Articles | Volume 13, issue 2
https://doi.org/10.5194/gmd-13-825-2020
© 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-13-825-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Coupling of a sediment diagenesis model (MEDUSA) and an Earth system model (CESM1.2): a contribution toward enhanced marine biogeochemical modelling and long-term climate simulations
Takasumi Kurahashi-Nakamura
CORRESPONDING AUTHOR
MARUM – Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany
André Paul
MARUM – Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany
Guy Munhoven
Laboratoire de Physique Atmosphérique et Planétaire, Université de Liège, Liège, Belgium
Ute Merkel
MARUM – Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany
Michael Schulz
MARUM – Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany
Related authors
Takasumi Kurahashi-Nakamura, André Paul, Ute Merkel, and Michael Schulz
Clim. Past, 18, 1997–2019, https://doi.org/10.5194/cp-18-1997-2022, https://doi.org/10.5194/cp-18-1997-2022, 2022
Short summary
Short summary
With a comprehensive Earth-system model including the global carbon cycle, we simulated the climate state during the last glacial maximum. We demonstrated that the CO2 concentration in the atmosphere both in the modern (pre-industrial) age (~280 ppm) and in the glacial age (~190 ppm) can be reproduced by the model with a common configuration by giving reasonable model forcing and total ocean inventories of carbon and other biogeochemical matter for the respective ages.
T. Kurahashi-Nakamura, M. Losch, and A. Paul
Geosci. Model Dev., 7, 419–432, https://doi.org/10.5194/gmd-7-419-2014, https://doi.org/10.5194/gmd-7-419-2014, 2014
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
Short summary
Short summary
Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Nathaelle Bouttes, Lester Kwiatkowski, Elodie Bougeot, Manon Berger, Victor Brovkin, and Guy Munhoven
EGUsphere, https://doi.org/10.5194/egusphere-2024-3738, https://doi.org/10.5194/egusphere-2024-3738, 2024
Short summary
Short summary
Coral reefs are under threat due to warming and ocean acidification. It is difficult to project future coral reef production due to uncertainties in climate models, socio-economic scenarios and coral adaptation to warming. Here we have included a coral reef module within a climate model for the first time to evaluate the range of possible futures. We show that coral reef production decreases in most future scenarios, but in some cases coral reef carbonate production can persist.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Nils Weitzel, Heather Andres, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lukas Jonkers, Oliver Bothe, Elisa Ziegler, Thomas Kleinen, André Paul, and Kira Rehfeld
Clim. Past, 20, 865–890, https://doi.org/10.5194/cp-20-865-2024, https://doi.org/10.5194/cp-20-865-2024, 2024
Short summary
Short summary
The ability of climate models to faithfully reproduce past warming episodes is a valuable test considering potentially large future warming. We develop a new method to compare simulations of the last deglaciation with temperature reconstructions. We find that reconstructions differ more between regions than simulations, potentially due to deficiencies in the simulation design, models, or reconstructions. Our work is a promising step towards benchmarking simulations of past climate transitions.
Brian R. Crow, Lev Tarasov, Michael Schulz, and Matthias Prange
Clim. Past, 20, 281–296, https://doi.org/10.5194/cp-20-281-2024, https://doi.org/10.5194/cp-20-281-2024, 2024
Short summary
Short summary
An abnormally warm period around 400,000 years ago is thought to have resulted in a large melt event for the Greenland Ice Sheet. Using a sequence of climate model simulations connected to an ice model, we estimate a 50 % melt of Greenland compared to today. Importantly, we explore how the exact methodology of connecting the temperatures and precipitation from the climate model to the ice sheet model can influence these results and show that common methods could introduce errors.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
Short summary
Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Alexandre Cauquoin, Ayako Abe-Ouchi, Takashi Obase, Wing-Le Chan, André Paul, and Martin Werner
Clim. Past, 19, 1275–1294, https://doi.org/10.5194/cp-19-1275-2023, https://doi.org/10.5194/cp-19-1275-2023, 2023
Short summary
Short summary
Stable water isotopes are tracers of climate processes occurring in the hydrological cycle. They are widely used to reconstruct the past variations of polar temperature before the instrumental era thanks to their measurements in ice cores. However, the relationship between measured isotopes and temperature has large uncertainties. In our study, we investigate how the sea surface conditions (temperature, sea ice, ocean circulation) impact this relationship for a cold to warm climate change.
Takasumi Kurahashi-Nakamura, André Paul, Ute Merkel, and Michael Schulz
Clim. Past, 18, 1997–2019, https://doi.org/10.5194/cp-18-1997-2022, https://doi.org/10.5194/cp-18-1997-2022, 2022
Short summary
Short summary
With a comprehensive Earth-system model including the global carbon cycle, we simulated the climate state during the last glacial maximum. We demonstrated that the CO2 concentration in the atmosphere both in the modern (pre-industrial) age (~280 ppm) and in the glacial age (~190 ppm) can be reproduced by the model with a common configuration by giving reasonable model forcing and total ocean inventories of carbon and other biogeochemical matter for the respective ages.
Kaveh Purkiani, Matthias Haeckel, Sabine Haalboom, Katja Schmidt, Peter Urban, Iason-Zois Gazis, Henko de Stigter, André Paul, Maren Walter, and Annemiek Vink
Ocean Sci., 18, 1163–1181, https://doi.org/10.5194/os-18-1163-2022, https://doi.org/10.5194/os-18-1163-2022, 2022
Short summary
Short summary
Based on altimetry data and in situ hydrographic observations, the impacts of an anticyclone mesoscale eddy (large rotating body of water) on the seawater characteristics were investigated during a research campaign. The particular eddy presents significant anomalies on the seawater properties at 1500 m. The potential role of eddies in the seafloor and its consequential effect on the altered dispersion of mining-related sediment plumes are important to assess future mining operations.
