scenario) the forest C sink of the EU27 member states and the UK may decrease to about −250 Mt CO2eq yr-1 in 2050. The expected impacts of future climate change, however, add a considerable uncertainty, potentially nearly doubling or halving the sink associated with forest management.
Johnathan Daniel Maxey, Neil David Hartstein, Aazani Mujahid, and Moritz Müller
Biogeosciences, 19, 3131–3150, https://doi.org/10.5194/bg-19-3131-2022, https://doi.org/10.5194/bg-19-3131-2022, 2022
Short summary
Short summary
Deep coastal inlets are important sites for regulating land-based organic pollution before it enters coastal oceans. This study focused on how large climate forces, rainfall, and river flow impact organic loading and oxygen conditions in a coastal inlet in Tasmania. Increases in rainfall were linked to higher organic loading and lower oxygen in basin waters. Finally we observed a significant correlation between the Southern Annular Mode and oxygen concentrations in the system's basin waters.
Cited articles
Amthor, J. S.: Terrestrial higher-plant response to increasing atmospheric
[CO2] in relation to the global carbon cycle, Global Change Biol., 1,
243–274, 1995. a
Arora, V. and Boer, G.: Uncertainties in the 20th century carbon budget
associated with land use change, Global Change Biol., 16, 3327–3348, 2010. a
Arora, V., Boer, G., Christian, J., Curry, C., Denman, K., Zahariev, K., Flato,
G., Scinocca, J., Merryfield, W., and Lee, W.: The effect of terrestrial
photosynthesis down regulation on the twentieth-century carbon budget
simulated with the CCCma Earth System Model, J. Climate, 22,
6066–6088, 2009. a
Arora, V. K., Boer, G. J., Friedlingstein, P., Eby, M., Jones, C. D.,
Christian, J. R., Bonan, G., Bopp, L., Brovkin, V., Cadule, P., Hajima, T., Ilyina, T., Lindsay, K., Tjiputra, J. F., and Wu, T.:
Carbon–concentration and carbon–climate feedbacks in CMIP5 Earth system
models, J. Climate, 26, 5289–5314, 2013. a, b, c
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–-4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a, b, c, d, e, f
Beer, C.: Permafrost sub-grid heterogeneity of soil properties key for 3-D soil
processes and future climate projections, Front. Earth Sci., 4, 81, https://doi.org/10.3389/feart.2016.00081,
2016. a
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–-720, https://doi.org/10.5194/gmd-6-687-2013, 2013. a
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a
Bloom, A. and Williams, M.: CARDAMOM 2001–2010 global carbon Model-Data
Fusion (MDF) analysis, https://doi.org/10.7488/ds/316, 2015. a, b
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., et al.:
Presentation and evaluation of the IPSL-CM6A-LR climate model, J. Adv. Model. Earth Sy., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010, 2020. a
Burke, E. J., Ekici, A., Huang, Y., Chadburn, S. E., Huntingford, C., Ciais, P., Friedlingstein, P., Peng, S., and Krinner, G.: Quantifying uncertainties of permafrost carbon–climate feedbacks, Biogeosciences, 14, 3051–-3066, https://doi.org/10.5194/bg-14-3051-2017, 2017. a
Burke, E. J., Zhang, Y., and Krinner, G.: Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change, The Cryosphere, 14, 3155–-3174, https://doi.org/10.5194/tc-14-3155-2020, 2020. a, b
Canadell, J., Monteiro, P., Costa, M., Cotrim da Cunha, L., Cox, P., Eliseev,
A., Henson, S., Ishii, M., Jaccard, S., Koven, C., Lohila, A., Patra, P.,
Piao, S., Rogelj, J., Syampungani, S., Zaehle, S., and Zickfeld, K.: Global
Carbon and other Biogeochemical Cycles and Feedbacks, Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA, https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter05.pdf (last access: 28 July 2022), 2021. a
CARDAMOM: 2001–2010 global carbon Model-Data Fusion (MDF) analysis, DataShare Edinburgh [data set], https://datashare.ed.ac.uk/handle/10283/875, last access: 14 January 2022.
