Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4187-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-4187-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
05 Jul 2021
Model description paper |
| 05 Jul 2021
| 05 Jul 2021
Inclusion of a suite of weathering tracers in the cGENIE Earth system model – muffin release v.0.9.23
BRIDGE (Bristol Research Initiative for the Dynamic Global Environment), School of Geographical Sciences, University of Bristol, Bristol, UK
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
Andy Ridgwell
BRIDGE (Bristol Research Initiative for the Dynamic Global Environment), School of Geographical Sciences, University of Bristol, Bristol, UK
Department of Earth and Planetary Sciences, University of California Riverside, Riverside, California, USA
Fanny M. Monteiro
BRIDGE (Bristol Research Initiative for the Dynamic Global Environment), School of Geographical Sciences, University of Bristol, Bristol, UK
Ian J. Parkinson
School of Earth Sciences, University of Bristol, Bristol, UK
Alexander J. Dickson
Department of Earth Sciences, Royal Holloway University of London, London, UK
Philip A. E. Pogge von Strandmann
London Geochemistry and Isotope Centre (LOGIC), Institute of Earth and Planetary Sciences, University College London and Birkbeck, University of London, London, UK
Institute of Geosciences, Johannes Gutenberg University, 55122 Mainz, Germany
Matthew S. Fantle
Department of Geosciences, Penn State University, Pennsylvania, USA
Sarah E. Greene
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
Related authors
Markus Adloff, Aurich Jeltsch-Thömmes, Frerk Pöppelmeier, Thomas F. Stocker, and Fortunat Joos
Clim. Past, 21, 571–592, https://doi.org/10.5194/cp-21-571-2025, https://doi.org/10.5194/cp-21-571-2025, 2025
Short summary
Short summary
We simulated how different processes affected the carbon cycle over the last eight glacial cycles. We found that the effects of interactive marine sediments enlarge the carbon fluxes that result from these processes, especially in the ocean, and alter various proxy signals. We provide an assessment of the directions of regional and global proxy changes that might be expected in response to different glacial–interglacial Earth system changes in the presence of interactive marine sediments.
Markus Adloff, Frerk Pöppelmeier, Aurich Jeltsch-Thömmes, Thomas F. Stocker, and Fortunat Joos
Clim. Past, 20, 1233–1250, https://doi.org/10.5194/cp-20-1233-2024, https://doi.org/10.5194/cp-20-1233-2024, 2024
Short summary
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is an ocean current that transports heat into the North Atlantic. Over the ice age cycles, AMOC strength and its spatial pattern varied. We tested the role of heat forcing for these AMOC changes by simulating the temperature changes of the last eight glacial cycles. In our model, AMOC shifts between four distinct circulation modes caused by heat and salt redistributions that reproduce reconstructed long-term North Atlantic SST changes.
Markus Adloff, Christian H. Reick, and Martin Claussen
Earth Syst. Dynam., 9, 413–425, https://doi.org/10.5194/esd-9-413-2018, https://doi.org/10.5194/esd-9-413-2018, 2018
Short summary
Short summary
Computer simulations show that during an ice age a strong atmospheric CO2 increase would have resulted in stronger carbon uptake of the continents than today. Causes are the larger potential of glacial vegetation to increase its photosynthetic efficiency under increasing CO2 and the smaller amount of carbon in extratropical soils during an ice age that can be released under greenhouse warming. Hence, for different climates the Earth system is differently sensitive to carbon cycle perturbations.
Markus Adloff, Aurich Jeltsch-Thömmes, Frerk Pöppelmeier, Thomas F. Stocker, and Fortunat Joos
Clim. Past, 21, 571–592, https://doi.org/10.5194/cp-21-571-2025, https://doi.org/10.5194/cp-21-571-2025, 2025
Short summary
Short summary
We simulated how different processes affected the carbon cycle over the last eight glacial cycles. We found that the effects of interactive marine sediments enlarge the carbon fluxes that result from these processes, especially in the ocean, and alter various proxy signals. We provide an assessment of the directions of regional and global proxy changes that might be expected in response to different glacial–interglacial Earth system changes in the presence of interactive marine sediments.
Kirsty Marie Edgar, Maria Grigoratou, Fanny Monteiro, Ruby Barrett, Rui Ying, and Daniela Schmidt
EGUsphere, https://doi.org/10.5194/egusphere-2024-3295, https://doi.org/10.5194/egusphere-2024-3295, 2024
Short summary
Short summary
Planktic foraminifera are microscopic marine organisms whose calcium carbonate shells provide valuable insights into past ocean conditions. A promising means of understanding foraminiferal ecology and their environmental interactions is to constrain their key functional traits relating to feeding, symbioses, motility, calcification and reproduction. Here we review what we know of their functional traits, key gaps in our understanding and suggestions on how to fill them.
Keyi Cheng, Andy Ridgwell, and Dalton S. Hardisty
Biogeosciences, 21, 4927–4949, https://doi.org/10.5194/bg-21-4927-2024, https://doi.org/10.5194/bg-21-4927-2024, 2024
Short summary
Short summary
The carbonate paleoredox proxy, I / Ca, has shown its potential to quantify the redox change in the past ocean, which is of broad importance for understanding climate change and evolution. Here, we tuned and optimized the marine iodine cycling embedded in an Earth system model, “cGENIE”, against modern ocean observations and then tested its ability to estimate I / Ca in the Cretaceous ocean. Our study implies cGENIE’s potential to quantify redox change in the past using the I / Ca proxy.
Markus Adloff, Frerk Pöppelmeier, Aurich Jeltsch-Thömmes, Thomas F. Stocker, and Fortunat Joos
Clim. Past, 20, 1233–1250, https://doi.org/10.5194/cp-20-1233-2024, https://doi.org/10.5194/cp-20-1233-2024, 2024
Short summary
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is an ocean current that transports heat into the North Atlantic. Over the ice age cycles, AMOC strength and its spatial pattern varied. We tested the role of heat forcing for these AMOC changes by simulating the temperature changes of the last eight glacial cycles. In our model, AMOC shifts between four distinct circulation modes caused by heat and salt redistributions that reproduce reconstructed long-term North Atlantic SST changes.
Joost de Vries, Fanny Monteiro, Gerald Langer, Colin Brownlee, and Glen Wheeler
Biogeosciences, 21, 1707–1727, https://doi.org/10.5194/bg-21-1707-2024, https://doi.org/10.5194/bg-21-1707-2024, 2024
Short summary
Short summary
Calcifying phytoplankton (coccolithophores) utilize a life cycle in which they can grow and divide into two different phases. These two phases (HET and HOL) vary in terms of their physiology and distributions, with many unknowns about what the key differences are. Using a combination of lab experiments and model simulations, we find that nutrient storage is a critical difference between the two phases and that this difference allows them to inhabit different nitrogen input regimes.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Stephen P. Hesselbo, Aisha Al-Suwaidi, Sarah J. Baker, Giorgia Ballabio, Claire M. Belcher, Andrew Bond, Ian Boomer, Remco Bos, Christian J. Bjerrum, Kara Bogus, Richard Boyle, James V. Browning, Alan R. Butcher, Daniel J. Condon, Philip Copestake, Stuart Daines, Christopher Dalby, Magret Damaschke, Susana E. Damborenea, Jean-Francois Deconinck, Alexander J. Dickson, Isabel M. Fendley, Calum P. Fox, Angela Fraguas, Joost Frieling, Thomas A. Gibson, Tianchen He, Kat Hickey, Linda A. Hinnov, Teuntje P. Hollaar, Chunju Huang, Alexander J. L. Hudson, Hugh C. Jenkyns, Erdem Idiz, Mengjie Jiang, Wout Krijgsman, Christoph Korte, Melanie J. Leng, Timothy M. Lenton, Katharina Leu, Crispin T. S. Little, Conall MacNiocaill, Miguel O. Manceñido, Tamsin A. Mather, Emanuela Mattioli, Kenneth G. Miller, Robert J. Newton, Kevin N. Page, József Pálfy, Gregory Pieńkowski, Richard J. Porter, Simon W. Poulton, Alberto C. Riccardi, James B. Riding, Ailsa Roper, Micha Ruhl, Ricardo L. Silva, Marisa S. Storm, Guillaume Suan, Dominika Szűcs, Nicolas Thibault, Alfred Uchman, James N. Stanley, Clemens V. Ullmann, Bas van de Schootbrugge, Madeleine L. Vickers, Sonja Wadas, Jessica H. Whiteside, Paul B. Wignall, Thomas Wonik, Weimu Xu, Christian Zeeden, and Ke Zhao
Sci. Dril., 32, 1–25, https://doi.org/10.5194/sd-32-1-2023, https://doi.org/10.5194/sd-32-1-2023, 2023
Short summary
Short summary
We present initial results from a 650 m long core of Late Triasssic to Early Jurassic (190–202 Myr) sedimentary strata from the Cheshire Basin, UK, which is shown to be an exceptional record of Earth evolution for the time of break-up of the supercontinent Pangaea. Further work will determine periodic changes in depositional environments caused by solar system dynamics and used to reconstruct orbital history.
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
Short summary
Short summary
Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Katherine A. Crichton, Andy Ridgwell, Daniel J. Lunt, Alex Farnsworth, and Paul N. Pearson
Clim. Past, 17, 2223–2254, https://doi.org/10.5194/cp-17-2223-2021, https://doi.org/10.5194/cp-17-2223-2021, 2021
Short summary
Short summary
The middle Miocene (15 Ma) was a period of global warmth up to 8 °C warmer than present. We investigate changes in ocean circulation and heat distribution since the middle Miocene and the cooling to the present using the cGENIE Earth system model. We create seven time slices at ~2.5 Myr intervals, constrained with paleo-proxy data, showing a progressive reduction in atmospheric CO2 and a strengthening of the Atlantic Meridional Overturning Circulation.
