Articles | Volume 11, issue 9
https://doi.org/10.5194/gmd-11-3883-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-3883-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
27 Sep 2018
Development and technical paper |
| 27 Sep 2018
| 27 Sep 2018
LCice 1.0 – a generalized Ice Sheet System Model coupler for LOVECLIM version 1.3: description, sensitivities, and validation with the Glacial Systems Model (GSM version D2017.aug17)
Taimaz Bahadory
Dept. of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL, Canada
Lev Tarasov
CORRESPONDING AUTHOR
Dept. of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL, Canada
Related authors
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Benoit S. Lecavalier and Lev Tarasov
The Cryosphere, 19, 919–953, https://doi.org/10.5194/tc-19-919-2025, https://doi.org/10.5194/tc-19-919-2025, 2025
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We present the evolution of the Antarctic Ice Sheet (AIS) over the last 200 kyr by means of a history-matching analysis where an updated observational database constrained ~ 10 000 model simulations. During peak glaciation at the Last Glacial Maximum (LGM), the best-fitting sub-ensemble of AIS simulations reached an excess grounded ice volume relative to the present of 9.2 to 26.5 m equivalent sea level relative to the present. The LGM AIS volume can help resolve the LGM missing-ice problem.
Marilena Sophie Geng, Lev Tarasov, and April Sue Dalton
EGUsphere, https://doi.org/10.5194/egusphere-2025-495, https://doi.org/10.5194/egusphere-2025-495, 2025
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We used a fully coupled ice-climate model to simulate the last two glacial inceptions, and compare the ensemble simulated ice sheet evolution to limited geological data. Our results show that Northern Hemisphere ice sheets grew rapidly, sometimes merging in ways not previously assumed and that capturing one glacial inception does not guarantee capturing another. These findings improve our understanding of ice-age dynamics and highlight challenges in predicting past and future climate evolution.
Lev Tarasov, Benoit S. Lecavalier, Kevin Hank, and David Pollard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-175, https://doi.org/10.5194/gmd-2024-175, 2025
Preprint under review for GMD
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We document the glacial system model (GSM), a 3D glaciological ice sheet systems model specifically designed for large ensemble modelling in glacial cycle contexts. The model is distinguished by the breadth of relevant processes represented for this context. This ranges from meltwater surface drainage with proglacial lake formation to state-of-the-art subglacial sediment production/transport/deposition. The other key distinguishing design feature is attention to addressing process uncertainties.
Benoit S. Lecavalier and Lev Tarasov
EGUsphere, https://doi.org/10.5194/egusphere-2024-3268, https://doi.org/10.5194/egusphere-2024-3268, 2024
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To simulate the past evolution of the Antarctic ice sheet (AIS) during past warm and cold periods, a modelling analysis was performed that compared thousands of AIS simulations to a large collection of field observations. As the AIS changes, so does the surface load which leads to crustal deformation, gravitational and sea-level change. The present-day rate of bedrock deformation due to past AIS changes is used with satellite observations to infer AIS changes due to contemporary climate change.
Ryan Love, Glenn A. Milne, Parviz Ajourlou, Soran Parang, Lev Tarasov, and Konstantin Latychev
Geosci. Model Dev., 17, 8535–8551, https://doi.org/10.5194/gmd-17-8535-2024, https://doi.org/10.5194/gmd-17-8535-2024, 2024
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A relatively recent advance in glacial isostatic adjustment modeling has been the development of models that include 3D Earth structure, as opposed to 1D structure. However, a major limitation is the computational expense. We have developed a method using artificial neural networks to emulate the influence of 3D Earth models to affordably constrain the viscosity parameter space. Our results indicate that the misfits are of a scale such that useful predictions of relative sea level can be made.
Kevin Hank and Lev Tarasov
Clim. Past, 20, 2499–2524, https://doi.org/10.5194/cp-20-2499-2024, https://doi.org/10.5194/cp-20-2499-2024, 2024
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The ice-rafted debris signature of Heinrich events in marine sedimentary cores is usually attributed to massive ice discharge from the Laurentide Ice Sheet. However, the driving mechanism of this pulsed discharge remains unclear. We compare three previously proposed hypotheses and examine the role of relevant system processes. We find ice stream surge cycling is the most likely mechanism, but its character is sensitive to both the geothermal heat flux and the form of the basal drag law.
Matthew Drew and Lev Tarasov
EGUsphere, https://doi.org/10.5194/egusphere-2024-620, https://doi.org/10.5194/egusphere-2024-620, 2024
Preprint withdrawn
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We model the sediment-ice-climate system over North America for the last 2.58 Myr showing that ice sheets are capable of excavating features the size of the Hudson bay. This work provides a basis for reconstructing past landscapes important to climate modelling efforts, helping us to understand past earth system change.
Brian R. Crow, Lev Tarasov, Michael Schulz, and Matthias Prange
Clim. Past, 20, 281–296, https://doi.org/10.5194/cp-20-281-2024, https://doi.org/10.5194/cp-20-281-2024, 2024
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An abnormally warm period around 400,000 years ago is thought to have resulted in a large melt event for the Greenland Ice Sheet. Using a sequence of climate model simulations connected to an ice model, we estimate a 50 % melt of Greenland compared to today. Importantly, we explore how the exact methodology of connecting the temperatures and precipitation from the climate model to the ice sheet model can influence these results and show that common methods could introduce errors.