Stefan Mulitza, Torsten Bickert, Helen C. Bostock, Cristiano M. Chiessi, Barbara Donner, Aline Govin, Naomi Harada, Enqing Huang, Heather Johnstone, Henning Kuhnert, Michael Langner, Frank Lamy, Lester Lembke-Jene, Lorraine Lisiecki, Jean Lynch-Stieglitz, Lars Max, Mahyar Mohtadi, Gesine Mollenhauer, Juan Muglia, Dirk Nürnberg, André Paul, Carsten Rühlemann, Janne Repschläger, Rajeev Saraswat, Andreas Schmittner, Elisabeth L. Sikes, Robert F. Spielhagen, and Ralf Tiedemann
Earth Syst. Sci. Data, 14, 2553–2611, https://doi.org/10.5194/essd-14-2553-2022, https://doi.org/10.5194/essd-14-2553-2022, 2022
Short summary
Short summary
Stable isotope ratios of foraminiferal shells from deep-sea sediments preserve key information on the variability of ocean circulation and ice volume. We present the first global atlas of harmonized raw downcore oxygen and carbon isotope ratios of various planktonic and benthic foraminiferal species. The atlas is a foundation for the analyses of the history of Earth system components, for finding future coring sites, and for teaching marine stratigraphy and paleoceanography.
Brian R. Crow, Matthias Prange, and Michael Schulz
Clim. Past, 18, 775–792, https://doi.org/10.5194/cp-18-775-2022, https://doi.org/10.5194/cp-18-775-2022, 2022
Short summary
Short summary
To better understand the climate conditions which lead to extensive melting of the Greenland ice sheet, we used climate models to reconstruct the climate conditions of the warmest period of the last 800 000 years, which was centered around 410 000 years ago. Surprisingly, we found that atmospheric circulation changes may have acted to reduce the melt of the ice sheet rather than enhance it, despite the extensive warmth of the time.
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021, https://doi.org/10.5194/gmd-14-4225-2021, 2021
Short summary
Short summary
SolveSAPHE (Munhoven, 2013) was the first package to calculate pH reliably from any physically sensible pair of total alkalinity (AlkT) and dissolved inorganic carbon (CT) data and to do so in an autonomous and efficient way. Here, we extend it to use CO2, HCO3 or CO3 instead of CT. For each one of these pairs, the new SolveSAPHE calculates all of the possible pH values (0, 1, or 2), again without any prior knowledge of the solutions.
Guy Munhoven
Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, https://doi.org/10.5194/gmd-14-3603-2021, 2021
Short summary
Short summary
Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
Short summary
Short summary
The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
André Paul, Stefan Mulitza, Rüdiger Stein, and Martin Werner
Clim. Past, 17, 805–824, https://doi.org/10.5194/cp-17-805-2021, https://doi.org/10.5194/cp-17-805-2021, 2021
Short summary
Short summary
Maps and fields of near-sea-surface temperature differences between the past and present can be used to visualize and quantify climate changes and perform simulations with climate models. We used a statistical method to map sparse and scattered data for the Last Glacial Maximum time period (23 000 to 19 000 years before present) to a regular grid. The estimated global and tropical cooling would imply an equilibrium climate sensitivity in the lower to middle part of the currently accepted range.
Markus Raitzsch, Jelle Bijma, Torsten Bickert, Michael Schulz, Ann Holbourn, and Michal Kučera
Clim. Past, 17, 703–719, https://doi.org/10.5194/cp-17-703-2021, https://doi.org/10.5194/cp-17-703-2021, 2021
Short summary
Short summary
At approximately 14 Ma, the East Antarctic Ice Sheet expanded to almost its current extent, but the role of CO2 in this major climate transition is not entirely known. We show that atmospheric CO2 might have varied on 400 kyr cycles linked to the eccentricity of the Earth’s orbit. The resulting change in weathering and ocean carbon cycle affected atmospheric CO2 in a way that CO2 rose after Antarctica glaciated, helping to stabilize the climate system on its way to the “ice-house” world.
Kaveh Purkiani, André Paul, Annemiek Vink, Maren Walter, Michael Schulz, and Matthias Haeckel
Biogeosciences, 17, 6527–6544, https://doi.org/10.5194/bg-17-6527-2020, https://doi.org/10.5194/bg-17-6527-2020, 2020
Short summary
Short summary
There has been a steady increase in interest in mining of deep-sea minerals in the eastern Pacific Ocean recently. The ocean state in this region is known to be highly influenced by rotating bodies of water (eddies), some of which can travel long distances in the ocean and impact the deeper layers of the ocean. Better insight into the variability of eddy activity in this region is of great help to mitigate the impact of the benthic ecosystem from future potential deep-sea mining activity.
Pepijn Bakker, Irina Rogozhina, Ute Merkel, and Matthias Prange
Clim. Past, 16, 371–386, https://doi.org/10.5194/cp-16-371-2020, https://doi.org/10.5194/cp-16-371-2020, 2020
Short summary
Short summary
Northeastern Siberia is currently known for its harsh cold climate, but remarkably it did not experience large-scale glaciation during the last ice age. We show that the region is also exceptional in climate models. As a result of subtle changes in model setup, climate models show a strong divergence in simulated glacial summer temperatures that is ultimately driven by changes in the circumpolar atmospheric stationary wave pattern and associated northward heat transport to northeastern Siberia.
