Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1729-2024
© Author(s) 2024. 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-17-1729-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
27 Feb 2024
Model description paper |
| 27 Feb 2024
| 27 Feb 2024
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Aaron A. Naidoo-Bagwell
CORRESPONDING AUTHOR
Department of Geology, Lund University, Lund, Sweden
School of Geographical Sciences, BRIDGE, University of Bristol, Bristol, UK
Fanny M. Monteiro
CORRESPONDING AUTHOR
School of Geographical Sciences, BRIDGE, University of Bristol, Bristol, UK
Katharine R. Hendry
School of Earth Sciences, University of Bristol, Bristol, UK
Polar Oceans Team, British Antarctic Survey, Cambridge, UK
Scott Burgan
Met Office, Exeter, UK
Jamie D. Wilson
School of Earth Sciences, University of Bristol, Bristol, UK
Department of Earth, Ocean and Ecological Sciences, University of Liverpool, Liverpool, UK
Ben A. Ward
School of Ocean and Earth Science, University of Southampton, Waterfront Campus, Southampton, UK
Andy Ridgwell
Department of Earth and Planetary Sciences, University of California, Riverside, California, USA
Daniel J. Conley
Department of Geology, Lund University, Lund, Sweden
Related authors
No articles found.
David A. Stappard, Jamie D. Wilson, Andrew Yool, and Toby Tyrrell
EGUsphere, https://doi.org/10.5194/egusphere-2025-436, https://doi.org/10.5194/egusphere-2025-436, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This research explores nutrient limitations in oceanic primary production. While traditional experiments identify the immediate limiting nutrient at specific locations, this study aims to identify the ultimate limiting nutrient (ULN), which governs long-term productivity. A mathematical model incorporating nitrogen, phosphorus, and iron nutrient cycles is used. The model's results are compared with ocean observational data to assess its effectiveness in investigating the ULN.
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.
Isabell Hochfeld, Ben A. Ward, Anke Kremp, Juliane Romahn, Alexandra Schmidt, Miklós Bálint, Lutz Becks, Jérôme Kaiser, Helge W. Arz, Sarah Bolius, Laura S. Epp, Markus Pfenninger, Christopher A. Klausmeier, Elena Litchman, and Jana Hinners
EGUsphere, https://doi.org/10.5194/egusphere-2024-3297, https://doi.org/10.5194/egusphere-2024-3297, 2024
Short summary
Short summary
Marine ecosystem models (MEMs) are valuable for assessing the threats of global warming to biodiversity and ecosystem functioning, but their predictions vary widely. We argue that MEMs should consider evolutionary processes and undergo independent validation. Here, we present a novel framework for MEM development using validation data from sediment archives, which map long-term environmental and evolutionary change. Our approach is a crucial step towards improving the predictive power of MEMs.
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.
Giulia Lodi, Julia Cooke, Rebecca A. Pickering, Lucie Cassarino, Mike Murray-Hudson, Keotshephile Mosimane, and Daniel J. Conley
EGUsphere, https://doi.org/10.5194/egusphere-2024-225, https://doi.org/10.5194/egusphere-2024-225, 2024
Preprint archived
Short summary
Short summary
Papyrus, Cyperus papyrus, is abundant in the Okavango Delta. We explored nutrient and Silicon (Si) isotopes distribution in papyrus to learn more about how this species affects nutrient cycles which are still moderately understood in Botswana. We found large amounts of Si in roots, rhizomes, stems and umbels. We showed that this plant takes up lighter Si isotopes and deposits lighter isotopes first, starting in the roots, leading to an enrichment in heavy isotopes along the transpiration stream.
