Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5687-2020
© Author(s) 2020. 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-13-5687-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
20 Nov 2020
Development and technical paper |
| 20 Nov 2020
| 20 Nov 2020
Oceanic and atmospheric methane cycling in the cGENIE Earth system model – release v0.9.14
Christopher T. Reinhard
CORRESPONDING AUTHOR
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA 30332, USA
NASA Astrobiology Institute, Alternative Earths Team, Riverside, CA, USA
NASA Nexus for Exoplanet System Science (NExSS) Upside-Down Biospheres
Team, Georgia Institute of Technology, Atlanta, GA, USA
Stephanie L. Olson
NASA Astrobiology Institute, Alternative Earths Team, Riverside, CA, USA
Department of Geophysical Sciences, University of Chicago, Chicago, IL
60637, USA
Department of Earth, Atmospheric, and Planetary Science, Purdue
University, West Lafayette, IN 47907, USA
Sandra Kirtland Turner
Department of Earth and Planetary Sciences, University of California,
Riverside, Riverside, CA 92521, USA
Cecily Pälike
MARUM Center for Marine Environmental Sciences, University of Bremen, Bremen,
Germany
Yoshiki Kanzaki
Department of Earth and Planetary Sciences, University of California,
Riverside, Riverside, CA 92521, USA
Andy Ridgwell
Department of Earth and Planetary Sciences, University of California,
Riverside, Riverside, CA 92521, USA
Related authors
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
Short summary
Short summary
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
Short summary
Short summary
Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
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.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
Keyi Cheng, Andy Ridgwell, and Dalton Hardisty
EGUsphere, https://doi.org/10.5194/egusphere-2024-677, https://doi.org/10.5194/egusphere-2024-677, 2024
Short summary
Short summary
The carbonate paleoredox proxy, I:Ca, has shown its potential in quantifying 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 observation, and then tested its ability to estimate I:Ca in the Cretaceous ocean. Our study implies cGENIE’s potential in quantifying redox change in the past using the I:Ca proxy.
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.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
Short summary
Short summary
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
Short summary
Short summary
Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
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.
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.
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.
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.
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.
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
Biogeosciences
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Quantifying the role of ozone-caused damage to vegetation in the Earth system: A new parameterization scheme for photosynthetic and stomatal responses
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
Exploring the Potential of History Matching for Land Surface Model Calibration
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
Using Deep Learning to integrate paleoclimate and global biogeochemistry over Phanerozoic time
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Assimilation of Carbonyl Sulfide (COS) fluxes within the adjoint-based data assimilation system–Nanjing University Carbon Assimilation System (NUCAS v1.0)
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling boreal forest’s mineral soil and peat C stock dynamics with Yasso07 model coupled with updated moisture modifier
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-6, https://doi.org/10.5194/gmd-2024-6, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study introduces a new scheme to simulate surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal response to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2996, https://doi.org/10.5194/egusphere-2023-2996, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. Here we test a technique called “History matching” against more common approaches. This method adapts well to these models, helping better understand how they work and therefore how to make them more realistic.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Dongyu Zheng, Andrew Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-230, https://doi.org/10.5194/gmd-2023-230, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study uses a deep learning method to enhance the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model for more accurate predictions of climate shifts. The method may be critical in developing new fully-continuous methods that are able to translate over a moving continental surface in deep time with high-resolution at a reasonable computational expense.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-242, https://doi.org/10.5194/gmd-2023-242, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems as the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-238, https://doi.org/10.5194/gmd-2023-238, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through “data assimilation”, which blends numerical models and observations. Here, we present EAT, a flexible and efficient testbed that allows any scientist to explore and further develop the state-of-the-art in data assimilation.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1955, https://doi.org/10.5194/egusphere-2023-1955, 2023
Short summary
Short summary
In this work, Nanjing University Carbon Assimilation System (NUCAS) was developed. Data assimilation experiments were conducted to demonstrate the robustness and to investigate the feasibility and applicability of NUCAS. The assimilation of COS significantly improved the model performance in gross primary productivity, sensible heat, latent heat and even soil moisture, demonstrating that COS can provide strong constraints on parameters relevant to water, energy and carbon processes.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Stefano Manzoni, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
EGUsphere, https://doi.org/10.5194/egusphere-2023-1523, https://doi.org/10.5194/egusphere-2023-1523, 2023
Short summary
Short summary
Improving representation of peatlands in Earth system models (ESMs) (e.g., in Yasso soil C model coupled with JSBACH model) is rare. We updated Yasso07 moisture dependency for applications on both the mineral soils and peatlands of boreal forest. Our moisture function improved the simulated peatland C stocks and CO2 dynamics. However, due to nature of the measurements used for Bayesian MCMC data assimilation, it contrasts with functions in other ESMs (see graphical abstract).
