Articles | Volume 7, issue 4
https://doi.org/10.5194/gmd-7-1419-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-7-1419-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
15 Jul 2014
Development and technical paper |
| 15 Jul 2014
Numerical simulations of oceanic oxygen cycling in the FAMOUS Earth-System model: FAMOUS-ES, version 1.0
J. H. T. Williams
BRIDGE, School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
I. J. Totterdell
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
P. R. Halloran
School of Geography, University of Exeter, Exeter, EX4 4RJ, UK
previously at: Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
P. J. Valdes
BRIDGE, School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
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J. H. T. Williams, R. S. Smith, P. J. Valdes, B. B. B. Booth, and A. Osprey
Geosci. Model Dev., 6, 141–160, https://doi.org/10.5194/gmd-6-141-2013, https://doi.org/10.5194/gmd-6-141-2013, 2013
Brooke Snoll, Ruza Ivanovic, Lauren Gregoire, Sam Sherriff-Tadano, Laurie Menviel, Takashi Obase, Ayako Abe-Ouchi, Nathaelle Bouttes, Chengfei He, Feng He, Marie Kapsch, Uwe Mikolajewicz, Juan Muglia, and Paul Valdes
Clim. Past, 20, 789–815, https://doi.org/10.5194/cp-20-789-2024, https://doi.org/10.5194/cp-20-789-2024, 2024
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Geological records show rapid climate change throughout the recent deglaciation. The drivers of these changes are still misunderstood but are often attributed to shifts in the Atlantic Ocean circulation from meltwater input. A cumulative effort to understand these processes prompted numerous simulations of this period. We use these to explain the chain of events and our collective ability to simulate them. The results demonstrate the importance of the meltwater amount used in the simulation.
Yixuan Xie, Daniel J. Lunt, and Paul J. Valdes
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-22, https://doi.org/10.5194/cp-2024-22, 2024
Preprint under review for CP
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Dust plays a crucial role in the climate system; while it is relatively well studied for the present day, we still lack how it was in the past and the underlying mechanism in the multi-million-year time scale of Earth’s history. Here, for the first time, we simulate dust emissions with the newly developed DUSTY model over the past 540 million years with a temporal resolution of ~5 million years and identify palaeogeography as the primary control of these variations.
Jim M. Haywood, Andy Jones, Anthony C. Jones, Paul Halloran, and Philip J. Rasch
Atmos. Chem. Phys., 23, 15305–15324, https://doi.org/10.5194/acp-23-15305-2023, https://doi.org/10.5194/acp-23-15305-2023, 2023
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The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
Takashi Obase, Laurie Menviel, Ayako Abe-Ouchi, Tristan Vadsaria, Ruza Ivanovic, Brooke Snoll, Sam Sherriff-Tadano, Paul Valdes, Lauren Gregoire, Marie-Luise Kapsch, Uwe Mikolajewicz, Nathaelle Bouttes, Didier Roche, Fanny Lhardy, Chengfei He, Bette Otto-Bliesner, Zhengyu Liu, and Wing-Le Chan
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-86, https://doi.org/10.5194/cp-2023-86, 2023
Preprint under review for CP
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This study analyses transient simulations of the last deglaciation performed by six climate models to understand the processes driving southern high latitude temperature changes. We find that atmospheric CO2 changes and AMOC changes are the primary drivers of the major warming and cooling during the middle stage of the deglaciation. The multi-model analysis highlights the model’s sensitivity of CO2, AMOC to meltwater, and the meltwater history on temperature changes in southern high latitudes.
George Manville, Thomas G. Bell, Jane P. Mulcahy, Rafel Simó, Martí Galí, Anoop S. Mahajan, Shrivardhan Hulswar, and Paul R. Halloran
Biogeosciences, 20, 1813–1828, https://doi.org/10.5194/bg-20-1813-2023, https://doi.org/10.5194/bg-20-1813-2023, 2023
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We present the first global investigation of controls on seawater dimethylsulfide (DMS) spatial variability over scales of up to 100 km. Sea surface height anomalies, density, and chlorophyll a help explain almost 80 % of DMS variability. The results suggest that physical and biogeochemical processes play an equally important role in controlling DMS variability. These data provide independent confirmation that existing parameterisations of seawater DMS concentration use appropriate variables.