Anna Belcher, Sian F. Henley, Katharine Hendry, Marianne Wootton, Lisa Friberg, Ursula Dallman, Tong Wang, Christopher Coath, and Clara Manno
Biogeosciences, 20, 3573–3591, https://doi.org/10.5194/bg-20-3573-2023, https://doi.org/10.5194/bg-20-3573-2023, 2023
Short summary
Short summary
The oceans play a crucial role in the uptake of atmospheric carbon dioxide, particularly the Southern Ocean. The biological pumping of carbon from the surface to the deep ocean is key to this. Using sediment trap samples from the Scotia Sea, we examine biogeochemical fluxes of carbon, nitrogen, and biogenic silica and their stable isotope compositions. We find phytoplankton community structure and physically mediated processes are important controls on particulate fluxes to the deep ocean.
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.
Michael J. Whitehouse, Katharine R. Hendry, Geraint A. Tarling, Sally E. Thorpe, and Petra ten Hoopen
Earth Syst. Sci. Data, 15, 211–224, https://doi.org/10.5194/essd-15-211-2023, https://doi.org/10.5194/essd-15-211-2023, 2023
Short summary
Short summary
We present a database of Southern Ocean macronutrient, temperature and salinity measurements collected on 20 oceanographic cruises between 1980 and 2009. Vertical profiles and underway surface measurements were collected year-round as part of an integrated ecosystem study. Our data provide a novel view of biogeochemical cycling in biologically productive regions across a critical period in recent climate history and will contribute to a better understanding of the drivers of primary production.
James P. J. Ward, Katharine R. Hendry, Sandra Arndt, Johan C. Faust, Felipe S. Freitas, Sian F. Henley, Jeffrey W. Krause, Christian März, Allyson C. Tessin, and Ruth L. Airs
Biogeosciences, 19, 3445–3467, https://doi.org/10.5194/bg-19-3445-2022, https://doi.org/10.5194/bg-19-3445-2022, 2022
Short summary
Short summary
The seafloor plays an important role in the cycling of silicon (Si), a key nutrient that promotes marine primary productivity. In our model study, we disentangle major controls on the seafloor Si cycle to better anticipate the impacts of continued warming and sea ice melt in the Barents Sea. We uncover a coupling of the iron redox and Si cycles, dissolution of lithogenic silicates, and authigenic clay formation, comprising a Si sink that could have implications for the Arctic Ocean Si budget.
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.
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.
Markus Adloff, Andy Ridgwell, Fanny M. Monteiro, Ian J. Parkinson, Alexander J. Dickson, Philip A. E. Pogge von Strandmann, Matthew S. Fantle, and Sarah E. Greene
Geosci. Model Dev., 14, 4187–4223, https://doi.org/10.5194/gmd-14-4187-2021, https://doi.org/10.5194/gmd-14-4187-2021, 2021
Short summary
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.
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.
Petra Zahajská, Carolina Olid, Johanna Stadmark, Sherilyn C. Fritz, Sophie Opfergelt, and Daniel J. Conley
Biogeosciences, 18, 2325–2345, https://doi.org/10.5194/bg-18-2325-2021, https://doi.org/10.5194/bg-18-2325-2021, 2021
Short summary
Short summary
The drivers of high accumulation of single-cell siliceous algae (diatoms) in a high-latitude lake have not been fully characterized before. We studied silicon cycling of the lake through water, radon, silicon, and stable silicon isotope balances. Results showed that groundwater brings 3 times more water and dissolved silica than the stream inlet. We demonstrate that groundwater discharge and low sediment deposition have driven the high diatom accumulation in the studied lake in the past century.
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.
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.
Johanna Stadmark, Claudia Jesus-Rydin, and Daniel J. Conley
Adv. Geosci., 53, 107–115, https://doi.org/10.5194/adgeo-53-107-2020, https://doi.org/10.5194/adgeo-53-107-2020, 2020
Short summary
Short summary
A similar proportion of women and men that submit applications to for example the European Research Council are successful in receiving funding. However, in this article we show that in all countries women are applying to a lower extent than their proportion of the workforce of researchers in the higher education sector would suggest, and men are therefore allocated disproportionally more research funds. We speculate on potential causes and hope to stimulate future investigations on this topic.