Kate E. Ashley, Xavier Crosta, Johan Etourneau, Philippine Campagne, Harry Gilchrist, Uthmaan Ibraheem, Sarah E. Greene, Sabine Schmidt, Yvette Eley, Guillaume Massé, and James Bendle
Biogeosciences, 18, 5555–5571, https://doi.org/10.5194/bg-18-5555-2021, https://doi.org/10.5194/bg-18-5555-2021, 2021
Short summary
Short summary
We explore the potential for the use of carbon isotopes of algal fatty acid as a new proxy for past primary productivity in Antarctic coastal zones. Coastal polynyas are hotspots of primary productivity and are known to draw down CO2 from the atmosphere. Reconstructions of past productivity changes could provide a baseline for the role of these areas as sinks for atmospheric CO2.
Yoshiki Kanzaki, Dominik Hülse, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 14, 5999–6023, https://doi.org/10.5194/gmd-14-5999-2021, https://doi.org/10.5194/gmd-14-5999-2021, 2021
Short summary
Short summary
Sedimentary carbonate plays a central role in regulating Earth’s carbon cycle and climate, and also serves as an archive of paleoenvironments, hosting various trace elements/isotopes. To help obtain
trueenvironmental changes from carbonate records over diagenetic distortion, IMP has been newly developed and has the capability to simulate the diagenesis of multiple carbonate particles and implement different styles of particle mixing by benthos using an adapted transition matrix method.
Jun Shao, Lowell D. Stott, Laurie Menviel, Andy Ridgwell, Malin Ödalen, and Mayhar Mohtadi
Clim. Past, 17, 1507–1521, https://doi.org/10.5194/cp-17-1507-2021, https://doi.org/10.5194/cp-17-1507-2021, 2021
Short summary
Short summary
Planktic and shallow benthic foraminiferal stable carbon isotope
(δ13C) data show a rapid decline during the last deglaciation. This widespread signal was linked to respired carbon released from the deep ocean and its transport through the upper-ocean circulation. Using numerical simulations in which a stronger flux of respired carbon upwells and outcrops in the Southern Ocean, we find that the depleted δ13C signal is transmitted to the rest of the upper ocean through air–sea gas exchange.
Sebastiaan J. van de Velde, Dominik Hülse, Christopher T. Reinhard, and Andy Ridgwell
Geosci. Model Dev., 14, 2713–2745, https://doi.org/10.5194/gmd-14-2713-2021, https://doi.org/10.5194/gmd-14-2713-2021, 2021
Short summary
Short summary
Biogeochemical interactions between iron and sulfur are central to the long-term biogeochemical evolution of Earth’s oceans. Here, we introduce an iron–sulphur cycle in a model of Earth's oceans. Our analyses show that the results of the model are robust towards parameter choices and that simulated concentrations and reactions are comparable to those observed in ancient ocean analogues (anoxic lakes). Our model represents an important step forward in the study of iron–sulfur cycling.
Joost de Vries, Fanny Monteiro, Glen Wheeler, Alex Poulton, Jelena Godrijan, Federica Cerino, Elisa Malinverno, Gerald Langer, and Colin Brownlee
Biogeosciences, 18, 1161–1184, https://doi.org/10.5194/bg-18-1161-2021, https://doi.org/10.5194/bg-18-1161-2021, 2021
Short summary
Short summary
Coccolithophores are important calcifying phytoplankton with an overlooked life cycle. We compile a global dataset of marine coccolithophore abundance to investigate the environmental characteristics of each life cycle phase. We find that both phases contribute to coccolithophore abundance and that their different environmental preference increases coccolithophore habitat. Accounting for the life cycle of coccolithophores is thus crucial for understanding their ecology and biogeochemical impact.
Katherine A. Crichton, Jamie D. Wilson, Andy Ridgwell, and Paul N. Pearson
Geosci. Model Dev., 14, 125–149, https://doi.org/10.5194/gmd-14-125-2021, https://doi.org/10.5194/gmd-14-125-2021, 2021
Short summary
Short summary
Temperature is a controller of metabolic processes and therefore also a controller of the ocean's biological carbon pump (BCP). We calibrate a temperature-dependent version of the BCP in the cGENIE Earth system model. Since the pre-industrial period, warming has intensified near-surface nutrient recycling, supporting production and largely offsetting stratification-induced surface nutrient limitation. But at the same time less carbon that sinks out of the surface then reaches the deep ocean.
Tom Dunkley Jones, Yvette L. Eley, William Thomson, Sarah E. Greene, Ilya Mandel, Kirsty Edgar, and James A. Bendle
Clim. Past, 16, 2599–2617, https://doi.org/10.5194/cp-16-2599-2020, https://doi.org/10.5194/cp-16-2599-2020, 2020
Short summary
Short summary
We explore the utiliity of the composition of fossil lipid biomarkers, which are commonly preserved in ancient marine sediments, in providing estimates of past ocean temperatures. The group of lipids concerned show compositional changes across the modern oceans that are correlated, to some extent, with local surface ocean temperatures. Here we present new machine learning approaches to improve our understanding of this temperature sensitivity and its application to reconstructing past climates.
Christopher T. Reinhard, Stephanie L. Olson, Sandra Kirtland Turner, Cecily Pälike, Yoshiki Kanzaki, and Andy Ridgwell
Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, https://doi.org/10.5194/gmd-13-5687-2020, 2020
Short summary
Short summary
We provide documentation and testing of new developments for the oceanic and atmospheric methane cycles in the cGENIE Earth system model. The model is designed to explore Earth's methane cycle across a wide range of timescales and scenarios, in particular assessing the mean climate state and climate perturbations in Earth's deep past. We further document the impact of atmospheric oxygen levels and ocean chemistry on fluxes of methane to the atmosphere from the ocean biosphere.
Malin Ödalen, Jonas Nycander, Andy Ridgwell, Kevin I. C. Oliver, Carlye D. Peterson, and Johan Nilsson
Biogeosciences, 17, 2219–2244, https://doi.org/10.5194/bg-17-2219-2020, https://doi.org/10.5194/bg-17-2219-2020, 2020
Short summary
Short summary
In glacial periods, ocean uptake of carbon is likely a key player for achieving low atmospheric CO2. In climate models, ocean biological uptake of carbon (C) and phosphorus (P) are often assumed to occur in fixed proportions.
In this study, we allow the ratio of C : P to vary and simulate, to first approximation, the complex biological changes that occur in the ocean over long timescales. We show here that, for glacial–interglacial cycles, this complexity contributes to low atmospheric CO2.
Yoshiki Kanzaki, Bernard P. Boudreau, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 12, 4469–4496, https://doi.org/10.5194/gmd-12-4469-2019, https://doi.org/10.5194/gmd-12-4469-2019, 2019
Short summary
Short summary
This paper provides eLABS, an extension of the lattice-automaton bioturbation simulator LABS. In our new model, the benthic animal behavior interacts and changes dynamically with oxygen and organic matter concentrations and the water flows caused by benthic animals themselves, in a 2-D marine-sediment grid. The model can address the mechanisms behind empirical observations of bioturbation based on the interactions between physical, chemical and biological aspects of marine sediment.
Jamie D. Wilson, Stephen Barker, Neil R. Edwards, Philip B. Holden, and Andy Ridgwell
Biogeosciences, 16, 2923–2936, https://doi.org/10.5194/bg-16-2923-2019, https://doi.org/10.5194/bg-16-2923-2019, 2019
Short summary
Short summary
The remains of plankton rain down from the surface ocean to the deep ocean, acting to store CO2 in the deep ocean. We used a model of biology and ocean circulation to explore the importance of this process in different regions of the ocean. The amount of CO2 stored in the deep ocean is most sensitive to changes in the Southern Ocean. As plankton in the Southern Ocean are likely those most impacted by future climate change, the amount of CO2 they store in the deep ocean could also be affected.
Krista M. S. Kemppinen, Philip B. Holden, Neil R. Edwards, Andy Ridgwell, and Andrew D. Friend
Clim. Past, 15, 1039–1062, https://doi.org/10.5194/cp-15-1039-2019, https://doi.org/10.5194/cp-15-1039-2019, 2019
Short summary
Short summary
We simulate the Last Glacial Maximum atmospheric CO2 decrease with a large ensemble of parameter sets to investigate the range of possible physical and biogeochemical Earth system changes accompanying the CO2 decrease. Amongst the dominant ensemble changes is an increase in terrestrial carbon, which we attribute to a slower soil respiration rate, and the preservation of carbon by the LGM ice sheets. Further investigation into the role of terrestrial carbon is warranted.
Maria Grigoratou, Fanny M. Monteiro, Daniela N. Schmidt, Jamie D. Wilson, Ben A. Ward, and Andy Ridgwell
Biogeosciences, 16, 1469–1492, https://doi.org/10.5194/bg-16-1469-2019, https://doi.org/10.5194/bg-16-1469-2019, 2019
Short summary
Short summary
The paper presents a novel study based on the traits of shell size, calcification and feeding behaviour of two planktonic foraminifera life stages using modelling simulations. With the model, we tested the cost and benefit of calcification and explored how the interactions of planktonic foraminifera among other plankton groups influence their biomass under different environmental conditions. Our results provide new insights into environmental controls in planktonic foraminifera ecology.