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
Short summary
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
Short summary
Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
Short summary
Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
Short summary
Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
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.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
Short summary
Short summary
In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Short summary
Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Cited articles
Archer, D. and Buffett, B.: Time-dependent response of the global ocean
clathrate reservoir to climatic and anthropogenic forcing, Geochem.
Geophys., Geosys., 6,
GB1008, https://doi.org/10.1029/2004GC000854, 2005.
Archer, D., Buffett, B., and Brovkin, V.: Ocean methane hydrates as a slow tipping point in the global carbon cycle, P. Natl. Acad. Sci. USA, 106, 20596–20601, 2009.
Bartdorff, O., Wallmann, K., Latif, M., and Semenov, V.: Phanerozoic
evolution of atmospheric methane, Global Biogeochem. Cy., 22, GB1008,
https://doi.org/10.1029/2007GB002985, 2008.
Beerling, D., Berner, R. A., Mackenzie, F. T., Harfoot, M. B., and Pyle, J.
A.: Methane and the CH4-related greenhouse effect over the past 400 million
years, Am. J. Sci., 309, 97–113, 2009.
Bender, M. and Conrad, R.: Kinetics of CH4 oxidation in oxic soils exposed to ambient air or high CH4 mixing ratios, Fems. Microbiol. Lett., 101, 261–270, 1992.
Bender, M. and Conrad, R.: Kinetics of methane oxidation in oxic soils, Chemosphere, 26, 687–696, 1993.
Berner, R. A.: Activity Coefficients of Bicarbonate Carbonate and Calcium
Ions in Sea Water, Geochim. Cosmochim. Ac., 29, 947–965, 1965.
Bethke, C. M., Ding, D., Jin, Q., and Sanford, R. A.: Origin of
microbiological zoning in groundwater flows, Geology, 36, 739–742, 2008.
Bianchi, D., Weber, T. S., Kiko, R., and Deutsch, C.: Global niche of marine
anaerobic metabolisms expanded by particle microenvironments, Nat. Geosci.,
11, 263–268, 2018.
Bjerrum, C. J. and Canfield, D. E.: Towards a quantitative understanding of the late Neoproterozoic carbon cycle, P. Natl. Acad. Sci. USA, 108, 5542–5547, 2011.
Bock, M., Schmitt, J., Beck, J., Seth, B., Chappellaz, J., and Fischer, H.:
Glacial/interglacial wetland, biomass burning, and geologic methane
emissions constrained by dual stable isotopic CH4 ice core records,
P. Natl. Acad. Sci. USA, 114, E5778–E5786, 2017.
Boetius, A., Ravenschlag, K., Schubert, C. J., Rickert, D., Widdel, F.,
Gieseke, A., Amann, R., Jørgensen, B. B., Witte, U., and Pfannkuche, O.:
A marine microbial consortium apparently mediating anaerobic oxidation of
methane, Nature, 407, 623–626, 2000.
Boudreau, B. P.: Diagenetic Models and Their Implementation, Springer-Verlag, Berlin, 1996a.
Boudreau, B. P.: A method-of-lines code for carbon and nutrient diagenesis
in aquatic sediments, Comput. Geosci., 22, 479–496, 1996b.
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.
Catling, D. C., Claire, M. W., and Zahnle, K. J.: Anaerobic methanotrophy
and the rise of atmospheric oxygen, Philos. T. R. Soc. A, 365, 1867–1888, 2007.
