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Geoscientific Model Development
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IF5.240
IF 5-year
5.768
5.768
CiteScore
8.9
8.9
SNIP1.713
IPP5.53
SJR3.18
Scimago H
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index71
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Abstracted/indexed
Abstracted/indexedSpecial issue
Short summary
Oceanic sediment cores are commonly used to understand past climates. The composition of the sediments changes with the ocean above it. An understanding of oceanographic conditions that existed many thousands of years ago, in some cases many millions of years ago, can therefore be extracted from sediment cores. We simulate two chemical signatures (13C and 15N) of sediment cores in a model. This study assesses the model before it is applied to reinterpret the sedimentary record.
Oceanic sediment cores are commonly used to understand past climates. The composition of the...
GMD | Articles | Volume 12, issue 4
Geosci. Model Dev., 12, 1491–1523, 2019
https://doi.org/10.5194/gmd-12-1491-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: The CSIRO Mk3L climate system model
Geosci. Model Dev., 12, 1491–1523, 2019
https://doi.org/10.5194/gmd-12-1491-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper 16 Apr 2019
Model description paper | 16 Apr 2019
Ocean carbon and nitrogen isotopes in CSIRO Mk3L-COAL version 1.0: a tool for palaeoceanographic research
Pearse J. Buchanan et al.
Related authors
Pearse J. Buchanan, Richard J. Matear, Andrew Lenton, Steven J. Phipps, Zanna Chase, and David M. Etheridge
Clim. Past, 12, 2271–2295, https://doi.org/10.5194/cp-12-2271-2016, https://doi.org/10.5194/cp-12-2271-2016, 2016
Short summary
Short summary
We quantify the contributions of physical and biogeochemical changes in the ocean to enhancing ocean carbon storage at the Last Glacial Maximum. We find that simulated circulation and surface conditions cannot explain changes in carbon storage or other major biogeochemical fields that existed during the glacial climate. Key modifications to the functioning of the biological pump are therefore required to explain the glacial climate and improve model–proxy agreement for all fields.
Steven J. Phipps, Jason L. Roberts, and Matt A. King
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-382, https://doi.org/10.5194/gmd-2020-382, 2020
Preprint under review for GMD
Short summary
Short summary
Simplified schemes, known as parameterisations, are sometimes used to describe physical processes within numerical models. However, the values of the parameters are uncertain. This introduces uncertainty into the model outputs. We develop a simple approach to identify plausible ranges for model parameters. Using a model of the Antarctic Ice Sheet, we find that the value of one parameter can depend on the values of others. We conclude that a single optimal set of parameter values does not exist.
Hakase Hayashida, Meibing Jin, Nadja S. Steiner, Neil C. Swart, Eiji Watanabe, Russell Fiedler, Andrew McC. Hogg, Andrew E. Kiss, Richard J. Matear, and Peter G. Strutton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-305, https://doi.org/10.5194/gmd-2020-305, 2020
Preprint under review for GMD
Short summary
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Ice algae are tiny plants like phytoplankton but they grow within sea ice. In polar regions, both phytoplankton and ice algae are the foundation of marine ecosystems and play an important role in taking up carbon dioxide in the atmosphere. However, state-of-the-art climate models typically do not include ice algae, and therefore their role in the climate system remains unclear. This project aims to address this knowledge gap by coordinating a set of experiments using sea ice-ocean models.
Yaowen Zheng, Lenneke M. Jong, Steven J. Phipps, Jason L. Roberts, Andrew D. Moy, Mark A. J. Curran, and Tas D. van Ommen
Clim. Past Discuss., https://doi.org/10.5194/cp-2020-124, https://doi.org/10.5194/cp-2020-124, 2020
Preprint under review for CP
Short summary
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South West Western Australia has experienced a prolonged drought in recent decades. The causes of this drought are unclear. We use an ice core from East Antarctica to reconstruct changes in rainfall over the past 2,000 years. We find that the current drought is unusual, with only two other droughts of similar severity having occurred during this period. Climate modelling shows that greenhouse gas emissions during the industrial era are likely to have contributed to the recent drying trend.
Andrew Lenton, Richard J. Matear, David P. Keller, Vivian Scott, and Naomi E. Vaughan
Earth Syst. Dynam., 9, 339–357, https://doi.org/10.5194/esd-9-339-2018, https://doi.org/10.5194/esd-9-339-2018, 2018
Short summary
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Artificial ocean alkalinization (AOA) is capable of reducing atmospheric carbon dioxide concentrations and surface warming while also addressing ocean acidification. We simulate the Earth system response to a fixed addition of AOA under low and high emissions. We explore the regional and global response to AOA. A key finding is that AOA is much more effective at reducing warming and ocean acidification under low emissions, despite lower carbon uptake.
Richard J. Matear and Andrew Lenton
Biogeosciences, 15, 1721–1732, https://doi.org/10.5194/bg-15-1721-2018, https://doi.org/10.5194/bg-15-1721-2018, 2018
Short summary
Short summary
We show climate–carbon feedbacks accelerate and enhance ocean acidification. Such an acceleration of ocean acidification may further undermine the ability of marine biota to adapt to the changing environment. Our study also identifies the need to use Earth system models to make future ocean acidification projections (relevance to AR6) and the need to reduce the uncertainty in the climate–carbon feedbacks.
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
Short summary
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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.
Camilla W. Stjern, Helene Muri, Lars Ahlm, Olivier Boucher, Jason N. S. Cole, Duoying Ji, Andy Jones, Jim Haywood, Ben Kravitz, Andrew Lenton, John C. Moore, Ulrike Niemeier, Steven J. Phipps, Hauke Schmidt, Shingo Watanabe, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 18, 621–634, https://doi.org/10.5194/acp-18-621-2018, https://doi.org/10.5194/acp-18-621-2018, 2018
Short summary
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Marine cloud brightening (MCB) has been proposed to help limit global warming. We present here the first multi-model assessment of idealized MCB simulations from the Geoengineering Model Intercomparison Project. While all models predict a global cooling as intended, there is considerable spread between the models both in terms of radiative forcing and the climate response, largely linked to the substantial differences in the models' representation of clouds.
PAGES Hydro2k Consortium
Clim. Past, 13, 1851–1900, https://doi.org/10.5194/cp-13-1851-2017, https://doi.org/10.5194/cp-13-1851-2017, 2017
Short summary
Short summary
Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited due to a paucity of modern instrumental observations. We review how proxy records of past climate and climate model simulations can be used in tandem to understand hydroclimate variability over the last 2000 years and how these tools can also inform risk assessments of future hydroclimatic extremes.
Duncan Ackerley, Jessica Reeves, Cameron Barr, Helen Bostock, Kathryn Fitzsimmons, Michael-Shawn Fletcher, Chris Gouramanis, Helen McGregor, Scott Mooney, Steven J. Phipps, John Tibby, and Jonathan Tyler
Clim. Past, 13, 1661–1684, https://doi.org/10.5194/cp-13-1661-2017, https://doi.org/10.5194/cp-13-1661-2017, 2017
Short summary
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A selection of climate models have been used to simulate both pre-industrial (1750 CE) and mid-Holocene (6000 years ago) conditions. This study presents an assessment of the temperature, rainfall and flow over Australasia from those climate models. The model data are compared with available proxy data reconstructions (e.g. tree rings) for 6000 years ago to identify whether the models are reliable. Places where there is both agreement and conflict are highlighted and investigated further.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
Short summary
Short summary
Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. LeGrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Francesco S. R. Pausata, Jean-Yves Peterschmitt, Steven J. Phipps, Hans Renssen, and Qiong Zhang
Geosci. Model Dev., 10, 3979–4003, https://doi.org/10.5194/gmd-10-3979-2017, https://doi.org/10.5194/gmd-10-3979-2017, 2017
Short summary
Short summary
The PMIP4 and CMIP6 mid-Holocene and Last Interglacial simulations provide an opportunity to examine the impact of two different changes in insolation forcing on climate at times when other forcings were relatively similar to present. This will allow exploration of the role of feedbacks relevant to future projections. Evaluating these simulations using paleoenvironmental data will provide direct out-of-sample tests of the reliability of state-of-the-art models to simulate climate changes.
Rachel M. Law, Tilo Ziehn, Richard J. Matear, Andrew Lenton, Matthew A. Chamberlain, Lauren E. Stevens, Ying-Ping Wang, Jhan Srbinovsky, Daohua Bi, Hailin Yan, and Peter F. Vohralik
Geosci. Model Dev., 10, 2567–2590, https://doi.org/10.5194/gmd-10-2567-2017, https://doi.org/10.5194/gmd-10-2567-2017, 2017
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The paper describes a version of the Australian Community Climate and Earth System Simulator that has been enabled to simulate the carbon cycle, which is designated ACCESS-ESM1. The model performance for pre-industrial conditions is assessed and land and ocean carbon fluxes are found to be simulated realistically.
Tilo Ziehn, Andrew Lenton, Rachel M. Law, Richard J. Matear, and Matthew A. Chamberlain
Geosci. Model Dev., 10, 2591–2614, https://doi.org/10.5194/gmd-10-2591-2017, https://doi.org/10.5194/gmd-10-2591-2017, 2017
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Our work presents the evaluation of the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) over the historical period (1850–2005). The main focus is on climate and carbon related variables. Globally integrated land–atmosphere and ocean–atmosphere fluxes and flux patterns are well reproduced and show good agreement with most recent observations. This makes ACCESS-ESM1 a useful tool to explore the change in land and oceanic carbon uptake in the future.