Carvalhais, N., Forkel, M., Khomik, M., Bellarby, J., Jung, M., Migliavacca,
M., Mu, M., Saatchi, S., Santoro, M., Thurner, M., Weber, U., Ahrens, B., Beer, C., Cescatti, A., Randerson, J. T., and Reichstein, M.: Global covariation
of carbon turnover times with climate in terrestrial ecosystems, Nature, 514,
213, https://doi.org/10.1038/nature13731, 2014. a, b, c
Chadburn, S. E., Burke, E. J., Gallego-Sala, A. V., Smith, N. D., Bret-Harte, M. S., Charman, D. J., Drewer, J., Edgar, C. W., Euskirchen, E. S., Fortuniak, K., Gao, Y., Nakhavali, M., Pawlak, W., Schuur, E. A. G., and Westermann, S.: A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands, Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, 2022. a
Cheruy, F., Ducharne, A., Hourdin, F., Musat, I., Vignon, É., Gastineau,
G., Bastrikov, V., Vuichard, N., Diallo, B., Dufresne, J.-L., Ghattas, J., Grandpeix, J.-Y., Idelkadi, A., Mellul, L., Maignan, F., Ménégoz, M., Ottlé, C., Peylin, P., Servonnat, J., Wang, F., and Zhao, Y.:
Improved near-surface continental climate in IPSL-CM6A-LR by combined
evolutions of atmospheric and land surface physics, J. Adv.
Model. Earth Sy., 12, e2019MS002005, https://doi.org/10.1029/2019MS002005, 2020. a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–-722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a
Copernicus Climate Change Service, E. K.: Copernicus Climate Change Service,
Product User Guide and Specification,
https://datastore.copernicus-climate.eu/documents/satellite-soil-moisture/C3S_312b_Lot4.D3.SM.5-v3.0_202101_Product_User_Guide_Specification_i1.0.pdf (last access: 14 January 2022),
2021. a
Copernicus: Soil moisture gridded data from 1978 to present, Copernicus [data set], https://doi.org/10.24381/cds.d7782f18, 2022. a
Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., and Totterdell, I. J.:
Acceleration of global warming due to carbon-cycle feedbacks in a coupled
climate model, Nature, 408, 184, https://doi.org/10.1038/35041539, 2000. a
Crowther, T. W., Todd-Brown, K. E. O., Rowe, C. W., Wieder, W. R., Carey, J. C., Machmuller, M. B., Snoek, B. L., Fang, S., Zhou, G., Allison, S. D., Blair, J. M., Bridgham, S. D., Burton, A. J., Carrillo, Y., Reich, P. B., Clark, J. S., Classen, A. T., Dijkstra, F. A., Elberling, B., Emmett, B. A., Estiarte, M., Frey, S. D., Guo, J., Harte, J., Jiang, L., Johnson, B. R., Kröel-Dulay, G., Larsen, K. S., Laudon, H., Lavallee, J. M., Luo, Y., Lupascu, M., Ma, L. N., Marhan, S., Michelsen, A., Mohan, J., Niu, S., Pendall, E., Peñuelas, J., Pfeifer-Meister, L., Poll, C., Reinsch, S., Reynolds, L. L., Schmidt, I. K., Sistla, S., Sokol, N. W., Templer, P. H., Treseder, K. K., Welker, J. M., and Bradford, M. A.:
Quantifying global soil carbon losses in response to warming, Nature, 540,
104, https://doi.org/10.1038/nature20150, 2016. a
Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich,
M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G., Oleson, K. W., Schlosser, C. A., and Yang, Z.-L.: The
common land model, B. Am. Meteorol. Soc., 84,
1013–1024, 2003. a
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D., DuVivier, A.,
Edwards, J., Emmons, L., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The community earth system model version 2 (CESM2), J. Adv.
Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a
Davidson, E. A. and Janssens, I. A.: Temperature sensitivity of soil carbon
decomposition and feedbacks to climate change, Nature, 440, 165, https://doi.org/10.1038/nature04514, 2006. a, b
Davies-Barnard, T., Meyerholt, J., Zaehle, S., Friedlingstein, P., Brovkin, V., Fan, Y., Fisher, R. A., Jones, C. D., Lee, H., Peano, D., Smith, B., Wårlind, D., and Wiltshire, A. J.: Nitrogen cycling in CMIP6 land surface models: progress and limitations, Biogeosciences, 17, 5129–-5148, https://doi.org/10.5194/bg-17-5129-2020, 2020. a
Del Grosso, S., Parton, W., Mosier, A., Holland, E., Pendall, E., Schimel, D.,
and Ojima, D.: Modeling soil CO2 emissions from ecosystems, Biogeochemistry,
73, 71–91, 2005. a
Delire, C., Séférian, R., Decharme, B., Alkama, R., Calvet, J.-C.,
Carrer, D., Gibelin, A.-L., Joetzjer, E., Morel, X., Rocher, M., and Diane Tzanos, D.: The
global land carbon cycle simulated with ISBA-CTRIP: Improvements over the
last decade, J. Adv. Model. Earth Sy., 12,
e2019MS001886, https://doi.org/10.1029/2019MS001886, 2020. a
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L.,
Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI Soil Moisture
for improved Earth system understanding: State-of-the art and future
directions, Remote Sens. Environ., 203, 185–215, 2017. a
Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont, O., Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., de Noblet, N., Duvel, J.-P., Ethé, C., Fairhead, L., Fichefet, T., Flavoni, S., Friedlingstein, P., Grandpeix, J.-Y., Guez, L., Guilyardi, E., Hauglustaine, D., Hourdin, F., Idelkadi, A., Ghattas, J., Joussaume, S., Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, A., Lefebvre, M.-P., Lefevre, F., Levy, C., Li, Z. X., Lloyd, J., Lott, F., Madec, G., Mancip, M., Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J., Musat, I., Parouty, S., Polcher, J., Rio, C., Schulz, M., Swingedouw, D., Szopa, S., Talandier, C., Terray, P., Viovy, N., and Vuichard, N.: Climate change
projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5,
Clim. Dynam., 40, 2123–2165, 2013. a
Dunne, J. P., Horowitz, L. W., Adcroft, A. J., Ginoux, P., Held, I. M., John, J. G., Krasting, J. P., Malyshev, S., Naik, V., Paulot, F., Shevliakova, E., Stock, C. A., Zadeh, N., Balaji, V., Blanton, C., Dunne, K. A., Dupuis, C., Durachta, J., Dussin, R., Gauthier, P. P. G., Griffies, S. M., Guo, H., Hallberg, R. W., Harrison, M., He, J., Hurlin, W., McHugh, C., Menzel, R., Milly, P. C. D., Nikonov, S., Paynter, D. J., Ploshay, J., Radhakrishnan, A., Rand, K., Reichl, B. G., Robinson, T., Schwarzkopf, D. M., Sentman, L. T., Underwood, S., Vahlenkamp, H., Winton, M., Wittenberg, A. T., Wyman B., Zeng, Y., and Zhao, M.: The GFDL Earth System Model
version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation
characteristics, J. Adv. Model. Earth Sy., 12,
e2019MS002015, https://doi.org/10.1029/2019MS002015, 2020. a
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W.,
Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J., Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman, L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., and Zadeh, N.: GFDL’s ESM2 global coupled climate–carbon earth system models.
Part I: Physical formulation and baseline simulation characteristics, J. Climate, 25, 6646–6665, 2012. a
Dunne, J. P., John, J. G., Shevliakova, E., Stouffer, R. J., Krasting, J. P.,
Malyshev, S. L., Milly, P., Sentman, L. T., Adcroft, A. J., Cooke, W., Dunne, K. A., Griffies, S. M., Hallberg, R. W., Harrison, M. J., Levy, H., Wittenberg, A. T., Phillips, P. J., and Zadeh, N.: GFDL’s ESM2 global coupled climate–carbon earth system models.
Part II: carbon system formulation and baseline simulation characteristics,
J. Climate, 26, 2247–2267, 2013. a
ESGF: WCRP Coupled Model Intercomparison Project (Phase 5), CMIP5 [data set], https://esgf-node.llnl.gov/search/cmip5/ (last access: 12 April 2022), 2022a.
ESGF: WCRP Coupled Model Intercomparison Project (Phase 6), CMIP [data set], https://esgf-node.llnl.gov/search/cmip6/ (last access: 12 April 2022), 2022b.
Eswaran, H., Van Den Berg, E., and Reich, P.: Organic carbon in soils of the
world, Soil Sci. Soc. Am. J., 57, 192–194, 1993. a
Evans, C., Peacock, M., Baird, A., et al.: Overriding water table
control on managed peatland greenhouse gas emissions, Nature, 593, 548–552,
2021. a
Exbrayat, J.-F., Pitman, A. J., Zhang, Q., Abramowitz, G., and Wang, Y.-P.: Examining soil carbon uncertainty in a global model: response of microbial decomposition to temperature, moisture and nutrient limitation, Biogeosciences, 10, 7095–-7108, https://doi.org/10.5194/bg-10-7095-2013, 2013. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–-1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b
FAO, I. and ISRIC, I.: JRC: Harmonized World Soil Database (version 1.2), FAO,
Rome, Italy and IIASA, Laxenburg, Austria, https://doi.org/10.3334/ORNLDAAC/1247, 2012 (data available at: https://github.com/rebeccamayvarney/CMIP_soilcarbon_evaluation, last access: 14 January 2022). a, b, c, d
Friedlingstein, P., Fung, I., Holland, E., John, J., Brasseur, G., Erickson,
D., and Schimel, D.: On the contribution of CO2 fertilization to the missing
biospheric sink, Global Biogeochem. Cy., 9, 541–556, 1995. a
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V.,
Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur, R., Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.: Climate–carbon cycle
feedback analysis: results from the C4MIP model intercomparison, J.