Chapelle, F. H., McMahon, P. B., Dubrovsky, N. M., Fujii, R. F., Oaksford,
E. T., and Vroblesky, D. A.: Deducing the distribution of terminal
electron-accepting processes in hydrologically diverse groundwater systems,
Water Resour. Res., 31, 359–371, 1995.
Chronopoulou, P.-M., Shelley, F., Pritchard, W. J., Maanoja, S., and Trimmer, M.: Origin and fate of methane in the Eastern Tropical North
Pacific oxygen minimum zone, ISME J., 11, 1386–1399, 2017.
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J.,
Chhabra, A., DeFries, R., Galloway, J., Heimann, M., Jones, C., Le
Quéré, C., Myneni, R. B., Piao, S., and Thornton, P.: Carbon and
Other Biogeochemical Cycles, in: Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A.,
Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge,
467–544, 2013.
Claire, M. W., Catling, D. C., and Zahnle, K. J.: Biogeochemical modelling of the rise in atmospheric oxygen, Geobiology, 4, 239–269, 2006.
Clegg, S. L. and Brimblecombe, P.: The solubility and activity coefficient
of oxygen in salt solutions and brines, Geochim. Cosmochim. Ac., 54,
3315–3328, 1990.
Cramer, S. D.: Solubility of methane in brines from 0 to
300 ∘C, Ind. Eng. Chem. Proc. Dd., 23, 533–538, 1984.
Crespo-Medina, M., Meile, C. D., Hunter, K. S., Diercks, A.-R., Asper, V.
L., Orphan, V. J., Tavormina, P. L., Nigro, L. M., Battles, J. J., Chanton,
J. P., Shiller, A. M., Joung, D.-J., Amon, R. M. W., Bracco, A., Montoya, J.
P., Villareal, T. A., Wood, A. M., and Joye, S. B.: The rise and fall of
methanotrophy following a deepwater oil-well blowout, Nat. Geosci., 7,
423–427, 2014.
Crowe, S. A., Paris, G., Katsev, S., Jones, C., Kim, S., Zerkle, A. L., Nomosatryo, S., Fowle, D. A., Adkins, J. F., Sessions, A. L., Farquhar, J., and Canfield, D. E.: Sulfate was a trace constituent of Archean seawater, Science, 346, 735–739, 2014.
Curtis, G. P.: Comparison of approaches for simulating reactive solute
transport involving organic degredation reactions by multiple terminal
electron acceptors, Comput. Geosci., 29, 319–329, 2003.
Daines, S. J. and Lenton, T. M.: The effect of widespread early aerobic
marine ecosystems on methane cycling and the Great Oxidation, Earth Planet. Sc. Lett., 434, 42–51, 2016.
Dale, A. W., Regnier, P., and Van Cappellen, P.: Bioenergetic controls on
anaerobic oxidation of methane (AOM) in coastal marine sediments: A
theoretical analysis, Am. J. Sci., 306, 246–294, 2006.
Dale, A. W., Regnier, P., Knab, N. J., Jørgensen, B. B., and Van
Cappellen, P.: Anaerobic oxidation of methane (AOM) in marine sediments from
the Skagerrak (Denmark): II. Reaction-transport modeling, Geochim.
Cosmochim. Ac., 72, 2880–2894, 2008.
Dickens, G. R., Castillo, M. M., and Walker, J. C. G.: A blast of gas in the
latest Paleocene: simulating first-order effects of massive dissociation of
oceanic methane hydrate, Geology, 25, 259–262, 1997.
Dickens, G. R.: Rethinking the global carbon cycle with a large, dynamic and
microbially mediated gas hydrate capacitor, Earth Planet. Sc.
Lett., 213, 169–183, 2003.
Doney, S. C., Lindsay, K., Fung, I., and John, J.: Natural variability in a
stable, 1000-yr global coupled climate-carbon cycle simulation, J.
Climate, 19, 3033–3054, 2006.