James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
Short summary
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The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Serena Schroeter, Will Hobbs, and Nathaniel L. Bindoff
The Cryosphere, 11, 789–803, https://doi.org/10.5194/tc-11-789-2017, https://doi.org/10.5194/tc-11-789-2017, 2017
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Observed trends of Antarctic sea ice are not reproduced by global climate models. We examine observed and simulated interactions between sea ice and large-scale atmospheric variability, showing that global climate models generally capture observed interactions during the season of sea ice advance, but not during sea ice retreat. Most models overestimate the zonally symmetric influence of the dominant atmospheric mode on sea ice, while the importance of tropical variability is underestimated.
Pearse J. Buchanan, Richard J. Matear, Andrew Lenton, Steven J. Phipps, Zanna Chase, and David M. Etheridge
Clim. Past, 12, 2271–2295, https://doi.org/10.5194/cp-12-2271-2016, https://doi.org/10.5194/cp-12-2271-2016, 2016
Short summary
Short summary
We quantify the contributions of physical and biogeochemical changes in the ocean to enhancing ocean carbon storage at the Last Glacial Maximum. We find that simulated circulation and surface conditions cannot explain changes in carbon storage or other major biogeochemical fields that existed during the glacial climate. Key modifications to the functioning of the biological pump are therefore required to explain the glacial climate and improve model–proxy agreement for all fields.
Emlyn M. Jones, Mark E. Baird, Mathieu Mongin, John Parslow, Jenny Skerratt, Jenny Lovell, Nugzar Margvelashvili, Richard J. Matear, Karen Wild-Allen, Barbara Robson, Farhan Rizwi, Peter Oke, Edward King, Thomas Schroeder, Andy Steven, and John Taylor
Biogeosciences, 13, 6441–6469, https://doi.org/10.5194/bg-13-6441-2016, https://doi.org/10.5194/bg-13-6441-2016, 2016
Short summary
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Marine biogeochemical models are often used to understand water quality, nutrient and blue-carbon dynamics at scales that range from estuaries and bays, through to the global ocean. We introduce a new methodology allowing for the assimilation of observed remote sensing reflectances, avoiding the need to use empirically derived chlorophyll-a concentrations. This method opens up the possibility to assimilate of reflectances from a variety of missions and potentially non-satellite platforms.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. Legrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Jean-Yves Peterschmidt, Francesco S.-R. Pausata, Steven Phipps, and Hans Renssen
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-106, https://doi.org/10.5194/cp-2016-106, 2016
Preprint retracted
Steven J. Phipps, Christopher J. Fogwill, and Christian S. M. Turney
The Cryosphere, 10, 2317–2328, https://doi.org/10.5194/tc-10-2317-2016, https://doi.org/10.5194/tc-10-2317-2016, 2016
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We explore the effects of melting of the East Antarctic Ice Sheet on the Southern Ocean. Using a climate model, we find that melting changes the ocean circulation and causes warming of more than 1 °C at depth. We also discover the potential existence of a "domino effect", whereby the initial warming spreads westwards around the Antarctic continent. Melting of just one sector could therefore destabilise the wider Antarctic Ice Sheet, leading to substantial increases in global sea level.
Andrew Lenton, Bronte Tilbrook, Richard J. Matear, Tristan P. Sasse, and Yukihiro Nojiri
Biogeosciences, 13, 1753–1765, https://doi.org/10.5194/bg-13-1753-2016, https://doi.org/10.5194/bg-13-1753-2016, 2016
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We reconstruct the observed variability and mean state in pH and aragonite saturation state around Australia at high spatial resolution and reconstruct the changes that have occurred in the Australian region over the last 140 years. We find that large changes in aragonite saturation state and pH have very different spatial patterns, which suggests that the biological responses to ocean acidification are likely to be non-uniform and dependent on the relative sensitivity of organisms to change.
Paulina Cetina-Heredia, Erik van Sebille, Richard Matear, and Moninya Roughan
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-53, https://doi.org/10.5194/bg-2016-53, 2016
Revised manuscript not accepted
Short summary
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Characterizing phytoplankton growth influences fisheries and climate. We use a lagrangian approach to identify phytoplankton blooms in the Great Australian Bight (GAB), and associate them with nitrate sources. We find that 88 % of the nitrate utilized in blooms is originated between the GAB and the SubAntarctic Front. Large nitrate concentrations are supplied at depth but do not reach the euphotic zone often. As a result, 55 % of blooms utilize nitrate supplied in the top 100 m.
X. Zhang, P. R. Oke, M. Feng, M. A. Chamberlain, J. A. Church, D. Monselesan, C. Sun, R. J. Matear, A. Schiller, and R. Fiedler
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-17, https://doi.org/10.5194/gmd-2016-17, 2016
Revised manuscript not accepted
Short summary
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Eddy-resolving global ocean models are highly desired, but expensive to run, and also subject to many problems including drift. Here we modified a near-global eddy-resolving OGCM for climate studies with some novel strategies. We demonstrated that the historical experiment driven by Japanese atmospheric reanalysis product, didn't have significant drifts, and also provided an eddy-resolving simulation of the global ocean over 1979–2014. Our experiences can be helpful to other modelling groups.
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
T. P. Sasse, B. I. McNeil, R. J. Matear, and A. Lenton
Biogeosciences, 12, 6017–6031, https://doi.org/10.5194/bg-12-6017-2015, https://doi.org/10.5194/bg-12-6017-2015, 2015
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Our results show that accounting for oceanic CO2 seasonality is crucial to projecting the future onset of critical ocean acidification levels (i.e. aragonite undersaturation). In particular, seasonality will bring forward the initial onset of month-long undersaturation by a global average of 17 years. Importantly, widespread undersaturation is projected to occur once atmospheric CO2 reaches 496ppm in the North Pacific and 511ppm in the Southern Ocean, independent of emissions scenario.
P. G. Strutton, V. J. Coles, R. R. Hood, R. J. Matear, M. J. McPhaden, and H. E. Phillips
Biogeosciences, 12, 2367–2382, https://doi.org/10.5194/bg-12-2367-2015, https://doi.org/10.5194/bg-12-2367-2015, 2015
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In 2010, a first-of-its-kind deployment of biological sensors on a mooring in the central Indian Ocean revealed interesting variability in chlorophyll (a proxy for ocean productivity) at timescales of about 2 weeks. Using the mooring data with satellite observations and a biogeochemical model, it was determined that local wind mixing and entrainment, rather than mixed Rossby gravity waves, were likely responsible for much of the observed variability.
R. J. Matear, A. Lenton, D. Etheridge, and S. J. Phipps
Clim. Past Discuss., https://doi.org/10.5194/cpd-11-1093-2015, https://doi.org/10.5194/cpd-11-1093-2015, 2015
Revised manuscript has not been submitted
Short summary
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Global climate models provide an important tool for simulating the earth's climate. Here we present a simulation of the climate of the Last Glacial Maximum, which was obtained by setting atmospheric greenhouse gas concentrations and the earth's orbital parameters to the 21 000 years before present values. We simulate an ocean behaviour that agrees with paleoclimate reconstructions supporting our ability to model the climate system and use the model to explore the impacts on the carbon cycle.
R. J. Matear and A. Lenton
Biogeosciences, 11, 3965–3983, https://doi.org/10.5194/bg-11-3965-2014, https://doi.org/10.5194/bg-11-3965-2014, 2014
U. Heikkilä, X. Shi, S. J. Phipps, and A. M. Smith
Clim. Past, 10, 687–696, https://doi.org/10.5194/cp-10-687-2014, https://doi.org/10.5194/cp-10-687-2014, 2014
O. Duteil, W. Koeve, A. Oschlies, D. Bianchi, E. Galbraith, I. Kriest, and R. Matear
Biogeosciences, 10, 7723–7738, https://doi.org/10.5194/bg-10-7723-2013, https://doi.org/10.5194/bg-10-7723-2013, 2013
U. Heikkilä, S. J. Phipps, and A. M. Smith
Clim. Past, 9, 2641–2649, https://doi.org/10.5194/cp-9-2641-2013, https://doi.org/10.5194/cp-9-2641-2013, 2013
A. Lenton, B. Tilbrook, R. M. Law, D. Bakker, S. C. Doney, N. Gruber, M. Ishii, M. Hoppema, N. S. Lovenduski, R. J. Matear, B. I. McNeil, N. Metzl, S. E. Mikaloff Fletcher, P. M. S. Monteiro, C. Rödenbeck, C. Sweeney, and T. Takahashi
Biogeosciences, 10, 4037–4054, https://doi.org/10.5194/bg-10-4037-2013, https://doi.org/10.5194/bg-10-4037-2013, 2013
P. R. Oke, D. A. Griffin, A. Schiller, R. J. Matear, R. Fiedler, J. Mansbridge, A. Lenton, M. Cahill, M. A. Chamberlain, and K. Ridgway
Geosci. Model Dev., 6, 591–615, https://doi.org/10.5194/gmd-6-591-2013, https://doi.org/10.5194/gmd-6-591-2013, 2013
B. I. McNeil and R. J. Matear
Biogeosciences, 10, 2219–2228, https://doi.org/10.5194/bg-10-2219-2013, https://doi.org/10.5194/bg-10-2219-2013, 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
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Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applications
Ecological ReGional Ocean Model with vertically resolved sediments (ERGOM SED 1.0): coupling benthic and pelagic biogeochemistry of the south-western Baltic Sea
Reanalysis of the PacIOOS Hawaiian Island Ocean Forecast System, an implementation of the Regional Ocean Modeling System v3.6
Thetis coastal ocean model: discontinuous Galerkin discretization for the three-dimensional hydrostatic equations
Data assimilation cycle length and observation impact in mesoscale ocean forecasting
Verification of the mixed layer depth in the OceanMAPS operational forecast model for Austral autumn
A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with improved particle dynamics (NEMO–ProThorP 0.1)
Veros v0.1 – a fast and versatile ocean simulator in pure Python
Cohesive and mixed sediment in the Regional Ocean Modeling System (ROMS v3.6) implemented in the Coupled Ocean–Atmosphere–Wave–Sediment Transport Modeling System (COAWST r1234)
OpenDrift v1.0: a generic framework for trajectory modelling
A 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM 1.4
AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf
SedFoam-2.0: a 3-D two-phase flow numerical model for sediment transport
Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age
The Oceanographic Multipurpose Software Environment (OMUSE v1.0)
The CO5 configuration of the 7 km Atlantic Margin Model: large-scale biases and sensitivity to forcing, physics options and vertical resolution
Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6
“Climate response functions” for the Arctic Ocean: a proposed coordinated modelling experiment
The iFlow modelling framework v2.4: a modular idealized process-based model for flow and transport in estuaries
Development of BFMCOUPLER (v1.0), the coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations
Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution
Tor Nordam and Rodrigo Duran
Geosci. Model Dev., 13, 5935–5957, https://doi.org/10.5194/gmd-13-5935-2020, https://doi.org/10.5194/gmd-13-5935-2020, 2020
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In applied oceanography, a common task is to calculate the trajectory of objects floating at the sea surface or submerged in the water. We have investigated different numerical methods for doing such calculations and discuss the benefits and challenges of some common methods. We then propose a small change to some common methods that make them more efficient for this particular application. This will allow researchers to obtain more accurate answers with fewer computer resources.