Ben A. Ward, Jamie D. Wilson, Ros M. Death, Fanny M. Monteiro, Andrew Yool, and Andy Ridgwell
Geosci. Model Dev., 11, 4241–4267, https://doi.org/10.5194/gmd-11-4241-2018, https://doi.org/10.5194/gmd-11-4241-2018, 2018
Short summary
Short summary
A novel configuration of an Earth system model includes a diverse plankton community. The model – EcoGEnIE – is sufficiently complex to reproduce a realistic, size-structured plankton community, while at the same time retaining the efficiency to run to a global steady state (~ 10k years). The increased capabilities of EcoGEnIE will allow future exploration of ecological communities on much longer timescales than have so far been examined in global ocean models and particularly for past climate.
Tom Dunkley Jones, Hayley R. Manners, Murray Hoggett, Sandra Kirtland Turner, Thomas Westerhold, Melanie J. Leng, Richard D. Pancost, Andy Ridgwell, Laia Alegret, Rob Duller, and Stephen T. Grimes
Clim. Past, 14, 1035–1049, https://doi.org/10.5194/cp-14-1035-2018, https://doi.org/10.5194/cp-14-1035-2018, 2018
Short summary
Short summary
The Paleocene–Eocene Thermal Maximum (PETM) is a transient global warming event associated with a doubling of atmospheric carbon dioxide concentrations. Here we document a major increase in sediment accumulation rates on a subtropical continental margin during the PETM, likely due to marked changes in hydro-climates and sediment transport. These high sedimentation rates persist through the event and may play a key role in the removal of carbon from the atmosphere by the burial of organic carbon.
Dominik Hülse, Sandra Arndt, Stuart Daines, Pierre Regnier, and Andy Ridgwell
Geosci. Model Dev., 11, 2649–2689, https://doi.org/10.5194/gmd-11-2649-2018, https://doi.org/10.5194/gmd-11-2649-2018, 2018
Short summary
Short summary
We present a 1-D analytical diagenetic model resolving organic matter (OM) cycling and the associated biogeochemical dynamics in marine sediments designed to be coupled to Earth system models (ESMs). The reaction network accounts for the most important reactions associated with OM dynamics. The coupling is described and the OM degradation rate constant is tuned. Various observations, such as pore water profiles, sediment water interface fluxes and OM content, are reproduced with good accuracy.
Markus Adloff, Christian H. Reick, and Martin Claussen
Earth Syst. Dynam., 9, 413–425, https://doi.org/10.5194/esd-9-413-2018, https://doi.org/10.5194/esd-9-413-2018, 2018
Short summary
Short summary
Computer simulations show that during an ice age a strong atmospheric CO2 increase would have resulted in stronger carbon uptake of the continents than today. Causes are the larger potential of glacial vegetation to increase its photosynthetic efficiency under increasing CO2 and the smaller amount of carbon in extratropical soils during an ice age that can be released under greenhouse warming. Hence, for different climates the Earth system is differently sensitive to carbon cycle perturbations.
Malin Ödalen, Jonas Nycander, Kevin I. C. Oliver, Laurent Brodeau, and Andy Ridgwell
Biogeosciences, 15, 1367–1393, https://doi.org/10.5194/bg-15-1367-2018, https://doi.org/10.5194/bg-15-1367-2018, 2018
Short summary
Short summary
We conclude that different initial states for an ocean model result in different capacities for ocean carbon storage due to differences in the ocean circulation state and the origin of the carbon in the initial ocean carbon reservoir. This could explain why it is difficult to achieve comparable responses of the ocean carbon system in model inter-comparison studies in which the initial states vary between models. We show that this effect of the initial state is quantifiable.
Natalie S. Lord, Michel Crucifix, Dan J. Lunt, Mike C. Thorne, Nabila Bounceur, Harry Dowsett, Charlotte L. O'Brien, and Andy Ridgwell
Clim. Past, 13, 1539–1571, https://doi.org/10.5194/cp-13-1539-2017, https://doi.org/10.5194/cp-13-1539-2017, 2017
Short summary
Short summary
We present projections of long-term changes in climate, produced using a statistical emulator based on climate data from a state-of-the-art climate model. We use the emulator to model changes in temperature and precipitation over the late Pliocene (3.3–2.8 million years before present) and the next 200 thousand years. The impact of the Earth's orbit and the atmospheric carbon dioxide concentration on climate is assessed, and the data for the late Pliocene are compared to proxy temperature data.
Taraka Davies-Barnard, Andy Ridgwell, Joy Singarayer, and Paul Valdes
Clim. Past, 13, 1381–1401, https://doi.org/10.5194/cp-13-1381-2017, https://doi.org/10.5194/cp-13-1381-2017, 2017
Short summary
Short summary
We present the first model analysis using a fully coupled dynamic atmosphere–ocean–vegetation GCM over the last 120 kyr that quantifies the net effect of vegetation on climate. This analysis shows that over the whole period the biogeophysical effect (albedo, evapotranspiration) is dominant, and that the biogeochemical impacts may have a lower possible range than typically estimated. This emphasises the temporal reliance of the balance between biogeophysical and biogeochemical effects.
Clemens Vinzenz Ullmann and Philip A. E. Pogge von Strandmann
Biogeosciences, 14, 89–97, https://doi.org/10.5194/bg-14-89-2017, https://doi.org/10.5194/bg-14-89-2017, 2017
Short summary
Short summary
This study documents how much control growth rate has on the chemical composition of fossil shell material. Using a series of chemical analyses of the fossil hard part of a belemnite, an extinct marine predator, a clear connection between the rate of calcite formation and its magnesium and strontium contents was found. These findings provide further insight into biomineralization processes and help better understand chemical signatures of fossils as proxies for palaeoenvironmental conditions.
J. D. Wilson, A. Ridgwell, and S. Barker
Biogeosciences, 12, 5547–5562, https://doi.org/10.5194/bg-12-5547-2015, https://doi.org/10.5194/bg-12-5547-2015, 2015
Short summary
Short summary
We explore whether ocean model transport rates, in the form of a transport matrix, can be used to estimate remineralisation rates from dissolved nutrient concentrations and infer vertical fluxes of particulate organic carbon. Estimated remineralisation rates are significantly sensitive to uncertainty in the observations and the modelled circulation. The remineralisation of dissolved organic matter is an additional source of uncertainty when inferring vertical fluxes from remineralisation rates.
N. S. Jones, A. Ridgwell, and E. J. Hendy
Biogeosciences, 12, 1339–1356, https://doi.org/10.5194/bg-12-1339-2015, https://doi.org/10.5194/bg-12-1339-2015, 2015
Short summary
Short summary
Production of calcium carbonate by coral reefs is important in the global carbon cycle. Using a global framework we evaluate four models of reef calcification against observed values. The temperature-only model showed significant skill in reproducing coral calcification rates. The absence of any predictive power for whole reef systems highlights the importance of coral cover and the need for an ecosystem modelling approach accounting for population dynamics in terms of mortality and recruitment.