Caitlyn R. Witkowski, Vittoria Lauretano, Alex Farnsworth, Shufeng Li, Shi-Hu Li, Jan Peter Mayser, B. David A. Naafs, Robert A. Spicer, Tao Su, He Tang, Zhe-Kun Zhou, Paul J. Valdes, and Richard D. Pancost
EGUsphere, https://doi.org/10.5194/egusphere-2023-373, https://doi.org/10.5194/egusphere-2023-373, 2023
Preprint archived
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Untangling the complex tectonic evolution in the Tibetan region can help us understand its impacts on climate, the Asian monsoon system, and the development of major biodiversity hotspots. We show that this “missing link” site between high elevation Tibet and low elevation coastal China had a dynamic environment but no temperature change, meaning its been at its current-day elevation for the past 34 million years.
Suzanne Robinson, Ruza F. Ivanovic, Lauren J. Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul J. Valdes
Geosci. Model Dev., 16, 1231–1264, https://doi.org/10.5194/gmd-16-1231-2023, https://doi.org/10.5194/gmd-16-1231-2023, 2023
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We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (Nd v1.0). Nd fluxes from seafloor sediment and incorporation of Nd onto sinking particles represent the major global sources and sinks, respectively. However, model–data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Michael P. Erb, Nicholas P. McKay, Nathan Steiger, Sylvia Dee, Chris Hancock, Ruza F. Ivanovic, Lauren J. Gregoire, and Paul Valdes
Clim. Past, 18, 2599–2629, https://doi.org/10.5194/cp-18-2599-2022, https://doi.org/10.5194/cp-18-2599-2022, 2022
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To look at climate over the past 12 000 years, we reconstruct spatial temperature using natural climate archives and information from model simulations. Our results show mild global mean warmth around 6000 years ago, which differs somewhat from past reconstructions. Undiagnosed seasonal biases in the data could explain some of the observed temperature change, but this still would not explain the large difference between many reconstructions and climate models over this period.
Shrivardhan Hulswar, Rafel Simó, Martí Galí, Thomas G. Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville, and Anoop Sharad Mahajan
Earth Syst. Sci. Data, 14, 2963–2987, https://doi.org/10.5194/essd-14-2963-2022, https://doi.org/10.5194/essd-14-2963-2022, 2022
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The third climatological estimation of sea surface dimethyl sulfide (DMS) concentrations based on in situ measurements was created (DMS-Rev3). The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS, and shows significant regional differences compared to past climatologies.
Paul R. Halloran, Jennifer K. McWhorter, Beatriz Arellano Nava, Robert Marsh, and William Skirving
Geosci. Model Dev., 14, 6177–6195, https://doi.org/10.5194/gmd-14-6177-2021, https://doi.org/10.5194/gmd-14-6177-2021, 2021
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This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
Paul J. Valdes, Christopher R. Scotese, and Daniel J. Lunt
Clim. Past, 17, 1483–1506, https://doi.org/10.5194/cp-17-1483-2021, https://doi.org/10.5194/cp-17-1483-2021, 2021
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Deep ocean temperatures are widely used as a proxy for global mean surface temperature in the past, but the underlying assumptions have not been tested. We use two unique sets of 109 climate model simulations for the last 545 million years to show that the relationship is valid for approximately the last 100 million years but breaks down for older time periods when the continents (and hence ocean circulation) are in very different positions.
Daniel J. Lunt, Deepak Chandan, Alan M. Haywood, George M. Lunt, Jonathan C. Rougier, Ulrich Salzmann, Gavin A. Schmidt, and Paul J. Valdes
Geosci. Model Dev., 14, 4307–4317, https://doi.org/10.5194/gmd-14-4307-2021, https://doi.org/10.5194/gmd-14-4307-2021, 2021
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Often in science we carry out experiments with computers in which several factors are explored, for example, in the field of climate science, how the factors of greenhouse gases, ice, and vegetation affect temperature. We can explore the relative importance of these factors by
swapping in and outdifferent values of these factors, and can also carry out experiments with many different combinations of these factors. This paper discusses how best to analyse the results from such experiments.
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
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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.