Clément Bricaud, Julien Le Sommer, Gurvan Madec, Christophe Calone, Julie Deshayes, Christian Ethe, Jérôme Chanut, and Marina Levy
Geosci. Model Dev., 13, 5465–5483, https://doi.org/10.5194/gmd-13-5465-2020, https://doi.org/10.5194/gmd-13-5465-2020, 2020
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In order to reduce the cost of ocean biogeochemical models, a multi-grid approach where ocean dynamics and tracer transport are computed with different spatial resolution has been developed in the NEMO v3.6 OGCM. Different experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened without significantly affecting the resolved passive tracer fields. This approach leads to a factor of 7 reduction of the overhead associated with running a full biogeochemical model.
Clark Pennelly and Paul G. Myers
Geosci. Model Dev., 13, 4959–4975, https://doi.org/10.5194/gmd-13-4959-2020, https://doi.org/10.5194/gmd-13-4959-2020, 2020
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A high-resolution ocean simulation was carried out within the Labrador Sea, a region that low-resolution climate simulations may misrepresent. We show that small-scale eddies and their associated transport are better resolved at higher resolution than at lower resolution. These eddies transport important properties to the interior of the Labrador Sea, impacting the stratification and reducing the convection extent so that it is far more accurate when compared to what observations suggest.
Bijoy Thompson, Claudio Sanchez, Boon Chong Peter Heng, Rajesh Kumar, Jianyu Liu, Xiang-Yu Huang, and Pavel Tkalich
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-326, https://doi.org/10.5194/gmd-2020-326, 2020
Revised manuscript accepted for GMD
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This article describes the development and ocean forecast evaluation of an atmosphere-ocean coupled prediction system for the Maritime Continent domain, which includes the eastern Indian and western Pacific Oceans. The coupled system comprises regional configurations of the atmospheric model MetUM and ocean model NEMO, coupled using the OASIS3-MCT libraries. The model forecast deviation of selected fields relative to observation is within acceptable error limits of operational forecast models.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
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This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Mark E. Baird, Karen A. Wild-Allen, John Parslow, Mathieu Mongin, Barbara Robson, Jennifer Skerratt, Farhan Rizwi, Monika Soja-Woźniak, Emlyn Jones, Mike Herzfeld, Nugzar Margvelashvili, John Andrewartha, Clothilde Langlais, Matthew P. Adams, Nagur Cherukuru, Malin Gustafsson, Scott Hadley, Peter J. Ralph, Uwe Rosebrock, Thomas Schroeder, Leonardo Laiolo, Daniel Harrison, and Andrew D. L. Steven
Geosci. Model Dev., 13, 4503–4553, https://doi.org/10.5194/gmd-13-4503-2020, https://doi.org/10.5194/gmd-13-4503-2020, 2020
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For 20+ years, the Commonwealth Science Industry and Research Organisation (CSIRO) has been developing a biogeochemical (BGC) model for coupling with a hydrodynamic and sediment model for application in estuaries, coastal waters and shelf seas. This paper provides a full mathematical description (equations, parameters), model evaluation and access to the numerical code. The model is particularly suited to applications in shallow waters where benthic processes are critical to ecosystem function.
Kristen M. Thyng, Daijiro Kobashi, Veronica Ruiz-Xomchuk, Lixin Qu, Xu Chen, and Robert D. Hetland
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-221, https://doi.org/10.5194/gmd-2020-221, 2020
Revised manuscript accepted for GMD
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We modified the ROMS ocean model to run in offline mode so that previously-run fields of sea surface height and velocity fields are input to calculate tracer advection without running the full model with a larger time step to run faster. The code was tested with 2 advection schemes and both are robust with over 99% accuracy of the offline to online run after 14 simulation days. This allows for ROMS users to maximize use of new or existing output to quickly run additional tracer simulations.
Angela A. Bahamondes Dominguez, Anna E. Hickman, Robert Marsh, and C. Mark Moore
Geosci. Model Dev., 13, 4019–4040, https://doi.org/10.5194/gmd-13-4019-2020, https://doi.org/10.5194/gmd-13-4019-2020, 2020
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The central Celtic Sea has previously been studied with a 1-D model called S2P3, showing discrepancies between observations and the model results due to poor representation of some processes. Therefore, the S2P3 model was developed to include zooplankton and phytoplankton cells' adaptation to changes in irradiance. Results demonstrate that better agreement with biological observations can be achieved when the model includes these processes and is adequately constrained.
Pavel Perezhogin, Ilya Chernov, and Nikolay Iakovlev
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-182, https://doi.org/10.5194/gmd-2020-182, 2020
Revised manuscript accepted for GMD
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We describe the parallel implementation of the FEMAO model of an ice-covered sea with 2D Hilbert-curve domain decomposition. Load-balancing is crucial because performance depends on the local depth. We propose, compare, and discuss four approaches to load balancing. The parallel library allowed to modify the original sequential algorithm as little as possible. The performance increases almost linearly (tested up to 996 CPU cores) for the model of the shallow White Sea.
Alexander G. López, John L. Wilkin, and Julia C. Levin
Geosci. Model Dev., 13, 3709–3729, https://doi.org/10.5194/gmd-13-3709-2020, https://doi.org/10.5194/gmd-13-3709-2020, 2020
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This article describes a regional circulation model, Doppio, for the Mid-Atlantic Bight and the Gulf of Maine. The model demonstrates useful skill in comparison to a comprehensive suite of observations. Development focused on achieving a model configuration that allows decadal-scale simulations of physical ocean circulation that can underpin studies of ecosystems and biogeochemistry. Doppio captures the temperature and salinity stratification well, along with the large-scale mean circulation.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
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The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Jordyn E. Moscoso, Andrew L. Stewart, Daniele Bianchi, and James C. McWilliams
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-173, https://doi.org/10.5194/gmd-2020-173, 2020
Revised manuscript accepted for GMD
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This project was created to understand the across-shore distribution of plankton in the California Current System. To complete this study, we used a quasi-2D dynamical model coupled to an ecosystem model. This paper is a preliminary study to test and validate the model against data collected by The California Cooperative Oceanic Fisheries Investigations (CalCOFI). We show the solution of our model solution compares well to the data and discuss our model as a tool for further model development.
Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Hervé Giordani, Théo Brivoal, and Gurvan Madec
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-210, https://doi.org/10.5194/gmd-2020-210, 2020
Revised manuscript accepted for GMD
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A simplified model of the Atmospheric Boundary Layer (ABL) of intermediate complexity between a bulk parameterization and a full three-dimensional atmospheric model has been developed and integrated to the NEMO ocean model.
An objective in the derivation of such simplified model is to reach an apt representation in ocean-only numerical simulations of some of the key processes associated to air/sea interactions at the characteristic scales of the oceanic mesoscale.
Pedro Colombo, Bernard Barnier, Thierry Penduff, Jérôme Chanut, Julie Deshayes, Jean-Marc Molines, Julien Le Sommer, Polina Verezemskaya, Sergey Gulev, and Anne-Marie Treguier
Geosci. Model Dev., 13, 3347–3371, https://doi.org/10.5194/gmd-13-3347-2020, https://doi.org/10.5194/gmd-13-3347-2020, 2020
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In the ocean circulation model NEMO, the representation of the overflow of dense Arctic waters through the Denmark Strait is investigated. In this
z-coordinate context, sensitivity tests show that the mixing parameterizations preferably act along the model grid slope. Thus, the representation of the overflow is more sensitive to resolution than to parameterization and is best when the numerical grid matches the local topographic slope.
Hideharu Sasaki, Shinichiro Kida, Ryo Furue, Hidenori Aiki, Nobumasa Komori, Yukio Masumoto, Toru Miyama, Masami Nonaka, Yoshikazu Sasai, and Bunmei Taguchi
Geosci. Model Dev., 13, 3319–3336, https://doi.org/10.5194/gmd-13-3319-2020, https://doi.org/10.5194/gmd-13-3319-2020, 2020
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A quasi-global eddying ocean hindcast simulation using a new version of our model, called OFES2, was conducted to overcome several issues in its previous version. OFES2 simulated oceanic fields from 1958 to 2016 with improved global sea surface temperature and salinity, water mass properties in the Indonesian and Arabian seas, and Niño3.4 and Indian Ocean Dipole indexes. The output from OFES2 will be useful in studying various oceanic phenomena with broad spatiotemporal scales.
Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-61, https://doi.org/10.5194/gmd-2020-61, 2020
Revised manuscript accepted for GMD
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The problem of the optimization of ocean monitoring networks is tackled throughout the implementation of data assimilation techniques in a numerical model. The methodology has been applied and tested to the tide gauge network in the Lagoon of Venice (Italy). The data assimilation methods allow identifying the minimum number of stations and their distribution that correctly represent the lagoon’s dynamics. With the help of the numerical model, two-thirds of the monitoring network can be dismissed.
Katixa Lajaunie-Salla, Frédéric Diaz, Cathy Wimart-Rousseau, Thibaut Wagener, Dominique Lefèvre, Christophe Yohia, Irène Xueref-Remy, Brian Nathan, Alexandre Armengaud, and Christel Pinazo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-41, https://doi.org/10.5194/gmd-2020-41, 2020
Revised manuscript accepted for GMD
Dafydd Stephenson, Simon A. Müller, and Florian Sévellec
Geosci. Model Dev., 13, 2031–2050, https://doi.org/10.5194/gmd-13-2031-2020, https://doi.org/10.5194/gmd-13-2031-2020, 2020
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Different water types are created at the sea surface with a signature based on the local conditions of the atmosphere. They then take these conditions with them into the deeper ocean, and so their journey is an important climate process to understand. In this study, we modify and repurpose a specialised model which simulates the ocean forward and backward in time to determine where new ocean water goes, where at the surface existing water comes from, and how old it is, by tracking it as a dye.
Violaine Piton, Marine Herrmann, Florent Lyard, Patrick Marsaleix, Thomas Duhaut, Damien Allain, and Sylvain Ouillon
Geosci. Model Dev., 13, 1583–1607, https://doi.org/10.5194/gmd-13-1583-2020, https://doi.org/10.5194/gmd-13-1583-2020, 2020
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Consequences of tidal dynamics on hydro-sedimentary processes are a recurrent issue in estuarine and coastal processes studies, and accurate tidal solutions are a prerequisite for modeling sediment transport. This study presents the implementation and optimization of a model configuration in terms of bathymetry and bottom friction and assess the influence of these parameters on tidal solutions, in a macro-tidal environment: the Gulf of Tonkin (Vietnam).
Alexander Barth, Aida Alvera-Azcárate, Matjaz Licer, and Jean-Marie Beckers
Geosci. Model Dev., 13, 1609–1622, https://doi.org/10.5194/gmd-13-1609-2020, https://doi.org/10.5194/gmd-13-1609-2020, 2020
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DINCAE is a method for reconstructing missing data in satellite datasets using a neural network. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convolutional auto-encoder is developed to reconstruct the missing data based on the available cloud-free pixels in satellite images.
Jiangyu Li and Shaoqing Zhang
Geosci. Model Dev., 13, 1035–1054, https://doi.org/10.5194/gmd-13-1035-2020, https://doi.org/10.5194/gmd-13-1035-2020, 2020
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Two assimilation systems developed using two nearly independent wave models are used to study the influences of various error sources including mode bias on wave data assimilation; a statistical method is explored to make full use of the merits of individual assimilation systems for bias correction, thus improving wave analysis greatly. This study opens a door to further our understanding of physical processes in waves and associated air–sea interactions for improving wave modeling.
Heiner Dietze, Ulrike Löptien, and Julia Getzlaff
Geosci. Model Dev., 13, 71–97, https://doi.org/10.5194/gmd-13-71-2020, https://doi.org/10.5194/gmd-13-71-2020, 2020
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We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
Jaap H. Nienhuis and Jorge Lorenzo-Trueba
Geosci. Model Dev., 12, 4013–4030, https://doi.org/10.5194/gmd-12-4013-2019, https://doi.org/10.5194/gmd-12-4013-2019, 2019
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The response of barrier islands to sea level rise depends on their ability to move landward through the transport of sediment from the beach to the back barrier. The BRIE model simulates these processes and the resulting landward movement of barrier islands. The novelty of the BRIE model is the incorporation of tidal inlets (gaps between barrier islands) that can transport sediment landward and therefore help keep barrier islands above sea level.
Bjarne Büchmann
Geosci. Model Dev., 12, 3915–3922, https://doi.org/10.5194/gmd-12-3915-2019, https://doi.org/10.5194/gmd-12-3915-2019, 2019
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Operational forecasting of the ocean state – e.g. used for ship route planning, sea rescue, and oil spill drift models – relies on data (forcing) obtained from weather forecasting. Unfortunately, the so-called meteorological analysis step introduces a discontinuity, which affects the ocean models adversely. In the present paper, a straightforward method to deal with the issue is introduced. Practical examples are given to illuminate the scale of the problem.
Philippe Delandmeter and Erik van Sebille
Geosci. Model Dev., 12, 3571–3584, https://doi.org/10.5194/gmd-12-3571-2019, https://doi.org/10.5194/gmd-12-3571-2019, 2019
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Parcels is a framework to compute how ocean currents transport
stuffsuch as plankton and plastic around. In the latest version 2.0 of Parcels, we focus on more accurate interpolation schemes and implement methods to seamlessly combine data from different sources (such as winds and currents, possibly in different regions). We show that this framework is very efficient for tracking how microplastic is transported through the North Sea into the Arctic.
Franziska U. Schwarzkopf, Arne Biastoch, Claus W. Böning, Jérôme Chanut, Jonathan V. Durgadoo, Klaus Getzlaff, Jan Harlaß, Jan K. Rieck, Christina Roth, Markus M. Scheinert, and René Schubert
Geosci. Model Dev., 12, 3329–3355, https://doi.org/10.5194/gmd-12-3329-2019, https://doi.org/10.5194/gmd-12-3329-2019, 2019
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A family of nested global ocean general circulation model configurations, the INALT family, has been established with resolutions of 1/10°, 1/20° and 1/60° in the South Atlantic and western Indian oceans, covering the greater Agulhas Current (AC) system. The INALT family provides a consistent set of configurations that allows to address eddy dynamics in the AC system and their impact on the large-scale ocean circulation.
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, https://doi.org/10.5194/gmd-12-2635-2019, 2019
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Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
Keith J. Roberts, William J. Pringle, and Joannes J. Westerink
Geosci. Model Dev., 12, 1847–1868, https://doi.org/10.5194/gmd-12-1847-2019, https://doi.org/10.5194/gmd-12-1847-2019, 2019
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Computer simulations can be used to reproduce the dynamics of the ocean near the coast. These simulations often use a mesh of triangles to represent the domain since they can be orientated and disparately sized in such a way to accurately fit the coastline shape. This paper describes a software package (OceanMesh2D v1.0) that has been developed in order to automatically and objectively design triangular meshes based on geospatial data inputs that represent the coastline and ocean depths.
Carlos Rocha, Christopher A. Edwards, Moninya Roughan, Paulina Cetina-Heredia, and Colette Kerry
Geosci. Model Dev., 12, 441–456, https://doi.org/10.5194/gmd-12-441-2019, https://doi.org/10.5194/gmd-12-441-2019, 2019
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Off southeast Australia, the East Australian Current (EAC) moves warm nutrient-poor waters towards the pole. In this region, the EAC and a large number of vortices pinching off it strongly affect phytoplankton’s access to nutrients and light. To study these dynamics, we created a numerical model that is able to solve the ocean conditions and how they modulate the foundation of the region’s ecosystem. We validated model results against available data and this showed that the model performs well.
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
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Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Hagen Radtke, Marko Lipka, Dennis Bunke, Claudia Morys, Jana Woelfel, Bronwyn Cahill, Michael E. Böttcher, Stefan Forster, Thomas Leipe, Gregor Rehder, and Thomas Neumann
Geosci. Model Dev., 12, 275–320, https://doi.org/10.5194/gmd-12-275-2019, https://doi.org/10.5194/gmd-12-275-2019, 2019
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This paper describes a coupled benthic–pelagic biogeochemical model, ERGOM-SED. We demonstrate its use in a one-dimensional physical model, which is horizontally integrated and vertically resolved. We describe the application of the model to seven stations in the south-western Baltic Sea. The model was calibrated using pore water profiles from these stations. We compare the model results to these and to measured sediment compositions, benthopelagic fluxes and bioturbation intensities.
Dale Partridge, Tobias Friedrich, and Brian S. Powell
Geosci. Model Dev., 12, 195–213, https://doi.org/10.5194/gmd-12-195-2019, https://doi.org/10.5194/gmd-12-195-2019, 2019
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This paper demonstrates the improvements made to an operational ocean forecast model around the Hawaiian Islands by performing a reanalysis of the model over a 10-year period. Using a number of different measurements we show the role a variety of observations play in producing the forecast, in particular the contribution of high-frequency radar.
Tuomas Kärnä, Stephan C. Kramer, Lawrence Mitchell, David A. Ham, Matthew D. Piggott, and António M. Baptista
Geosci. Model Dev., 11, 4359–4382, https://doi.org/10.5194/gmd-11-4359-2018, https://doi.org/10.5194/gmd-11-4359-2018, 2018
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Unstructured meshes are attractive for coastal ocean modeling, as they allow more accurate representation of complex coastal topography. Unstructured mesh models are, however, often perceived as slow and inaccurate. We present a novel discontinuous Galerkin ocean model: Thetis. We demonstrate that the model is able to simulate baroclinic ocean flows with high accuracy on a triangular prismatic mesh. This work paves the way for highly accurate and efficient three-dimensional coastal ocean models.
Paul Sandery
Geosci. Model Dev., 11, 4011–4019, https://doi.org/10.5194/gmd-11-4011-2018, https://doi.org/10.5194/gmd-11-4011-2018, 2018
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This article compares global mesoscale ocean forecasts with different data assimilation cycle lengths. Mean absolute increment is used to quantify differences in the overall impact of observations. Greater observation impact does not necessarily improve a forecast system. Experiments show a 1-day cycle generates improved 7-day forecasts when compared to a 3-day cycle. Cycle length is an important choice that influences system bias and predictability.