P. A. E. Pogge von Strandmann, J. Forshaw, and D. N. Schmidt
Biogeosciences, 11, 5155–5168, https://doi.org/10.5194/bg-11-5155-2014, https://doi.org/10.5194/bg-11-5155-2014, 2014
R. Death, J. L. Wadham, F. Monteiro, A. M. Le Brocq, M. Tranter, A. Ridgwell, S. Dutkiewicz, and R. Raiswell
Biogeosciences, 11, 2635–2643, https://doi.org/10.5194/bg-11-2635-2014, https://doi.org/10.5194/bg-11-2635-2014, 2014
G. Colbourn, A. Ridgwell, and T. M. Lenton
Geosci. Model Dev., 6, 1543–1573, https://doi.org/10.5194/gmd-6-1543-2013, https://doi.org/10.5194/gmd-6-1543-2013, 2013
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
P. B. Holden, N. R. Edwards, S. A. Müller, K. I. C. Oliver, R. M. Death, and A. Ridgwell
Biogeosciences, 10, 1815–1833, https://doi.org/10.5194/bg-10-1815-2013, https://doi.org/10.5194/bg-10-1815-2013, 2013
Related subject area
Climate and Earth system modeling
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models
Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Process-based modeling framework for sustainable irrigation management at the regional scale: Integrating rice production, water use, and greenhouse gas emissions
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
Short summary
Short summary
We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
Short summary
Short summary
We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
Short summary
Short summary
Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
Short summary
Short summary
Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
Short summary
Short summary
Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
Short summary
Short summary
We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
Short summary
Short summary
Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
Short summary
Short summary
We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
Short summary
Short summary
Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
Short summary
Short summary
The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
Short summary
Short summary
HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
Short summary
Short summary
We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
Short summary
Short summary
This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
Short summary
Short summary
Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
Short summary
Short summary
The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
Short summary
Short summary
CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
Short summary
Short summary
The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
Short summary
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
Short summary
Short summary
A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
Short summary
Short summary
In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
Short summary
Short summary
The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
Short summary
Short summary
We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
Short summary
Short summary
We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
Short summary
Short summary
In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
Short summary
Short summary
We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
Short summary
Short summary
The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
Short summary
Short summary
The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
Short summary
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
Short summary
Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
Short summary
Short summary
Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
Short summary
Short summary
A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
Short summary
Short summary
This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
Short summary
Short summary
We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
Short summary
Short summary
Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
Short summary
Short summary
We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
Short summary
Short summary
We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
Short summary
Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
Short summary
Short summary
We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
Short summary
Short summary
We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
Short summary
Short summary
The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
Short summary
Short summary
We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
Short summary
Short summary
The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Cited articles
Allègre, C. J., Louvat, P., Gaillardet, J., Meynadier, L., Rad, S., and Capmas, F.: The fundamental role of island arc weathering in the oceanic Sr isotope budget, Earth Planet. Sc. Lett., 292, 51–56, https://doi.org/10.1016/j.epsl.2010.01.019, 2010. a, b
Basu, A. R., Jacobsen, S. B., Poreda, R. J., Dowling, C. B., and Aggarwal, P. K.: Large groundwater strontium flux to the oceans from the Bengal Basin and the marine strontium isotope record, Science, 293, 1470–1473, https://doi.org/10.1126/science.1060524, 2001. a, b
Bauer, K. W., Zeebe, R. E., and Wortmann, U. G.: Quantifying the volcanic emissions which triggered Oceanic Anoxic Event 1a and their effect on ocean acidification, Sedimentology, 64, 204–214, https://doi.org/10.1111/sed.12335, 2017. a
Beck, A. J., Charette, M. A., Cochran, J. K., Gonneea, M. E., and Peucker-Ehrenbrink, B.: Dissolved strontium in the subterranean estuary–implications for the marine strontium isotope budget, Geochim. Cosmochim. Ac., 117, 33–52, https://doi.org/10.1016/j.gca.2013.03.021, 2013. a, b
Berner, R.: GEOCARB II: a revised model of atmospheric CO2 levels over Phanerozoic time, Science, 249, 1382–1386, 1994. a
Blättler, C. L., Jenkyns, H. C., Reynard, L. M., and Henderson, G. M.: Significant increases in global weathering during Oceanic Anoxic Events 1a and 2 indicated by calcium isotopes, Earth Planet. Sc. Lett., 309, 77–88, https://doi.org/10.1016/j.epsl.2011.06.029, 2011. a
Blättler, C. L., Henderson, G. M., and Jenkyns, H. C.: Explaining the Phanerozoic Ca isotope history of seawater, Geology, 40, 843–846, https://doi.org/10.1130/G33191.1, 2012. a
Bluth, G. J. and Kump, L. R.: Lithologic and climatologic controls of river chemistry, Geochim. Cosmochim. Ac., 58, 2341–2359, 1994. a
Böhm, F., Eisenhauer, A., Tang, J., Dietzel, M., Krabbenhöft, A., Kisakürek, B., and Horn, C.: Strontium isotope fractionation of planktic foraminifera and inorganic calcite, Geochim. Cosmochim. Ac., 93, 300–314, https://doi.org/10.1016/j.gca.2012.04.038, 2012. a, b
Bottini, C., Cohen, A. S., Erba, E., Jenkyns, H. C., and Coe, A. L.: Osmium-isotope evidence for volcanism, weathering, and ocean mixing during the early Aptian OAE 1a, Geology, 40, 583–586, https://doi.org/10.1130/G33140.1, 2012. a, b
Brady, P. V.: The effect of silicate weathering on global temperature and atmospheric CO2, J. Geophys. Res.-Sol. Ea., 96, 18101–18106, https://doi.org/10.1029/91JB01898, 1991. a
Brady, P. V. and Gíslason, S. R.: Seafloor weathering controls on atmospheric CO2 and global climate, Geochim. Cosmochim. Ac., 61, 965–973, https://doi.org/10.1016/S0016-7037(96)00385-7, 1997. a
Bryant, C. J., McCulloch, M. T., and Bennett, V. C.: Impact of matrix effects on the accurate measurement of Li isotope ratios by inductively coupled plasma mass spectrometry (MC-ICP-MS) under “cold” plasma conditions, J. Anal. Atom. Spectrom., 18, 734–737, https://doi.org/10.1039/B212083F, 2003. a, b, c
Burton, K. W., Gannoun, A., and Parkinson, I. J.: Climate driven glacial–interglacial variations in the osmium isotope composition of seawater recorded by planktic foraminifera, Earth Planet. Sc. Lett., 295, 58–68, https://doi.org/10.1016/j.epsl.2010.03.026, 2010. a, b, c
Campbell, I. H. and Allen, C. M.: Formation of supercontinents linked to increases in atmospheric oxygen, Nat. Geosci., 1, 554–558, https://doi.org/10.1038/ngeo259, 2008. a
Carignan, J., Cardinal, D., Eisenhauer, A., Galy, A., Rehkamper, M., Wombacher, F., and Vigier, N.: A reflection on Mg, Cd, Ca, Li and Si isotopic measurements and related reference materials, Geostand. Geoanal. Res., 28, 139–148, https://doi.org/10.1111/j.1751-908X.2004.tb01050.x, 2004. a
Chan, L., Edmond, J., Thompson, G., and Gillis, K.: Lithium isotopic composition of submarine basalts: implications for the lithium cycle in the oceans, Earth Planet. Sc. Lett., 108, 151–160, https://doi.org/10.1016/0012-821X(92)90067-6, 1992. a
Chan, L. H.: Lithium isotope analysis by thermal ionization mass spectrometry of lithium tetraborate, Anal. Chem., 59, 2662–2665, https://doi.org/10.1021/ac00149a007, 1987. a, b, c, d