Niels A. G. M. van Helmond, Elizabeth K. Robertson, Daniel J. Conley, Martijn Hermans, Christoph Humborg, L. Joëlle Kubeneck, Wytze K. Lenstra, and Caroline P. Slomp
Biogeosciences, 17, 2745–2766, https://doi.org/10.5194/bg-17-2745-2020, https://doi.org/10.5194/bg-17-2745-2020, 2020
Short summary
Short summary
We studied the removal of phosphorus (P) and nitrogen (N) in the eutrophic Stockholm archipelago (SA). High sedimentation rates and sediment P contents lead to high P burial. Benthic denitrification is the primary nitrate-reducing pathway. Together, these mechanisms limit P and N transport to the open Baltic Sea. We expect that further nutrient load reduction will contribute to recovery of the SA from low-oxygen conditions and that the sediments will continue to remove part of the P and N loads.
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.
Stephanie Dutkiewicz, Pedro Cermeno, Oliver Jahn, Michael J. Follows, Anna E. Hickman, Darcy A. A. Taniguchi, and Ben A. Ward
Biogeosciences, 17, 609–634, https://doi.org/10.5194/bg-17-609-2020, https://doi.org/10.5194/bg-17-609-2020, 2020
Short summary
Short summary
Phytoplankton are an essential component of the marine food web and earth's carbon cycle. We use observations, ecological theory and a unique trait-based ecosystem model to explain controls on patterns of marine phytoplankton biodiversity. We find that different dimensions of diversity (size classes, biogeochemical functional groups, thermal norms) are controlled by a disparate combination of mechanisms. This may explain why previous studies of phytoplankton diversity had conflicting results.
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.
Wytze K. Lenstra, Matthias Egger, Niels A. G. M. van Helmond, Emma Kritzberg, Daniel J. Conley, and Caroline P. Slomp
Biogeosciences, 15, 6979–6996, https://doi.org/10.5194/bg-15-6979-2018, https://doi.org/10.5194/bg-15-6979-2018, 2018
Short summary
Short summary
We show that burial rates of phosphorus (P) in an estuary in the northern Baltic Sea are very high. We demonstrate that at high sedimentation rates, P retention in the sediment is related to the formation of vivianite. With a reactive transport model, we assess the sensitivity of sedimentary vivianite formation. We suggest that enrichments of iron and P in the sediment are linked to periods of enhanced riverine input of Fe, which subsequently strongly enhances P burial in coastal sediments.
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.
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.
Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, https://doi.org/10.5194/bg-14-1647-2017, 2017
Short summary
Short summary
Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
Raquel Vaquer-Sunyer, Heather E. Reader, Saraladevi Muthusamy, Markus V. Lindh, Jarone Pinhassi, Daniel J. Conley, and Emma S. Kritzberg
Biogeosciences, 13, 4751–4765, https://doi.org/10.5194/bg-13-4751-2016, https://doi.org/10.5194/bg-13-4751-2016, 2016
Short summary
Short summary
Nitrogen-rich dissolved organic matter inputs from wastewater treatment plant effluents increased bacterial production and decreased primary production and community respiration. Nutrient amendments and seasonally variable environmental conditions lead to shifts in bacterial community composition. Increases in bacterial production and simultaneous decreases in primary production lead to more carbon being consumed in the microbial loop and reduce its availability to sustain the food web.
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.
C. Lenz, T. Jilbert, D.J. Conley, M. Wolthers, and C.P. Slomp
Biogeosciences, 12, 4875–4894, https://doi.org/10.5194/bg-12-4875-2015, https://doi.org/10.5194/bg-12-4875-2015, 2015
W. Clymans, L. Barão, N. Van der Putten, S. Wastegård, G. Gísladóttir, S. Björck, B. Moine, E. Struyf, and D. J. Conley
Biogeosciences, 12, 3789–3804, https://doi.org/10.5194/bg-12-3789-2015, https://doi.org/10.5194/bg-12-3789-2015, 2015
Short summary
Short summary
Biogenic silica (BSi) is used as a proxy by soil scientists to identify biological effects on the Si cycle and by palaeoecologists to study environmental changes. We show the presence of tephra constituents can make measurements erroneous at low BSi concentrations, with repercussions for soil and palaeoecological studies. However, we also show that glass shards do not produce an identical dissolution signal to that of BSi, meaning they can be distinguished with appropriate experimental setups.