Daniel Boettger, Robin Robertson, and Gary B. Brassington
Geosci. Model Dev., 11, 3795–3805, https://doi.org/10.5194/gmd-11-3795-2018, https://doi.org/10.5194/gmd-11-3795-2018, 2018
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This study focuses on the impact of the model vertical mixing parameterisation on the representation of the mixed layer depth (MLD) in ocean forecast models. We compare data from two recent versions of the OceanMAPS forecast system, and find that while there were large improvements in the later version of the model, the skill of each parameterisation varies with spatial location.
Marco van Hulten, Jean-Claude Dutay, and Matthieu Roy-Barman
Geosci. Model Dev., 11, 3537–3556, https://doi.org/10.5194/gmd-11-3537-2018, https://doi.org/10.5194/gmd-11-3537-2018, 2018
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We present an ocean model of the natural radioactive isotopes thorium-230 and protactinium-231. These isotopes are often used to investigate past ocean circulation and particle transport. They are removed by particles produced by plankton and from uplifted desert dust that is deposited into the ocean. We approach observed dissolved and adsorbed Th-230 and Pa-231 activities. The Pa-231 / Th-230 sedimentation ratio is reproduced as well; this quantity can be used as a proxy for ocean circulation.
Dion Häfner, René Løwe Jacobsen, Carsten Eden, Mads R. B. Kristensen, Markus Jochum, Roman Nuterman, and Brian Vinter
Geosci. Model Dev., 11, 3299–3312, https://doi.org/10.5194/gmd-11-3299-2018, https://doi.org/10.5194/gmd-11-3299-2018, 2018
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Well-performing, easy-to-use ocean models are a central ingredient to further the understanding of our Earth and climate. Veros, the versatile ocean simulator, is the first full-blown ocean model entirely written in the high-level programming language Python. It is considerably more approachable than traditional Fortran models and leverages modern best practices; at the same time, thanks to the Bohrium framework, Veros is about half as fast as a reference implementation in Fortran 90.
Christopher R. Sherwood, Alfredo L. Aretxabaleta, Courtney K. Harris, J. Paul Rinehimer, Romaric Verney, and Bénédicte Ferré
Geosci. Model Dev., 11, 1849–1871, https://doi.org/10.5194/gmd-11-1849-2018, https://doi.org/10.5194/gmd-11-1849-2018, 2018
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Cohesive sediment (mud) is ubiquitous in the world's coastal regions, but its behavior is complicated and often oversimplified by computer models. This paper describes extensions to a widely used open-source coastal ocean model that allow users to simulate important components of cohesive sediment transport.
Knut-Frode Dagestad, Johannes Röhrs, Øyvind Breivik, and Bjørn Ådlandsvik
Geosci. Model Dev., 11, 1405–1420, https://doi.org/10.5194/gmd-11-1405-2018, https://doi.org/10.5194/gmd-11-1405-2018, 2018
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We have developed a computer code with ability to predict how various substances and objects drift in the ocean. This may be used to, e.g. predict the drift of oil to aid cleanup operations, the drift of man-over-board or lifeboats to aid search and rescue operations, or the drift of fish eggs and larvae to understand and manage fish stocks. This new code merges all such applications into one software tool, allowing to optimise and channel any available resources and developments.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255, https://doi.org/10.5194/gmd-11-1229-2018, https://doi.org/10.5194/gmd-11-1229-2018, 2018
Short summary
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For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, https://doi.org/10.5194/gmd-11-681-2018, 2018
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This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
Julien Chauchat, Zhen Cheng, Tim Nagel, Cyrille Bonamy, and Tian-Jian Hsu
Geosci. Model Dev., 10, 4367–4392, https://doi.org/10.5194/gmd-10-4367-2017, https://doi.org/10.5194/gmd-10-4367-2017, 2017
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This manuscript presents the development and validation of a two-phase flow Eulerian-Eulerian model based on OpenFOAM for sediment transport applications. The mathematical and numerical models are described in detail. The numerical implementation is demonstrated on four test cases: sedimentation of suspended particles, laminar bed load, sheet flow, and scour at an apron. These test cases illustrate the capabilities of SedFoam to deal with complex turbulent sediment transport problems.
Michael Lange and Erik van Sebille
Geosci. Model Dev., 10, 4175–4186, https://doi.org/10.5194/gmd-10-4175-2017, https://doi.org/10.5194/gmd-10-4175-2017, 2017
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Here, we present version 0.9 of Parcels (Probably A Really Computationally Efficient Lagrangian Simulator). Parcels is an experimental prototype code aimed at exploring novel approaches for Lagrangian tracking of virtual ocean particles in the petascale age. The modularity, flexibility and scalability will allow the code to be used to track water, nutrients, microbes, plankton, plastic and even fish.
Inti Pelupessy, Ben van Werkhoven, Arjen van Elteren, Jan Viebahn, Adam Candy, Simon Portegies Zwart, and Henk Dijkstra
Geosci. Model Dev., 10, 3167–3187, https://doi.org/10.5194/gmd-10-3167-2017, https://doi.org/10.5194/gmd-10-3167-2017, 2017
Short summary
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Researchers from the Netherlands present OMUSE, a software package
developed from core technology originating in the astrophysical
community. Using OMUSE, oceanographic and climate researchers can
develop numerical models of the ocean and the interactions between
different parts of the ocean and the atmosphere. This provides a novel
way to investigate, for example, the local effects of climate change on
the ocean. OMUSE is freely available as open-source software.
Enda O'Dea, Rachel Furner, Sarah Wakelin, John Siddorn, James While, Peter Sykes, Robert King, Jason Holt, and Helene Hewitt
Geosci. Model Dev., 10, 2947–2969, https://doi.org/10.5194/gmd-10-2947-2017, https://doi.org/10.5194/gmd-10-2947-2017, 2017
Short summary
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An update to an ocean modelling configuration for the European North West Shelf is described. It is assessed against observations and climatologies for 1981–2012. Sensitivities in the model configuration updates are assessed to understand changes in the model system. The model improves upon an existing model of the region, although there remain some areas with significant biases. The paper highlights the dependence upon the quality of the river inputs.
Pierre Mathiot, Adrian Jenkins, Christopher Harris, and Gurvan Madec
Geosci. Model Dev., 10, 2849–2874, https://doi.org/10.5194/gmd-10-2849-2017, https://doi.org/10.5194/gmd-10-2849-2017, 2017
John Marshall, Jeffery Scott, and Andrey Proshutinsky
Geosci. Model Dev., 10, 2833–2848, https://doi.org/10.5194/gmd-10-2833-2017, https://doi.org/10.5194/gmd-10-2833-2017, 2017
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A coordinated set of Arctic modeling experiments is proposed which explores how the Arctic responds to abrupt changes in external forcing by computing
climate response functions(CRFs). We illustrate the approach in the context of a coarse-resolution model of the Arctic and conclude by encouraging other modeling groups to compute CRFs with their own models so that we might begin to document how robust they are to model formulation, resolution, and parameterization.
Yoeri M. Dijkstra, Ronald L. Brouwer, Henk M. Schuttelaars, and George P. Schramkowski
Geosci. Model Dev., 10, 2691–2713, https://doi.org/10.5194/gmd-10-2691-2017, https://doi.org/10.5194/gmd-10-2691-2017, 2017
Gianpiero Cossarini, Stefano Querin, Cosimo Solidoro, Gianmaria Sannino, Paolo Lazzari, Valeria Di Biagio, and Giorgio Bolzon
Geosci. Model Dev., 10, 1423–1445, https://doi.org/10.5194/gmd-10-1423-2017, https://doi.org/10.5194/gmd-10-1423-2017, 2017
Short summary
Short summary
The BFMCOUPLER (v1.0) is a coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations. The online coupling is based on an open-source code characterizd by a modular structure. Modularity preserves the potentials of the two models, allowing for a sustainable programming effort to handle future evolutions in the two codes. The BFMCOUPLER code is released along with an idealized problem (a cyclonic gyre in a mid-latitude closed basin).
Laurent Bessières, Stéphanie Leroux, Jean-Michel Brankart, Jean-Marc Molines, Marie-Pierre Moine, Pierre-Antoine Bouttier, Thierry Penduff, Laurent Terray, Bernard Barnier, and Guillaume Sérazin
Geosci. Model Dev., 10, 1091–1106, https://doi.org/10.5194/gmd-10-1091-2017, https://doi.org/10.5194/gmd-10-1091-2017, 2017
Short summary
Short summary
A new, probabilistic version of an ocean modelling system has been implemented in order to simulate the chaotic and the atmospherically forced contributions to the ocean variability. For that purpose, a large ensemble of global hindcasts has been performed. Results illustrate the importance of the oceanic chaos on climate-related oceanic indices, and the relevance of such probabilistic ocean modelling approaches to anticipating the behaviour of the next generation of coupled climate models.
Cited articles
Altabet, M. A. and Francois, R.: Nitrogen isotope biogeochemistry of the
Antarctic Polar Frontal Zone at 170 degrees W, Deep-Sea Res. Pt. II, 48, 4247–4273,
https://doi.org/10.1016/S0967-0645(01)00088-1, 2001. a, b
Bohlen, L., Dale, A. W., and Wallmann, K.: Simple transfer functions for
calculating benthic fixed nitrogen losses and
Boudreau, B. P.: Carbonate dissolution rates at the deep ocean floor,
Geophys. Res. Lett., 40, 744–748, https://doi.org/10.1029/2012GL054231,
2013. a
Boyd, P. W., Strzepek, R. F., Ellwood, M. J., Hutchins, D. A., Nodder, S. D.,
Twining, B. S., and Wilhelm, S. W.: Why are biotic iron pools uniform across
high- and low-iron pelagic ecosystems?, Global Biogeochem. Cy., 29,
1028–1043, https://doi.org/10.1002/2014GB005014, 2015. a
Brandes, J. A. and Devol, A. H.: A global marine-fixed nitrogen isotopic
budget: Implications for Holocene nitrogen cycling, Global Biogeochem.