Chan, L.-H. and Edmond, J. M.: Variation of lithium isotope composition in the marine environment: A preliminary report, Geochim. Cosmochim. Ac., 52, 1711–1717, https://doi.org/10.1016/0016-7037(88)90239-6, 1988. a, b, c, d
Choi, M. S., Shin, H. S., and Kil, Y. W.: Precise determination of lithium isotopes in seawater using MC-ICP-MS, Microchem. J., 95, 274–278, https://doi.org/10.1016/j.microc.2009.12.013, 2010. a, b, c
Clergue, C., Dellinger, M., Buss, H., Gaillardet, J., Benedetti, M., and Dessert, C.: Influence of atmospheric deposits and secondary minerals on Li isotopes budget in a highly weathered catchment, Guadeloupe (Lesser Antilles), Chem. Geol., 414, 28–41, https://doi.org/10.1016/j.chemgeo.2015.08.015, 2015. a
Cocker, J., Griffin, B., and Muehlenbachs, K.: Oxygen and carbon isotope evidence for seawater-hydrothermal alteration of the Macquarie Island ophiolite, Earth Planet. Sc. Lett., 61, 112–122, 1982. a
Colbourn, G., Ridgwell, A., and Lenton, T. M.: The Rock Geochemical Model (RokGeM) v0.9, Geosci. Model Dev., 6, 1543–1573, https://doi.org/10.5194/gmd-6-1543-2013, 2013. a, b, c
Coogan, L. A. and Gillis, K. M.: Low-temperature alteration of the seafloor: Impacts on ocean chemistry, Annu. Rev. Earth Pl. Sc., 46, 21–45, 2018. a
Dąbek, J. and Halas, S.: Physical foundations of rhenium-osmium method-a review, Geochronometria, 27, 23–26, https://doi.org/10.2478/v10003-007-0011-4, 2007. a, b
Data Announcement 88-MGG-02: Digital relief of the Surface of the Earth, NOAA, National Geophysical Data Center, Boulder, Colorado, 1988. a
Death, R., Wadham, J. L., Monteiro, F., Le Brocq, A. M., Tranter, M., Ridgwell, A., Dutkiewicz, S., and Raiswell, R.: Antarctic ice sheet fertilises the Southern Ocean, Biogeosciences, 11, 2635–2643, https://doi.org/10.5194/bg-11-2635-2014, 2014. a
Dellinger, M., Gaillardet, J., Bouchez, J., Calmels, D., Louvat, P., Dosseto, A., Gorge, C., Alanoca, L., and Maurice, L.: Riverine Li isotope fractionation in the Amazon River basin controlled by the weathering regimes, Geochim. Cosmochim. Ac., 164, 71–93, https://doi.org/10.1016/j.gca.2015.04.042, 2015. a, b, c, d
Dellinger, M., West, A. J., Paris, G., Adkins, J. F., Pogge von Strandmann, P. A., Ullmann, C. V., Eagle, R. A., Freitas, P., Bagard, M.-L., Ries, J. B., Corsetti, F. A., Perez-Huerta, A., and Kampf, A. R.: The Li isotope composition of marine biogenic carbonates: Patterns and Mechanisms, Geochim. Cosmochim. Ac., 236, 315–335, https://doi.org/10.1016/j.gca.2018.03.014, 2018. a
DePaolo, D. J.: Calcium isotopic variations produced by biological, kinetic, radiogenic and nucleosynthetic processes, Reviews in Mineralogy and Geochemistry, 55, 255–288, https://doi.org/10.2138/gsrmg.55.1.255, 2004. a
DePaolo, D. J.: Surface kinetic model for isotopic and trace element fractionation during precipitation of calcite from aqueous solutions, Geochim. Cosmochim. Ac., 75, 1039–1056, https://doi.org/10.1016/j.gca.2010.11.020, 2011. a, b
Derry, L. A.: Geochemistry: A glacial hangover, Nature, 458, 417–418, https://doi.org/10.1038/458417a, 2009. a
Dickson, A. J., Cohen, A. S., Coe, A. L., Davies, M., Shcherbinina, E. A., and Gavrilov, Y. O.: Evidence for weathering and volcanism during the PETM from Arctic Ocean and Peri-Tethys osmium isotope records, Palaeogeogr. Palaeocl., 438, 300–307, https://doi.org/10.1016/j.palaeo.2015.08.019, 2015. a
Dubin, A. and Peucker-Ehrenbrink, B.: The importance of organic-rich shales to the geochemical cycles of rhenium and osmium, Chem. Geol., 403, 111–120, https://doi.org/10.1016/j.chemgeo.2015.03.010, 2015. a, b
Edwards, N. R. and Marsh, R.: Uncertainties due to transport-parameter sensitivity in an efficient 3-D ocean-climate model, Clim. Dynam., 24, 415–433, https://doi.org/10.1007/s00382-004-0508-8, 2005. a
Elderfield, H.: Strontium isotope stratigraphy, Palaeogeogr. Palaeocl., 57, 71–90, https://doi.org/10.1016/0031-0182(86)90007-6, 1986. a
Elderfield, H. and Gieskes, J. M.: Sr isotopes in interstitial waters of marine sediments from Deep Sea Drilling Project cores, Nature, 300, 493–497, https://doi.org/10.1038/300493a0, 1982. a
Erba, E., Bottini, C., Weissert, H. J., and Keller, C. E.: Calcareous nannoplankton response to surface-water acidification around Oceanic Anoxic Event 1a, Science, 329, 428–432, https://doi.org/10.1126/science.1188886, 2010. a
Fantle, M. S. and Ridgwell, A.: Towards an understanding of the Ca isotopic signal related to ocean acidification and alkalinity overshoots in the rock record, Chem. Geol., 547, 119672, https://doi.org/10.1016/j.chemgeo.2020.119672, 2020. a, b, c
Fantle, M. S., Tollerud, H., Eisenhauer, A., and Holmden, C.: The Ca isotopic composition of dust-producing regions: Measurements of surface sediments in the Black Rock Desert, Nevada, Geochim. Cosmochim. Ac., 87, 178–193, https://doi.org/10.1016/j.gca.2012.03.037, 2012. a
Fantle, M. S., Barnes, B. D., and Lau, K. V.: The Role of Diagenesis in Shaping the Geochemistry of the Marine Carbonate Record, Annu. Rev. Earth Pl. Sc., 48, 549–583, https://doi.org/10.1146/annurev-earth-073019-060021, 2020. a, b
Farkaš, J., Böhm, F., Wallmann, K., Blenkinsop, J., Eisenhauer, A., Van Geldern, R., Munnecke, A., Voigt, S., and Veizer, J.: Calcium isotope record of Phanerozoic oceans: Implications for chemical evolution of seawater and its causative mechanisms, Geochim. Cosmochim. Ac., 71, 5117–5134, https://doi.org/10.1016/j.gca.2007.09.004, 2007. a, b
Fietzke, J. and Eisenhauer, A.: Determination of temperature-dependent stable strontium isotope (
Finlay, A. J., Selby, D., and Gröcke, D. R.: Tracking the Hirnantian glaciation using Os isotopes, Earth Planet. Sc. Lett., 293, 339–348, https://doi.org/10.1016/j.epsl.2010.02.049, 2010. a
Fries, D. M., James, R. H., Dessert, C., Bouchez, J., Beaumais, A., and Pearce, C. R.: The response of Li and Mg isotopes to rain events in a highly-weathered catchment, Chem. Geol., 519, 68–82, https://doi.org/10.1016/j.chemgeo.2019.04.023, 2019. a, b
Gehler, A., Gingerich, P. D., and Pack, A.: Temperature and atmospheric CO2 concentration estimates through the PETM using triple oxygen isotope analysis of mammalian bioapatite, P. Natl. Acad. Sci. USA, 113, 7739–7744, 2016. a
Gibbs, M. T. and Kump, L. R.: Global chemical erosion during the last glacial maximum and the present: sensitivity to changes in lithology and hydrology, Paleoceanography, 9, 529–543, 1994. a
Gibbs, M. T., Bluth, G. J., Fawcett, P. J., and Kump, L. R.: Global chemical erosion over the last 250 My; variations due to changes in paleogeography, paleoclimate, and paleogeology, Am. J. Sci., 299, 611–651, 1999. a
Goddéris, Y. and François, L.: The Cenozoic evolution of the strontium and carbon cycles: relative importance of continental erosion and mantle exchanges, Chem. Geol., 126, 169–190, https://doi.org/10.1016/0009-2541(95)00117-3, 1995. a
Goldschmidt, V. M.: Der Stoffwechsel der Erde, Z. Elektrochem. Angew. P., 28, 411–421, 1922. a
Gou, L.-F., Jin, Z., Pogge von Strandmann, P. A., Li, G., Qu, Y.-X., Xiao, J., Deng, L., and Galy, A.: Li isotopes in the middle Yellow River: Seasonal variability, sources and fractionation, Geochim. Cosmochim. Ac., 248, 88–108, https://doi.org/10.1016/j.gca.2019.01.007, 2019. a, b, c
Griffith, E. M., Paytan, A., Caldeira, K., Bullen, T. D., and Thomas, E.: A dynamic marine calcium cycle during the past 28 million years, Science, 322, 1671–1674, https://doi.org/10.1126/science.1163614, 2008. a
Hall, J. M. and Chan, L.-H.:
Hall, J. M., Chan, L.-H., McDonough, W. F., and Turekian, K. K.: Determination of the lithium isotopic composition of planktic foraminifera and its application as a paleo-seawater proxy, Mar. Geol., 217, 255–265, https://doi.org/10.1016/j.margeo.2004.11.015, 2005. a
Henchiri, S., Gaillardet, J., Dellinger, M., Bouchez, J., and Spencer, R. G.: Riverine dissolved lithium isotopic signatures in low-relief central Africa and their link to weathering regimes, Geophys. Res. Lett., 43, 4391–4399, https://doi.org/10.1002/2016GL067711, 2016. a, b
Heuser, A., Eisenhauer, A., Gussone, N., Bock, B., Hansen, B., and Nägler, T. F.: Measurement of calcium isotopes (δ44Ca) using a multicollector TIMS technique, Int. J. Mass Spectrom., 220, 385–397, https://doi.org/10.1016/S1387-3806(02)00838-2, 2002. a
Hindshaw, R. S., Reynolds, B. C., Wiederhold, J. G., Kiczka, M., Kretzschmar, R., and Bourdon, B.: Calcium isotope fractionation in alpine plants, Biogeochemistry, 112, 373–388, https://doi.org/10.1007/s10533-012-9732-1, 2013. a