Andreia Rebotim, Antje Helga Luise Voelker, Lukas Jonkers, Joanna J. Waniek, Michael Schulz, and Michal Kucera
J. Micropalaeontol., 38, 113–131, https://doi.org/10.5194/jm-38-113-2019, https://doi.org/10.5194/jm-38-113-2019, 2019
Short summary
Short summary
To reconstruct subsurface water conditions using deep-dwelling planktonic foraminifera, we must fully understand how the oxygen isotope signal incorporates into their shell. We report δ18O in four species sampled in the eastern North Atlantic with plankton tows. We assess the size and crust effect on the isotopic δ18O and compared them with predictions from two equations. We reveal different patterns of calcite addition with depth, highlighting the need to perform species-specific calibrations.
Charlotte Breitkreuz, André Paul, and Michael Schulz
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-52, https://doi.org/10.5194/cp-2019-52, 2019
Publication in CP not foreseen
Short summary
Short summary
We combined a model simulation of the Last Glacial Maximum ocean with sea surface temperature and calcite oxygen isotope data through data assimilation. The reconstructed ocean state is very similar to the modern and it follows that the employed proxy data do not require an ocean state very different from today's. Sensitivity experiments reveal that data from the deep North Atlantic but also from the global deep Southern Ocean are most important to constrain the Atlantic overturning circulation.
Charlotte Breitkreuz, André Paul, Stefan Mulitza, Javier García-Pintado, and Michael Schulz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-32, https://doi.org/10.5194/gmd-2019-32, 2019
Publication in GMD not foreseen
Short summary
Short summary
We present a technique for ocean state estimation based on the combination of a simple data assimilation method with a state reduction approach. The technique proves to be very efficient and successful in reducing the model-data misfit and reconstructing a target ocean circulation from synthetic observations. In an application to Last Glacial Maximum proxy data the model-data misfit is greatly reduced but some misfit remains. Two different ocean states are found with similar model-data misfit.
Javier García-Pintado and André Paul
Geosci. Model Dev., 11, 5051–5084, https://doi.org/10.5194/gmd-11-5051-2018, https://doi.org/10.5194/gmd-11-5051-2018, 2018
Short summary
Short summary
Earth system models (ESMs) integrate interactions of atmosphere, ocean, land, ice, and biosphere to estimate the state of regional and global climate under a variety of conditions. Past climate field reconstructions with deterministic ESMs through the assimilation of climate proxies need to consider the required high computations and model non-linearity. Our tests indicate that iterative schemes based on the Kalman filter and careful sensitivity analysis are adequate for approaching the problem.
Andrea Klus, Matthias Prange, Vidya Varma, Louis Bruno Tremblay, and Michael Schulz
Clim. Past, 14, 1165–1178, https://doi.org/10.5194/cp-14-1165-2018, https://doi.org/10.5194/cp-14-1165-2018, 2018
Short summary
Short summary
Numerous proxy records from the northern North Atlantic suggest substantial climate variability including the occurrence of multi-decadal-to-centennial cold events during the Holocene. We analyzed two abrupt cold events in a Holocene simulation using a comprehensive climate model. It is shown that the events were ultimately triggered by prolonged phases of positive North Atlantic Oscillation causing changes in ocean circulation followed by severe cooling, freshening, and expansion of sea ice.
Kerstin Kretschmer, Lukas Jonkers, Michal Kucera, and Michael Schulz
Biogeosciences, 15, 4405–4429, https://doi.org/10.5194/bg-15-4405-2018, https://doi.org/10.5194/bg-15-4405-2018, 2018
Short summary
Short summary
The fossil shells of planktonic foraminifera are widely used to reconstruct past climate conditions. To do so, information about their seasonal and vertical habitat is needed. Here we present an updated version of a planktonic foraminifera model to better understand species-specific habitat dynamics under climate change. This model produces spatially and temporally coherent distribution patterns, which agree well with available observations, and can thus aid the interpretation of proxy records.
Amanda Frigola, Matthias Prange, and Michael Schulz
Geosci. Model Dev., 11, 1607–1626, https://doi.org/10.5194/gmd-11-1607-2018, https://doi.org/10.5194/gmd-11-1607-2018, 2018
Short summary
Short summary
The application of climate models to study the Middle Miocene Climate Transition, characterized by major Antarctic ice-sheet expansion and global cooling at the interval 15–13 million years ago, is currently hampered by the lack of boundary conditions. To fill this gap, we compiled two internally consistent sets of boundary conditions, including global topography, bathymetry, vegetation and ice volume, for the periods before and after the transition.
Catarina V. Guerreiro, Karl-Heinz Baumann, Geert-Jan A. Brummer, Gerhard Fischer, Laura F. Korte, Ute Merkel, Carolina Sá, Henko de Stigter, and Jan-Berend W. Stuut
Biogeosciences, 14, 4577–4599, https://doi.org/10.5194/bg-14-4577-2017, https://doi.org/10.5194/bg-14-4577-2017, 2017
Short summary
Short summary
Our study provides insights into the factors governing the spatio-temporal variability of coccolithophores in the equatorial North Atlantic and illustrates how this supposedly oligotrophic and stable open-ocean region actually reveals significant ecological variability. We provide evidence for Saharan dust and the Amazon River acting as fertilizers for phytoplankton and highlight the the importance of the thermocline depth for coccolithophore productivity in the lower photic zone.