Daniel J. Lunt, Fran Bragg, Wing-Le Chan, David K. Hutchinson, Jean-Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Ayako Abe-Ouchi, Eleni Anagnostou, Agatha M. de Boer, Helen K. Coxall, Yannick Donnadieu, Gavin Foster, Gordon N. Inglis, Gregor Knorr, Petra M. Langebroek, Caroline H. Lear, Gerrit Lohmann, Christopher J. Poulsen, Pierre Sepulchre, Jessica E. Tierney, Paul J. Valdes, Evgeny M. Volodin, Tom Dunkley Jones, Christopher J. Hollis, Matthew Huber, and Bette L. Otto-Bliesner
Clim. Past, 17, 203–227, https://doi.org/10.5194/cp-17-203-2021, https://doi.org/10.5194/cp-17-203-2021, 2021
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This paper presents the first modelling results from the Deep-Time Model Intercomparison Project (DeepMIP), in which we focus on the early Eocene climatic optimum (EECO, 50 million years ago). We show that, in contrast to previous work, at least three models (CESM, GFDL, and NorESM) produce climate states that are consistent with proxy indicators of global mean temperature and polar amplification, and they achieve this at a CO2 concentration that is consistent with the CO2 proxy record.
Irene Malmierca-Vallet, Louise C. Sime, Paul J. Valdes, and Julia C. Tindall
Clim. Past, 16, 2485–2508, https://doi.org/10.5194/cp-16-2485-2020, https://doi.org/10.5194/cp-16-2485-2020, 2020
Charles J. R. Williams, Maria-Vittoria Guarino, Emilie Capron, Irene Malmierca-Vallet, Joy S. Singarayer, Louise C. Sime, Daniel J. Lunt, and Paul J. Valdes
Clim. Past, 16, 1429–1450, https://doi.org/10.5194/cp-16-1429-2020, https://doi.org/10.5194/cp-16-1429-2020, 2020
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Computer simulations of the geological past are an important tool to improve our understanding of climate change. We present results from two simulations using the latest version of the UK's climate model, the mid-Holocene (6000 years ago) and Last Interglacial (127 000 years ago). The simulations reproduce temperatures consistent with the pattern of incoming radiation. Model–data comparisons indicate that some regions (and some seasons) produce better matches to the data than others.
Alan T. Kennedy-Asser, Daniel J. Lunt, Paul J. Valdes, Jean-Baptiste Ladant, Joost Frieling, and Vittoria Lauretano
Clim. Past, 16, 555–573, https://doi.org/10.5194/cp-16-555-2020, https://doi.org/10.5194/cp-16-555-2020, 2020
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Global cooling and a major expansion of ice over Antarctica occurred ~ 34 million years ago at the Eocene–Oligocene transition (EOT). A large secondary proxy dataset for high-latitude Southern Hemisphere temperature before, after and across the EOT is compiled and compared to simulations from two coupled climate models. Although there are inconsistencies between the models and data, the comparison shows amongst other things that changes in the Drake Passage were unlikely the cause of the EOT.
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, Laura F. Robinson, and Paul J. Valdes
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-365, https://doi.org/10.5194/bg-2019-365, 2019
Publication in BG not foreseen
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We have added three new tracers (a dye tracer and two representations of radiocarbon, 14C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model performs well compared to modern 14C observations, both spatially and temporally. Proxy 14C records are interpreted in terms of water age, but comparing our dye tracer to our 14C tracer, we find that this is only valid in certain areas; elsewhere, the carbon cycle complicates the signal.
David C. Wade, Nathan Luke Abraham, Alexander Farnsworth, Paul J. Valdes, Fran Bragg, and Alexander T. Archibald
Clim. Past, 15, 1463–1483, https://doi.org/10.5194/cp-15-1463-2019, https://doi.org/10.5194/cp-15-1463-2019, 2019
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The amount of O2 in the atmosphere may have varied from as little as 10 % to as much as 35 % during the last 541 Myr. These changes are large enough to have led to changes in atmospheric mass, which may alter the radiative budget of the atmosphere. We present the first fully 3-D numerical model simulations to investigate the climate impacts of changes in O2 during different climate states. We identify a complex new mechanism causing increases in surface temperature when O2 levels were higher.