Cy., 16, 67–1–67–14, https://doi.org/10.1029/2001GB001856, 2002. a, b, c
Buchanan, P., Matear, R., Chase, Z., Phipps, S., and Bindoff, N.: Dynamic
Biological Functioning Important for Simulating and Stabilizing Ocean
Biogeochemistry, Global Biogeochem. Cy., 32, 565–593, https://doi.org/10.1002/2017GB005753,
2018. a, b
Buchanan, P. J., Matear, R. J., Lenton, A., Phipps, S. J., Chase, Z., and
Etheridge, D. M.: The simulated climate of the Last Glacial Maximum and
insights into the global marine carbon cycle, Clim. Past, 12, 2271–2295,
https://doi.org/10.5194/cp-12-2271-2016, 2016. a, b
Buchanan, P. J., Matear, R. J., Chase, Z., Phipps, S. J., and
Bindoff, N. L.:
Oceanic carbon-13 and nitrogen-15 isotopes simulated by CSIRO Mk3L-COAL version
1.0, https://doi.org/10.25914/5c6643f64446c, 2019. a
Capone, D. G., Burns, J. A., Montoya, J. P., Subramaniam, A., Mahaffey, C.,
Gunderson, T., Michaels, A. F., and Carpenter, E. J.: Nitrogen fixation by
Trichodesmium spp.: An important source of new nitrogen to the tropical and
subtropical North Atlantic Ocean, Global Biogeochem. Cy., 19, GB2024,
https://doi.org/10.1029/2004GB002331, 2005. a
Carpenter, E. J. and Guillard, R. R. L.: Intraspecific differences in
nitrate
half-saturation constants for three species of marine phytoplankton,
Ecology, 52, 183–185, 1971. a
Carpenter, E. J., Harvey, H. R., Brian, F., and Capone, D. G.:
Biogeochemical
tracers of the marine cyanobacterium Trichodesmium, Deep-Sea Res. Pt.
I, 44, 27–38,
https://doi.org/10.1016/S0967-0637(96)00091-X, 1997. a
Cartapanis, O., Bianchi, D., Jaccard, S. L., and Galbraith, E. D.: Global
pulses of organic carbon burial in deep-sea sediments during glacial maxima,
Nat. Commun., 7, 1–7, https://doi.org/10.1038/ncomms10796, 2016. a
Ciais, P., Tagliabue, A., Cuntz, M., Bopp, L., Scholze, M., Hoffmann, G.,
Lourantou, A., Harrison, S. P., Prentice, I. C., Kelley, D. I., Koven, C.,
and Piao, S. L.: Large inert carbon pool in the terrestrial biosphere during
the Last Glacial Maximum, Nat. Geosci., 5, 74–79,
https://doi.org/10.1038/ngeo1324, 2011. a
Clementson, L., Parslow, J., Griffiths, F., Lyne, V., Mackey, D., Harris, G.,
McKenzie, D., Bonham, P., Rathbone, C., and Rintoul, S.: Controls on
phytoplankton production in the Australasian sector of the subtropical
convergence, Deep-Sea Res. Pt. I, 45,
1627–1661, https://doi.org/10.1016/S0967-0637(98)00035-1, 1998. a
Cline, J. D. and Kaplan, I. R.: Isotopic fractionation of dissolved nitrate
during denitrification in the eastern tropical north pacific ocean, Mar.
Chem., 3, 271–299, https://doi.org/10.1016/0304-4203(75)90009-2, 1975. a
Codispoti, L. A. and Richards, F. A.: An analysis of the horizontal regime
of
denitrification in the eastern tropical North Pacific, Limnol.
Oceanogr., 21, 379–388, https://doi.org/10.4319/lo.1976.21.3.0379, 1976. a
Craig, H.: Isotopic standards for carbon and oxygen and correction factors
for
mass-spectrometric analysis of carbon dioxide, Geochim. Cosmochim.
Ac., 12, 133–149, https://doi.org/10.1016/0016-7037(57)90024-8, 1957. a
Dugdale, R. C.: Nutrient limitation in the Sea: Dynamics, identification,
and
significance, Limnol. Oceanogr., 12, 685–695, 1967. a
Duteil, O., Koeve, W., Oschlies, A., Bianchi, D., Galbraith, E., Kriest, I.,
and Matear, R.: A novel estimate of ocean oxygen utilisation points to a
reduced rate of respiration in the ocean interior, Biogeosciences, 10,
7723–7738, https://doi.org/10.5194/bg-10-7723-2013, 2013. a
Eppley, R. W.: Temperature and phytoplankton growth in the sea, Fish.
B.-NOAA, 70, 1063–1085, 1972. a
Eppley, R. W., Rogers, J. N., and Mccarthy, J. J.: Half-saturation constants
for uptake of nitrate and ammonium by marine phytoplankton, Limnol.
Oceanogr., 14, 912–920, https://doi.org/10.4319/lo.1969.14.6.0912, 1969. a
Freing, A., Wallace, D. W. R., and Bange, H. W.: Global oceanic production
of
nitrous oxide, Philos. T. R. Soc. B, 367, 1245–1255, https://doi.org/10.1098/rstb.2011.0360, 2012. a
Friedli, H., Lötscher, H., Oeschger, H., Siegenthaler, U., and
Stauffer,
B.: Ice core record of the 13C/12C ratio of atmospheric CO2 in the past two
centuries, Nature, 324, 237–238, https://doi.org/10.1038/324237a0, 1986. a
Galbraith, E. D. and Martiny, A. C.: A simple nutrient-dependence mechanism
for predicting the stoichiometry of marine ecosystems, P.
Natl. Acad. Sci. USA, 112, 201423917,
https://doi.org/10.1073/pnas.1423917112, 2015. a
Galbraith, E. D., Kienast, M., Albuquerque, A. L., Altabet, M. A., Batista,
F.,
Bianchi, D., Calvert, S. E., Contreras, S., Crosta, X., De Pol-Holz, R.,
Dubois, N., Etourneau, J., Francois, R., Hsu, T. C., Ivanochko, T., Jaccard,
S. L., Kao, S. J., Kiefer, T., Kienast, S., Lehmann, M. F., Martinez, P.,
McCarthy, M., Meckler, A. N., Mix, A., Möbius, J., Pedersen, T. F.,
Pichevin, L., Quan, T. M., Robinson, R. S., Ryabenko, E., Schmittner, A.,
Schneider, R., Schneider-Mor, A., Shigemitsu, M., Sinclair, D., Somes, C.,
Studer, A. S., Tesdal, J. E., Thunell, R., and Terence Yang, J.: The
acceleration of oceanic denitrification during deglacial warming, Nat.
Geosci., 6, 579–584, https://doi.org/10.1038/ngeo1832, 2013. a, b
Ganeshram, R. S., Pedersen, T. F., Calvert, S. E., and Murray, J. W.: Large
changes in oceanic nutrient inventories from glacial to interglacial
periods, Nature, 376, 755–758, https://doi.org/10.1038/376755a0,
1995. a, b, c
Gruber, N. and Sarmiento, J. L.: Global patterns of marine nitrogen fixation
and denitrification, Global Biogeochem. Cy., 11, 235–266,
https://doi.org/10.1029/97GB00077, 1997. a
Gundersen, J. K. and Jorgensen, B. B.: Microstructure of diffusive boundary
layers and the oxygen uptake of the sea floor, Nature, 345, 604–607,
https://doi.org/10.1038/345604a0, 1990. a
Hoogakker, B. A., Lu, Z., Umling, N., Jones, L., Zhou, X., Rickaby, R. E.,
Thunell, R., Cartapanis, O., and Galbraith, E.: Glacial expansion of
oxygen-depleted seawater in the eastern tropical Pacific, Nature, 562,
410–413, https://doi.org/10.1038/s41586-018-0589-x,
2018. a, b
Hülse, D., Arndt, S., Wilson, J. D., Munhoven, G., and Ridgwell, A.:
Earth-Science Reviews Understanding the causes and consequences of past
marine carbon cycling variability through models, Earth-Sci. Revi.s,
171, 349–382, https://doi.org/10.1016/j.earscirev.2017.06.004,
2017. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9,
90–95, 2007. 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
Karl, D. M. and Letelier, R. M.: Nitrogen fixation-enhanced carbon
sequestration in low nitrate, low chlorophyll seascapes, Mar. Ecol.
Prog. Ser., 364, 257–268, https://doi.org/10.3354/meps07547, 2008. a
Kemeny, P. C., Kast, E. R., Hain, M. P., Fawcett, S. E., Fripiat, F., Studer,
A. S., Martínez-García, A., Haug, G. H., and Sigman, D. M.: A
seasonal model of nitrogen isotopes in the ice age Antarctic Zone: Support
for weakening of the Southern Ocean upper overturning cell, Paleoceanography
and Paleoclimatology, 33, 1453–1471, https://doi.org/10.1029/2018PA003478,
2018. a
Kriest, I. and Oschlies, A.: MOPS-1.0: towards a model for the regulation of
the global oceanic nitrogen budget by marine biogeochemical processes,
Geosci. Model Dev., 8, 2929–2957, https://doi.org/10.5194/gmd-8-2929-2015,
2015. a
Kustka, A., Sañudo-Wilhelmy, S., Carpenter, E. J., Capone, D. G., and
Raven, J. A.: A revised estimate of the iron use efficiency of nitrogen
fixation, with special reference to the marine cyanobacterium Trichodesmium
spp. (Cyanophyta), J. Phycol., 39, 12–25,
https://doi.org/10.1046/j.1529-8817.2003.01156.x, 2003. a
Laws, E. A., Popp, B. N., Bidigare, R. R., Kennicutt, M. C., and Macko,
S. A.:
Dependence of phytoplankton carbon isotopic composition on growth rate and
[CO2)aq: Theoretical considerations and experimental results, Geochim.