Rike Völpel, André Paul, Annegret Krandick, Stefan Mulitza, and Michael Schulz
Geosci. Model Dev., 10, 3125–3144, https://doi.org/10.5194/gmd-10-3125-2017, https://doi.org/10.5194/gmd-10-3125-2017, 2017
Short summary
Short summary
This study presents the implementation of stable water isotopes in the MITgcm and describes the results of an equilibrium simulation under pre-industrial conditions. The model compares well to observational data and measurements of plankton tow records and thus opens wide prospects for long-term simulations in a paleoclimatic context.
Andreia Rebotim, Antje H. L. Voelker, Lukas Jonkers, Joanna J. Waniek, Helge Meggers, Ralf Schiebel, Igaratza Fraile, Michael Schulz, and Michal Kucera
Biogeosciences, 14, 827–859, https://doi.org/10.5194/bg-14-827-2017, https://doi.org/10.5194/bg-14-827-2017, 2017
Short summary
Short summary
Planktonic foraminifera species depth habitat remains poorly constrained and the existing conceptual models are not sufficiently tested by observational data. Here we present a synthesis of living planktonic foraminifera abundance data in the subtropical eastern North Atlantic from vertical plankton tows. We also test potential environmental factors influencing the species depth habitat and investigate yearly or lunar migration cycles. These findings may impact paleoceanographic studies.
Thomas Kleinen, Victor Brovkin, and Guy Munhoven
Clim. Past, 12, 2145–2160, https://doi.org/10.5194/cp-12-2145-2016, https://doi.org/10.5194/cp-12-2145-2016, 2016
Short summary
Short summary
We investigate trends in atmospheric CO2 during three recent interglacials – the Holocene, the Eemian and MIS 11 – using an earth system model of intermediate complexity. Our model experiments show a considerable improvement in the modelled CO2 trends for all three interglacials if peat accumulation and shallow water CaCO3 sedimentation are included, forcing the model only with orbital and sea level changes. The Holocene CO2 trend requires anthropogenic emissions of CO2 only after 3 ka BP.
Vidya Varma, Matthias Prange, and Michael Schulz
Geosci. Model Dev., 9, 3859–3873, https://doi.org/10.5194/gmd-9-3859-2016, https://doi.org/10.5194/gmd-9-3859-2016, 2016
Short summary
Short summary
We compare the results from simulations of the present and the last interglacial, with and without acceleration of the orbital forcing, using a comprehensive coupled climate model. In low latitudes, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique and hence model–data comparison of surface variables is therefore not hampered but major repercussions of the orbital forcing are obvious below thermocline.
Gerhard Fischer, Oscar Romero, Ute Merkel, Barbara Donner, Morten Iversen, Nico Nowald, Volker Ratmeyer, Götz Ruhland, Marco Klann, and Gerold Wefer
Biogeosciences, 13, 3071–3090, https://doi.org/10.5194/bg-13-3071-2016, https://doi.org/10.5194/bg-13-3071-2016, 2016
Short summary
Short summary
The studies were initiated to investigate potential changes in the important coastal upwelling system off NW Africa and to evaluate the role of mineral dust for carbon sequestration into the deep ocean. For this purpose, we deployed time series sediment traps in the deep water column off Cape Blanc, Mauritania. A more than two-decadal sediment trap record from this coastal upwelling system is now presented with respect to deep ocean mass fluxes, flux components and their longer term variability.
Rima Rachmayani, Matthias Prange, and Michael Schulz
Clim. Past, 12, 677–695, https://doi.org/10.5194/cp-12-677-2016, https://doi.org/10.5194/cp-12-677-2016, 2016
Short summary
Short summary
A set of 13 interglacial time slice experiments was carried out using a CCSM3-DGVM to study global climate variability between and within the Quaternary interglaciations of MIS 1, 5, 11, 13, and 15. Seasonal surface temperature anomalies can be explained by local insolation anomalies induced by the astronomical forcing in most regions and by GHG forcing at high latitudes and early Bruhnes interglacials. However, climate feedbacks may modify the surface temperature response in specific regions.
R. Rachmayani, M. Prange, and M. Schulz
Clim. Past, 11, 175–185, https://doi.org/10.5194/cp-11-175-2015, https://doi.org/10.5194/cp-11-175-2015, 2015
Short summary
Short summary
The role of vegetation-precipitation feedbacks in modifying the North African rainfall response to enhanced early to mid-Holocene summer insolation is analysed using the climate-vegetation model CCSM3-DGVM. Dynamic vegetation amplifies the positive early to mid-Holocene summer precipitation anomaly by ca. 20% in the Sahara-Sahel region. The primary vegetation feedback operates through surface latent heat flux anomalies by canopy evapotranspiration and their effect on the African easterly jet.