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.
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
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
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
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
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
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)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
From Weather Data to River Runoff: Leveraging Spatiotemporal Convolutional Networks for Comprehensive Discharge Forecasting
Historical Trends and Controlling Factors of Isoprene Emissions in CMIP6 Earth System Models
Modeling Commercial-Scale CO2 Storage in the Gas Hydrate Stability Zone with PFLOTRAN v6.0
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Using feature importance as exploratory data analysis tool on earth system models
CropSuite – 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)
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
Coupled Carbon-Nitrogen Cycle in MAGICC v1.0.0: Model Description and Calibration
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
T&C-CROP: Representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5): Model formulation and validation
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
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.
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.
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.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. 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.
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.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
Short summary
Short summary
In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
Short summary
Short summary
This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
Short summary
Short summary
We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
Short summary
Short summary
In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
Short summary
Short summary
Forecasting river runoff, 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.
Thi Nhu Ngoc Do, Kengo Sudo, Akihiko Ito, Louisa Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2313, https://doi.org/10.5194/egusphere-2024-2313, 2024
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 climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant-climate interactions.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous 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 sub-sea CO2 injection.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
Short summary
Short summary
This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
Short summary
Short summary
Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
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.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
Short summary
Short summary
CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used 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. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The Icosahedral Nonhydrostatic (ICON) Model 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.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
Short summary
Short summary
In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
Short summary
Short summary
Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1941, https://doi.org/10.5194/egusphere-2024-1941, 2024
Short summary
Short summary
We studied the coupled carbon-nitrogen cycle effect in Earth System Models by developing a carbon-nitrogen coupling in a reduced complexity model, MAGICC. Our model successfully emulated the global carbon-nitrogen cycle dynamics seen in CMIP6 complex models. Results indicate consistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100. Our findings suggest that nitrogen deficiency could reduce future land carbon sequestration.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
Short summary
Short summary
This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
Short summary
Short summary
We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
Short summary
Short summary
This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
Short summary
Short summary
The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged 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.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
Short summary
Short summary
We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
Short summary
Short summary
A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Cited articles
Albani, S., Mahowald, N. M., Murphy, L. N., Raiswell, R., Moore, J. K., Anderson, R. F., McGee, D., Bradtmiller, L. I., Delmonte, B., Hesse, P. P., and Mayewski, P. A.: Paleodust variability since the Last Glacial Maximum and implications for iron inputs to the ocean, Geophys. Res. Lett., 43, 3944–3954, https://doi.org/10.1002/2016gl067911, 2016.
Assmy, P., Smetacek, V., Montresor, M., Klaas, C., Henjes, J., Strass, V. H., Arrieta, J. M., Bathmann, U., Berg, G. M., Breitbarth, E., Cisewski, B., Friedrichs, L., Fuchs, N., Herndl, G. J., Jansen, S., Krägefsky, S., Latasa, M., Peeken, I., Röttgers, R., Scharek, R., Schüller, S. E., Steigenberger, S., Webb, A., and Wolf-Gladrow, D.: Thick-shelled, grazer-protected diatoms decouple ocean carbon and silicon cycles in the iron-limited Antarctic Circumpolar Current, P. Natl. Acad. Sci. USA, 110, 20633–20638, https://doi.org/10.1073/pnas.1309345110, 2013.
Banse, K.: Cell volumes, maximal growth rates of unicellular algae and ciliates, and the role of ciliates in the marine pelagial1,2, Limnol. Oceanogr., 27, 1059–1071, https://doi.org/10.4319/lo.1982.27.6.1059, 1982.