Duan, Z., Møller, N., Greenberg, J., and Weare, J. H.: The prediction of
methane solubility in natural waters to high ionic strength from 0 to
250∘C and from 0 to 1600 bar, Geochim. Cosmochim.
Ac., 56, 1451–1460, 1992.
Dunfield, P. F. and Conrad, R.: Starvation alters the apparent
half-saturation constant for methane in the Type II methanotroph
Methylocystis strain LR1, Appl. Environ. Microb., 66, 4136–4138, 2000.
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, 2005.
Egger, M., Rasigraf, O., Sapart, C. J., Jilbert, T., Jetten, M. S. M.,
Röckmann, T., van der Veen, C., Banda, N., Kartal, B., Ettwig, K. F.,
and Slomp, C. P.: Iron-mediated anaerobic oxidation of methane in brackish
coastal sediments, Environ. Sci. Technol., 49, 277–283, 2015.
Egger, M., Riedinger, N., Mogollón, J. M., and Jørgensen, B. B.:
Global diffusive fluxes of methane in marine sediments, Nat. Geosci., 11,
421–425, 2018.
Elliot, S., Maltrud, M., Reagan, M., Moridis, G., and Cameron-Smith, P.:
Marine methane cycle simulations for the period of early global warming,
J. Geophys. Res.-Biogeo., 116, G01010, https://doi.org/10.1029/2010JG001300,
2011.
Froelich, P. N., Klinkhammer, G. P., Bender, M. L., Luedtke, N. A., Heath,
G. R., Cullen, D., and Duaphin, P.: Early oxidation of organic matter in
pelagic sediments of the eastern equatorial Atlantic: suboxic diagenesis,
Geochim. Cosmochim. Ac., 43, 1075–1090, 1979.
Goldblatt, C., Lenton, T. M., and Watson, A. J.: Bistability of atmospheric
oxygen and the Great Oxidation, Nature, 443, 683–686, 2006.
Griffies, S. M.: The Gent-McWilliams skew flux, J. Phys.
Oceanogr., 28, 831–841, 1998.
Hanson, R. S. and Hanson, T. E.: Methanotrophic bacteria, Microbiol. Rev., 60, 439–471, 1996.
Haqq-Misra, J., Domagal-Goldman, S. D., Kasting, P. J., and Kasting, J. F.:
A revised, hazy methane greenhouse for the Archean Earth, Astrobiol., 8,
1127–1137, 2008.
Haroon, M. F., Hu, S., Shi, Y., Imelfort, M., Keller, J., Hugenholtz, P.,
Yuan, Z., and Tyson, G. W.: Anaerobic oxidation of methane coupled to
nitrate reduction in a novel archaeal lineage, Nature, 500, 567–570, 2013.
Hayes, J. M.: Global methanotrophy at the Archean-Proterozoic transition,
in: Nobel Symp. 84, Early Life on Earth, edited by: Bengston, S.,
Columbia University Press, New York, 220–236, 1994.
Helz, G. R., Bura-Nakíc, E., Mikac, N., and Ciglenecki, I.: New model
for molybdenum behavior in euxinic waters, Chem. Geol., 284, 323–332,
2011.
Hinrichs, K.-U., Hayes, J. M., Sylva, S. P., Brewer, P. G., and DeLong, E.
F.: Methane-consuming archaebacteria in marine sediments, Nature, 398,
802–805, 1999.
Hinrichs, K.-U.: Microbial fixation of methane carbon at 2.7 Ga: Was an anaerobic mechanism possible?, Geochem. Geophy. Geosy., 3, 1–10, 2002.
Hitchcock, D. R. and Lovelock, J. E.: Life detection by atmospheric analysis, Icarus, 7, 149–159, 1967.
Hoehler, T. M., Alperin, M. J., Albert, D. B., and Martens, C. S.: Field and
laboratory studies of methane oxidation in an anoxic marine sediments:
Evidence for a methanogen-sulfate reducer consortium, Global Biogeochem.
Cy., 8, 451–463, 1994.