T. Kurahashi-Nakamura, M. Losch, and A. Paul
Geosci. Model Dev., 7, 419–432, https://doi.org/10.5194/gmd-7-419-2014, https://doi.org/10.5194/gmd-7-419-2014, 2014
Y. Milker, R. Rachmayani, M. F. G. Weinkauf, M. Prange, M. Raitzsch, M. Schulz, and M. Kučera
Clim. Past, 9, 2231–2252, https://doi.org/10.5194/cp-9-2231-2013, https://doi.org/10.5194/cp-9-2231-2013, 2013
G. Munhoven
Geosci. Model Dev., 6, 1367–1388, https://doi.org/10.5194/gmd-6-1367-2013, https://doi.org/10.5194/gmd-6-1367-2013, 2013
D. Handiani, A. Paul, M. Prange, U. Merkel, L. Dupont, and X. Zhang
Clim. Past, 9, 1683–1696, https://doi.org/10.5194/cp-9-1683-2013, https://doi.org/10.5194/cp-9-1683-2013, 2013
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
J. C. Hargreaves, J. D. Annan, R. Ohgaito, A. Paul, and A. Abe-Ouchi
Clim. Past, 9, 811–823, https://doi.org/10.5194/cp-9-811-2013, https://doi.org/10.5194/cp-9-811-2013, 2013
P. Bakker, E. J. Stone, S. Charbit, M. Gröger, U. Krebs-Kanzow, S. P. Ritz, V. Varma, V. Khon, D. J. Lunt, U. Mikolajewicz, M. Prange, H. Renssen, B. Schneider, and M. Schulz
Clim. Past, 9, 605–619, https://doi.org/10.5194/cp-9-605-2013, https://doi.org/10.5194/cp-9-605-2013, 2013
Related subject area
Climate and Earth system modeling
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
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
SURFER v3.0: a fast model with ice sheet tipping points and carbon cycle feedbacks for short and long-term climate scenarios
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
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
Short summary
Short summary
A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
Short summary
Short summary
In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
Short summary
Short summary
The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
Short summary
Short summary
We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
Short summary
Short summary
We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
Short summary
Short summary
In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
Short summary
Short summary
We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
Short summary
Short summary
The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
Short summary
Short summary
The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
Short summary
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
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.
Victor Couplet, Marina Martínez Montero, and Michel Crucifix
EGUsphere, https://doi.org/10.5194/egusphere-2024-2279, https://doi.org/10.5194/egusphere-2024-2279, 2024
Short summary
Short summary
We present SURFER v3.0, a simple climate model designed to estimate the impact of CO2 and CH4 emissions on global temperatures, sea levels, and ocean pH. We added new carbon cycle processes and calibrated the model to observations and results from more complex models, enabling use over time scales ranging from decades to millions of years. SURFER v3.0 is fast, transparent, and easy to use, making it an ideal tool for policy assessments and suitable for educational purposes.
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.
Cited articles
Archer, D., Winguth, A., Lea, D., and Mahowald, N.: What caused the
glacial/interglacial atmospheric pCO2 cycles?, Rev. Geophys.,
38, 159–189, https://doi.org/10.1029/1999RG000066, 2000. a, b, c
Armstrong, R. A., Lee, C., Hedges, J. I., Honjo, S., and Wakeham,
S. G.: A new, mechanistic model for organic carbon fluxes in the ocean based
on the quantitative association of POC with ballast minerals, Deep-Sea
Res. Pt. II, 49, 219–236,
https://doi.org/10.1016/S0967-0645(01)00101-1, 2002. a
Augustin, L., Barbante, C., Barnes, P. R. F., Marc Barnola, J.,
Bigler, M., Castellano, E., Cattani, O., Chappellaz, J.,
Dahl-Jensen, D., Delmonte, B., Dreyfus, G., Durand, G., Falourd,
S., Fischer, H., Flückiger, J., Hansson, M. E., Huybrechts, P.,
Jugie, G., Johnsen, S. J., Jouzel, J., Kaufmann, P., Kipfstuhl, J.,
Lambert, F., Lipenkov, V. Y., Littot, G. C., Longinelli, A.,
Lorrain, R., Maggi, V., Masson-Delmotte, V., Miller, H., Mulvaney,
R., Oerlemans, J., Oerter, H., Orombelli, G., Parrenin, F., Peel,
D. A., Petit, J.-R., Raynaud, D., Ritz, C., Ruth, U., Schwander,
J., Siegenthaler, U., Souchez, R., Stauffer, B., Peder Steffensen,
J., Stenni, B., Stocker, T. F., Tabacco, I. E., Udisti, R., van de
Wal, R. S. W., van den Broeke, M., Weiss, J., Wilhelms, F., Winther,
J.-G., Wolff, E. W., and Zucchelli, M.: Eight glacial cycles from an
Antarctic ice core, Nature, 429, 623–628, https://doi.org/10.1038/nature02599, 2004. a
Barnola, J. M., Raynaud, D., Lorius, C., and Korotkevich, Y. S.:
Vostok ice core provides 160,000-year record of atmospheric CO2, Nature,
329, 408–414, https://doi.org/10.1038/329408a0, 1987. a
Battaglia, G., Steinacher, M., and Joos, F.: A probabilistic assessment of calcium carbonate export and dissolution in the modern ocean, Biogeosciences, 13, 2823–2848, https://doi.org/10.5194/bg-13-2823-2016, 2016. a
Berelson, W. M., Balch, W. M., Najjar, R., Feely, R. A., Sabine, C., and Lee,
K.: Relating estimates of CaCO3 production, export, and dissolution in the
water column to measurements of CaCO3 rain into sediment traps and
dissolution on the sea floor: A revised global carbonate budget, Global
Biogeochem. Cy., 21, GB1024, https://doi.org/10.1029/2006GB002803,
2007. a, b
Berner, W., Oeschger, H., and Stauffer, B.: Information on the CO2
Cycle from Ice Core Studies, Radiocarbon, 22, 227–235,
https://doi.org/10.1017/S0033822200009498, 1980. a
Boudreau, B. P., Middelburg, J. J., Hofmann, A. F., and Meysman, F.