Mario Krapp, Robert Beyer, Stephen L. Edmundson, Paul J. Valdes, and Andrea Manica
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-91, https://doi.org/10.5194/cp-2019-91, 2019
Revised manuscript not accepted
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The local response of the global climate system to the external drivers of the glacial–interglacial climates throughout the Quaternary can be approximated by a simple linear regression model. Based on numerical climate model simulations for the last glacial cycle, our global climate model emulator (GCMET) is able to reconstruct the climate of the last 800 000 years, in good agreement with long-term terrestrial and marine proxy records.
David J. Wilton, Marcus P. S. Badger, Euripides P. Kantzas, Richard D. Pancost, Paul J. Valdes, and David J. Beerling
Geosci. Model Dev., 12, 1351–1364, https://doi.org/10.5194/gmd-12-1351-2019, https://doi.org/10.5194/gmd-12-1351-2019, 2019
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Methane is an important greenhouse gas naturally produced in wetlands (areas of land inundated with water). Models of the Earth's past climate need estimates of the amounts of methane wetlands produce; and in order to calculate those we need to model wetlands. In this work we develop a method for modelling the fraction of an area of the Earth that is wetland, repeat this over all the Earth's land surface and apply this to a study of the Earth as it was around 50 million years ago.
Matthew P. Couldrey, Kevin I. C. Oliver, Andrew Yool, Paul R. Halloran, and Eric P. Achterberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-16, https://doi.org/10.5194/bg-2019-16, 2019
Revised manuscript not accepted
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Determining how much carbon dioxide (CO2) the oceans absorb is key to predicting human-caused climate change. A computer model of the ocean shows how the North Atlantic will change up to the end of the century. Year-to-year variations are mostly caused by changes in ocean temperature and seawater chemistry, altering CO2 solubility. By 2100, human emissions cause the biggest changes. The near term changes are physically driven, which may be more predictable than biological changes.
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, https://doi.org/10.5194/gmd-11-1033-2018, 2018
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The Paleoclimate Modelling Intercomparison Project (PMIP) takes advantage of the existence of past climate states radically different from the recent past to test climate models used for climate projections and to better understand these climates. This paper describes the PMIP contribution to CMIP6 (Coupled Model Intercomparison Project, 6th phase) and possible analyses based on PMIP results, as well as on other CMIP6 projects.
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
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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.
Paul J. Valdes, Edward Armstrong, Marcus P. S. Badger, Catherine D. Bradshaw, Fran Bragg, Michel Crucifix, Taraka Davies-Barnard, Jonathan J. Day, Alex Farnsworth, Chris Gordon, Peter O. Hopcroft, Alan T. Kennedy, Natalie S. Lord, Dan J. Lunt, Alice Marzocchi, Louise M. Parry, Vicky Pope, William H. G. Roberts, Emma J. Stone, Gregory J. L. Tourte, and Jonny H. T. Williams
Geosci. Model Dev., 10, 3715–3743, https://doi.org/10.5194/gmd-10-3715-2017, https://doi.org/10.5194/gmd-10-3715-2017, 2017
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In this paper we describe the family of climate models used by the BRIDGE research group at the University of Bristol as well as by various other institutions. These models are based on the UK Met Office HadCM3 models and here we describe the various modifications which have been made as well as the key features of a number of configurations in use.
Emma J. Stone, Emilie Capron, Daniel J. Lunt, Antony J. Payne, Joy S. Singarayer, Paul J. Valdes, and Eric W. Wolff
Clim. Past, 12, 1919–1932, https://doi.org/10.5194/cp-12-1919-2016, https://doi.org/10.5194/cp-12-1919-2016, 2016
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Climate models forced only with greenhouse gas concentrations and orbital parameters representative of the early Last Interglacial are unable to reproduce the observed colder-than-present temperatures in the North Atlantic and the warmer-than-present temperatures in the Southern Hemisphere. Using a climate model forced also with a freshwater amount derived from data representing melting from the remnant Northern Hemisphere ice sheets accounts for this response via the bipolar seesaw mechanism.