Cao, L., Eby, M., Ridgwell, A., Caldeira, K., Archer, D., Ishida, A., Joos, F., Matsumoto, K., Mikolajewicz, U., Mouchet, A., Orr, J. C., Plattner, G.-K., Schlitzer, R., Tokos, K., Totterdell, I., Tschumi, T., Yamanaka, Y., and Yool, A.: The role of ocean transport in the uptake of anthropogenic CO2, Biogeosciences, 6, 375–390, https://doi.org/10.5194/bg-6-375-2009, 2009.
Conley, D. J., Frings, P. J., Fontorbe, G., Clymans, W., Stadmark, J., Hendry, K. R., Marron, A. O., and De La Rocha, C. L.: Biosilicification Drives a Decline of Dissolved Si in the Oceans through Geologic Time, Front. Mar. Sci., 4, 397, https://doi.org/10.3389/fmars.2017.00397, 2017.
Crichton, K. A., Wilson, J. D., Ridgwell, A., and Pearson, P. N.: Calibration of temperature-dependent ocean microbial processes in the cGENIE.muffin (v0.9.13) Earth system model, Geosci. Model Dev., 14, 125–149, https://doi.org/10.5194/gmd-14-125-2021, 2021.
Devries, T. and Weber, T.: The export and fate of organic matter in the ocean: New constraints from combining satellite and oceanographic tracer observations, Global Biogeochem. Cy., 31, 535–555, https://doi.org/10.1002/2016gb005551, 2017.
Dierssen, H. M.: Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate, P. Natl. Acad. Sci. USA, 107, 17073–17078, https://doi.org/10.1073/pnas.0913800107, 2010.
Dunne, J. P., Armstrong, R. A., Gnanadesikan, A., and Sarmiento, J. L.: Empirical and mechanistic models for the particle export ratio, Global Biogeochem. Cy., 19, https://doi.org/10.1029/2004gb002390, 2005.
Dutkiewicz, S., Cermeno, P., Jahn, O., Follows, M. J., Hickman, A. E., Taniguchi, D. A. A., and Ward, B. A.: Dimensions of marine phytoplankton diversity, Biogeosciences, 17, 609–634, https://doi.org/10.5194/bg-17-609-2020, 2020.
Falkowski, P. G., Katz, M. E., Knoll, A. H., Quigg, A., Raven, J. A., Schofield, O., and Taylor, F. J. R.: The Evolution of Modern Eukaryotic Phytoplankton, Science, 305, 354–360, https://doi.org/10.1126/science.1095964, 2004.
Field, C. B., Behrenfeld, M. J., Randerson, J. T., and Falkowski, P.: Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components, Science, 281, 237–240, https://doi.org/10.1126/science.281.5374.237, 1998.
Follows, M. J. and Dutkiewicz, S.: Modeling Diverse Communities of Marine Microbes, Annu. Rev. Mar. Sci., 3, 427–451, https://doi.org/10.1146/annurev-marine-120709-142848, 2011.
Follows, M. J., Dutkiewicz, S., Grant, S., and Chisholm, S. W.: Emergent Biogeography of Microbial Communities in a Model Ocean, Science, 315, 1843–1846, https://doi.org/10.1126/science.1138544, 2007.
Friedrichs, M. A. M., Dusenberry, J. A., Anderson, L. A., Armstrong, R. A., Chai, F., Christian, J. R., Doney, S. C., Dunne, J., Fujii, M., Hood, R., McGillicuddy, D. J., Moore, J. K., Schartau, M., Spitz, Y. H., and Wiggert, J. D.: Assessment of skill and portability in regional marine biogeochemical models: Role of multiple planktonic groups, J. Geophys. Res., 112, https://doi.org/10.1029/2006jc003852, 2007.
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O. K., Zweng, M. M., Reagan, J. R., Johnson, D. R., Mishonov, A. V., and Levitus, S.: World ocean atlas 2013. Volume 4, Dissolved inorganic nutrients (phosphate, nitrate, silicate), NOAA Atlas NESDIS, 76, https://doi.org/10.7289/V5J67DWD, 2013.