Clim., 19, 3337–3353, 2006. a, b
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Bakker, D. C. E., Hauck, J., Le Quéré, C., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Bates, N. R., Becker, M., Bellouin, N., Bopp, L., Chau, T. T. T., Chevallier, F., Chini, L. P., Cronin, M., Currie, K. I., Decharme, B., Djeutchouang, L. M., Dou, X., Evans, W., Feely, R. A., Feng, L., Gasser, T., Gilfillan, D., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Luijkx, I. T., Jain, A., Jones, S. D., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lienert, S., Liu, J., Marland, G., McGuire, P. C., Melton, J. R., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Niwa, Y., Ono, T., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Schwingshackl, C., Séférian, R., Sutton, A. J., Sweeney, C., Tanhua, T., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F., van der Werf, G. R., Vuichard, N., Wada, C., Wanninkhof, R., Watson, A. J., Willis, D., Wiltshire, A. J., Yuan, W., Yue, C., Yue, X., Zaehle, S., and Zeng, J.: Global Carbon Budget 2021, Earth Syst. Sci. Data, 14, 1917–-2005, https://doi.org/10.5194/essd-14-1917-2022, 2022. a, b
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C.,
Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z.-L., and Zhang, M.: The community climate system model version 4, J. Climate, 24,
4973–4991, 2011. a
Georgiou, K., Malhotra, A., Wieder, W. R., Ennis, J. H., Hartman, M. D.,
Sulman, B. N., Berhe, A. A., Grandy, A. S., Kyker-Snowman, E., Lajtha, K., Moore, J. A. M., Pierson, D., and Jackson, R. B.: Divergent controls of soil organic carbon between observations and
process-based models, Biogeochemistry, 156, 5–17, 2021. a
Goll, D. S., Brovkin, V., Liski, J., Raddatz, T., Thum, T., and Todd-Brown,
K. E.: Strong dependence of CO2 emissions from anthropogenic land cover
change on initial land cover and soil carbon parametrization, Global
Biogeochem. Cy., 29, 1511–1523, 2015. a
Goll, D. S., Winkler, A. J., Raddatz, T., Dong, N., Prentice, I. C., Ciais, P., and Brovkin, V.: Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10), Geosci. Model Dev., 10, 2009–-2030, https://doi.org/10.5194/gmd-10-2009-2017, 2017. a
Gruber, A., Dorigo, W. A., Crow, W., and Wagner, W.: Triple collocation-based
merging of satellite soil moisture retrievals, IEEE T. Geosci. Remote, 55, 6780–6792, 2017. a
Guimberteau, M., Zhu, D., Maignan, F., Huang, Y., Yue, C., Dantec-Nédélec, S., Ottlé, C., Jornet-Puig, A., Bastos, A., Laurent, P., Goll, D., Bowring, S., Chang, J., Guenet, B., Tifafi, M., Peng, S., Krinner, G., Ducharne, A., Wang, F., Wang, T., Wang, X., Wang, Y., Yin, Z., Lauerwald, R., Joetzjer, E., Qiu, C., Kim, H., and Ciais, P.: ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation, Geosci. Model Dev., 11, 121–-163, https://doi.org/10.5194/gmd-11-121-2018, 2018. a
Hajima, T., Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Abe, M., Ohgaito, R., Ito, A., Yamazaki, D., Okajima, H., Ito, A., Takata, K., Ogochi, K., Watanabe, S., and Kawamiya, M.: Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks, Geosci. Model Dev., 13, 2197–-2244, https://doi.org/10.5194/gmd-13-2197-2020, 2020. a
Harper, A. B., Wiltshire, A. J., Cox, P. M., Friedlingstein, P., Jones, C. D., Mercado, L. M., Sitch, S., Williams, K., and Duran-Rojas, C.: Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types, Geosci. Model Dev., 11, 2857–-2873, https://doi.org/10.5194/gmd-11-2857-2018, 2018. a
HARVARD dataverse: Soil carbon profile data from paired land use comparisons, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/QQQM8V, 2022.