J. R.: Ongoing transients in carbonate compensation, Global Biogeochem.
Cy., 24, GB4010, https://doi.org/10.1029/2009GB003654, 2010. a
Boudreau, B. P., Middelburg, J. J., and Luo, Y.: The role of
calcification in carbonate compensation, Nat. Geosci., 11, 894–900,
https://doi.org/10.1038/s41561-018-0259-5, 2018. a
Breitkreuz, C., Paul, A., Kurahashi-Nakamura, T., Losch, M., and
Schulz, M.: A dynamical reconstruction of the global monthly-mean oxygen
isotopic composition of seawater, J. Geophys. Res.-Oceans, 123, 7206–7219,
https://doi.org/10.1029/2018JC014300, 2018. a
Broecker, W. S. and Peng, T.-H.: The role of CaCO3 compensation in
the glacial to interglacial atmospheric CO2 change, Global
Biogeochem. Cy., 1, 15–29, https://doi.org/10.1029/GB001i001p00015, 1987. a
Brovkin, V., Ganopolski, A., Archer, D., and Rahmstorf, S.: Lowering
of glacial atmospheric CO2 in response to changes in oceanic circulation
and marine biogeochemistry, Paleoceanography, 22, PA4202,
https://doi.org/10.1029/2006PA001380, 2007. a, b
Brovkin, V., Ganopolski, A., Archer, D., and Munhoven, G.: Glacial CO2 cycle as a succession of key physical and biogeochemical processes, Clim. Past, 8, 251–264, https://doi.org/10.5194/cp-8-251-2012, 2012. a
Carr, M.-E., Friedrichs, M. A., Schmeltz, M., Aita, M. N., Antoine, D., Arrigo,
K. R., Asanuma, I., Aumont, O., Barber, R., Behrenfeld, M., Bidigare, R.,
Buitenhuis, E. T., Campbell, J., Ciotti, A., Dierssen, H., Dowell, M., Dunne,
J., Esaias, W., Gentili, B., Gregg, W., Groom, S., Hoepffner, N., Ishizaka,
J., Kameda, T., Quéré, C. L., Lohrenz, S., Marra, J., Mélin, F., Moore,
K., Morel, A., Reddy, T. E., Ryan, J., Scardi, M., Smyth, T., Turpie, K.,
Tilstone, G., Waters, K., and Yamanaka, Y.: A comparison of global estimates
of marine primary production from ocean color, Deep-Sea Res. Pt. II, 53, 741–770,
https://doi.org/10.1016/j.dsr2.2006.01.028,
2006. a
Chikamoto, M. O., Matsumoto, K., and Ridgwell, A.: Response of deep-sea CaCO3
sedimentation to Atlantic meridional overturning circulation shutdown,
J. Geophys. Res.-Biogeo., 113, G03017,
https://doi.org/10.1029/2007JG000669,
2008. a
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., 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., Qin, D., Plattner, G.-K., Tignor,
M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.,
book section 6, Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA, 465–570, https://doi.org/10.1017/CBO9781107415324.015,
2013. a, b
Craig, A. P., Vertenstein, M., and Jacob, R.: A new flexible coupler for earth
system modeling developed for CCSM4 and CESM1, Int. J.
High Perform. C., 26, 31–42,
https://doi.org/10.1177/1094342011428141,
2012. a
Danabasoglu, G.: A comparison of global ocean general circulation model
solutions obtained with synchronous and accelerated integration methods,
Ocean Model., 7, 323–341, https://doi.org/10.1016/j.ocemod.2003.10.001, 2004. a
Danabasoglu, G., McWilliams, J. C., and Large, W. G.: Approach to
Equilibrium in Accelerated Global Oceanic Models, J. Climate, 9,
1092–1110, https://doi.org/10.1175/1520-0442(1996)009<1092:ATEIAG>2.0.CO;2, 1996. a
Dunne, J. P., Hales, B., and Toggweiler, J. R.: Global calcite cycling
constrained by sediment preservation controls, Global Biogeochem. Cy.,
26, GB3023, https://doi.org/10.1029/2010GB003935, 2012. a, b
Dutkiewicz, A., Müller, R. D., O'Callaghan, S., and Jónasson,
H.: Census of seafloor sediments in the world's ocean, Geology, 43,
795–798, https://doi.org/10.1130/G36883.1, 2015. a, b
Etheridge, D. M., Steele, L. P., Langenfelds, R. L., Francey, R. J., Barnola,
J.-M., and Morgan, V. I.: Natural and anthropogenic changes in atmospheric
CO2 over the last 1000 years from air in Antarctic ice and firn, J.