Matthew Drew and Lev Tarasov
The Cryosphere, 17, 5391–5415, https://doi.org/10.5194/tc-17-5391-2023, https://doi.org/10.5194/tc-17-5391-2023, 2023
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The interaction of fast-flowing regions of continental ice sheets with their beds governs how quickly they slide and therefore flow. The coupling of fast ice to its bed is controlled by the pressure of meltwater at its base. It is currently poorly understood how the physical details of these hydrologic systems affect ice speedup. Using numerical models we find, surprisingly, that they largely do not, except for the duration of the surge. This suggests that cheap models are sufficient.
Ryan Love, Lev Tarasov, Heather Andres, Alan Condron, Xu Zhang, and Gerrit Lohmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2225, https://doi.org/10.5194/egusphere-2023-2225, 2023
Preprint archived
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Freshwater injection into bands across the North Atlantic are a mainstay of climate modelling when investigating topics such as climate change or the role of glacial runoff in the glacial climate system. However, this approach is unrealistic and results in a systematic bias in the climate response to a given flux of freshwater. We evaluate the magnitude of this bias by comparison to two other approaches for introducing freshwater into a coupled climate model setup for glacial conditions.
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023, https://doi.org/10.5194/gmd-16-5627-2023, 2023
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Physically meaningful modeling of geophysical system instabilities is numerically challenging, given the potential effects of purely numerical artifacts. Here we explore the sensitivity of ice stream surge activation to numerical and physical model aspects. We find that surge characteristics exhibit a resolution dependency but converge at higher horizontal grid resolutions and are significantly affected by the incorporation of bed thermal and sub-glacial hydrology models.
Benoit S. Lecavalier, Lev Tarasov, Greg Balco, Perry Spector, Claus-Dieter Hillenbrand, Christo Buizert, Catherine Ritz, Marion Leduc-Leballeur, Robert Mulvaney, Pippa L. Whitehouse, Michael J. Bentley, and Jonathan Bamber
Earth Syst. Sci. Data, 15, 3573–3596, https://doi.org/10.5194/essd-15-3573-2023, https://doi.org/10.5194/essd-15-3573-2023, 2023
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The Antarctic Ice Sheet Evolution constraint database version 2 (AntICE2) consists of a large variety of observations that constrain the evolution of the Antarctic Ice Sheet over the last glacial cycle. This includes observations of past ice sheet extent, past ice thickness, past relative sea level, borehole temperature profiles, and present-day bedrock displacement rates. The database is intended to improve our understanding of past Antarctic changes and for ice sheet model calibrations.
Lev Tarasov and Michael Goldstein
EGUsphere, https://doi.org/10.5194/egusphere-2022-1410, https://doi.org/10.5194/egusphere-2022-1410, 2023
Preprint archived
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This overview: 1. Illustrates how current climate and/or ice sheet model-based inferences about the past tend to have little interpretable value about the real world given inadequate accounting of uncertainties. 2. Explains Bayesian inference to a non-statistical community. 3. Sketches out some tractable inferential steps for computationally expensive models in a way that meaningfully accounts for uncertainties. 4. Lays out some steps for the community to move forward.
Lev Tarasov and Michael Goldstein
Clim. Past Discuss., https://doi.org/10.5194/cp-2021-145, https://doi.org/10.5194/cp-2021-145, 2021
Revised manuscript not accepted
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This review: 1. Illustrates how current climate and/or ice sheet model-based inferences about the past tend to have limited interpretable value about the real world given inadequate accounting of uncertainties. 2. Explains Bayesian inference to a non-statistical community. 3. Sketches out tractable Bayesian inference for computationally expensive models in a way that meaningfully accounts for uncertainties. 4. Lays out some steps for the community to move forward.
Ryan Love, Heather J. Andres, Alan Condron, and Lev Tarasov
Clim. Past, 17, 2327–2341, https://doi.org/10.5194/cp-17-2327-2021, https://doi.org/10.5194/cp-17-2327-2021, 2021
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Freshwater, in the form of glacial runoff, is hypothesized to play a critical role in centennial- to millennial-scale climate variability and climate transitions. We track the routing of glaciologically constrained freshwater volumes in glacial ocean simulations. Our simulations capture important generally not well-represented small-scale features (boundary currents, eddies). We show that the dilution of freshwater as it is transported to key climate regions reduces the freshening to 20 %–60 %.
Taimaz Bahadory, Lev Tarasov, and Heather Andres
Clim. Past, 17, 397–418, https://doi.org/10.5194/cp-17-397-2021, https://doi.org/10.5194/cp-17-397-2021, 2021
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We present an ensemble of last glacial inception simulations using a fully coupled ice–climate model for the Northern Hemisphere. The ensemble largely captures inferred ice volume changes within proxy uncertainties. Notable features include an ice bridge across Davis Strait and between Greenland and Iceland. Via an equilibrium climate response experiment, we also demonstrate the potential value of fully coupled ice–climate modelling of last glacial inception to constrain future climate change.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
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In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Heather J. Andres and Lev Tarasov
Clim. Past, 15, 1621–1646, https://doi.org/10.5194/cp-15-1621-2019, https://doi.org/10.5194/cp-15-1621-2019, 2019
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Abrupt climate shifts of large magnitudes were common during glacial states, with explanations centred on the oceans. However, winds drive ocean surface currents so shifts in mean wind conditions could also have played a critical role. In a small ensemble of transient deglacial simulations, we find abrupt shifts in both jet stream location and variability over the North Atlantic. We show that the eastern North American ice sheet margin strongly constrains regional jet characteristics.