Hoehler, T. M., Alperin, M. J., Albert, D. B., and Martens, C. S.: Apparent
minimum free energy requirements for methanogenic Archaean and
sulfate-reducing bacteria in an anoxic marine sediment, Fems. Microbiol. Ecol.,
38, 33–41, 2001.
Hoehler, T. M.: Biological energy requirements as quantitative boundary
conditions for life in the subsurface, Geobiology, 2, 205–215, 2004.
Hunter, S. J., Goldobin, D. S., Haywood, A. M., Ridgwell, A., and Rees, J.
G.: Sensitivity of the global submarine hydrate inventory to scenarios of
future climate change, Earth Planet. Sc. Lett., 367, 105–115,
2013.
Jakobsen, R. and Postma, D.: Redox zoning, rates of sulfate reduction and
interactions with Fe-reduction and methanogenesis in a shallow sandy
aquifer, Rømø, Denmark, Geochim. Cosmochim. Ac., 63, 137–151,
1999.
Jayakumar, D. A., Naqvi, S. W. A., Narvekar, P. V., and George, M. D.:
Methane in coastal and offshore waters of the Arabian Sea, Mar. Chem.,
74, 1–13, 2001.
Jin, Q. and Bethke, C. M.: Predicting the rate of microbial respiration in
geochemical environments, Geochim. Cosmochim. Ac., 69, 1133–1143,
2005.
Jin, Q. and Bethke, C. M.: The thermodynamics and kinetics of microbial
metabolism, Am. J. Sci., 307, 643–677, 2007.
Johnson, K. S.: Carbon dioxide hydration and dehydration kinetics in
seawater, Limnol. Oceanogr., 27, 849–855, 1982.
Kasting, J. F., Zahnle, K. J., and Walker, J. C. G.: Photochemistry of
methane in the Earth's early atmosphere, Precambrian Res., 20, 121–148,
1983.
Kasting, J. F., Pavlov, A. A., and Siefert, J. L.: A coupled
ecosystem-climate model for predicting the methane concentration in the
Archean atmosphere, Origin of life and evolution of the Biosphere, 31,
271–285, 2001.
Kessler, J. D., Valentine, D. L., Redmond, M. C., Du, M., Chan, E. W.,
Mendes, S. D., Quiroz, E. W., Villanueva, C. J., Shusta, S. S., Werra, L.
M., Yvon-Lewis, S. A., and Weber, T. C.: A persistent oxygen anomaly reveals
the fate of spilled methane in the deep Gulf of Mexico, Science, 331,
312–315, 2011.
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G.,
Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler,
L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A.,
Heimann, M., Hodson, E. L., Houweling, S., Josse, B., Fraser, P. J.,
Krummel, P. B., Lamarque, J.-F., Langenfelds, R. L., Le Quére, C., Naik,
V., O'Doherty, S., Palmer, P. I., Pison, I., Plummer, D., Poulter, B.,
Prinn, R. G., Rigby, M., Ringeval, B., Santini, M., Schmidt, M., Shindell,
D. T., Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo, K.,
Szopa, S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R.
F., Williams, J. E., and Zeng, G.: Three decades of global methane sources
and sinks, Nat. Geosci., 6, 813–823, 2013.
Kirtland Turner, S. 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, 2016.
Kirtland Turner, S.: Constraints on the onset duration of the
Paleocene-Eocene Thermal Maximum, Philos. T. Roy.
Soc. A, 376, 20170082, https://doi.org/10.1098/rsta.2017.0082, 2018.
Konijnendijk, T. Y. M., Weber, S. L., Tuenter, E., and van Weele, M.: Methane variations on orbital timescales: a transient modeling experiment, Clim. Past, 7, 635–648, https://doi.org/10.5194/cp-7-635-2011, 2011.
Krissansen-Totton, J., Garland, R., Irwin, P., and Catling, D. C.:
Detectability of biosignatures in anoxic atmospheres with the James Webb Space Telescope: A
TRAPPIST-1e cast study, Astro. J., 156, 114, https://doi.org/10.3847/1538-3881/aad564, 2018.