Geophys. Res.-Atmos., 101, 4115–4128, https://doi.org/10.1029/95JD03410,
1996. a
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. a
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S., Collins, W.,
Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P.,
Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.:
Evaluation of Climate Models, book section 9, Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA,
741–866, https://doi.org/10.1017/CBO9781107415324.020,
2013. a
Ganopolski, A. and Brovkin, V.: Simulation of climate, ice sheets and CO2 evolution during the last four glacial cycles with an Earth system model of intermediate complexity, Clim. Past, 13, 1695–1716, https://doi.org/10.5194/cp-13-1695-2017, 2017. a
Gnanadesikan, A.: A global model of silicon cycling: Sensitivity to eddy
parameterization and dissolution, Global Biogeochem. Cy., 13,
199–220, https://doi.org/10.1029/1998GB900013, 1999. a
Goddéris, Y. and Joachimski, M. M.: Global change in the Late Devonian:
modelling the Frasnian–Famennian short-term carbon isotope excursions,
Palaeogeogr. Palaeocl., 202, 309–329,
https://doi.org/10.1016/S0031-0182(03)00641-2,
2004. a
Heinze, C., Maier-Reimer, E., Winguth, A. M. E., and Archer, D.: A
global oceanic sediment model for long-term climate studies, Global
Biogeochem. Cy., 13, 221–250, https://doi.org/10.1029/98GB02812, 1999. a
Henson, S. A., Sanders, R., and Madsen, E.: Global patterns in efficiency of
particulate organic carbon export and transfer to the deep ocean, Global
Biogeochem. Cy., 26, GB1028, https://doi.org/10.1029/2011GB004099,
2012. a
Hülse, D., Arndt, S., Wilson, J. D., Munhoven, G., and Ridgwell,
A.: Understanding the causes and consequences of past marine carbon cycling
variability through models, Earth-Sci. Rev., 171, 349–382,
https://doi.org/10.1016/j.earscirev.2017.06.004,
2017. a
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E.,
Kushner, P. J., Lamarque, J.-F., Large, W. G., Lawrence, D.,
Lindsay, K., Lipscomb, W. H., Long, M. C., Mahowald, N., Marsh,
D. R., Neale, R. B., Rasch, P., Vavrus, S., Vertenstein, M., Bader,
D., Collins, W. D., Hack, J. J., Kiehl, J., and Marshall, S.: The
Community Earth System Model: A Framework for Collaborative Research,
B. Am. Meteorol. Soc., 94, 1339–1360,
https://doi.org/10.1175/BAMS-D-12-00121.1, 2013. a
Jahn, A., Lindsay, K., Giraud, X., Gruber, N., Otto-Bliesner, B. L., Liu, Z., and Brady, E. C.: Carbon isotopes in the ocean model of the Community Earth System Model (CESM1), Geosci. Model Dev., 8, 2419–2434, https://doi.org/10.5194/gmd-8-2419-2015, 2015. a
Jahnke, R. A.: The global ocean flux of particulate organic carbon: Areal
distribution and magnitude, Global Biogeochem. Cy., 10, 71–88,
https://doi.org/10.1029/95GB03525, 1996. a
Jungclaus, J. H., Lorenz, S. J., Timmreck, C., Reick, C. H., Brovkin, V., Six, K., Segschneider, J., Giorgetta, M. A., Crowley, T. J., Pongratz, J., Krivova, N. A., Vieira, L. E., Solanki, S. K., Klocke, D., Botzet, M., Esch, M., Gayler, V., Haak, H., Raddatz, T. J., Roeckner, E., Schnur, R., Widmann, H., Claussen, M., Stevens, B., and Marotzke, J.: Climate and carbon-cycle variability over the last millennium, Clim. Past, 6, 723–737, https://doi.org/10.5194/cp-6-723-2010, 2010. a
Kump, L. R., Brantley, S. L., and Arthur, M. A.: Chemical Weathering,
Atmospheric CO2, and Climate, Annu. Rev. Earth Pl.
Sc., 28, 611–667, https://doi.org/10.1146/annurev.earth.28.1.611, 2000. a
Kurahashi-Nakamura, T., Paul, A., and Losch, M.: Dynamical
reconstruction of the global ocean state during the Last Glacial Maximum,
Paleoceanography, 32, 326–350, https://doi.org/10.1002/2016PA003001, 2017. a
Kurahashi-Nakamura, T., Paul, A., Munhoven, G., Merkel, U., and Schulz, M.: Newly developed model code and scripts for the coupling of CESM1.2 and MEDUSA, PANGAEA, https://doi.org/10.1594/PANGAEA.905821, 2019. a
Lauvset, S. K., Key, R. M., Olsen, A., van Heuven, S., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Perez, F. F., Suzuki, T., and Watelet, S.: A new global interior ocean mapped climatology: the GLODAP version 2, Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016, 2016.
Laws, E. A., D'Sa, E., and Naik, P.: Simple equations to estimate ratios of new
or export production to total production from satellite-derived estimates of
sea surface temperature and primary production, Limnol. Oceanogr., 9, 593–601, https://doi.org/10.4319/lom.2011.9.593,
2011. a, b
Lee, K.: Global net community production estimated from the annual cycle of
surface water total dissolved inorganic carbon, Limnol. Oceanogr.,
46, 1287–1297, https://doi.org/10.4319/lo.2001.46.6.1287,
2001. a
Lindsay, K., Bonan, G. B., Doney, S. C., Hoffman, F. M., Lawrence,
D. M., Long, M. C., Mahowald, N. M., Keith Moore, J., Randerson,
J. T., and Thornton, P. E.: Preindustrial-Control and Twentieth-Century
Carbon Cycle Experiments with the Earth System Model CESM1(BGC), J.