Laurie Menviel, Emilie Capron, Aline Govin, Andrea Dutton, Lev Tarasov, Ayako Abe-Ouchi, Russell N. Drysdale, Philip L. Gibbard, Lauren Gregoire, Feng He, Ruza F. Ivanovic, Masa Kageyama, Kenji Kawamura, Amaelle Landais, Bette L. Otto-Bliesner, Ikumi Oyabu, Polychronis C. Tzedakis, Eric Wolff, and Xu Zhang
Geosci. Model Dev., 12, 3649–3685, https://doi.org/10.5194/gmd-12-3649-2019, https://doi.org/10.5194/gmd-12-3649-2019, 2019
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As part of the Past Global Changes (PAGES) working group on Quaternary Interglacials, we propose a protocol to perform transient simulations of the penultimate deglaciation for the Paleoclimate Modelling Intercomparison Project (PMIP4). This design includes time-varying changes in orbital forcing, greenhouse gas concentrations, continental ice sheets as well as freshwater input from the disintegration of continental ice sheets. Key paleo-records for model-data comparison are also included.
Laurie Menviel, Emilie Capron, Aline Govin, Andrea Dutton, Lev Tarasov, Ayako Abe-Ouchi, Russell Drysdale, Philip Gibbard, Lauren Gregoire, Feng He, Ruza Ivanovic, Masa Kageyama, Kenji Kawamura, Amaelle Landais, Bette L. Otto-Bliesner, Ikumi Oyabu, Polychronis Tzedakis, Eric Wolff, and Xu Zhang
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-106, https://doi.org/10.5194/cp-2018-106, 2018
Preprint withdrawn
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The penultimate deglaciation (~ 138–128 ka), which represents the transition into the Last Interglacial period, provides a framework to investigate the climate and environmental response to large changes in boundary conditions. Here, as part of the PAGES-PMIP working group on Quaternary Interglacials, we propose a protocol to perform transient simulations of the penultimate deglaciation as well as a selection of paleo records for upcoming model-data comparisons.
Mark Kavanagh and Lev Tarasov
Geosci. Model Dev., 11, 3497–3513, https://doi.org/10.5194/gmd-11-3497-2018, https://doi.org/10.5194/gmd-11-3497-2018, 2018
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We present and validate BrAHMs (BAsal Hydrology Model): a new
physically based basal hydrology model, which captures the two main
types of subglacial drainage systems (high-pressure distributed systems and
low-pressure channelized systems). BrAHMs is designed for continental
glacial cycle scale contexts, for which computational speed is
essential. This speed is accomplished, in part, by numerical methods
novel to basal hydrology contexts.
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.
Mohammad Hizbul Bahar Arif, Lev Tarasov, and Tristan Hauser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-276, https://doi.org/10.5194/gmd-2017-276, 2018
Revised manuscript has not been submitted
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This study is a first step answer to the following question: Can you
use emulators (machine learning techniques) to make the output of fast
simple climate models (a 2-D energy balance model in this test case)
indistinguishable from that of a much more computationally expensive
General Circulation climate model (GCM) within the uncertainties of
GCMs? Our preliminary test of this concept for large spatio-temporal
contexts gives a positive answer.
Masa Kageyama, Samuel Albani, Pascale Braconnot, Sandy P. Harrison, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Olivier Marti, W. Richard Peltier, Jean-Yves Peterschmitt, Didier M. Roche, Lev Tarasov, Xu Zhang, Esther C. Brady, Alan M. Haywood, Allegra N. LeGrande, Daniel J. Lunt, Natalie M. Mahowald, Uwe Mikolajewicz, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Hans Renssen, Robert A. Tomas, Qiong Zhang, Ayako Abe-Ouchi, Patrick J. Bartlein, Jian Cao, Qiang Li, Gerrit Lohmann, Rumi Ohgaito, Xiaoxu Shi, Evgeny Volodin, Kohei Yoshida, Xiao Zhang, and Weipeng Zheng
Geosci. Model Dev., 10, 4035–4055, https://doi.org/10.5194/gmd-10-4035-2017, https://doi.org/10.5194/gmd-10-4035-2017, 2017
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The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
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.
André Düsterhus, Alessio Rovere, Anders E. Carlson, Benjamin P. Horton, Volker Klemann, Lev Tarasov, Natasha L. M. Barlow, Tom Bradwell, Jorie Clark, Andrea Dutton, W. Roland Gehrels, Fiona D. Hibbert, Marc P. Hijma, Nicole Khan, Robert E. Kopp, Dorit Sivan, and Torbjörn E. Törnqvist
Clim. Past, 12, 911–921, https://doi.org/10.5194/cp-12-911-2016, https://doi.org/10.5194/cp-12-911-2016, 2016
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This review/position paper addresses problems in creating new interdisciplinary databases for palaeo-climatological sea-level and ice-sheet data and gives an overview on new advances to tackle them. The focus therein is to define and explain strategies and highlight their importance to allow further progress in these fields. It also offers important insights into the general problem of designing competitive databases which are also applicable to other communities within the palaeo-environment.
A. Abe-Ouchi, F. Saito, M. Kageyama, P. Braconnot, S. P. Harrison, K. Lambeck, B. L. Otto-Bliesner, W. R. Peltier, L. Tarasov, J.-Y. Peterschmitt, and K. Takahashi
Geosci. Model Dev., 8, 3621–3637, https://doi.org/10.5194/gmd-8-3621-2015, https://doi.org/10.5194/gmd-8-3621-2015, 2015
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We describe the creation of boundary conditions related to the presence of ice sheets, including ice-sheet extent and height, ice-shelf extent, and the distribution and altitude of ice-free land, at the Last Glacial Maximum (LGM), for use in LGM experiments conducted as part of the Coupled Modelling Intercomparison Project (CMIP5) and Palaeoclimate Modelling Intercomparison Project (PMIP3). The difference in the ice sheet boundary conditions as well as the climate response to them are discussed.