Hindshaw, R. S., Tosca, R., Goût, T. L., Farnan, I., Tosca, N. J., and Tipper, E. T.: Experimental constraints on Li isotope fractionation during clay formation, Geochim. Cosmochim. Ac., 250, 219–237, https://doi.org/10.1016/j.gca.2019.02.015, 2019. a, b, c
Hodell, D. A., Mueller, P. A., McKenzie, J. A., and Mead, G. A.: Strontium isotope stratigraphy and geochemistry of the late Neogene ocean, Earth Planet. Sc. Lett., 92, 165–178, https://doi.org/10.1016/0012-821X(89)90044-7, 1989. a
Hodell, D. A., Mead, G. A., and Mueller, P. A.: Variation in the strontium isotopic composition of seawater (8 Ma to present): Implications for chemical weathering rates and dissolved fluxes to the oceans, Chemical Geology: Isotope Geoscience section, 80, 291–307, https://doi.org/10.1016/0168-9622(90)90011-Z, 1990. a
Hooper, J., Mayewski, P., Marx, S., Henson, S., Potocki, M., Sneed, S., Handley, M., Gassó, S., Fischer, M., and Saunders, K. M.: Examining links between dust deposition and phytoplankton response using ice cores, Aeolian Res., 36, 45–60, https://doi.org/10.1016/j.aeolia.2018.11.001, 2019. a
Huh, Y., Chan, L.-H., Zhang, L., and Edmond, J. M.: Lithium and its isotopes in major world rivers: implications for weathering and the oceanic budget, Geochim. Cosmochim. Ac., 62, 2039–2051, https://doi.org/10.1016/S0016-7037(98)00126-4, 1998. a
Hülse, D., Arndt, S., and Ridgwell, A.: Mitigation of extreme Ocean Anoxic Event conditions by organic matter sulfurization, Paleoceanography and Paleoclimatology, 34, 476–489, https://doi.org/10.1029/2018PA003470, 2019. a
Jaffe, L. A., Peucker-Ehrenbrink, B., and Petsch, S. T.: Mobility of rhenium, platinum group elements and organic carbon during black shale weathering, Earth Planet. Sc. Lett., 198, 339–353, https://doi.org/10.1016/S0012-821X(02)00526-5, 2002. a
James, R. H. and Palmer, M. R.: The lithium isotope composition of international rock standards, Chem. Geol., 166, 319–326, https://doi.org/10.1016/S0009-2541(99)00217-X, 2000. a, b, c
Jenkyns, H. C.: Geochemistry of oceanic anoxic events, Geochem. Geophy. Geosy., 11, Q03004, https://doi.org/10.1029/2009GC002788, 2010. a
John, E. H., Wilson, J. D., Pearson, P. N., and Ridgwell, A.: Temperature-dependent remineralization and carbon cycling in the warm Eocene oceans, Palaeogeogr. Palaeocl., 413, 158–166, https://doi.org/10.1016/j.palaeo.2014.05.019, 2014. a
Kasemann, S. A., Hawkesworth, C. J., Prave, A. R., Fallick, A. E., and Pearson, P. N.: Boron and calcium isotope composition in Neoproterozoic carbonate rocks from Namibia: evidence for extreme environmental change, Earth Planet. Sc. Lett., 231, 73–86, https://doi.org/10.1016/j.epsl.2004.12.006, 2005. a
Kasemann, S. A., Schmidt, D. N., Pearson, P. N., and Hawkesworth, C. J.: Biological and ecological insights into Ca isotopes in planktic foraminifers as a palaeotemperature proxy, Earth Planet. Sc. Lett., 271, 292–302, https://doi.org/10.1016/j.epsl.2008.04.007, 2008. a, b
Kasemann, S. A., Pogge von Strandmann, P. A., Prave, A. R., Fallick, A. E., Elliott, T., and Hoffmann, K.-H.: Continental weathering following a Cryogenian glaciation: Evidence from calcium and magnesium isotopes, Earth Planet. Sc. Lett., 396, 66–77, https://doi.org/10.1016/j.epsl.2014.03.048, 2014. a, b
Kent, D. V. and Muttoni, G.: Modulation of Late Cretaceous and Cenozoic climate by variable drawdown of atmospheric pCO2 from weathering of basaltic provinces on continents drifting through the equatorial humid belt, Clim. Past, 9, 525–546, https://doi.org/10.5194/cp-9-525-2013, 2013. a
Kirtland Turner, S. and Ridgwell, A.: Recovering the true size of an Eocene hyperthermal from the marine sedimentary record, Paleoceanography, 28, 700–712, 2013. a
Kısakűrek, B., James, R. H., and Harris, N. B.: Li and δ7Li
in Himalayan rivers: proxies for silicate weathering?, Earth Planet. Sc. Lett., 237, 387–401, https://doi.org/10.1016/j.epsl.2005.07.019, 2005. a, b
Komar, N. and Zeebe, R.: Calcium and calcium isotope changes during carbon cycle perturbations at the end-Permian, Paleoceanography, 31, 115–130, 2016. a
Košler, J., Kučera, M., and Sylvester, P.: Precise measurement of Li isotopes in planktonic foraminiferal tests by quadrupole ICPMS, Chem. Geol., 181, 169–179, https://doi.org/10.1016/S0009-2541(01)00280-7, 2001. a, b, c
Krabbenhöft, A.: Stable Strontium Isotope (
Krabbenhöft, A., Eisenhauer, A., Böhm, F., Vollstaedt, H., Fietzke, J., Liebetrau, V., Augustin, N., Peucker-Ehrenbrink, B., Müller, M., Horn, C., Hansen, B. T., Nolte, N., and Wallmann, K.: Constraining the marine strontium budget with natural strontium isotope fractionations (
Krissansen-Totton, J. and Catling, D. C.: Constraining climate sensitivity and continental versus seafloor weathering using an inverse geological carbon cycle model, Nat. Commun., 8, 1–15, https://doi.org/10.1038/ncomms15423, 2017. a, b
Kump, L. R. and Barley, M. E.: Increased subaerial volcanism and the rise of
atmospheric oxygen 2.5 billion years ago, Nature, 448, 1033,
https://doi.org/10.1038/nature06058, 2007. a
Lechler, M., Pogge von Strandmann, P. A., Jenkyns, H. C., Prosser, G., and Parente, M.: Lithium-isotope evidence for enhanced silicate weathering during OAE 1a (Early Aptian Selli event), Earth Planet. Sc. Lett., 432, 210–222, 2015. a
Lemarchand, E., Chabaux, F., Vigier, N., Millot, R., and Pierret, M.-C.: Lithium isotope systematics in a forested granitic catchment (Strengbach, Vosges Mountains, France), Geochim. Cosmochim. Ac., 74, 4612–4628, https://doi.org/10.1016/j.gca.2010.04.057, 2010. a
Lenton, T. M., Marsh, R., Price, A. R., Lunt, D. J., Aksenov, Y., Annan, J. D., Cooper-Chadwick, T., Cox, S. J., Edwards, N. R., Goswami, S., Hargreaves, J. C., Harris, P. P., Jiao, Z., Livina, V. N., Payne, A. J., Rutt, I. C., Shepherd, J. G., Valdes, P. J., Williams, G., Williamson, M. S., and Yool, A.: Effects of atmospheric dynamics and ocean resolution on bi-stability of the thermohaline circulation examined using the Grid ENabled Integrated Earth system modelling (GENIE) framework, Clim. Dynam., 29, 591–613, 2007. a
Levasseur, S., Birck, J.-L., and Allegre, C.: The osmium riverine flux and the oceanic mass balance of osmium, Earth Planet. Sc. Lett., 174, 7–23, 1999. a
Li, G., Ji, J., Chen, J., and Kemp, D. B.: Evolution of the Cenozoic carbon cycle: The roles of tectonics and CO2 fertilization, Global Biogeochem. Cy., 23, GB1009, https://doi.org/10.1029/2008GB003220, 2009. a
Lin, J., Liu, Y., Hu, Z., Yang, L., Chen, K., Chen, H., Zong, K., and Gao, S.: Accurate determination of lithium isotope ratios by MC-ICP-MS without strict matrix-matching by using a novel washing method, J. Anal. Atom. Spectrom., 31, 390–397, https://doi.org/10.1039/C5JA00231A, 2016. a, b, c
Loveley, M. R., Marcantonio, F., Wisler, M. M., Hertzberg, J. E., Schmidt, M. W., and Lyle, M.: Millennial-scale iron fertilization of the eastern equatorial Pacific over the past 100,000 years, Nature Geoscience, 10, 760–764, https://doi.org/10.1038/ngeo3024, 2017. a
Lu, X., Kendall, B., Stein, H. J., and Hannah, J. L.: Temporal record of osmium concentrations and 187Os/188Os in organic-rich mudrocks: Implications for the osmium geochemical cycle and the use of osmium as a paleoceanographic tracer, Geochim. Cosmochim. Ac., 216, 221–241, https://doi.org/10.1016/j.gca.2017.06.046, 2017. a, b, c, d, e, f, g, h, i, j
Marriott, C. S., Henderson, G. M., Belshaw, N. S., and Tudhope, A. W.: Temperature dependence of δ7Li, δ44Ca and
Martin, J. H.: Glacial-interglacial CO2 change: The iron hypothesis, Paleoceanography, 5, 1–13, https://doi.org/10.1029/PA005i001p00001, 1990. a
Martínez-Garcia, A., Rosell-Melé, A., Jaccard, S. L., Geibert, W., Sigman, D. M., and Haug, G. H.: Southern Ocean dust–climate coupling over the past four million years, Nature, 476, 312–315, https://doi.org/10.1038/nature10310, 2011. a
Mason, E., Edmonds, M., and Turchyn, A. V.: Remobilization of crustal carbon may dominate volcanic arc emissions, Science, 357, 290–294, https://doi.org/10.1126/science.aan5049, 2017. a
Menzies, M. and Seyfried Jr., W.: Basalt-seawater interaction: trace element and strontium isotopic variations in experimentally altered glassy basalt, Earth Planet. Sc. Lett., 44, 463–472, https://doi.org/10.1016/0012-821X(79)90084-0, 1979. a
Milliman, J. D.: Production and accumulation of calcium carbonate in the ocean: budget of a nonsteady state, Global Biogeochem. Cy., 7, 927–957, https://doi.org/10.1029/93GB02524, 1993. a, b, c
Milliman, J. D. and Farnsworth, K. L.: River discharge to the coastal ocean: a global synthesis, Cambridge University Press, Cambridge University, ISBN: 9780511781247, 2013. a
Millot, R., Guerrot, C., and Vigier, N.: Accurate and high-precision measurement of lithium isotopes in two reference materials by MC-ICP-MS, Geostand. Geoanal. Res., 28, 153–159, https://doi.org/10.1111/j.1751-908X.2004.tb01052.x, 2004. a, b, c