Kuivila, K. M., Murray, J. W., and Devol, A. H.: Methane production, sulfate
reduction and competition for substrates in the sediments of Lake
Washington, Geochim. Cosmochim. Ac., 53, 409–416, 1989.
Lamarque, J.-F., Kiehl, J. T., Shields, C. A., Boville, B. A., and Kinnison,
D. E.: Modeling the response to changes in tropospheric methane
concentration: Application to the Permian-Triassic boundary,
Paleoceanography, 21, PA3006, https://doi.org/10.1029/2006PA001276, 2006.
Lovley, D. R., Dwyer, D. F., and Klug, M. J.: Kinetic analysis of
competition between sulfate reducers and methanogens for hydrogen in
sediments, Appl. Environ. Microb., 43, 1373–1379, 1982.
Lunt, D. J., Ridgwell, A., Sluijs, A., Zachos, J. C., Hunter, S. J., and
Haywood, A.: A model for orbital pacing of methane hydrate destabilization
during the Palaeogene, Nat. Geosci., 4, 775–778, 2011.
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.
Martens, C. S. and Berner, R. A.: Interstitial water chemistry of anoxic
Long Island Sound sediments. 1. Dissolved gases, Limnol. Oceanogr.,
22, 10–25, 1977.
McGlynn, S. E., Chadwick, G. L., Kempes, C. P., and Orphan, V. J.: Single
cell activity reveals direct electron transfer in methanotrophic consortia,
Nature, 526, 531–535, 2015.
Melton, J. R., Wania, R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Beerling, D. J., Chen, G., Eliseev, A. V., Denisov, S. N., Hopcroft, P. O., Lettenmaier, D. P., Riley, W. J., Singarayer, J. S., Subin, Z. M., Tian, H., Zürcher, S., Brovkin, V., van Bodegom, P. M., Kleinen, T., Yu, Z. C., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP), Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, 2013.
Meyer, K. M., Ridgwell, A., and Payne, J. L.: The influence of the
biological pump on ocean chemistry: implications for long-term trends in
marine redox chemistry, the global carbon cycle, and marine animal
ecosystems, Geobiology, 14, 207–219, 2016.
Milucka, J., Ferdelman, T. G., Polerecky, L., Franzke, D., Wegener, G.,
Schmid, M., Lieberwirth, I., Wagner, M., Widdel, F., and Kuypers, M. M. M.:
Zero-valent sulphur is a key intermediate in marine methane oxidation,
Nature, 491, 541–546, 2012.
Myhre, G., Shindell, D., Breon, F.-M., Collins, W., Fuglestvedt, J., Huang,
J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T., Robock,
A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and natural
radiative forcing, in: Climate Change 2013: The Physical Science Basis.
Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A.,
Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge,
659–740, 2013.
Olson, S. L., Kump, L. R., and Kasting, J. F.: Quantifying the areal extent
and dissolved oxygen concentrations of Archean oxygen oases, Chem.
Geol., 362, 35–43, 2013.
Olson, S. L., Reinhard, C. T., and Lyons, T. W.: Limited role for methane in
the mid-Proterozoic greenhouse, P. Natl. Acad. Sci. USA, 113, 11447–11452, 2016.
Orphan, V. J., House, C. H., Hinrichs, K.-U., McKeegan, K. D., and DeLong,
E. F.: Methane-consuming Archaea revealed by directly coupled isotopic and
phylogenetic analysis, Science, 293, 484–487, 2001.
Ozaki, K., Tajika, E., Hong, P. K., Nakagawa, Y., and Reinhard, C. T.:
Effects of primitive photosynthesis on Earth's early climate system, Nat.
Geosci., 11, 55–59, 2018.
Paudel, R., Mahowald, N. M., Hess, P. G. M., Meng, L., and Riley, W. J.:
Attribution of changes in global wetland methane emissions from
pre-industrial to present using CLM4.5-BGC, Environ. Res. Lett.,
11, 034020, https://doi.org/10.1088/1748-9326/11/3/034020, 2016.