Climate, 27, 8981–9005, https://doi.org/10.1175/JCLI-D-12-00565.1, 2014. a
Ma, S., Tao, Z., Yang, X., Yu, Y., Zhou, X., Ma, W., and Li, Z.: Estimation of
Marine Primary Productivity From Satellite-Derived Phytoplankton Absorption
Data, IEEE J. Sel. Top. Appl., 7, 3084–3092, https://doi.org/10.1109/JSTARS.2014.2298863, 2014. a
Marchal, O., Stocker, T. F., and Joos, F.: A latitude-depth,
circulation-biogeochemical ocean model for paleoclimate studies. Development
and sensitivities, Tellus B, 50, 290–316,
https://doi.org/10.3402/tellusb.v50i3.16130,
1998. a
Matsumoto, K., Sarmiento, J. L., and Brzezinski, M. A.: Silicic acid
leakage from the Southern Ocean: A possible explanation for glacial
atmospheric pCO2, Global Biogeochem. Cy., 16, 1031,
https://doi.org/10.1029/2001GB001442, 2002. a
Mayorga, E., Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H.,
Bouwman, A., Fekete, B. M., Kroeze, C., and Drecht, G. V.: Global Nutrient
Export from WaterSheds 2 (NEWS 2): Model development and implementation,
Environ. Model. Softw., 25, 837–853,
https://doi.org/10.1016/j.envsoft.2010.01.007,
2010. a
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem
dynamics and iron cycling in a global three-dimensional model, Global
Biogeochem. Cy., 18, GB4028, https://doi.org/10.1029/2004GB002220, 2004. a
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.:
Marine Ecosystem Dynamics and Biogeochemical Cycling in the Community Earth
System Model [CESM1(BGC)]: Comparison of the 1990s with the 2090s under the
RCP4.5 and RCP8.5 Scenarios, J. Climate, 26, 9291–9312,
https://doi.org/10.1175/JCLI-D-12-00566.1, 2013. a
Norris, R. D., Turner, S. K., Hull, P. M., and Ridgwell, A.: Marine Ecosystem
Responses to Cenozoic Global Change, Science, 341, 492–498,
https://doi.org/10.1126/science.1240543,
2013. a
Ragueneau, O., Tréguer, P., Leynaert, A., Anderson, R. F.,
Brzezinski, M. A., DeMaster, D. J., Dugdale, R. C., Dymond, J.,
Fischer, G., François, R., Heinze, C., Maier-Reimer, E.,
Martin-Jézéquel, V., Nelson, D. M., and Quéguiner, B.: A
review of the Si cycle in the modern ocean: recent progress and missing gaps
in the application of biogenic opal as a paleoproductivity proxy, Global
Planet. Chang., 26, 317–365, https://doi.org/10.1016/S0921-8181(00)00052-7, 2000. a, b
Ridgwell, A.: Interpreting transient carbonate compensation depth changes by
marine sediment core modeling, Paleoceanography, 22, PA4102,
https://doi.org/10.1029/2006PA001372, 2007. a
Ridgwell, A. and Hargreaves, J. C.: Regulation of atmospheric CO2 by deep-sea
sediments in an Earth system model, Global Biogeochem. Cy., 21, GB2008,
https://doi.org/10.1029/2006GB002764,
2007. a
Ridgwell, A. and Zeebe, R. E.: The role of the global carbonate cycle in
the regulation and evolution of the Earth system [rapid communication],
Earth Planet. Sc. Lett., 234, 299–315,
https://doi.org/10.1016/j.epsl.2005.03.006, 2005. a
Seitzinger, S. P., Mayorga, E., Bouwman, A. F., Kroeze, C., Beusen,
A. H. W., Billen, G., van Drecht, G., Dumont, E., Fekete, B. M.,
Garnier, J., and Harrison, J. A.: Global river nutrient export: A
scenario analysis of past and future trends, Global Biogeochem. Cy.,
24, GB0A08, https://doi.org/10.1029/2009GB003587, 2010. a
Shields, C. A., Bailey, D. A., Danabasoglu, G., Jochum, M., Kiehl,
J. T., Levis, S., and Park, S.: The Low-Resolution CCSM4, J.
Climate, 25, 3993–4014, https://doi.org/10.1175/JCLI-D-11-00260.1, 2012. a, b
Siegel, D. A., Buesseler, K. O., Doney, S. C., Sailley, S. F.,
Behrenfeld, M. J., and Boyd, P. W.: Global assessment of ocean carbon
export by combining satellite observations and food-web models, Global
Biogeochem. Cy., 28, 181–196, https://doi.org/10.1002/2013GB004743, 2014. a
Soetaert, K., Middelburg, J. J., Herman, P. M. J., and Buis, K.: On
the coupling of benthic and pelagic biogeochemical models, Earth-Sci.
Rev., 51, 173–201, https://doi.org/10.1016/S0012-8252(00)00004-0, 2000. a
Stammer, D., Balmaseda, M., Heimbach, P., Köhl, A., and Weaver,
A.: Ocean Data Assimilation in Support of Climate Applications: Status and
Perspectives, Ann. Rev. Mar. Sci., 8, 491–518,
https://doi.org/10.1146/annurev-marine-122414-034113, 2016.
a
Tréguer, P., Nelson, D. M., Van Bennekom, A. J., DeMaster, D. J., Leynaert,
A., and Quéguiner, B.: The Silica Balance in the World Ocean: A
Reestimate, Science, 268, 375–379, https://doi.org/10.1126/science.268.5209.375, 1995. a, b
Tréguer, P. J. and De La Rocha, C. L.: The World Ocean Silica Cycle, Annu.
Rev Mar. Sci., 5, 477–501,
https://doi.org/10.1146/annurev-marine-121211-172346, 2013. a, b
Tschumi, T., Joos, F., Gehlen, M., and Heinze, C.: Deep ocean ventilation, carbon isotopes, marine sedimentation and the deglacial CO2 rise, Clim. Past, 7, 771–800, https://doi.org/10.5194/cp-7-771-2011, 2011. a
Yamanaka, Y. and Tajika, E.: The role of the vertical fluxes of
particulate organic matter and calcite in the oceanic carbon cycle: Studies
using an ocean biogeochemical general circulation model, Global
Biogeochem. Cy., 10, 361–382, https://doi.org/10.1029/96GB00634, 1996. a
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. a
Short summary
Chemical processes in ocean-floor sediments have a large influence on the marine carbon cycle, hence the global climate, at long timescales. We developed a new coupling scheme for a chemical sediment model and a comprehensive climate model. The new coupled model outperformed the original uncoupled climate model in reproducing the global distribution of sediment properties. The sediment model will also act as a
bridgebetween the ocean model and paleoceanographic data.
Chemical processes in ocean-floor sediments have a large influence on the marine carbon cycle,...