K. Le Morzadec, L. Tarasov, M. Morlighem, and H. Seroussi
Geosci. Model Dev., 8, 3199–3213, https://doi.org/10.5194/gmd-8-3199-2015, https://doi.org/10.5194/gmd-8-3199-2015, 2015
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A long-term challenge for any model of complex large-scale processes
is accounting for the impact of unresolved sub-grid (SG) processes.
We quantify the impact of SG mass-balance and ice fluxes on glacial
cycle ensemble results for North America. We find no easy solutions to
accurately capture these impacts. We show that SG process
representation and associated parametric uncertainties can have
significant impact on coarse resolution model results for glacial
cycle ice sheet evolution.
H. Beltrami, G. S. Matharoo, L. Tarasov, V. Rath, and J. E. Smerdon
Clim. Past, 10, 1693–1706, https://doi.org/10.5194/cp-10-1693-2014, https://doi.org/10.5194/cp-10-1693-2014, 2014
R. Briggs, D. Pollard, and L. Tarasov
The Cryosphere, 7, 1949–1970, https://doi.org/10.5194/tc-7-1949-2013, https://doi.org/10.5194/tc-7-1949-2013, 2013
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This study represents the primary marine organic aerosol (PMOA) emissions, focusing on their sea–atmosphere transfer. Using the FESOM2.1–REcoM3 model, concentrations of key organic biomolecules were estimated and integrated into the ECHAM6.3–HAM2.3 aerosol–climate model. Results highlight the influence of marine biological activity and surface winds on PMOA emissions, with reasonably good agreement with observations improving aerosol representation in the southern oceans.
Ziming Ke, Qi Tang, Jean-Christophe Golaz, Xiaohong Liu, and Hailong Wang
Geosci. Model Dev., 18, 4137–4153, https://doi.org/10.5194/gmd-18-4137-2025, https://doi.org/10.5194/gmd-18-4137-2025, 2025
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This study assesses volcanic aerosol representation in E3SM (Energy Exascale Earth System Model), showing that an emission-based approach moderately improves temperature variability and cloud responses compared to a prescribed forcing approach, yet significant bias persists.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev., 18, 4009–4021, https://doi.org/10.5194/gmd-18-4009-2025, https://doi.org/10.5194/gmd-18-4009-2025, 2025
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Philipp Weiss, Ross Herbert, and Philip Stier
Geosci. Model Dev., 18, 3877–3894, https://doi.org/10.5194/gmd-18-3877-2025, https://doi.org/10.5194/gmd-18-3877-2025, 2025
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Aerosols strongly influence Earth's climate as they interact with radiation and clouds. New Earth system models run at resolutions of a few kilometers. To simulate the Earth system with interactive aerosols, we developed a new aerosol module. It represents aerosols as an ensemble of lognormal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of 5 km. It captures key processes like the formation of dust storms in the Sahara.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev., 18, 3799–3817, https://doi.org/10.5194/gmd-18-3799-2025, https://doi.org/10.5194/gmd-18-3799-2025, 2025
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with vital physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for multi-objective optimization of rice irrigation schemes at a large scale.
Carolina A. Bieri, Francina Dominguez, Gonzalo Miguez-Macho, and Ying Fan
Geosci. Model Dev., 18, 3755–3779, https://doi.org/10.5194/gmd-18-3755-2025, https://doi.org/10.5194/gmd-18-3755-2025, 2025
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Access to deep moisture below the Earth's surface is important for vegetation in areas of the Amazon where there is little precipitation for part of the year. Most existing numerical models of the Earth system do not adequately capture where and when deep root water uptake occurs. We address this by adding deep soil layers and a root water uptake feature to an existing model. Out modifications lead to increased dry-month transpiration and improved simulation of the annual transpiration cycle.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev., 18, 3661–3679, https://doi.org/10.5194/gmd-18-3661-2025, https://doi.org/10.5194/gmd-18-3661-2025, 2025
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We present an automatic tool that optimizes resource distribution in coupled climate models, enhancing speed and reducing computational costs without requiring expert knowledge. Users can set energy/time criteria or limit resource usage. Tested on various European Community Earth System Model (EC-Earth) configurations and high-performance computing (HPC) platforms, it achieved up to 34 % faster simulations with fewer resources.
Maria Lucia Ferreira Barbosa, Douglas I. Kelley, Chantelle A. Burton, Igor J. M. Ferreira, Renata Moura da Veiga, Anna Bradley, Paulo Guilherme Molin, and Liana O. Anderson
Geosci. Model Dev., 18, 3533–3557, https://doi.org/10.5194/gmd-18-3533-2025, https://doi.org/10.5194/gmd-18-3533-2025, 2025
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As fire seasons in Brazil become increasingly severe, confidently understanding the factors driving fires is more critical than ever. To address this challenge, we developed FLAME (Fire Landscape Analysis using Maximum Entropy), a new model designed to predict fires and to analyse the spatial influence of both environmental and human factors while accounting for uncertainties. By adapting the model to different regions, we can enhance fire management strategies, making FLAME a powerful tool for protecting landscapes in Brazil and beyond.