Claudie Beaulieu, Harriet Cole, Stephanie Henson, Andrew Yool, Thomas R. Anderson, Lee de Mora, Erik T. Buitenhuis, Momme Butenschön, Ian J. Totterdell, and J. Icarus Allen
Biogeosciences, 13, 4533–4553, https://doi.org/10.5194/bg-13-4533-2016, https://doi.org/10.5194/bg-13-4533-2016, 2016
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Regime shifts have been suggested in the late 1970s and late 1980s in the Gulf of Alaska with important consequences for fisheries. Here we investigate the ability of a suite of ocean biogeochemical models of varying complexity to simulate these regime shifts. Our results demonstrate that ocean models can successfully simulate regime shifts in the Gulf of Alaska region, thereby improving our understanding of how changes in physical conditions are propagated from lower to upper trophic levels.
William H. G. Roberts, Antony J. Payne, and Paul J. Valdes
Clim. Past, 12, 1601–1617, https://doi.org/10.5194/cp-12-1601-2016, https://doi.org/10.5194/cp-12-1601-2016, 2016
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There are observations from ocean sediment cores that during the last ice age the Laurentide Ice Sheet, which sat over North America, periodically surged. In this study we show the role that water at the base of an ice sheet plays in these surges. We show that with a more realistic representation of water drainage at the base of the ice sheet than usually used, these surges can still occur and that they are triggered by an internal ice sheet instability; no external trigger is needed.
Ruza F. Ivanovic, Lauren J. Gregoire, Masa Kageyama, Didier M. Roche, Paul J. Valdes, Andrea Burke, Rosemarie Drummond, W. Richard Peltier, and Lev Tarasov
Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, https://doi.org/10.5194/gmd-9-2563-2016, 2016
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This manuscript presents the experiment design for the PMIP4 Last Deglaciation Core experiment: a transient simulation of the last deglaciation, 21–9 ka. Specified model boundary conditions include time-varying orbital parameters, greenhouse gases, ice sheets, ice meltwater fluxes and other geographical changes (provided for 26–0 ka). The context of the experiment and the choices for the boundary conditions are explained, along with the future direction of the working group.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
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This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
M. Clare Smith, Joy S. Singarayer, Paul J. Valdes, Jed O. Kaplan, and Nicholas P. Branch
Clim. Past, 12, 923–941, https://doi.org/10.5194/cp-12-923-2016, https://doi.org/10.5194/cp-12-923-2016, 2016
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We used climate modelling to estimate the biogeophysical impacts of agriculture on the climate over the last 8000 years of the Holocene. Our results show statistically significant surface temperature changes (mainly cooling) from as early as 7000 BP in the JJA season and throughout the entire annual cycle by 2–3000 BP. The changes were greatest in the areas of land use change but were also seen in other areas. Precipitation was also affected, particularly in Europe, India, and the ITCZ region.
Matthew J. Carmichael, Daniel J. Lunt, Matthew Huber, Malte Heinemann, Jeffrey Kiehl, Allegra LeGrande, Claire A. Loptson, Chris D. Roberts, Navjit Sagoo, Christine Shields, Paul J. Valdes, Arne Winguth, Cornelia Winguth, and Richard D. Pancost
Clim. Past, 12, 455–481, https://doi.org/10.5194/cp-12-455-2016, https://doi.org/10.5194/cp-12-455-2016, 2016
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In this paper, we assess how well model-simulated precipitation rates compare to those indicated by geological data for the early Eocene, a warm interval 56–49 million years ago. Our results show that a number of models struggle to produce sufficient precipitation at high latitudes, which likely relates to cool simulated temperatures in these regions. However, calculating precipitation rates from plant fossils is highly uncertain, and further data are now required.