Cosmochim. Ac., 59, 1131–1138, https://doi.org/10.1016/0016-7037(95)00030-4, 1995. a, b
Liu, Z., Altabet, M. A., and Herbert, T. D.: Plio-Pleistocene
denitrification in the eastern tropical North Pacific: Intensification at
2.1 Ma, Geochem. Geophy. Geosy., 9, 1–14, https://doi.org/10.1029/2008GC002044,
2008. a
Luo, Y.-W., Lima, I. D., Karl, D. M., Deutsch, C. A., and Doney, S. C.:
Data-based assessment of environmental controls on global marine nitrogen
fixation, Biogeosciences, 11, 691–708,
https://doi.org/10.5194/bg-11-691-2014, 2014. a
Mao, J., Phipps, S. J., Pitman, A. J., Wang, Y. P., Abramowitz, G., and Pak,
B.: The CSIRO Mk3L climate system model v1.0 coupled to the CABLE land
surface scheme v1.4b: evaluation of the control climatology, Geosci. Model
Dev., 4, 1115–1131, https://doi.org/10.5194/gmd-4-1115-2011, 2011. a
Marconi, D., Sigman, D. M., Casciotti, K. L., Campbell, E. C., Alexandra
Weigand, M., Fawcett, S. E., Knapp, A. N., Rafter, P. A., Ward, B. B., and
Haug, G. H.: Tropical Dominance of N2 Fixation in the North Atlantic
Ocean, Global Biogeochem. Cy., 31, 1608–1623,
https://doi.org/10.1002/2016GB005613, 2017. a
Mariotti, A., Germon, J., Hubert, P., Kaiser, P., Letolle, R., Tardieux, A.,
and Tardieux, P.: Experimental determination of nitrogen kinetic isotope
fractionation: some principles; ilustration for the denitrification and
nitrification process, Plant Soil, 62, 413–430,
https://doi.org/10.1007/BF02374138, 1981. a
Martin, J. H., Knauer, G. A., Karl, D. M., and Broenkow, W. W.: VERTEX:
carbon
cycling in the northeast Pacific, Deep-Sea Res. Pt. A, 34, 267–285, https://doi.org/10.1016/0198-0149(87)90086-0, 1987. a, b
Martinez-Garcia, A., Sigman, D. M., Ren, H., Anderson, R. F., Straub, M.,
Hodell, D. A., Jaccard, S. L., Eglinton, T. I., and Haug, G. H.: Iron
Fertilization of the Subantarctic Ocean During the Last Ice Age, Science,
343, 1347–1350, https://doi.org/10.1126/science.1246848, 2014. a, b
Matear, R. J. and Holloway, G.: Modeling the inorganic phosphorus cycle of
the
North Pacific using an adjoint data assimilation model to assess the role of
dissolved organic phosphorus, Global Biogeochem. Cy., 9, 101–119,
https://doi.org/10.1029/94GB03104, 1995. a
Matear, R. J. and Lenton, A.: Quantifying the impact of ocean acidification
on our future climate, Biogeosciences, 11, 3965–3983,
https://doi.org/10.5194/bg-11-3965-2014, 2014. a, b
Matear, R. J. and Lenton, A.: Carbon–climate feedbacks accelerate ocean
acidification, Biogeosciences, 15, 1721–1732,
https://doi.org/10.5194/bg-15-1721-2018, 2018. a
McGillicuddy, D. J.: Do Trichodesmium spp. populations in the North Atlantic
export most of the nitrogen they fix?, Global Biogeochem. Cy., 28,
103–114, https://doi.org/10.1002/2013GB004652, 2014. a
McRose, D. L., Lee, A., Kopf, S. H., Baars, O., Kraepiel, A. M., Sigman,
D. M.,
Morel, F. M., and Zhang, X.: Effect of iron limitation on the isotopic
composition of cellular and released fixed nitrogen in Azotobacter
vinelandii, Geochim. Cosmochim. Ac., 244, 12–23,
https://doi.org/10.1016/j.gca.2018.09.023,
2019. a
Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J.
F. B., Stouffer, R. J., Taylor, K. E., Meehl, G. A., Covey, C., Delworth, T.,
Latif, M., McAvaney, B., Mitchell, J. F. B., Stouffer, R. J., and Taylor,
K. E.: THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change
Research, B. Am. Meteorol. Soc., 88, 1383–1394,
https://doi.org/10.1175/BAMS-88-9-1383, 2007. a
Menviel, L., Yu, J., Joos, F., Mouchet, A., Meissner, K. J., and England,
M. H.: Poorly ventilated deep ocean at the Last Glacial Maximum inferred
from carbon isotopes: A data-model comparison study, Paleoceanography, 32,
2–17, https://doi.org/10.1002/2016PA003024, 2017a. a, b, c, d
Menviel, L., Yu, J., Joos, F., Mouchet, A., Meissner, K. J., and England, M. H.: LOVECLIM Last Glacial Maximum oceanic d13C and d14C v 1.0,
https://doi.org/10.4225/41/58192cb8bff06, 2017b. a
Mills, M. M. and Arrigo, K. R.: Magnitude of oceanic nitrogen fixation
influenced by the nutrient uptake ratio of phytoplankton, Nat. Geosci.,
3, 412–416, https://doi.org/10.1038/ngeo856, 2010. a
Moore, C. M., Mills, M. M., Arrigo, K. R., Berman-Frank, I., Bopp, L., Boyd,
P. W., Galbraith, E. D., Geider, R. J., Guieu, C., Jaccard, S. L., Jickells,
T. D., La Roche, J., Lenton, T. M., Mahowald, N. M., Marañón,
E., Marinov, I., Moore, J. K., Nakatsuka, T., Oschlies, A., Saito, M. A.,
Thingstad, T. F., Tsuda, A., and Ulloa, O.: Processes and patterns of
oceanic nutrient limitation, Nat. Geosci., 6, 701–710,
https://doi.org/10.1038/ngeo1765, 2013. a
Muglia, J., Skinner, L. C., and Schmittner, A.: Weak overturning circulation
and high Southern Ocean nutrient utilization maximized glacial ocean carbon,
Earth Planet. Sc. Lett., 496, 47–56,
https://doi.org/10.1016/j.epsl.2018.05.038, 2018. a, b
Orr, J. C., Najjar, R. G., Aumont, O., Bopp, L., Bullister, J. L.,
Danabasoglu, G., Doney, S. C., Dunne, J. P., Dutay, J.-C., Graven, H.,
Griffies, S. M., John, J. G., Joos, F., Levin, I., Lindsay, K., Matear, R.
J., McKinley, G. A., Mouchet, A., Oschlies, A., Romanou, A., Schlitzer, R.,
Tagliabue, A., Tanhua, T., and Yool, A.: Biogeochemical protocols and
diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP), Geosci.
Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, 2017. a, b
Ortiz, J. D., Mix, A., Rugh, W., Watkins, J., and Collier, R.: Deep-dwelling
planktonic foraminifera of the northeastern Pacific Ocean reveal
environmental control of oxygen and carbon isotopic disequilibria, Geochim.