Haverd, V., Smith, B., Nieradzik, L., Briggs, P. R., Woodgate, W., Trudinger, C. M., Canadell, J. G., and Cuntz, M.: A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis, Geosci. Model Dev., 11, 2995–-3026, https://doi.org/10.5194/gmd-11-2995-2018, 2018. a
Hugelius, G., Tarnocai, C., Broll, G., Canadell, J. G., Kuhry, P., and Swanson, D. K.: The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions, Earth Syst. Sci. Data, 5, 3–13, https://doi.org/10.5194/essd-5-3-2013, 2013 (data available at: https://github.com/rebeccamayvarney/CMIP_soilcarbon_evaluation, last access: 14 January 2022). a, b, c, d
Hugelius, G., Loisel, J., Chadburn, S., Jackson, R. B., Jones, M., MacDonald,
G., Marushchak, M., Olefeldt, D., Packalen, M., Siewert, M. B., Treat, C., Turetsky, M., Voigt, C., and Yu, Z.: Large
stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw,
P. Natl. Acad. Sci. USA, 117, 20438–20446, 2020. a
IGBP: Global Gridded Surfaces of Selected Soil Characteristics
(IGBP-DIS), DAAC [data set],
https://doi.org/10.3334/ORNLDAAC/569, 2000. a, b, c
IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2391 pp., 2021. a
ISRIC World Soil Information Service (WoSIS): WISE Soil Property Databases, ISRIC [data set], https://www.isric.org/explore/wise-databases, last access: 14 January 2022. a
Ito, A., Hajima, T., Lawrence, D. M., Brovkin, V., Delire, C., Guenet, B.,
Jones, C. D., Malyshev, S., Materia, S., McDermid, S. P., Peano, D., Pongratz, J., Robertson, E., Shevliakova, E., Vuichard, N., Wårlind, D., Wiltshire, A., and Ziehn, T.: Soil carbon
sequestration simulated in CMIP6-LUMIP models: implications for climatic
mitigation, Environ. Res. Lett., 15, 124061, https://doi.org/10.1088/1748-9326/abc912, 2020. a, b, c
Iversen, T., Bentsen, M., Bethke, I., Debernard, J. B., Kirkevåg, A., Seland, Ø., Drange, H., Kristjansson, J. E., Medhaug, I., Sand, M., and Seierstad, I. A.: The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections, Geosci. Model Dev., 6, 389–-415, https://doi.org/10.5194/gmd-6-389-2013, 2013. a
Ji, D., Wang, L., Feng, J., Wu, Q., Cheng, H., Zhang, Q., Yang, J., Dong, W., Dai, Y., Gong, D., Zhang, R.-H., Wang, X., Liu, J., Moore, J. C., Chen, D., and Zhou, M.: Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1, Geosci. Model Dev., 7, 2039-–2064, https://doi.org/10.5194/gmd-7-2039-2014, 2014. a, b
Ji, J., Huang, M., and Li, K.: Prediction of carbon exchanges between China
terrestrial ecosystem and atmosphere in 21st century, Sci. China Ser. D, 51, 885–898, 2008. a
Jobbágy, E. G. and Jackson, R. B.: The vertical distribution of soil
organic carbon and its relation to climate and vegetation, Ecol.
Appl., 10, 423–436, 2000. a
Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S., Knight, J., Liddicoat, S., O'Connor, F. M., Andres, R. J., Bell, C., Boo, K.-O., Bozzo, A., Butchart, N., Cadule, P., Corbin, K. D., Doutriaux-Boucher, M., Friedlingstein, P., Gornall, J., Gray, L., Halloran, P. R., Hurtt, G., Ingram, W. J., Lamarque, J.-F., Law, R. M., Meinshausen, M., Osprey, S., Palin, E. J., Parsons Chini, L., Raddatz, T., Sanderson, M. G., Sellar, A. A., Schurer, A., Valdes, P., Wood, N., Woodward, S., Yoshioka, M., and Zerroukat, M.: The HadGEM2-ES implementation of CMIP5 centennial simulations, Geosci. Model Dev., 4, 543–-570, https://doi.org/10.5194/gmd-4-543-2011, 2011. a
Kimball, B., Mauney, J., Nakayama, F., and Idso, S.: Effects of increasing
atmospheric CO2 on vegetation, Vegetatio, 104, 65–75, 1993. a
Knorr, W.: Annual and interannual CO2 exchanges of the terrestrial biosphere:
Process-based simulations and uncertainties, Global Ecol. Biogeogr.,
9, 225–252, 2000. a
Koster, R. D., Guo, Z., Yang, R., Dirmeyer, P. A., Mitchell, K., and Puma,
M. J.: On the nature of soil moisture in land surface models, J. Climate, 22, 4322–4335, 2009. a