Victor Couplet, Marina Martínez Montero, and Michel Crucifix
Geosci. Model Dev., 18, 3081–3129, https://doi.org/10.5194/gmd-18-3081-2025, https://doi.org/10.5194/gmd-18-3081-2025, 2025
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We present SURFER v3.0, a simple climate model designed to estimate the impact of CO2 and CH4 emissions on global temperatures, sea levels, and ocean pH. We added new carbon cycle processes and calibrated the model to observations and results from more complex models, enabling use over timescales ranging from decades to millions of years. SURFER v3.0 is fast, transparent, and easy to use, making it an ideal tool for policy assessments and suitable for educational purposes.
Yong-He Liu and Zong-Liang Yang
Geosci. Model Dev., 18, 3157–3174, https://doi.org/10.5194/gmd-18-3157-2025, https://doi.org/10.5194/gmd-18-3157-2025, 2025
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NMH-CS 3.0 is a C#-based ecohydrological model reconstructed from the WRF-Hydro/Noah-MP model by translating the Fortran code of WRF-Hydro 3.0 and integrating a parallel river routing module. It enables efficient execution on multi-core personal computers. Simulations in the Yellow River basin demonstrate its consistency with WRF-Hydro outputs, providing a reliable alternative to the original Noah-MP model.
Conor T. Doherty, Weile Wang, Hirofumi Hashimoto, and Ian G. Brosnan
Geosci. Model Dev., 18, 3003–3016, https://doi.org/10.5194/gmd-18-3003-2025, https://doi.org/10.5194/gmd-18-3003-2025, 2025
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We present, analyze, and validate a methodology for quantifying uncertainty in gridded meteorological data products produced by spatial interpolation. In a validation case study using daily maximum near-surface air temperature (Tmax), the method works well and produces predictive distributions with closely matching theoretical versus actual coverage levels. Application of the method reveals that the magnitude of uncertainty in interpolated Tmax varies significantly in both space and time.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O'Rourke, and Beth Dingley
Geosci. Model Dev., 18, 2639–2663, https://doi.org/10.5194/gmd-18-2639-2025, https://doi.org/10.5194/gmd-18-2639-2025, 2025
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used variables from Earth system models based on an assessment of data publication and download records from the largest archive of global climate projects.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, https://doi.org/10.5194/gmd-18-2609-2025, 2025
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PaleoSTeHM v1.0 is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo-records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
Geosci. Model Dev., 18, 2587–2608, https://doi.org/10.5194/gmd-18-2587-2025, https://doi.org/10.5194/gmd-18-2587-2025, 2025
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Tropical ocean basins influence each other through multiple pathways and mechanisms, referred to here as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models but have obtained conflicting results. This may be partly due to differences in experiment protocols and partly due to systematic model errors. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 2479–2508, https://doi.org/10.5194/gmd-18-2479-2025, https://doi.org/10.5194/gmd-18-2479-2025, 2025
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth's orbit. We demonstrate that ZEMBA reproduces many features of the Earth's climate for both the pre-industrial period and the Earth's most recent cold extreme – the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025, https://doi.org/10.5194/gmd-18-2443-2025, 2025
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Improving climate predictions has significant socio-economic impacts. In this study, we develop and apply a new weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. This system is meant to advance our understanding of the ocean's role in climate predictability.
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Our research presents a novel deep learning approach called "TemDeep" for downscaling atmospheric variables at arbitrary time resolutions based on temporal coherence. Results show that our method can accurately recover evolution details superior to other methods, reaching 53.7 % in the restoration rate. Our findings are important for advancing weather forecasting models and enabling more precise and reliable predictions to support disaster preparedness, agriculture, and sustainable development.
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Zhongwang Wei, Qingchen Xu, Fan Bai, Xionghui Xu, Zixin Wei, Wenzong Dong, Hongbin Liang, Nan Wei, Xingjie Lu, Lu Li, Shupeng Zhang, Hua Yuan, Laibo Liu, and Yongjiu Dai
EGUsphere, https://doi.org/10.5194/egusphere-2025-1380, https://doi.org/10.5194/egusphere-2025-1380, 2025
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Land surface models are used for simulating earth's surface interacts with the atmosphere. As models grow more complex and detailed, researchers need better tools to evaluate their performance. OpenBench, a new software system that makes evaluation process more comprehensive and efficient. It stands out by incorporating various factors and working with data at any scale which enabling scientists to incorporate new types of models and measurements as our understanding of Earth’s systems evolves.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Kostas Tsigaridis, Andrew S. Ackerman, Igor Aleinov, Mark A. Chandler, Thomas L. Clune, Christopher M. Colose, Anthony D. Del Genio, Maxwell Kelley, Nancy Y. Kiang, Anthony Leboissetier, Jan P. Perlwitz, Reto A. Ruedy, Gary L. Russell, Linda E. Sohl, Michael J. Way, and Eric T. Wolf
EGUsphere, https://doi.org/10.5194/egusphere-2025-925, https://doi.org/10.5194/egusphere-2025-925, 2025
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We present the second generation of ROCKE-3D, a generalized 3-dimensional model for use in Solar System and exoplanetary simulations of rocky planet climates. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169, https://doi.org/10.5194/egusphere-2025-169, 2025
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Satellites have observed earth's emission of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about the earth and atmosphere. We present a tool that runs alongside global climate models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Noribeth Mariscal, Louisa K. Emmons, Duseong S. Jo, Ying Xiong, Laura M. Judd, Scott J. Janz, Jiajue Chai, and Yaoxian Huang
EGUsphere, https://doi.org/10.5194/egusphere-2025-228, https://doi.org/10.5194/egusphere-2025-228, 2025
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The distribution of ozone (O3) and its precursors (NOx, VOCs) is explored using the chemistry-climate model, MUSICAv0, and evaluated using measurements from the Michigan-Ontario Ozone Source Experiment. A custom grid of ~7 km was created over Michigan. A sector-based diurnal cycle for anthropogenic nitric oxide was included in the model. This work shows that grid resolution played a more important role for O3 precursors, and the diurnal cycle significantly impacted nighttime O3 formation.
