Articles | Volume 14, issue 3
https://doi.org/10.5194/esd-14-549-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-549-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 May 2023
Research article |
| 05 May 2023
| 05 May 2023
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Lina Teckentrup
CORRESPONDING AUTHOR
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Martin G. De Kauwe
School of Biological Sciences, University of Bristol, Bristol, UK
Gab Abramowitz
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Andrew J. Pitman
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Anna M. Ukkola
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Sanaa Hobeichi
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Bastien François
Laboratoire des Sciences du Climat et l'Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
Benjamin Smith
Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
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J. Cale Baguley, Tristin Quaife, Lucy Rowland, Patrick Meir, Michael C. Bell, Manon E. B. Sabot, and Martin G. De Kauwe
EGUsphere, https://doi.org/10.5194/egusphere-2026-4729, https://doi.org/10.5194/egusphere-2026-4729, 2026
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Drought can affect trees both immediately and for months or years afterwards. To improve predictions of how forests respond to drought, we added new representations of how trees regulate water loss and how drought can leave lasting damage to the movement of water within trees in a widely used model. When applied to a 2002 drought in the United Kingdom, the improved model better captured tree responses and suggested that the effects of drought were small in an oak woodland in the following year.
Xueyan Cheng, Chunhui Zhan, Martin G. De Kauwe, Anke Hildebrandt, and Rene Orth
Biogeosciences, 23, 5117–5131, https://doi.org/10.5194/bg-23-5117-2026, https://doi.org/10.5194/bg-23-5117-2026, 2026
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Using long-term satellite greenness data and a machine-learning attribution approach, we assessed vegetation responses to wet and dry soil moisture extremes and identified their dominant drivers. Dry extremes caused widespread negative greenness anomalies mainly controlled by pre-extreme conditions and seasonal timing, while wet extremes showed more heterogeneous responses additionally shaped by climate and topography, highlighting contrasting ecosystem sensitivity to hydrological extremes.
Prashant Paudel, Stefan Olin, Mark Tjoelker, Mikael Pontarp, Daniel Metcalfe, and Benjamin Smith
Biogeosciences, 23, 4999–5018, https://doi.org/10.5194/bg-23-4999-2026, https://doi.org/10.5194/bg-23-4999-2026, 2026
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We used computer simulations to study how vegetation changes from low to high elevations in the Himalayas. We found that competition between plants is more important in warm lowlands, while cold conditions limit plant growth at high elevations. These differences influence plant diversity, vegetation structure, and the amount of plant growth across mountain landscapes, showing how climate and plant strategies together shape ecosystems.
Joséphine Schmutz, Mathieu Vrac, Bastien François, and Burak Bulut
Nat. Hazards Earth Syst. Sci., 26, 881–900, https://doi.org/10.5194/nhess-26-881-2026, https://doi.org/10.5194/nhess-26-881-2026, 2026
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In recent years, Europe has faced severe hot and dry events affecting biodiversity, agriculture, and health. Understanding past significant variation in their occurrence is key for adaptation. This paper identifies emerging hotspots in Europe and North Africa. Since the 1970s, the Iberian Peninsula, Maghreb, and Central Europe have seen more frequent events, driven by rising temperature maxima, while Eastern Europe has experienced a decline due to changes in drought.
Georgina Falster, Gab Abramowitz, Sanaa Hobeichi, Catherine Hughes, Pauline Treble, Nerilie J. Abram, Michael I. Bird, Alexandre Cauquoin, Bronwyn Dixon, Russell Drysdale, Chenhui Jin, Niels Munksgaard, Bernadette Proemse, Jonathan J. Tyler, Martin Werner, and Carol V. Tadros
Hydrol. Earth Syst. Sci., 30, 289–315, https://doi.org/10.5194/hess-30-289-2026, https://doi.org/10.5194/hess-30-289-2026, 2026
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We used a random forest approach to produce estimates of monthly precipitation stable isotope variability from 1962–2023, at high resolution across the entire Australian continent. Comprehensive skill and sensitivity testing shows that our random forest models skilfully predict precipitation isotope values in places and times that observations are not available. We make all outputs freely available, facilitating use in fields from ecology and hydrology to archaeology and forensic science.
Jon Cranko Page, Martin G. De Kauwe, Andy J. Pitman, Isaac R. Towers, Gabriele Arduini, Martin J. Best, Craig R. Ferguson, Jürgen Knauer, Hyungjun Kim, David M. Lawrence, Tomoko Nitta, Keith W. Oleson, Catherine Ottlé, Anna Ukkola, Nicholas Vuichard, Xiaoni Wang-Faivre, and Gab Abramowitz
Biogeosciences, 23, 263–282, https://doi.org/10.5194/bg-23-263-2026, https://doi.org/10.5194/bg-23-263-2026, 2026
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This paper used a large dataset of observations, machine learning predictions, and computer model simulations to test how well land surface models represent the water, energy, and carbon cycles. We found that the models work well under "normal" weather but do not meet performance expectations during coinciding extreme conditions. Since these extremes are relatively rare, targeted model improvements could deliver major performance gains.