Pavlov, A. A. and Kasting, J. F.: Mass-independent fractionation of sulfur isotopes in Archean sediments: Strong evidence for an anoxic Archean atmosphere, Astrobiology, 2, 27–41, 2002.
Pavlov, A. A., Kasting, J. F., and Brown, L. L.: Greenhouse warming by
CH4 in the atmosphere of early Earth, J. Geophys. Res.,
105, 11981–11990, 2000.
Pavlov, A. A., Hurtgen, M. T., Kasting, J. F., and Arthur, M. A.:
Methane-rich Proterozoic atmosphere?, Geology, 31, 87–90, 2003.
Prather, M. J.: Time scales in atmospheric chemistry: Theory, GWPs for CH4
and CO, and runaway growth, Geophys. Res. Lett., 23, 2597–2600,
1996.
Rabouille, C. and Gaillard, J. F.: A coupled model representing the
deep-sea organic carbon mineralization and oxygen consumption in surficial
sediments, J. Geophys. Res.-Oceans., 96, 2761–2776, https://doi.org/10.1029/90jc02332, 1991.
Reeburgh, W. S.: Methane consumption in Cariaco Trench waters and sediments,
Earth Planet. Sc. Lett., 28, 337–344, 1976.
Reeburgh, W. S.: Oceanic methane biogeochemistry, Chem. Rev., 107,
486–513, 2007.
Regnier, P., Dale, A. W., Arndt, S., LaRowe, D. E., Mogollón, J., and
Van Cappellen, P.: Quantitative analysis of anaerobic oxidation of methane
(AOM) in marine sediments: A modeling perspective, Earth-Sci. Rev.,
106, 105–130, 2011.
Reinhard, C. T.: Reinhard.GMD.2020.RateData [Data set], Zenodo, https://doi.org/10.5281/zenodo.4081700, 2020.
Reinhard, C. T., Planavsky, N. J., Olson, S. L., Lyons, T. W., and Erwin, D.
H.: Earth's oxygen cycle and the evolution of animal life, P. Natl. Acad. Sci. USA, 113, 8933–8938, 2016.
Reinhard, C. T., Olson, S. L., Schwieterman, E. W., and Lyons, T. W.: False
negatives for remote life detection on ocean-bearing planets: Lessons from
the early Earth, Astrobiology, 17, 287–297, https://doi.org/10.1089/ast.2016.1598, 2017.
Ridgwell, A.: Glacial-interglacial perturbations in the global carbon cycle, PhD thesis, University of East Anglia, Norwich, UK, 2001.
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., Marshall, S. J., and Gregson, K.: Consumption of
atmospheric methane by soils: A process-based model, Global Biogeochem.
Cy., 13, 59–70, 1999.
Sagan, C. and Mullen, G.: Earth and Mars: Evolution of atmospheres and
surface temperatures, Science, 177, 52–56, 1972.
Sagan, C., Thompson, W. R., Carlson, R., Gurnett, D., and Hord, C.: A search
for life on Earth from the Galileo spacecraft, Nature, 365, 715–721, 1993.
Sansone, F. J., Popp, B. N., Gasc, A., Graham, A. W., and Rust, T. M.:
Highly elevated methane in the eastern tropical North Pacific and associated
isotopically enriched fluxes to the atmosphere, Geophys. Res.
Lett., 28, 4567–4570, 2001.
Schink, B.: Energetics of syntrophic cooperation in methanogenic
degradation, Microbiol. Mol. Biol. R., 61, 262–280, 1997.
Schmidt, G. A. and Shindell, D. T.: Atmospheric composition, radiative
forcing, and climate change as a consequence of a massive methane release
from gas hydrates, Paleoceanography, 18, 1004, https://doi.org/10.1029/2002PA000757, 2003.
Schrag, D. P., Berner, R. A., Hoffman, P. F., and Halverson, G. P.: On the
initiation of a snowball Earth, Geochem. Geophys. Geosyst., 3,
https://doi.org/10.1029/2001GC000219, 2002.
Scranton, M. I. and Brewer, P. G.: Consumption of dissolved methane in the
deep ocean, Limnol. Oceanogr., 23, 1207–1213, 1978.