Maria Vittoria Struglia, Alessandro Anav, Marta Antonelli, Sandro Calmanti, Franco Catalano, Alessandro Dell'Aquila, Emanuela Pichelli, and Giovanna Pisacane
EGUsphere, https://doi.org/10.5194/egusphere-2025-387, https://doi.org/10.5194/egusphere-2025-387, 2025
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We present the results of downscaling global climate projections for the Mediterranean and Italian regions aiming to produce high-resolution climate information for the assessment of climate change signals, focusing on extreme events. A general warming is foreseen by the end of century with a mean precipitation reduction accompanied, over Italian Peninsula, by a strong increase in the intensity of extreme precipitation events, particularly relevant for the high emissions scenario during autumn
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Katherine Grayson, Stephan Thober, Aleksander Lacima-Nadolnik, Ehsan Sharifi, Llorenç Lledó, and Francisco Doblas-Reyes
EGUsphere, https://doi.org/10.5194/egusphere-2025-28, https://doi.org/10.5194/egusphere-2025-28, 2025
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To provide the most accurate climate adaptation information, climate models are being run with finer grid resolution, resulting in larger data output. This paper presents intelligent data reduction algorithms that act on streamed data, a novel way of processing climate data as soon as it is produced. Using these algorithms to calculate statistics, we show that the accuracy provided is well within acceptable bounds while still providing memory savings that bypass unfeasible storage requirements.
Cited articles
Arnold, N. S., Rees, W. G., Hodson, A. J., and Kohler, J.: Topographic controls
on the surface energy balance of a high Arctic valley glacier, J.
Geophys. Res.-Earth Surf., 111, F02011, https://doi.org/10.1029/2005JF000426, 2006. a, b
Bahadory, T. and Tarasov, L.: LCice 1.0: A generalized Ice Sheet
Systems Model coupler for LOVECLIM version 1.3, Zenodo,
available at: http://doi.org/10.5281/zenodo.1409282, last access: 21 September 2018.
Balmaseda, M. A., Vidard, A., and Anderson, D. L. T.: The ECMWF Ocean Analysis
System: ORA-S3, Mon. Weather Rev., 136, 3018–3034,
https://doi.org/10.1175/2008MWR2433.1, 2008. a, b
Bassford, R., Siegert, M., and Dowdeswell, J.: Quantifying the mass balance of
ice caps on Severnaya Zemlya, Russian High Arctic. II: Modeling the flow of
the Vavilov Ice Cap under the present climate, Arct. Antarct. Alpine
Res., 38, 13–20, 2006a. a
Bassford, R., Siegert, M., Dowdeswell, J., Oerlemans, J., Glazovsky, A., and
Macheret, Y.: Quantifying the mass balance of ice caps on Severnaya Zemlya,
Russian High Arctic. I: Climate and mass balance of the Vavilov Ice Cap,
Arct. Antarct. Alpine Res., 38, 1–12, 2006b. a
Berger, A.: Milankovitch and astronomical theories of paleoclimates, in:
Milankovitch Anniversary UNESCO Symposium-Water Management in Transition
Countries as Impacted by Climate Change and Other Global Changes, Lessons
from Paleoclimate, and Regional Issues, Jaroslav Černi Institute for
the Development of Water Resources, Belgrade (Serbia), 2014. a
Berger, A. L.: Long-Term Variations of Caloric Insolation Resulting from the
Earth's Orbital Elements 1, Quaternary Res., 9, 139–167, 1978.
Birch, L., Tziperman, E., and Cronin, T.: Glacial Inception in
north-east Canada: The Role of Topography and Clouds, in: EGU General
Assembly Conference Abstracts, Vol. 18 of EGU General Assembly
Conference Abstracts, EPSC2016–948, 2016. a
Birch, L., Cronin, T., and Tziperman, E.: Glacial Inception on Baffin Island:
The Role of Insolation, Meteorology, and Topography, J. Climate, 30,
4047–4064, https://doi.org/10.1175/JCLI-D-16-0576.1, 2017. a
Brovkin, V., Ganopolski, A., and Svirezhev, Y.: A continuous climate-vegetation
classification for use in climate-biosphere studies, Ecol. Modell.,
101, 251–261, https://doi.org/10.1016/S0304-3800(97)00049-5, 1997. a
Brovkin, V., Bendtsen, J., Claussen, M., Ganopolski, A., Kubatzki, C.,
Petoukhov, V., and Andreev, A.: Carbon cycle, vegetation, and climate
dynamics in the Holocene: Experiments with the CLIMBER-2 model, Global
Biogeochem. Cy., 16, 861–8620, https://doi.org/10.1029/2001GB001662, 2002. a, b
Campin, J.-M. and Goosse, H.: Parameterization of density-driven downsloping
flow for a coarse-resolution ocean model in z-coordinate, Tellus A, 51, 412–430, 1999. a
De Boer, A. M. and Nof, D.: The exhaust valve of the North Atlantic, J.