Koven, C. D., Riley, W. J., Subin, Z. M., Tang, J. Y., Torn, M. S., Collins, W. D., Bonan, G. B., Lawrence, D. M., and Swenson, S. C.: The effect of vertically resolved soil biogeochemistry and alternate soil C and N models on C dynamics of CLM4, Biogeosciences, 10, 7109–-7131, https://doi.org/10.5194/bg-10-7109-2013, 2013 a
Koven, C. D., Chambers, J. Q., Georgiou, K., Knox, R., Negron-Juarez, R., Riley, W. J., Arora, V. K., Brovkin, V., Friedlingstein, P., and Jones, C. D.: Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models, Biogeosciences, 12, 5211–-5228, https://doi.org/10.5194/bg-12-5211-2015, 2015. a, b, c, d
Koven, C. D., Hugelius, G., Lawrence, D. M., and Wieder, W. R.: Higher
climatological temperature sensitivity of soil carbon in cold than warm
climates, Nat. Clim. Change, 7, 817, https://doi.org/10.1038/nclimate3421, 2017. a, b, c
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J.,
Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic
global vegetation model for studies of the coupled atmosphere-biosphere
system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005. a
Land-Atmosphere Interaction Research Group at Sun Yat-sen University: Global Soil Dataset [data set], http://globalchange.bnu.edu.cn/research/soilw, last access: 14 January 2022.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson,
S. C., Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S., Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements and functional and structural advances
in version 4 of the Community Land Model, J. Adv. Model. Earth Sy., 3, M03001, https://doi.org/10.1029/2011MS00045, 2011. a, b
Liu, Y., Dorigo, W. A., Parinussa, R., de Jeu, R. A., Wagner, W., McCabe,
M. F., Evans, J., and Van Dijk, A.: Trend-preserving blending of passive and
active microwave soil moisture retrievals, Remote Sens. Environ.,
123, 280–297, 2012. a
Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425–-436, https://doi.org/10.5194/hess-15-425-2011, 2011. a
Lloyd, J. and Taylor, J.: On the temperature dependence of soil respiration,
Funct. Ecol., 8, 315–323, https://doi.org/10.2307/2389824, 1994. a
Mauritsen, T., Bader, J., Becker, T., et al.: Developments in the
MPI-M Earth System Model version 1.2 (MPI-ESM1. 2) and its response to
increasing CO2, J. Adv. Model. Earth Sy., 11, 998–1038,
2019. a
Meehl, G. A., Boer, G. J., Covey, C., Latif, M., and Stouffer, R. J.: The
coupled model intercomparison project (CMIP), B. Am.
Meteorol. Soc., 81, 313–318, 2000. a
Meehl, G. A., Moss, R., Taylor, K. E., Eyring, V., Stouffer, R. J., Bony, S.,
and Stevens, B.: Climate model intercomparisons: Preparing for the next
phase, Eos T. Am. Geophys. Un., 95, 77–78, 2014. a
Melton, J. R., Arora, V. K., Wisernig-Cojoc, E., Seiler, C., Fortier, M., Chan, E., and Teckentrup, L.: CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance, Geosci. Model Dev., 13, 2825–-2850, https://doi.org/10.5194/gmd-13-2825-2020, 2020. a
Met Office: Iris: A Python package for analysing and visualising
meteorological and oceanographic data sets, Exeter, Devon, v1.2 edn.,
http://scitools.org.uk/ (last access: 14 January 2022), 2010–2013. a
NASA: MODIS, MODIS Gross Primary Production(GPP)/Net Primary Production (NPP) [data set] https://modis.gsfc.nasa.gov/data/dataprod/mod17.php, last access: 14 January 2022.
NCAR: The WFDEI Meteorological Forcing Data, Research Data Archive [data set], https://rda.ucar.edu/datasets/ds314.2/, last access: 14 January 2022.
Nishina, K., Ito, A., Beerling, D. J., Cadule, P., Ciais, P., Clark, D. B., Falloon, P., Friend, A. D., Kahana, R., Kato, E., Keribin, R., Lucht, W., Lomas, M., Rademacher, T. T., Pavlick, R., Schaphoff, S., Vuichard, N., Warszawaski, L., and Yokohata, T.: Quantifying uncertainties in soil carbon responses to changes in global mean temperature and precipitation, Earth Syst. Dynam., 5, 197–-209, https://doi.org/10.5194/esd-5-197-2014, 2014. a
ORNL-DAAC Oak Ridge National Laboratory: Global Gridded Surfaces of Selected Soil Characteristics (IGBP-DIS), ORNL-DAAC [data set], https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=569, last access: 14 January 2022.