Cosmochim. Ac., 60, 4509–4523, 1996. a
Oschlies, A.: Equatorial nutrient trapping in biogeochemical ocean models:
The
role of advection numerics, Global Biogeochem. Cy., 14, 655–667,
https://doi.org/10.1029/1999GB001217, 2000. a
Oschlies, A., Schulz, K. G., Riebesell, U., and Schmittner, A.: Simulated
21st
century's increase in oceanic suboxia by CO2-enhanced biotic carbon
export, Global Biogeochem. Cy., 22, 1–10, https://doi.org/10.1029/2007GB003147,
2008. a
Paulmier, A., Kriest, I., and Oschlies, A.: Stoichiometries of
remineralisation and denitrification in global biogeochemical ocean models,
Biogeosciences, 6, 923–935, https://doi.org/10.5194/bg-6-923-2009, 2009. a, b, c
Phipps, S. J., McGregor, H. V., Gergis, J., Gallant, A. J. E., Neukom, R.,
Stevenson, S., Ackerley, D., Brown, J. R., Fischer, M. J., and van Ommen,
T. D.: Paleoclimate Data-Model Comparison and the Role of Climate Forcings
over the Past 1500 Years, J. Climate, 26, 6915–6936,
https://doi.org/10.1175/JCLI-D-12-00108.1, 2013. a, b
Rafter, P. A., Sigman, D. M., and Mackey, K. R.: Recycled iron fuels new
production in the eastern equatorial Pacific Ocean, Nat. Commun.,
8, 1100, https://doi.org/10.1038/s41467-017-01219-7, 2017. a
Redfield, A. C., Smith, H. P., and Ketchum, B. H.: The cycle of organic
phosphorus in the Gulf of Maine, Biol. Bull., 73, 421–443,
1937. a
Ren, H., Sigman, D. M., Meckler, A. N., Plessen, B., Robinson, R. S.,
Rosenthal, Y., and Haug, G. H.: Foraminiferal Isotope Evidence of Reduced
Nitrogen Fixation in the Ice Age Atlantic Ocean, Science, 323, 244–248,
https://doi.org/10.1126/science.1165787, 2009. a
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M.,
Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in
an efficient Earth System Model of global biogeochemical cycling,
Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007. a
Robinson, R. S., Kienast, M., Luiza Albuquerque, A., Altabet, M.,
Contreras,
S., De Pol Holz, R., Dubois, N., Francois, R., Galbraith, E., Hsu, T. C.,
Ivanochko, T., Jaccard, S., Kao, S. J., Kiefer, T., Kienast, S., Lehmann, M.,
Martinez, P., McCarthy, M., Möbius, J., Pedersen, T., Quan, T. M.,
Ryabenko, E., Schmittner, A., Schneider, R., Schneider-Mor, A., Shigemitsu,
M., Sinclair, D., Somes, C., Studer, A., Thunell, R., and Yang, J. Y.: A
review of nitrogen isotopic alteration in marine sediments,
Paleoceanography, 27, PA4203, https://doi.org/10.1029/2012PA002321, 2012. a, b, c
Schmittner, A., Oschlies, A., Matthews, H. D., and Galbraith, E. D.: Future
changes in climate, ocean circulation, ecosystems, and biogeochemical cycling
simulated for a business-as-usual CO2 emission scenario until year 4000 AD,
Global Biogeochem. Cy., 22, GB1013, https://doi.org/10.1029/2007GB002953, 2008. a, b
Schmittner, A., Gruber, N., Mix, A. C., Key, R. M., Tagliabue, A., and
Westberry, T. K.: Biology and air–sea gas exchange controls on the
distribution of carbon isotope ratios (δ13C) in the ocean,
Biogeosciences, 10, 5793–5816, https://doi.org/10.5194/bg-10-5793-2013,
2013. a, b, c
Schmittner, A., Bostock, H. C., Cartapanis, O., Curry, W. B., Filipsson,
H. L.,
Galbraith, E. D., Gottschalk, J., Herguera, J. C., Hoogakker, B., Jaccard,
S. L., Lisiecki, L. E., Lund, D. C., Martínez-Méndez, G.,
Lynch-Stieglitz, J., Mackensen, A., Michel, E., Mix, A. C., Oppo, D. W.,
Peterson, C. D., Repschläger, J., Sikes, E. L., Spero, H. J., and
Waelbroeck, C.: Calibration of the carbon isotope composition (δ13C)
of benthic foraminifera, Paleoceanography, 32, 512–530,
https://doi.org/10.1002/2016PA003072, 2017. a, b, c, d, e, f, g, h, i, j, k
Sigman, D., Karsh, K., and Casciotti, K.: Nitrogen Isotopes in the Ocean,
in:
Encyclopedia of Ocean Sciences, Elsevier, 40–54,
https://doi.org/10.1016/B978-012374473-9.00632-9, 2009. a, b, c, d
Sigman, D. M., Hain, M. P., and Haug, G. H.: The polar ocean and glacial
cycles in atmospheric CO2 concentration, Nature, 466, 47–55,
https://doi.org/10.1038/nature09149, 2010. a
Sipler, R. E., Gong, D., Baer, S. E., Sanderson, M. P., Roberts, Q. N.,
Mulholland, M. R., and Bronk, D. A.: Preliminary estimates of the
contribution of Arctic nitrogen fixation to the global nitrogen budget,
Limnol. Oceanogr. Lett., 2, 159–166, https://doi.org/10.1002/lol2.10046,
2017. a
Smith, I.: Global climate modelling within CSIRO: 1981 to 2006, Aust.
Meteorol. Mag., 56, 153–166, 2007. a
Smith, R. E. H.: Size-dependent phosphorus uptake kinetics and cell quota in
phytoplankton, J. Phycol., 18, 275–284, 1982. a
Smith, S., Yamanaka, Y., Pahlow, M., and Oschlies, A.: Optimal uptake
kinetics: physiological acclimation explains the pattern of nitrate uptake by
phytoplankton in the ocean, Mar. Ecol. Prog. Ser., 384, 1–12,
https://doi.org/10.3354/meps08022, 2009. a
Sohm, J. A., Webb, E. A., and Capone, D. G.: Emerging patterns of marine
nitrogen fixation., Nature reviews, Microbiology, 9, 499–508,
https://doi.org/10.1038/nrmicro2594, 2011. a
Solomon, S., Qin, D., Manning, M., Averyt, K., and Marquis, M.: Climate
change
2007-the physical science basis: Working group I contribution to the fourth
assessment report of the IPCC, vol. 4, Cambridge university press, 2007. a
Somes, C. J., Schmittner, A., Galbraith, E. D., Lehmann, M. F., Altabet,
M. A.,
Montoya, J. P., Letelier, R. M., Mix, A. C., Bourbonnais, A., and Eby, M.:
Simulating the global distribution of nitrogen isotopes in the ocean,
Global Biogeochem. Cy., 24, 1–16, https://doi.org/10.1029/2009GB003767, 2010. a
Somes, C. J., Oschlies, A., and Schmittner, A.: Isotopic constraints on the pre-industrial oceanic nitrogen budget, Biogeosciences, 10, 5889–5910, https://doi.org/10.5194/bg-10-5889-2013, 2013. a, b
Straub, M., Sigman, D. M., Ren, H., Martínez-García, A., Meckler,
A. N., Hain, M. P., and Haug, G. H.: Changes in North Atlantic nitrogen
fixation controlled by ocean circulation, Nature, 501, p. 200, https://doi.org/10.1038/nature12397,
2013. a
Studer, A. S., Sigman, D. M., Martínez-García, A., Thöle,
L. M., Michel, E., Jaccard, S. L., Lippold, J. A., Mazaud, A., Wang, X. T.,
Robinson, L. F., Adkins, J. F., and Haug, G. H.: Increased nutrient supply
to the Southern Ocean during the Holocene and its implications for the
pre-industrial atmospheric CO2 rise, Nat. Geosci., 11, 756–760,
https://doi.org/10.1038/s41561-018-0191-8, 2018. a, b, c
Tagliabue, A. and Bopp, L.: Towards understanding global variability in
ocean
carbon-13, Global Biogeochem. Cy., 22, 1–13,
https://doi.org/10.1029/2007GB003037, 2008. a, b, c
Tagliabue, A., Bopp, L., Roche, D. M., Bouttes, N., Dutay, J.-C., Alkama, R.,
Kageyama, M., Michel, E., and Paillard, D.: Quantifying the roles of ocean
circulation and biogeochemistry in governing ocean carbon-13 and atmospheric
carbon dioxide at the last glacial maximum, Clim. Past, 5, 695–706,
https://doi.org/10.5194/cp-5-695-2009, 2009. a, b
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res., 106, 7183,
https://doi.org/10.1029/2000JD900719, 2001. a, b
Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M., and DiMarco,
S. F.: True Colors of Oceanography: Guidelines for Effective and Accurate
Colormap Selection, Oceanography, 29, 9–13, 2016. a
Timmermans, K. R., Gerringa, L. J. A., Baar, H. J. W. D., Der, B. V.,
Veldhuis,
M. J. W., Jong, J. T. M. D., Croot, P. L., Boye, M., and Boye, M.: Growth
rates of large and small Southern Ocean diatoms in relation to availability
of iron in natural seawater, Limnol. Oceanogr., 46, 260–266, 2001. a
Timmermans, K. R., van der Wagt, B., and de Baar, H. J. W.: Growth rates,
half-saturation constants, and silicate, nitrate, and phosphate depletion in
relation to iron availability of four large, open-ocean diatoms from the
Southern Ocean, Limnol. Oceanogr., 49, 2141–2151,
https://doi.org/10.4319/lo.2004.49.6.2141, 2004. a
Toggweiler, J. R., Dixon, K., and Bryan, K.: Simulations of radiocarbon in a
coarse-resolution world ocean model: 2. Distributions of bomb-produced carbon
14, J. Geophys. Res., 94, 8243,
https://doi.org/10.1029/JC094iC06p08243, 1989. a
Voss, M., Dippner, J. W., and Montoya, J. P.: Nitrogen isotope patterns in
the
oxygen-deficient waters of the Eastern Tropical North Pacific Ocean, Deep-Sea Res. Pt. I, 48, 1905–1921,
https://doi.org/10.1016/S0967-0637(00)00110-2, 2001. a
Wada, E.: Nitrogen isotope fractionation and its significance in
biogeochemical
processes occurring in marine environments, Isotope marine chemistry,
375–398, 1980. a
Weber, T., Cram, J. A., Leung, S. W., DeVries, T., and Deutsch, C.: Deep
ocean
nutrients imply large latitudinal variation in particle transfer efficiency,
P. Natl. Acad. Sci. USA, 113, 8606–8611,
https://doi.org/10.1073/pnas.1604414113, 2016. a, b
Wolf-Gladrow, D. A., Zeebe, R. E., Klaas, C., Körtzinger, A., and
Dickson, A. G.: Total alkalinity: The explicit conservative expression and
its application to biogeochemical processes, Mar. Chem., 106,
287–300, https://doi.org/10.1016/j.marchem.2007.01.006, 2007. 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, b
Yang, S. and Gruber, N.: The anthropogenic perturbation of the marine
nitrogen
cycle by atmospheric deposition, Global Biogeochem. Cy., 30,
1418–1440, 2016. a
Zhang, H. and Cao, L.: Simulated effect of calcification feedback on
atmospheric CO2 and ocean acidification, Sci. Rep.-UK, 6, 1–10,
https://doi.org/10.1038/srep20284, 2016.
a, b
Zhang, J., Quay, P., and Wilbur, D.: Carbon isotope fractionation during
gas-water exchange and dissolution of CO2, Geochim. Cosmochim. Ac.,
59, 107–114, 1995. a
Zondervan, I., Zeebe, R. E., Rost, B., and Riebesell, U.: Decreasing marine
biogenic calcification: A negative feedback on rising atmospheric pCO2,
Global Biogeochem. Cy., 15, 507–516, 2001. a
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Oceanic sediment cores are commonly used to understand past climates. The composition of the sediments changes with the ocean above it. An understanding of oceanographic conditions that existed many thousands of years ago, in some cases many millions of years ago, can therefore be extracted from sediment cores. We simulate two chemical signatures (13C and 15N) of sediment cores in a model. This study assesses the model before it is applied to reinterpret the sedimentary record.
Oceanic sediment cores are commonly used to understand past climates. The composition of the...
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