Climate, 17, 417–422, 2004. a
DeConto, R. M. and Pollard, D.: Contribution of Antarctica to past and future
sea-level rise, Nature, 531, 591–597, 2016. a
De Woul, M., Hock, R., Braun, M., Thorsteinsson, T., Jóhannesson, T., and
Halldórsdóttir, S.: Firn layer impact on glacial runoff: a case study
at Hofsjökull, Iceland, Hydrol. Process., 20, 2171–2185, 2006. a
Elison Timm, O., Friedrich, T., Timmermann, A., and Ganopolski, A.:
Separating the Effects of Northern Hemisphere Ice-Sheets, CO2
Concentrations and Orbital Parameters on Global Precipitation During the Late
Pleistocene Glacial Cycles, AGU Fall Meeting Abstracts, 2015. a
Erokhina, O., Rogozhina, I., Prange, M., Bakker, P., Bernales, J., Paul, A.,
and Schulz, M.: Dependence of slope lapse rate over the Greenland ice sheet
on background climate, J. Glaciol., 63, 568–572, 2017. a
Etheridge, D., Barnola, J., and Morgan, V.: Historical CO2 records from the Law
Dome DE08, DE08-2, and DSS ice cores, Tech. rep., ESS-DIVE (Environmental
System Science Data Infrastructure for a Virtual Ecosystem); Oak Ridge
National Lab.(ORNL), Oak Ridge, TN (United States), 1998.
Fichefet, T. and Maqueda, M. A. M.: Sensitivity of a global sea ice model to
the treatment of ice thermodynamics and dynamics, J. Geophys.
Res.-Oceans, 102, 12609–12646, https://doi.org/10.1029/97JC00480, 1997. a
Flowers, G. E. and Clarke, G. K.: A multicomponent coupled model of glacier
hydrology 1. Theory and synthetic examples, J. Geophys. Res.-Solid Earth, 107,
ECV9-1–ECV9-17, https://doi.org/10.1029/2001JB001122, 2002. a
Galle, H., Van Yperselb, J. P., Fichefet, T., Marsiat, I., Tricot, C., and
Berger, A.: Simulation of the last glacial cycle by a coupled, sectorially
averaged climate-ice sheet model: 2. Response to insolation and CO2
variations, J. Geophys. Res.-Atmos., 97,
15713–15740, https://doi.org/10.1029/92JD01256, 1992. a
Ganopolski, A., Calov, R., and Claussen, M.: Simulation of the last glacial
cycle with a coupled climate ice-sheet model of intermediate complexity,
Clim. Past, 6, 229–244, https://doi.org/10.5194/cp-6-229-2010, 2010. a
Ganopolski, A., Winkelmann, R., and Schellnhuber, H. J.: Critical
insolation–CO2 relation for diagnosing past and future glacial inception,
Nature, 529, 200–203, 2016. a
Gardner, A. S., Sharp, M. J., Koerner, R. M., Labine, C., Boon, S., Marshall,
S. J., Burgess, D. O., and Lewis, D.: Near-Surface Temperature Lapse Rates
over Arctic Glaciers and Their Implications for Temperature Downscaling,
J. Climate, 22, 4281–4298, https://doi.org/10.1175/2009JCLI2845.1, 2009. a, b
Goosse, H., Campin, J., Fichefet, T., and Deleersnijder, E.: Sensitivity of a
global ice–ocean model to the Bering Strait throughflow, Clim. Dynam.,
13, 349–358, 1997. a
Goosse, H., Campin, J.-M., Deleersnijder, E., Fichefet, T., Mathieu, P.-P.,
Maqueda, M. M., and Tartinville, B.: Description of the CLIO model version
3.0, Institut d'Astronomie et de Géophysique Georges Lemaitre, Catholic
University of Louvain, Belgium, 2001. a
Goosse, H., Renssen, H., Timmermann, A., and Bradley, R. S.: Internal and
forced climate variability during the last millennium: a model-data
comparison using ensemble simulations, Quaternary Sci. Rev., 24,
1345–1360, 2005. a
Goosse, H., Driesschaert, E., Fichefet, T., and Loutre, M.-F.: Information on
the early Holocene climate constrains the summer sea ice projections for the
21st century, Clim. Past, 3, 683–692, https://doi.org/10.5194/cp-3-683-2007,
2007. a, b
Goosse, H., Brovkin, V., Fichefet, T., Haarsma, R., Huybrechts, P., Jongma,
J., Mouchet, A., Selten, F., Barriat, P.-Y., Campin, J.-M., Deleersnijder,
E., Driesschaert, E., Goelzer, H., Janssens, I., Loutre, M.-F., Morales
Maqueda, M. A., Opsteegh, T., Mathieu, P.-P., Munhoven, G., Pettersson, E.
J., Renssen, H., Roche, D. M., Schaeffer, M., Tartinville, B., Timmermann,
A., and Weber, S. L.: Description of the Earth system model of intermediate
complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633,
https://doi.org/10.5194/gmd-3-603-2010, 2010. a, b, c, d
Haarsma, R., Selten, F., Opsteegh, J., Lenderink, G., and Liu, Q.: ECBILT, a
coupled atmosphere ocean sea-ice model for climate predictability studies,
KNMI, De Bilt, The Netherlands, 31, 1996. a
Hahn, J., Walsh, J., Widiasih, E., and McGehee, R.: Periodicity in a
Conceptual Model of Glacial Cycles in the Absence of Milankovitch Forcing,
AGU Fall Meeting Abstracts, 2015.