Hendry, K. R., Marron, A. O., Vincent, F., Conley, D. J., Gehlen, M., Ibarbalz, F. M., Quéguiner, B., and Bowler, C.: Competition between Silicifiers and Non-silicifiers in the Past and Present Ocean and Its Evolutionary Impacts, Front. Mar. Sci., 5, 22, https://doi.org/10.3389/fmars.2018.00022, 2018.
Henson, S. A., Sanders, R., Madsen, E., Morris, P. J., Le Moigne, F., and Quartly, G. D.: A reduced estimate of the strength of the ocean's biological carbon pump, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011gl046735, 2011.
Kiørboe, T., Visser, A., and Andersen, K. H.: A trait-based approach to ocean ecology, ICES J. Mar. Sci., 75, 1849–1863, https://doi.org/10.1093/icesjms/fsy090, 2018.
Kraus, E. B. and Turner, J. S.: A one-dimensional model of the seasonal thermocline II. The general theory and its consequences, Tellus, 19, 98–106, https://doi.org/10.3402/tellusa.v19i1.9753, 1967.
Kriest, I., Khatiwala, S., and Oschlies, A.: Towards an assessment of simple global marine biogeochemical models of different complexity, Prog. Oceanogr., 86, 337–360, https://doi.org/10.1016/j.pocean.2010.05.002, 2010.
Kwiatkowski, L., Yool, A., Allen, J. I., Anderson, T. R., Barciela, R., Buitenhuis, E. T., Butenschön, M., Enright, C., Halloran, P. R., Le Quéré, C., de Mora, L., Racault, M.-F., Sinha, B., Totterdell, I. J., and Cox, P. M.: iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework, Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, 2014.
Lavaud, J., Rousseau, B., and Etienne, A.-L.: General features of photoprotection by energy dissipation in planktonic diatoms (bacillariophyceae)1, J. Phycol., 40, 130–137, https://doi.org/10.1046/j.1529-8817.2004.03026.x, 2004.
Mahowald, N., Kohfeld, K., Hansson, M., Balkanski, Y., Harrison, S. P., Prentice, I. C., Schulz, M., and Rodhe, H.: Dust sources and deposition during the last glacial maximum and current climate: A comparison of model results with paleodata from ice cores and marine sediments, J. Geophys. Res.-Atmos., 104, 15895–15916, https://doi.org/10.1029/1999jd900084, 1999.
Maier-Reimer, E. and Hasselmann, K.: Transport and storage of CO2 in the ocean – an inorganic ocean-circulation carbon cycle model, Clim. Dynam., 2, 63–90, https://doi.org/10.1007/bf01054491, 1987.
Maldonado, M., López-Acosta, M., Sitjà, C., García-Puig, M., Galobart, C., Ercilla, G., and Leynaert, A.: Sponge skeletons as an important sink of silicon in the global oceans, Nat. Geosci., 12, 815–822, https://doi.org/10.1038/s41561-019-0430-7, 2019.
Malviya, S., Scalco, E., Audic, S., Vincent, F., Veluchamy, A., Poulain, J., Wincker, P., Iudicone, D., Vargas, C. D., Bittner, L., Zingone, A., and Bowler, C.: Insights into global diatom distribution and diversity in the world's ocean, P. Natl. Acad. Sci. USA, 113, E1516–E1525, https://doi.org/10.1073/pnas.1509523113, 2016.
Mann, D. G. and Vanormelingen, P.: An Inordinate Fondness? The Number, Distributions, and Origins of Diatom Species, J. Eukaryot. Microbiol., 60, 414–420, https://doi.org/10.1111/jeu.12047, 2013.
Marsh, R., Müller, S. A., Yool, A., and Edwards, N. R.: Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: ”eb_go_gs” configurations of GENIE, Geosci. Model Dev., 4, 957–992, https://doi.org/10.5194/gmd-4-957-2011, 2011.