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, Philippe Ciais, and Daniel S. Goll
Biogeosciences, 22, 7845–7863, https://doi.org/10.5194/bg-22-7845-2025, https://doi.org/10.5194/bg-22-7845-2025, 2025
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Accurate estimates of global soil organic carbon (SOC) content and its spatial pattern are critical for future climate change mitigation. However, the most advanced process-based SOC models struggle to do this task. Here we apply multiple explainable machine learning methods to identify missing variables and misrepresented relationships between environmental factors and SOC in these models, offering new insights to guide model development for more reliable SOC predictions.
Matthew O. Grant, Anna M. Ukkola, Elisabeth Vogel, Sanaa Hobeichi, Andy J. Pitman, Alex Raymond Borowiak, and Keirnan Fowler
Hydrol. Earth Syst. Sci., 29, 5555–5573, https://doi.org/10.5194/hess-29-5555-2025, https://doi.org/10.5194/hess-29-5555-2025, 2025
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Australia is regularly subjected to severe and widespread drought. By using multiple drought indicators, we show that although there have been widespread decreases in droughts since the beginning of the 20th century, many regions have seen an increase in droughts in more recent decades. Despite these changes, our analysis shows that they remain within the range of observed variability and are not unprecedented in the context of past droughts.
Prashant Paudel, Stefan Olin, Mark Tjoelker, Mikael Pontarp, Daniel Metcalfe, and Benjamin Smith
Biogeosciences, 22, 6153–6171, https://doi.org/10.5194/bg-22-6153-2025, https://doi.org/10.5194/bg-22-6153-2025, 2025
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Ecological processes respond to changes in rainfall conditions. Competition and stress created by water availability are two primary components at two ends of the rainfall gradient. In wetter areas, plants compete for resources, while in drier regions, stress limits growth. The complex interaction between plant characters and their response to growth conditions governs ecosystem processes. These findings can be used to understand how future rainfall changes could impact ecosystems.
Paul C. Astagneau, Raul R. Wood, Mathieu Vrac, Sven Kotlarski, Pradeebane Vaittinada Ayar, Bastien François, and Manuela I. Brunner
Hydrol. Earth Syst. Sci., 29, 5695–5718, https://doi.org/10.5194/hess-29-5695-2025, https://doi.org/10.5194/hess-29-5695-2025, 2025
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To study floods and droughts that are likely to change in the future, we use climate projections from climate models. However, we first need to adjust the systematic biases of these projections at the catchment scale before using them in hydrological models. Our study compares statistical methods that can adjust these biases but specifically for climate projections that enable a quantification of internal climate variability. We provide recommendations on the most appropriate methods.
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci., 29, 4711–4738, https://doi.org/10.5194/hess-29-4711-2025, https://doi.org/10.5194/hess-29-4711-2025, 2025
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Atmospheric variables from climate models often present biases relative to the past. In order to use these models to assess the impact of climate change on processes of interest, it is necessary to correct these biases. We tested several Multivariate Bias Correction Methods (MBCMs) for 5 physical variables that are input variables for 4 process models. We provide recommendations regarding the use of MBCMs when multivariate and time dependent processes are involved.
Anjana Devanand, Jason P. Evans, Andy J. Pitman, Sujan Pal, David Gochis, and Kevin Sampson
Hydrol. Earth Syst. Sci., 29, 4491–4513, https://doi.org/10.5194/hess-29-4491-2025, https://doi.org/10.5194/hess-29-4491-2025, 2025
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Including lateral flow increases evapotranspiration near major river channels in high-resolution land surface simulations in southeast Australia, consistent with observations. The 1-km resolution model shows a widespread pattern of dry ridges that does not exist at coarser resolutions. Our results have implications for improved simulations of droughts and future water availability.