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., Ciais, P., Jackson, R. B., Pacala, S. W., McGuire, A. D., Piao, S., Rautiainen, A., Sitch, S., Hayes, D.: A
large and persistent carbon sink in the world’s forests, Science, 333,
988–993, 2011. a
Post, W. M., Emanuel, W. R., Zinke, P. J., and Stangenberger, A. G.: Soil
carbon pools and world life zones, Nature, 298, 156–159, 1982. a
Raddatz, T., Reick, C., Knorr, W., Kattge, J., Roeckner, E., Schnur, R.,
Schnitzler, K.-G., Wetzel, P., and Jungclaus, J.: Will the tropical land
biosphere dominate the climate–carbon cycle feedback during the twenty-first
century?, Clim. Dynam., 29, 565–574, 2007. a
Ran, Y., Li, X., Cheng, G., Che, J., Aalto, J., Karjalainen, O., Hjort, J., Luoto, M., Jin, H., Obu, J., Hori, M., Yu, Q., and Chang, X.: New high-resolution estimates of the permafrost thermal state and hydrothermal conditions over the Northern Hemisphere, Earth Syst. Sci. Data, 14, 865–-884, https://doi.org/10.5194/essd-14-865-2022, 2022. a
Sato, H., Itoh, A., and Kohyama, T.: SEIB–DGVM: A new Dynamic Global
Vegetation Model using a spatially explicit individual-based approach,
Ecol. Model., 200, 279–307, 2007. a
Schmidt, G. A., Kelley, M., Nazarenko, L., et al.: Configuration
and assessment of the GISS ModelE2 contributions to the CMIP5 archive,
J. Adv. Model. Earth Sy., 6, 141–184, 2014. a
Schuur, E. A., McGuire, A. D., Schädel, C., Grosse, G., Harden, J. W.,
Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M., Natali, S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky ,M. R., Treat, C. C., and Vonk, J. E.:
Climate change and the permafrost carbon feedback, Nature, 520, 171–179,
2015. a
Séférian, R., Nabat, P., Michou, M., et al.:
Evaluation of CNRM earth system model, CNRM-ESM2-1: Role of earth system
processes in present-day and future climate, J. Adv. Model.
Earth Sy., 11, 4182–4227, 2019. a
Seiler, C., Melton, J. R., Arora, V. K., and Wang, L.: CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 2: Global benchmarking, Geosci. Model Dev., 14, 2371–-2417, https://doi.org/10.5194/gmd-14-2371-2021, 2021. a
Seland, Ø., Bentsen, M., Olivié, D., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y.-C., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations, Geosci. Model Dev., 13, 6165–-6200, https://doi.org/10.5194/gmd-13-6165-2020, 2020. a
Sellar, A. A., Walton, J., Jones, C. G., et al.:
Implementation of UK Earth system models for CMIP6, J. Adv. Model. Earth Sy., 12, e2019MS001946, https://doi.org/10.1029/2019MS001946, 2020. a
Shevliakova, E., Pacala, S. W., Malyshev, S., Hurtt, G. C., Milly, P.,
Caspersen, J. P., Sentman, L. T., Fisk, J. P., Wirth, C., and Crevoisier, C.:
Carbon cycling under 300 years of land use change: Importance of the
secondary vegetation sink, Global Biogeochem. Cy., 23, GB2022, https://doi.org/10.1029/2007GB003176, 2009. a, b
Sombroek, W. G., Nachtergaele, F. O., and Hebel, A.: Amounts, dynamics and
sequestering of carbon in tropical and subtropical soils, Ambio, Journal of
the Human Environment, Research and Management, Sweden, 22, 417–426, 1993. a
Song, X., Wang, D.-Y., Li, F., and Zeng, X.-D.: Evaluating the performance of
CMIP6 Earth system models in simulating global vegetation structure and
distribution, Advances in Climate Change Research, 12, 584–595, 2021. a
Sulman, B. N., Salmon, V. G., Iversen, C. M., Breen, A. L., Yuan, F., and
Thornton, P. E.: Integrating Arctic Plant Functional Types in a Land Surface
Model Using Above-and Belowground Field Observations, J. Adv.