Matsumoto, K., Rickaby, R., and Tanioka, T.: Carbon Export Buffering and CO2 Drawdown by Flexible Phytoplankton C:N:P Under Glacial Conditions, Paleoceanogr. Paleocl., 35, https://doi.org/10.1029/2019pa003823, 2020.
McKay, M. D., Beckman, R. J., and Conover, W. J.: A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code, Technometrics, 42, 55–61, https://doi.org/10.1080/00401706.2000.10485979, 2000.
Moriceau, B., Gehlen, M., Tréguer, P., Baines, S., Livage, J., and André, L.: Editorial: Biogeochemistry and Genomics of Silicification and Silicifiers, Front. Mar. Sci., 6, https://doi.org/10.3389/fmars.2019.00057, 2019.
Mullin, M. M., Sloan, P. R., and Eppley, R. W.: Relationship between carbon content, cell volume, and area in phytoplankton, Limnol. Oceanogr., 11, 307–311, https://doi.org/10.4319/lo.1966.11.2.0307, 1966.
Nelson, D. M., Tréguer, P., Brzezinski, M. A., Leynaert, A., and Quéguiner, B.: Production and dissolution of biogenic silica in the ocean: Revised global estimates, comparison with regional data and relationship to biogenic sedimentation, Global Biogeochem. Cy., 9, 359–372, https://doi.org/10.1029/95gb01070, 1995.
O'Donnell, D. R., Beery, S. M., and Litchman, E.: Temperature-dependent evolution of cell morphology and carbon and nutrient content in a marine diatom, Limnol. Oceanogr., 66, 4334–4346, https://doi.org/10.1002/lno.11964, 2021.
Quere, C. L., Harrison, S. P., Colin Prentice, I., Buitenhuis, E. T., Aumont, O., Bopp, L., Claustre, H., Cotrim Da Cunha, L., Geider, R., Giraud, X., Klaas, C., Kohfeld, K. E., Legendre, L., Manizza, M., Platt, T., Rivkin, R. B., Sathyendranath, S., Uitz, J., Watson, A. J., and Wolf-Gladrow, D.: Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models, Glob. Change Biol., 0, 051013014052005, https://doi.org/10.1111/j.1365-2486.2005.1004.x, 2005.
Reinhard, C. T., Planavsky, N. J., Ward, B. A., Love, G. D., Le Hir, G., and Ridgwell, A.: The impact of marine nutrient abundance on early eukaryotic ecosystems, Geobiology, 18, 139–151, https://doi.org/10.1111/gbi.12384, 2020.
Ridgwell, A: The Bumper Book of .muffins, https://www.seao2.info/cgenie/docs/muffin.pdf, last access: 22 November 2022
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.
Ridgwell, A. J., Watson, A. J., and Archer, D. E.: Modeling the response of the oceanic Si inventory to perturbation, and consequences for atmospheric CO2, Global Biogeochem. C., 16, 19-11–19-25, https://doi.org/10.1029/2002gb001877, 2002.
Ridgwell, A., Reinhard, C., van de Velde, S., Adloff, M., Monteiro, F., Kanzaki, Y., Vervoort, P., Ward, B., Hülse, D., Wilson, J., Naidoo-Bagwell, A., Turner, K., and Li, M.: derpycode/cgenie.muffin: v0.9.47 (v0.9.47), Zenodo [code], https://doi.org/10.5281/zenodo.10223295, 2023.
Séférian, R., Berthet, S., Yool, A., Palmiéri, J., Bopp, L., Tagliabue, A., Kwiatkowski, L., Aumont, O., Christian, J., Dunne, J., Gehlen, M., Ilyina, T., John, J. G., Li, H., Long, M. C., Luo, J. Y., Nakano, H., Romanou, A., Schwinger, J., Stock, C., Santana-Falcón, Y., Takano, Y., Tjiputra, J., Tsujino, H., Watanabe, M., Wu, T., Wu, F., and Yamamoto, A.: Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, 6, 95–119, https://doi.org/10.1007/s40641-020-00160-0, 2020.