B. A. A. Hoogakker, R. S. Smith, J. S. Singarayer, R. Marchant, I. C. Prentice, J. R. M. Allen, R. S. Anderson, S. A. Bhagwat, H. Behling, O. Borisova, M. Bush, A. Correa-Metrio, A. de Vernal, J. M. Finch, B. Fréchette, S. Lozano-Garcia, W. D. Gosling, W. Granoszewski, E. C. Grimm, E. Grüger, J. Hanselman, S. P. Harrison, T. R. Hill, B. Huntley, G. Jiménez-Moreno, P. Kershaw, M.-P. Ledru, D. Magri, M. McKenzie, U. Müller, T. Nakagawa, E. Novenko, D. Penny, L. Sadori, L. Scott, J. Stevenson, P. J. Valdes, M. Vandergoes, A. Velichko, C. Whitlock, and C. Tzedakis
Clim. Past, 12, 51–73, https://doi.org/10.5194/cp-12-51-2016, https://doi.org/10.5194/cp-12-51-2016, 2016
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In this paper we use two climate models to test how Earth’s vegetation responded to changes in climate over the last 120 000 years, looking at warm interglacial climates like today, cold ice-age glacial climates, and intermediate climates. The models agree well with observations from pollen, showing smaller forested areas and larger desert areas during cold periods. Forests store most terrestrial carbon; the terrestrial carbon lost during cold climates was most likely relocated to the oceans.
C. Laufkötter, M. Vogt, N. Gruber, M. Aita-Noguchi, O. Aumont, L. Bopp, E. Buitenhuis, S. C. Doney, J. Dunne, T. Hashioka, J. Hauck, T. Hirata, J. John, C. Le Quéré, I. D. Lima, H. Nakano, R. Seferian, I. Totterdell, M. Vichi, and C. Völker
Biogeosciences, 12, 6955–6984, https://doi.org/10.5194/bg-12-6955-2015, https://doi.org/10.5194/bg-12-6955-2015, 2015
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We analyze changes in marine net primary production (NPP) and its drivers for the 21st century in 9 marine ecosystem models under the RCP8.5 scenario. NPP decreases in 5 models and increases in 1 model; 3 models show no significant trend. The main drivers include stronger nutrient limitation, but in many models warming-induced increases in phytoplankton growth outbalance the nutrient effect. Temperature-driven increases in grazing and other loss processes cause a net decrease in biomass and NPP.
P. R. Halloran, B. B. B. Booth, C. D. Jones, F. H. Lambert, D. J. McNeall, I. J. Totterdell, and C. Völker
Biogeosciences, 12, 4497–4508, https://doi.org/10.5194/bg-12-4497-2015, https://doi.org/10.5194/bg-12-4497-2015, 2015
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The oceans currently take up around a quarter of the carbon dioxide (CO2) emitted by human activity. While stored in the ocean, this CO2 is not causing global warming. Here we explore high latitude North Atlantic CO2 uptake across a set of climate model simulations, and find that the models show a peak in ocean CO2 uptake around the middle of the century after which time CO2 uptake begins to decline. We identify the causes of this long-term change and interannual variability in the models.
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
R. F. Ivanovic, P. J. Valdes, R. Flecker, and M. Gutjahr
Clim. Past, 10, 607–622, https://doi.org/10.5194/cp-10-607-2014, https://doi.org/10.5194/cp-10-607-2014, 2014
L. Bopp, L. Resplandy, J. C. Orr, S. C. Doney, J. P. Dunne, M. Gehlen, P. Halloran, C. Heinze, T. Ilyina, R. Séférian, J. Tjiputra, and M. Vichi
Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
P. J. Irvine, L. J. Gregoire, D. J. Lunt, and P. J. Valdes
Geosci. Model Dev., 6, 1447–1462, https://doi.org/10.5194/gmd-6-1447-2013, https://doi.org/10.5194/gmd-6-1447-2013, 2013
O. D. Andrews, N. L. Bindoff, P. R. Halloran, T. Ilyina, and C. Le Quéré
Biogeosciences, 10, 1799–1813, https://doi.org/10.5194/bg-10-1799-2013, https://doi.org/10.5194/bg-10-1799-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
J. H. T. Williams, R. S. Smith, P. J. Valdes, B. B. B. Booth, and A. Osprey
Geosci. Model Dev., 6, 141–160, https://doi.org/10.5194/gmd-6-141-2013, https://doi.org/10.5194/gmd-6-141-2013, 2013
B. Ringeval, P. O. Hopcroft, P. J. Valdes, P. Ciais, G. Ramstein, A. J. Dolman, and M. Kageyama
Clim. Past, 9, 149–171, https://doi.org/10.5194/cp-9-149-2013, https://doi.org/10.5194/cp-9-149-2013, 2013
Related subject area
Climate and Earth system modeling
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach
Towards the definition of a solar forcing dataset for CMIP7
ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
The Regional Climate-Chemistry-Ecology Coupling Model RegCM-Chem (v4.6)-YIBs (v1.0): Development and Application
Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections
An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields
An emulation-based approach for interrogating reactive transport models
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
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
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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.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
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The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
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The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
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This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
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Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
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Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
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Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Baiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1733, https://doi.org/10.5194/egusphere-2023-1733, 2023
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For the first time, we coupled a regional climate chemistry model RegCM-Chem with a dynamic vegetation model YIBs to create a regional climate-chemistry-ecology model RegCM-Chem-YIBs. We applied it to simulate climatic, chemical and ecological parameters in East Asia and fully validated it on a variety of observational data. The research results show that RegCM-Chem-YIBs model is a valuable tool for studying terrestrial carbon cycle, atmospheric chemistry, and climate change in regional scale.