Bastien François, Khalil Teber, Lou Brett, Richard Leeding, Luis Gimeno-Sotelo, Daniela I. V. Domeisen, Laura Suarez-Gutierrez, and Emanuele Bevacqua
Earth Syst. Dynam., 16, 1029–1051, https://doi.org/10.5194/esd-16-1029-2025, https://doi.org/10.5194/esd-16-1029-2025, 2025
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Spatially compounding wind and precipitation (CWP) extremes can lead to severe impacts on society. We find that concurrent climate variability modes favor the occurrence of such wintertime spatially compounding events in the Northern Hemisphere and can even amplify the number of regions and population exposed. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management of such spatially compounding events.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
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Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
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This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, and Raphael A. Viscarra Rossel
SOIL, 10, 619–636, https://doi.org/10.5194/soil-10-619-2024, https://doi.org/10.5194/soil-10-619-2024, 2024
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Effective management of soil organic carbon (SOC) requires accurate knowledge of its distribution and factors influencing its dynamics. We identify the importance of variables in spatial SOC variation and estimate SOC stocks in Australia using various models. We find there are significant disparities in SOC estimates when different models are used, highlighting the need for a critical re-evaluation of land management strategies that rely on the SOC distribution derived from a single approach.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
H. E. Markus Meier, Marcus Reckermann, Joakim Langner, Ben Smith, and Ira Didenkulova
Earth Syst. Dynam., 14, 519–531, https://doi.org/10.5194/esd-14-519-2023, https://doi.org/10.5194/esd-14-519-2023, 2023
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The Baltic Earth Assessment Reports summarise the current state of knowledge on Earth system science in the Baltic Sea region. The 10 review articles focus on the regional water, biogeochemical and carbon cycles; extremes and natural hazards; sea-level dynamics and coastal erosion; marine ecosystems; coupled Earth system models; scenario simulations for the regional atmosphere and the Baltic Sea; and climate change and impacts of human use. Some highlights of the results are presented here.
Bastien François and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 23, 21–44, https://doi.org/10.5194/nhess-23-21-2023, https://doi.org/10.5194/nhess-23-21-2023, 2023
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Compound events (CEs) result from a combination of several climate phenomena. In this study, we propose a new methodology to assess the time of emergence of CE probabilities and to quantify the contribution of marginal and dependence properties of climate phenomena to the overall CE probability changes. By applying our methodology to two case studies, we show the importance of considering changes in both marginal and dependence properties for future risk assessments related to CEs.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Jon Cranko Page, Martin G. De Kauwe, Gab Abramowitz, Jamie Cleverly, Nina Hinko-Najera, Mark J. Hovenden, Yao Liu, Andy J. Pitman, and Kiona Ogle
Biogeosciences, 19, 1913–1932, https://doi.org/10.5194/bg-19-1913-2022, https://doi.org/10.5194/bg-19-1913-2022, 2022
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Although vegetation responds to climate at a wide range of timescales, models of the land carbon sink often ignore responses that do not occur instantly. In this study, we explore the timescales at which Australian ecosystems respond to climate. We identified that carbon and water fluxes can be modelled more accurately if we include environmental drivers from up to a year in the past. The importance of antecedent conditions is related to ecosystem aridity but is also influenced by other factors.
Anna M. Ukkola, Gab Abramowitz, and Martin G. De Kauwe
Earth Syst. Sci. Data, 14, 449–461, https://doi.org/10.5194/essd-14-449-2022, https://doi.org/10.5194/essd-14-449-2022, 2022
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Flux towers provide measurements of water, energy, and carbon fluxes. Flux tower data are invaluable in improving and evaluating land models but are not suited to modelling applications as published. Here we present flux tower data tailored for land modelling, encompassing 170 sites globally. Our dataset resolves several key limitations hindering the use of flux tower data in land modelling, including incomplete forcing variable, data format, and low data quality.
Sami W. Rifai, Martin G. De Kauwe, Anna M. Ukkola, Lucas A. Cernusak, Patrick Meir, Belinda E. Medlyn, and Andy J. Pitman
Biogeosciences, 19, 491–515, https://doi.org/10.5194/bg-19-491-2022, https://doi.org/10.5194/bg-19-491-2022, 2022
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Australia's woody ecosystems have experienced widespread greening despite a warming climate and repeated record-breaking droughts and heat waves. Increasing atmospheric CO2 increases plant water use efficiency, yet quantifying the CO2 effect is complicated due to co-occurring effects of global change. Here we harmonized a 38-year satellite record to separate the effects of climate change, land use change, and disturbance to quantify the CO2 fertilization effect on the greening phenomenon.
Adrian Gustafson, Paul A. Miller, Robert G. Björk, Stefan Olin, and Benjamin Smith
Biogeosciences, 18, 6329–6347, https://doi.org/10.5194/bg-18-6329-2021, https://doi.org/10.5194/bg-18-6329-2021, 2021
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We performed model simulations of vegetation change for a historic period and a range of climate change scenarios at a high spatial resolution. Projected treeline advance continued at the same or increased rates compared to our historic simulation. Temperature isotherms advanced faster than treelines, revealing a lag in potential vegetation shifts that was modulated by nitrogen availability. At the year 2100 projected treelines had advanced by 45–195 elevational metres depending on the scenario.
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Short summary
Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Studies analyzing the impact of the future climate on ecosystems employ climate projections...
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