Millot, R., Vigier, N., and Gaillardet, J.: Behaviour of lithium and its isotopes during weathering in the Mackenzie Basin, Canada, Geochim. Cosmochim. Ac., 74, 3897–3912, https://doi.org/10.1016/j.gca.2010.04.025, 2010. a, b
Mills, B., Daines, S. J., and Lenton, T. M.: Changing tectonic controls on the long-term carbon cycle from Mesozoic to present, Geochem. Geophy. Geosy., 15, 4866–4884, https://doi.org/10.1002/2014GC005530, 2014. a
Mokadem, F., Parkinson, I. J., Hathorne, E. C., Anand, P., Allen, J. T., and Burton, K. W.: High-precision radiogenic strontium isotope measurements of the modern and glacial ocean: Limits on glacial–interglacial variations in continental weathering, Earth Planet. Sc. Lett., 415, 111–120, https://doi.org/10.1016/j.epsl.2015.01.036, 2015. a, b, c, d, e, f
Monteiro, F., Pancost, R., Ridgwell, A., and Donnadieu, Y.: Nutrients as the dominant control on the spread of anoxia and euxinia across the Cenomanian-Turonian oceanic anoxic event (OAE2): Model-data comparison, Paleoceanography, 27, PA4209, https://doi.org/10.1029/2012PA002351, 2012. a
Moriguti, T. and Nakamura, E.: High-yield lithium separation and the precise isotopic analysis for natural rock and aqueous samples, Chem. Geol., 145, 91–104, https://doi.org/10.1016/S0009-2541(97)00163-0, 1998. a, b, c
Müller, M. N., Krabbenhöft, A., Vollstaedt, H., Brandini, F., and Eisenhauer, A.: Stable isotope fractionation of strontium in coccolithophore calcite: Influence of temperature and carbonate chemistry, Geobiology, 16, 297–306, https://doi.org/10.1111/gbi.12276, 2018. a
Murphy, M. J., Porcelli, D., Pogge von Strandmann, P. A., Hirst, C. A., Kutscher, L., Katchinoff, J. A., Mörth, C.-M., Maximov, T., and Andersson, P. S.: Tracing silicate weathering processes in the permafrost-dominated Lena River watershed using lithium isotopes, Geochim. Cosmochim. Ac., 245, 154–171, https://doi.org/10.1016/j.gca.2018.10.024, 2019. a, b, c
Naafs, B. D. A., Monteiro, F. M., Pearson, A., Higgins, M. B., Pancost, R. D., and Ridgwell, A.: Fundamentally different global marine nitrogen cycling in response to severe ocean deoxygenation, P. Natl. Acad. Sci. USA, 116, 24979–24984, 2019. a
Nägler, T. F., Eisenhauer, A., Müller, A., Hemleben, C., and Kramers, J.: The δ44Ca-temperature calibration on fossil and cultured Globigerinoides sacculifer: New tool for reconstruction of past sea surface temperatures, Geochem. Geophy. Geosy., 1, 1052, https://doi.org/10.1029/2000GC000091, 2000. a, b
Nanne, J. A., Millet, M.-A., Burton, K. W., Dale, C. W., Nowell, G. M., and Williams, H. M.: High precision osmium stable isotope measurements by double spike MC-ICP-MS and N-TIMS, J. Anal. Atom. Spectrom., 32, 749–765, https://doi.org/10.1039/C6JA00406G, 2017. a
Nier, A. O.: The isotopic constitution of strontium, barium, bismuth, thallium and mercury, Phys. Rev., 54, 275, https://doi.org/10.1103/PhysRev.54.275, 1938. a
Nishio, Y. and Nakai, S.: Accurate and precise lithium isotopic determinations of igneous rock samples using multi-collector inductively coupled plasma mass spectrometry, Anal. Chim. Acta, 456, 271–281, https://doi.org/10.1016/S0003-2670(02)00042-9, 2002. a, b, c
Oxburgh, R.: Residence time of osmium in the oceans, Geochem. Geophy. Geosy., 2, 1018, https://doi.org/10.1029/2000GC000104, 2001. a, b
Panchuk, K., Ridgwell, A., and Kump, L.: Sedimentary response to Paleocene-Eocene Thermal Maximum carbon release: A model-data comparison, Geology, 36, 315–318, https://doi.org/10.1130/G24474A.1, 2008. a, b
Parkinson, I. J., Hammond, S. J., James, R. H., and Rogers, N. W.: High-temperature lithium isotope fractionation: Insights from lithium isotope diffusion in magmatic systems, Earth Planet. Sc. Lett., 257, 609–621, https://doi.org/10.1016/j.epsl.2007.03.023, 2007. a
Pearce, C. R., Parkinson, I. J., Gaillardet, J., Charlier, B. L., Mokadem, F., and Burton, K. W.: Reassessing the stable (
Penniston-Dorland, S., Liu, X.-M., and Rudnick, R. L.: Lithium isotope geochemistry, Rev. Mineral. Geochem., 82, 165–217, https://doi.org/10.2138/rmg.2017.82.6, 2017. a, b, c
Percival, L., Witt, M., Mather, T., Hermoso, M., Jenkyns, H., Hesselbo, S., Al-Suwaidi, A., Storm, M., Xu, W., and Ruhl, M.: Globally enhanced mercury deposition during the end-Pliensbachian extinction and Toarcian OAE: A link to the Karoo–Ferrar Large Igneous Province, Earth Planet. Sc. Lett., 428, 267–280, https://doi.org/10.1016/j.epsl.2015.06.064, 2015. a
Perez-Fernandez, A., Berninger, U.-N., Mavromatis, V., Pogge von Strandmann, P. A., and Oelkers, E.: Ca and Mg isotope fractionation during the stoichiometric dissolution of dolomite at temperatures from 51 to 126 ∘C and 5 bars CO2 pressure, Chem. Geol., 467, 76–88, https://doi.org/10.1016/j.chemgeo.2017.07.026, 2017. a
Peucker-Ehrenbrink, B. and Jahn, B.-m.: Rhenium-osmium isotope systematics and platinum group element concentrations: Loess and the upper continental crust, Geochem. Geophy. Geosy., 2, 1061, https://doi.org/10.1029/2001GC000172, 2001. a
Peucker-Ehrenbrink, B. and Ravizza, G.: The marine osmium isotope record, Terra Nova, 12, 205–219, https://doi.org/10.1046/j.1365-3121.2000.00295.x, 2000. a
Peucker-Ehrenbrink, B., Ravizza, G., and Hofmann, A.: The marine
Peucker-Ehrenbrink, B., Miller, M. W., Arsouze, T., and Jeandel, C.: Continental bedrock and riverine fluxes of strontium and neodymium isotopes to the oceans, Geochem. Geophy. Geosy., 11, Q03016, https://doi.org/10.1029/2009GC002869, 2010. a, b
Phan, T. T., Capo, R. C., Stewart, B. W., Macpherson, G., Rowan, E. L., and Hammack, R. W.: Factors controlling Li concentration and isotopic composition in formation waters and host rocks of Marcellus Shale, Appalachian Basin, Chem. Geol., 420, 162–179, https://doi.org/10.1016/j.chemgeo.2015.11.003, 2016. a, b
Pogge von Strandmann, P. A. and Henderson, G. M.: The Li isotope response to mountain uplift, Geology, 43, 67–70, https://doi.org/10.1130/G36162.1, 2015. a, b, c, d
Pogge von Strandmann, P. A., Burton, K. W., James, R. H., van Calsteren, P., and Gislason, S. R.: Assessing the role of climate on uranium and lithium isotope behaviour in rivers draining a basaltic terrain, Chem. Geol., 270, 227–239, https://doi.org/10.1016/j.chemgeo.2009.12.002, 2010. a, b
Pogge von Strandmann, P. A., Burton, K. W., Opfergelt, S., Eiríksdóttir, E. S., Murphy, M. J., Einarsson, A., and Gislason, S. R.: The effect of hydrothermal spring weathering processes and primary productivity on lithium isotopes: Lake Myvatn, Iceland, Chem. Geol., 445, 4–13, https://doi.org/10.1016/j.chemgeo.2016.02.026, 2016. a
Pogge von Strandmann, P. A., Frings, P. J., and Murphy, M. J.: Lithium isotope behaviour during weathering in the Ganges Alluvial Plain, Geochim.
Cosmochim. Ac., 198, 17–31, https://doi.org/10.1016/j.gca.2016.11.017, 2017. a, b, c
Pogge von Strandmann, P., Jones, M., Schmidt, D., and Murphy, M.: Lithium Isotope Evidence for More Efficient CO2 Drawdown Across the PETM, Goldschmidt Abstracts, 2019a. a
Pogge von Strandmann, P. A., Hendry, K. R., Hatton, J., and Robinson, L.: The response of magnesium, silicon and calcium isotopes to rapidly uplifting and weathering terrains: South Island, New Zealand, Front. Earth Sci., 7, 240, https://doi.org/10.3389/feart.2019.00240, 2019b. a, b, c
Racionero-Gómez, B., Sproson, A., Selby, D., Gannoun, A., Gröcke, D., Greenwell, H., and Burton, K. W.: Osmium uptake, distribution, and
Reinhard, C. T., Olson, S. L., Kirtland Turner, S., Pälike, C., Kanzaki, Y., and Ridgwell, A.: Oceanic and atmospheric methane cycling in the cGENIE Earth system model – release v0.9.14, Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, 2020. a
Richter, E., Hennig, C., Zeimer, U., Weyers, M., Tränkle, G., Reiche, P., Ganschow, S., Uecker, R., and Peters, K.: Freestanding two inch c-plane GaN layers grown on (100) γ-lithium aluminium oxide by hydride vapour phase epitaxy, Phys. Status Solidi (c), 3, 1439–1443, https://doi.org/10.1002/pssc.200565278, 2006. a
Rickaby, R., Schrag, D., Zondervan, I., and Riebesell, U.: Growth rate dependence of Sr incorporation during calcification of Emiliania huxleyi, Global Biogeochem. Cy., 16, 6-1–6-8, https://doi.org/10.1029/2001GB001408, 2002. a
Ridgwell, A. and Hargreaves, J.: Regulation of atmospheric CO2 by deep-sea sediments in an Earth system model, Global Biogeochem. Cy., 21, GB2008, https://doi.org/10.1029/2006GB002764, 2007. a, b, c, d
Ridgwell, A. and Watson, A. J.: Feedback between aeolian dust, climate, and atmospheric CO2 in glacial time, Paleoceanography, 17, 11-1–11-11, 2002. a