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, https://doi.org/10.5194/gmd-16-7171-2023, 2023
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We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.
Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm
Geosci. Model Dev., 16, 7143–7170, https://doi.org/10.5194/gmd-16-7143-2023, https://doi.org/10.5194/gmd-16-7143-2023, 2023
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This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.
Angus Fotherby, Harold J. Bradbury, Jennifer L. Druhan, and Alexandra V. Turchyn
Geosci. Model Dev., 16, 7059–7074, https://doi.org/10.5194/gmd-16-7059-2023, https://doi.org/10.5194/gmd-16-7059-2023, 2023
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We demonstrate how, given a simulation of fluid and rock interacting, we can emulate the system using machine learning. This means that, for a given initial condition, we can predict the final state, avoiding the simulation step once the model has been trained. We present a workflow for applying this approach to any fluid–rock simulation and showcase two applications to different fluid–rock simulations. This approach has applications for improving model development and sensitivity analyses.
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The HadGEM2 Development Team: G. M. Martin, Bellouin, N., Collins, W. J., Culverwell, I. D., Halloran, P. R., Hardiman, S. C., Hinton, T. J., Jones, C. D., McDonald, R. E., McLaren, A. J., O'Connor, F. M., Roberts, M. J., Rodriguez, J. M., Woodward, S., Best, M. J., Brooks, M. E., Brown, A. R., Butchart, N., Dearden, C., Derbyshire, S. H., Dharssi, I., Doutriaux-Boucher, M., Edwards, J. M., Falloon, P. D., Gedney, N., Gray, L. J., Hewitt, H. T., Hobson, M., Huddleston, M. R., Hughes, J., Ineson, S., Ingram, W. J., James, P. M., Johns, T. C., Johnson, C. E., Jones, A., Jones, C. P., Joshi, M. M., Keen, A. B., Liddicoat, S., Lock, A. P., Maidens, A. V., Manners, J. C., Milton, S. F., Rae, J. G. L., Ridley, J. K., Sellar, A., Senior, C. A., Totterdell, I. J., Verhoef, A., Vidale, P. L., and Wiltshire, A.: The HadGEM2 family of Met Office Unified Model climate configurations, Geosci. Model Dev., 4, 723–757, https://doi.org/10.5194/gmd-4-723-2011, 2011.
Helm, K. P., Bindoff, N. L., and Chrusch, J. A.: Observed decreases in oxygen content of the global ocean, Geophys. Res. Lett., 38, L23602, https://doi.org/10.1029/2011GL049513, 2011.
Hewitt, H. T., Copsey, D., Culverwell, I. D., Harris, C. M., Hill, R. S. R., Keen, A. B., McLaren, A. J., and Hunke, E. C.: Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system, Geosci. Model Dev., 4, 223–253, https://doi.org/10.5194/gmd-4-223-2011, 2011.
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Smith, R. S.: The FAMOUS climate model (versions XFXWB and XFHCC): description update to version XDBUA, Geosci. Model Dev., 5, 269–276, https://doi.org/10.5194/gmd-5-269-2012, 2012.
Smith, R. S., Gregory, J. M., and Osprey, A.: A description of the FAMOUS (version XDBUA) climate model and control run, Geosci. Model Dev., 1, 53–68, https://doi.org/10.5194/gmd-1-53-2008, 2008.
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