Model. Earth Sy., 13, e2020MS002396, https://doi.org/10.1029/2020MS002396, 2021. a
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–-4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019. a
Tarnocai, C., Canadell, J., Schuur, E. A., Kuhry, P., Mazhitova, G., and Zimov,
S.: Soil organic carbon pools in the northern circumpolar permafrost region,
Global Biogeochem. Cy., 23, GB2023, https://doi.org/10.1029/2008GB003327, 2009. a
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, 2001. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the
experiment design, B. Am. Meteorol. Soci., 93,
485–498, 2012. a
Todd-Brown, K. E. O., Randerson, J. T., Post, W. M., Hoffman, F. M., Tarnocai, C., Schuur, E. A. G., and Allison, S. D.: Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations, Biogeosciences, 10, 1717–-1736, https://doi.org/10.5194/bg-10-1717-2013, 2013. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t
Trudinger, C. M., Haverd, V., Briggs, P. R., and Canadell, J. G.: Interannual variability in Australia's terrestrial carbon cycle constrained by multiple observation types, Biogeosciences, 13, 6363–-6383, https://doi.org/10.5194/bg-13-6363-2016, 2016. a
UNFCCC: Adoption of The Paris AgreementFCCC/CP/2015/L.9/Rev.1,
http://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf (last access: 14 January 2022),
2015. a
Waddington, J., Morris, P., Kettridge, N., Granath, G., Thompson, D., and
Moore, P.: Hydrological feedbacks in northern peatlands, Ecohydrology, 8,
113–127, 2015. a
Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E., and
Ertl, M.: Fusion of active and passive microwave observations to
create an essential climate variable data record on soil moisture, ISPRS
Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(ISPRS Annals), 7, 315–321, 2012. a
Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H., Nozawa, T., Kawase, H., Abe, M., Yokohata, T., Ise, T., Sato, H., Kato, E., Takata, K., Emori, S., and Kawamiya, M.: MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments, Geosci. Model Dev., 4, 845–-872, https://doi.org/10.5194/gmd-4-845-2011, 2011. a
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo,
P.: The WFDEI meteorological forcing data set: WATCH Forcing Data methodology
applied to ERA-Interim reanalysis data, Water Resour. Res., 50,
7505–7514, 2014. a
Wiltshire, A. J., Burke, E. J., Chadburn, S. E., Jones, C. D., Cox, P. M., Davies-Barnard, T., Friedlingstein, P., Harper, A. B., Liddicoat, S., Sitch, S., and Zaehle, S.: JULES-CN: a coupled terrestrial carbon–nitrogen scheme (JULES vn5.1), Geosci. Model Dev., 14, 2161–-2186, https://doi.org/10.5194/gmd-14-2161-2021, 2021. a, b
Witzgall, K., Vidal, A., Schubert, D. I., Höschen, C., Schweizer, S. A.,
Buegger, F., Pouteau, V., Chenu, C., and Mueller, C. W.: Particulate organic
matter as a functional soil component for persistent soil organic carbon,
Nat. Commun., 12, 1–10, 2021. a
Wu, D., Piao, S., Liu, Y., Ciais, P., and Yao, Y.: Evaluation of CMIP5 earth
system models for the spatial patterns of biomass and soil carbon turnover
times and their linkage with climate, J. Climate, 31, 5947–5960,
2018. a
Wu, T., Lu, Y., Fang, Y., Xin, X., Li, L., Li, W., Jie, W., Zhang, J., Liu, Y., Zhang, L., Zhang, F., Zhang, Y., Wu, F., Li, J., Chu, M., Wang, Z., Shi, X., Liu, X., Wei, M., Huang, A., Zhang, Y., and Liu, X.: The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6 , Geosci. Model Dev., 12, 1573–-1600, https://doi.org/10.5194/gmd-12-1573-2019, 2019. a
Yue, X. and Unger, N.: The Yale Interactive terrestrial Biosphere model version 1.0: description, evaluation and implementation into NASA GISS ModelE2, Geosci. Model Dev., 8, 2399–-2417, https://doi.org/10.5194/gmd-8-2399-2015, 2015. a
Zhang, Q., Wang, Y.-P., Matear, R., Pitman, A., and Dai, Y.: Nitrogen and
phosphorous limitations significantly reduce future allowable CO2 emissions,
Geophys. Res. Lett., 41, 632–637, 2014. a
Zhao, M., Golaz, J.-C., Held, I., et al.: The GFDL global atmosphere and land
model AM4. 0/LM4. 0: 2. Model description, sensitivity studies, and tuning
strategies, J. Adv. Model. Earth Sy., 10, 735–769,
2018. a
Zhu, D., Peng, S., Ciais, P., Zech, R., Krinner, G., Zimov, S., and Grosse, G.:
Simulating soil organic carbon in yedoma deposits during the Last Glacial
Maximum in a land surface model, Geophys. Res. Lett., 43,
5133–5142, 2016. a
Ziehn, T., Chamberlain, M. A., Law, R. M., Lenton, A., Bodman, R. W., Dix, M.,
Stevens, L., Wang, Y.-P., and Srbinovsky, J.: The Australian Earth System
Model: ACCESS-ESM1. 5, Journal of Southern Hemisphere Earth Systems Science,
70, 193–214, 2020. a
Zimov, S. A., Schuur, E. A., and Chapin III, F. S.: Permafrost and the global
carbon budget, Science (Washington), 312, 1612–1613, 2006. a
Download
- Article
(18664 KB) - Full-text XML
Short summary
Soil carbon is the Earth’s largest terrestrial carbon store, and the response to climate change represents one of the key uncertainties in obtaining accurate global carbon budgets required to successfully militate against climate change. The ability of climate models to simulate present-day soil carbon is therefore vital. This study assesses soil carbon simulation in the latest ensemble of models which allows key areas for future model development to be identified.
Soil carbon is the Earth’s largest terrestrial carbon store, and the response to climate...
Altmetrics
Final-revised paper
Preprint