Ridgwell, A. and Zeebe, R. E.: The role of the global carbonate cycle in the regulation and evolution of the Earth system, Earth Planet. Sc. Lett., 234, 299–315, https://doi.org/10.1016/j.epsl.2005.03.006, 2005. a, b
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007. a, b, c, d, e, f, g
Ridgwell, A., Reinhard, C., van de Velde, S., Adloff, M., Monteiro, F., Hülse, D., Wilson, J., Ward, B., Vervoort, P., Kirtland Turner, S., and Li, M.: derpycode/cgenie.muffin: Adloff et al. [revised for GMD] (Version v0.9.23), Zenodo [code], https://doi.org/10.5281/zenodo.4776445, 2021a. a
Ridgwell, A., Hülse, D., Peterson, C., Ward, B., sjszas, evansmn, and Jones, R.: derpycode/muffindoc: (Version v0.9.23), Zenodo [code], https://doi.org/10.5281/zenodo.4776512, 2021b. a
Ridgwell, A. J.: Glacial-interglacial perturbations in the global carbon cycle, PhD thesis, University of East Anglia, Norwich, UK, 2001. a
Rollion-Bard, C., Vigier, N., Meibom, A., Blamart, D., Reynaud, S., Rodolfo-Metalpa, R., Martin, S., and Gattuso, J.-P.: Effect of environmental conditions and skeletal ultrastructure on the Li isotopic composition of scleractinian corals, Earth Planet. Sc. Lett., 286, 63–70, https://doi.org/10.1016/j.epsl.2009.06.015, 2009. a
Rosner, M., Ball, L., Peucker-Ehrenbrink, B., Blusztajn, J., Bach, W., and Erzinger, J.: A simplified, accurate and fast method for lithium isotope analysis of rocks and fluids, and δ7Li values of seawater and rock reference materials, Geostand. Geoanal. Res., 31, 77–88, https://doi.org/10.1111/j.1751-908X.2007.00843.x, 2007. a
Rudnick, R. L., Tomascak, P. B., Njo, H. B., and Gardner, L. R.: Extreme lithium isotopic fractionation during continental weathering revealed in saprolites from South Carolina, Chem. Geol., 212, 45–57, https://doi.org/10.1016/j.chemgeo.2004.08.008, 2004. a
Rüggeberg, A., Fietzke, J., Liebetrau, V., Eisenhauer, A., Dullo, W.-C., and Freiwald, A.: Stable strontium isotopes (
Sharma, M., Papanastassiou, D., and Wasserburg, G.: The concentration and isotopic composition of osmium in the oceans, Geochim. Cosmochim. Ac., 61, 3287–3299, https://doi.org/10.1016/S0016-7037(97)00210-X, 1997. a
Sharma, M., Rosenberg, E. J., and Butterfield, D. A.: Search for the proverbial mantle osmium sources to the oceans: Hydrothermal alteration of mid-ocean ridge basalt, Geochim. Cosmochim. Ac., 71, 4655–4667, https://doi.org/10.1016/j.gca.2007.06.062, 2007. a, b, c, d
Sime, N. G., Christina, L., Tipper, E. T., Tripati, A., Galy, A., and Bickle, M. J.: Interpreting the Ca isotope record of marine biogenic carbonates, Geochim. Cosmochim. Ac., 71, 3979–3989, https://doi.org/10.1016/j.gca.2007.06.009, 2007. a
Stevenson, E. I., Hermoso, M., Rickaby, R. E., Tyler, J. J., Minoletti, F., Parkinson, I. J., Mokadem, F., and Burton, K. W.: Controls on stable strontium isotope fractionation in coccolithophores with implications for the marine Sr cycle, Geochim. Cosmochim. Ac., 128, 225–235, https://doi.org/10.1016/j.gca.2013.11.043, 2014. a, b, c, d, e
Stoll, H. M. and Schrag, D. P.: Sr/Ca variations in Cretaceous carbonates: relation to productivity and sea level changes, Palaeogeogr. Palaeocl., 168, 311–336, https://doi.org/10.1016/S0031-0182(01)00205-X, 2001. a
Suchet, P. A. and Probst, J.-L.: A global model for present-day atmospheric/soil CO2 consumption by chemical erosion of continental rocks (GEM-CO2), Tellus B, 47, 273–280, 1995. a
Talley, L. D.: Salinity patterns in the ocean, in: The Earth system: physical and chemical dimensions of global environmental change, edited by: MacCracken, M. C., Perry, J. S., and Munn, T., John Wiley & Sons, Ltd Chichester, England, 1, 629–640, 2002. a
Tang, J., Köhler, S. J., and Dietzel, M.:
Tejada, M. L. G., Suzuki, K., Kuroda, J., Coccioni, R., Mahoney, J. J., Ohkouchi, N., Sakamoto, T., and Tatsumi, Y.: Ontong Java Plateau eruption as a trigger for the early Aptian oceanic anoxic event, Geology, 37, 855–858, https://doi.org/10.1130/G25763A.1, 2009. a, b
Them, T. R., Gill, B. C., Selby, D., Gröcke, D. R., Friedman, R. M., and Owens, J. D.: Evidence for rapid weathering response to climatic warming during the Toarcian Oceanic Anoxic Event, Scientific Reports, 7, 1–10, https://doi.org/10.1038/s41598-017-05307-y, 2017. a
Tipper, E. T., Galy, A., and Bickle, M. J.: Calcium and magnesium isotope systematics in rivers draining the Himalaya-Tibetan-Plateau region: Lithological or fractionation control?, Geochim. Cosmochim. Ac., 72, 1057–1075, https://doi.org/10.1016/j.gca.2007.11.029, 2008. a
Tipper, E. T., Schmitt, A.-D., and Gussone, N.: Global Ca cycles: coupling of continental and oceanic processes, in: Calcium Stable Isotope Geochemistry, Springer, Berlin, Heidelberg, 173–222, 2016. a
Tomascak, P. B., Carlson, R. W., and Shirey, S. B.: Accurate and precise determination of Li isotopic compositions by multi-collector sector ICP-MS, Chem. Geol., 158, 145–154, https://doi.org/10.1016/S0009-2541(99)00022-4, 1999. a, b, c
Turekian, K. K., Sharma, M., and Gordon, G. W.: The behavior of natural and anthropogenic osmium in the Hudson River–Long Island Sound estuarine system, Geochim. Cosmochim. Ac., 71, 4135–4140, 2007. a
Turner, S. K. and Ridgwell, A.: Development of a novel empirical framework for interpreting geological carbon isotope excursions, with implications for the rate of carbon injection across the PETM, Earth Planet. Sc. Lett., 435, 1–13, https://doi.org/10.1016/j.epsl.2015.11.027, 2016. a
van de Velde, S. J., Hülse, D., Reinhard, C. T., and Ridgwell, A.: Iron and sulfur cycling in the cGENIE.muffin Earth system model (v0.9.21), Geosci. Model Dev., 14, 2713–2745, https://doi.org/10.5194/gmd-14-2713-2021, 2021. a
Vance, D., Teagle, D. A., and Foster, G. L.: Variable Quaternary chemical weathering fluxes and imbalances in marine geochemical budgets, Nature, 458, 493–496, https://doi.org/10.1038/nature07828, 2009. a, b
Veizer, J.: Strontium isotopes in seawater through time, Annu. Rev. Earth Pl. Sc., 17, 141–167, https://doi.org/10.1146/annurev.ea.17.050189.001041, 1989. a
Vervoort, P., Adloff, M., Greene, S., and Turner, S. K.: Negative carbon isotope excursions: an interpretive framework, Environ. Res. Lett., 14, 085014, https://doi.org/10.1088/1748-9326/ab3318, 2019. a
Vigier, N. and Goddéris, Y.: A new approach for modeling Cenozoic oceanic lithium isotope paleo-variations: the key role of climate, Clim. Past, 11, 635–645, https://doi.org/10.5194/cp-11-635-2015, 2015. a
Vollstaedt, H., Eisenhauer, A., Wallmann, K., Böhm, F., Fietzke, J., Liebetrau, V., Krabbenhöft, A., Farkaš, J., Tomašovýh, A., Raddatz, J., and Veizer, J.: The Phanerozoic
Wakaki, S., Obata, H., Tazoe, H., and Ishikawa, T.: Precise and accurate analysis of deep and surface seawater Sr stable isotopic composition by double-spike thermal ionization mass spectrometry, Geochem. J., 51, 227–239, https://doi.org/10.2343/geochemj.2.0461, 2017.
a, b, c, d
Ward, B. A., Wilson, J. D., Death, R. M., Monteiro, F. M., Yool, A., and Ridgwell, A.: EcoGEnIE 1.0: plankton ecology in the cGEnIE Earth system model, Geosci. Model Dev., 11, 4241–4267, https://doi.org/10.5194/gmd-11-4241-2018, 2018. a
Weynell, M., Wiechert, U., and Schuessler, J. A.: Lithium isotopes and implications on chemical weathering in the catchment of Lake Donggi Cona, northeastern Tibetan Plateau, Geochim. Cosmochim. Ac., 213, 155–177, https://doi.org/10.1016/j.gca.2017.06.026, 2017. a, b
Woodhouse, O., Ravizza, G., Falkner, K. K., Statham, P., and Peucker-Ehrenbrink, B.: Osmium in seawater: vertical profiles of concentration and isotopic composition in the eastern Pacific Ocean, Earth
Planet. Sci. Lett., 173, 223–233, https://doi.org/10.1016/S0012-821X(99)00233-2, 1999. a, b, c, d, e, f, g
You, C.-F. and Chan, L.-H.: Precise determination of lithium isotopic composition in low concentration natural samples, Geochim. Cosmochim. Ac., 60, 909–915, https://doi.org/10.1016/0016-7037(96)00003-8, 1996. a, b, c
Zhu, P. and Macdougall, J. D.: Calcium isotopes in the marine environment and the oceanic calcium cycle, Geochim. Cosmochim. Ac., 62, 1691–1698, https://doi.org/10.1016/S0016-7037(98)00110-0, 1998. a
Short summary
We present the first representation of the trace metals Sr, Os, Li and Ca in a 3D Earth system model (cGENIE). The simulation of marine metal sources (weathering, hydrothermal input) and sinks (deposition) reproduces the observed concentrations and isotopic homogeneity of these metals in the modern ocean. With these new tracers, cGENIE can be used to test hypotheses linking these metal cycles and the cycling of other elements like O and C and simulate their dynamic response to external forcing.
We present the first representation of the trace metals Sr, Os, Li and Ca in a 3D Earth system...