Shindell, D. T., Pechony, O., Voulgarakis, A., Faluvegi, G., Nazarenko, L., Lamarque, J.-F., Bowman, K., Milly, G., Kovari, B., Ruedy, R., and Schmidt, G. A.: Interactive ozone and methane chemistry in GISS-E2 historical and future climate simulations, Atmos. Chem. Phys., 13, 2653–2689, https://doi.org/10.5194/acp-13-2653-2013, 2013.
Sivan, O., Adler, M., Pearson, A., Gelman, F., Bar-Or, I., John, S. G., and
Eckert, W.: Geochemical evidence for iron-mediated anaerobic oxidation of
methane, Limnol. Oceanogr., 56, 1536–1544, 2011.
Stoessell, R. K. and Byrne, P. A.: Salting-out of methane in single-salt
solutions at 25∘C and below 800 psia, Geochim.
Cosmochim. Ac., 46, 1327–1332, 1982.
Thamdrup, B., Steinsdóttir, H. G. R., Bertagnolli, A. D., Padilla, C.
C., Patin, N. V., Garcia-Robledo, E., Bristow, L. A., and Stewart, F. J.:
Anaerobic methane oxidation is an important sink for methane in the ocean's
largest oxygen minimum zone, Limnol. Oceanogr., 64, 2569–2585, https://doi.org/10.1002/lno.11235, 2019.
Thompson, A. M. and Cicerone, R. J.: Possible perturbations to atmospheric
CO, CH4, and OH, J. Geophys. Res., 91, 10853–10864, 1986.
Ueno, Y., Yamada, K., Yoshida, N., Maruyama, S., and Isozaki, Y.: Evidence
from fluid inclusions for microbial methanogenesis in the early Archaean
era, Nature, 440, 516–519, 2006.
Ulfsbo, A., Abbas, Z., and Turner, D. R.: Activity coefficients of a
simplified seawater electrolyte at varying salinity (5–40) and temperature
(0 and 25∘C) using Monte Carlo simulations, Mar.
Chem., 171, 78–86, 2015.
Valentine, D. L.: Emerging topics in marine methane biogeochemistry, Annu.
Rev. Mar. Sci., 3, 147–171, 2011.
van Bodegom, P., Stams, F., Liesbeth, M., Boeke, S., and Leffelaar, P.:
Methane oxidation and the competition for oxygen in the rice rhizosphere,
Appl. Environ. Microb., 67, 3586–3597, 2001.
Van Cappellen, P., Gaillard, J.-F., and Rabouille, C.: Biogeochemical
transformations in sediments: Kinetic models of early diagenesis, in:
Interactions of C, N, P and S Biogeochemical Cycles and Global Change,
Springer-Verlag, Berlin, 401–445, 1993.
Walter, B. P. and Heimann, M.: A process-based, climate-sensitive model to
derive methane emissions from natural wetlands: Application to five wetland
sites, sensitivity to model parameters, and climate, Global Biogeochem.
Cy., 14, 745–765, 2000.
Wania, R., Ross, I., and Prentice, I. C.: Implementation and evaluation of a new methane model within a dynamic global vegetation model: LPJ-WHyMe v1.3.1, Geosci. Model Dev., 3, 565–584, https://doi.org/10.5194/gmd-3-565-2010, 2010.
Weber, T., Wiseman, N. A., and Kock, A.: Global ocean methane emissions
dominated by shallow coastal waters, Nat. Commun., 10, 4584,
https://doi.org/10.1038/s41467-019-12541-7, 2019.
Zeebe, R. E., Zachos, J. C., and Dickens, G. R.: Carbon dioxide forcing
alone insufficient to explain Palaeocene-Eocene Thermal Maximum warming, Nat.
Geosci., 2, 576–580, 2009.
Zeebe, R. E.: What caused the long duration of the Paleocene-Eocene Thermal
Maximum?, Paleoceanography, 28, 1–13, https://doi.org/10.1002/palo.20039, 2013.
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.
We provide documentation and testing of new developments for the oceanic and atmospheric methane...