Tagliabue, A., Aumont, O., Death, R., Dunne, J. P., Dutkiewicz, S., Galbraith, E., Misumi, K., Moore, J. K., Ridgwell, A., Sherman, E., Stock, C., Vichi, M., Völker, C., and Yool, A.: How well do global ocean biogeochemistry models simulate dissolved iron distributions?, Global Biogeochem. Cy., 30, 149–174, https://doi.org/10.1002/2015gb005289, 2016.
Tanioka, T., Garcia, C., Larkin, A., Garcia, N., Fagan, A., and Martiny, A.: Global patterns and drivers of C:N:P in marine ecosystems, Research Square, https://doi.org/10.21203/rs.3.rs-1344335/v1, 2022.
Teng, Y.-C., Primeau, F. W., Moore, J. K., Lomas, M. W., and Martiny, A. C.: Global-scale variations of the ratios of carbon to phosphorus in exported marine organic matter, Nat. Geosci., 7, 895–898, https://doi.org/10.1038/ngeo2303, 2014.
Tréguer, P., Bowler, C., Moriceau, B., Dutkiewicz, S., Gehlen, M., Aumont, O., Bittner, L., Dugdale, R., Finkel, Z., Iudicone, D., Jahn, O., Guidi, L., Lasbleiz, M., Leblanc, K., Levy, M., and Pondaven, P.: Influence of diatom diversity on the ocean biological carbon pump, Nat. Geosci., 11, 27–37, https://doi.org/10.1038/s41561-017-0028-x, 2018.
Tréguer, P. J., Sutton, J. N., Brzezinski, M., Charette, M. A., Devries, T., Dutkiewicz, S., Ehlert, C., Hawkings, J., Leynaert, A., Liu, S. M., Llopis Monferrer, N., López-Acosta, M., Maldonado, M., Rahman, S., Ran, L., and Rouxel, O.: Reviews and syntheses: The biogeochemical cycle of silicon in the modern ocean, Biogeosciences, 18, 1269–1289, https://doi.org/10.5194/bg-18-1269-2021, 2021.
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.
Van Tol, H. M., Irwin, A. J., and Finkel, Z. V.: Macroevolutionary trends in silicoflagellate skeletal morphology: the costs and benefits of silicification, Paleobiology, 38, 391–402, https://doi.org/10.1666/11022.1, 2012.
Wang, W.-L., Moore, J. K., Martiny, A. C., and Primeau, F. W.: Convergent estimates of marine nitrogen fixation, Nature, 566, 205–211, https://doi.org/10.1038/s41586-019-0911-2, 2019.
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.
Watterson, I. G.: Improved Simulation of Regional Climate by Global Models with Higher Resolution: Skill Scores Correlated with Grid Length, J. Climate, 28, 5985–6000, https://doi.org/10.1175/jcli-d-14-00702.1, 2015.
Wilson, J. D., Barker, S., and Ridgwell, A.: Assessment of the spatial variability in particulate organic matter and mineral sinking fluxes in the ocean interior: Implications for the ballast hypothesis, Global Biogeochem. Cy., 26, https://doi.org/10.1029/2012gb004398, 2012.
Wilson, J. D., Monteiro, F. M., Schmidt, D. N., Ward, B. A., and Ridgwell, A.: Linking Marine Plankton Ecosystems and Climate: A New Modeling Approach to the Warm Early Eocene Climate, Paleoceanogr. Paleocl., 33, 1439–1452, https://doi.org/10.1029/2018pa003374, 2018.
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies, Geosci. Model Dev., 6, 1767–1811, https://doi.org/10.5194/gmd-6-1767-2013, 2013.
Zhang, S., Liu, H., Ke, Y., and Li, B.: Effect of the Silica Content of Diatoms on Protozoan Grazing, Front. Mar. Sci., 4, 202, https://doi.org/10.3389/fmars.2017.00202, 2017.
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.
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton...