Heinemann, M., Timmermann, A., Elison Timm, O., Saito, F., and Abe-Ouchi, A.:
Deglacial ice sheet meltdown: orbital pacemaking and CO2 effects, Clim. Past,
10, 1567–1579, https://doi.org/10.5194/cp-10-1567-2014, 2014. a
Hewitt, C. D. and Mitchell, J. F. B.: Radiative forcing and response of a GCM
to ice age boundary conditions: cloud feedback and climate sensitivity,
Clim. Dynam., 13, 821–834, 1997. a
Hibler, W. D.: A Dynamic Thermodynamic Sea Ice Model, J. Phys.
Oceanogr., 9, 815–846,
https://doi.org/10.1175/1520-0485(1979)009<0815:ADTSIM>2.0.CO;2, 1979. a
Hu, A., Otto-Bliesner, B. L., Meehl, G. A., Han, W., Morrill, C., Brady, E. C.,
and Briegleb, B.: Response of Thermohaline Circulation to Freshwater Forcing
under Present-Day and LGM Conditions, J. Climate, 21, 2239–2258,
https://doi.org/10.1175/2007JCLI1985.1, 2008. a, b
Jacobs, S., Hellmer, H., Doake, C., Jenkins, A., and Frolich, R.: Melting of
ice shelves and the mass balance of Antarctica, J. Glaciol., 38, 375–387,
1992. a
Johns, T. C., Carnell, R. E., Crossley, J. F., Gregory, J. M., Mitchell, J.
F. B., Senior, C. A., Tett, S. F. B., and Wood, R. A.: The second Hadley
Centre coupled ocean-atmosphere GCM: model description, spinup and
validation, Clim. Dynam., 13, 103–134, 1997. a
Kageyama, M., Merkel, U., Otto-Bliesner, B., Prange, M., Abe-Ouchi, A.,
Lohmann, G., Ohgaito, R., Roche, D. M., Singarayer, J., Swingedouw, D., and X
Zhang: Climatic impacts of fresh water hosing under Last Glacial Maximum
conditions: a multi-model study, Clim. Past, 9, 935–953,
https://doi.org/10.5194/cp-9-935-2013, 2013. a
Krebs, U. and Timmermann, A.: Tropical air–sea interactions accelerate the
recovery of the Atlantic meridional overturning circulation after a major
shutdown, J. Climate, 20, 4940–4956, 2007. a
Liu, Z., Otto-Bliesner, B. L., He, F., Brady, E. C., Tomas, R., Clark, P. U.,
Carlson, A. E., Lynch-Stieglitz, J., Curry, W., Brook, E., Erickson, D.,
Jacob, R., Kutzbach, J., and Cheng, J.: Transient Simulation of Last
Deglaciation with a New Mechanism for Bølling-Allerød Warming, Science,
325, 310–314, https://doi.org/10.1126/science.1171041, 2009. a
Mairesse, A., Goosse, H., Mathiot, P., Wanner, H., and Dubinkina, S.:
Investigating the consistency between proxy-based reconstructions and climate
models using data assimilation: a mid-Holocene case study, Clim. Past, 9,
2741–2757, https://doi.org/10.5194/cp-9-2741-2013, 2013. a
Manabe, S., Stouffer, R., Spelman, M., and Bryan, K.: Transient responses of a
coupled ocean–atmosphere model to gradual changes of atmospheric CO2. Part
I. Annual mean response, J. Climate, 4, 785–818, 1991. a
Marshall, S. J., Sharp, M. J., Burgess, D. O., and Anslow, F. S.:
Near-surface-temperature lapse rates on the Prince of Wales Icefield,
Ellesmere Island, Canada: implications for regional downscaling of
temperature, Int. J. Climatol., 27, 385–398,
https://doi.org/10.1002/joc.1396, 2007. a, b
McManus, J. F., Francois, R., Gherardi, J.-M., Keigwin, L. D., and Brown-Leger,
S.: Collapse and rapid resumption of Atlantic meridional circulation linked
to deglacial climate changes, Nature, 428, 834–837, 2004. a
Monnin, E., Indermühle, A., Dällenbach, A., Flückiger, J.,
Stauffer, B., Stocker, T. F., Raynaud, D., and Barnola, J.-M.: Atmospheric
CO2 concentrations over the last glacial termination, Science, 291, 112–114,
2001.
Le Morzadec, K., Tarasov, L., Morlighem, M., and Seroussi, H.: A new sub-grid
surface mass balance and flux model for continental-scale ice sheet
modelling: testing and last glacial cycle, Geosci. Model Dev., 8, 3199–3213,
https://doi.org/https://doi.org/10.5194/gmd-8-3199-2015, 2015. a
Nikolova, I., Yin, Q., Berger, A., Singh, U. K., and Karami, M. P.: The last
interglacial (Eemian) climate simulated by LOVECLIM and CCSM3, Clim. Past, 9,
1789–1806, https://doi.org/10.5194/cp-9-1789-2013, 2013. a
Opsteegh, J. D., Haarsma, R. J., Selten, F. M., and Kattenberg, A.: ECBILT: a
dynamic alternative to mixed boundary conditions in ocean models, Tellus A,
50, 348–367, https://doi.org/10.1034/j.1600-0870.1998.t01-1-00007.x, 1998. a, b
Otto-Bliesner, B. L. and Brady, E. C.: The sensitivity of the climate response
to the magnitude and location of freshwater forcing: last glacial maximum
experiments, Quaternary Sci. Rev., 29, 56–73,
https://doi.org/10.1016/j.quascirev.2009.07.004, 2010. a, b
Rahmstorf, S.: Bifurcations of the Atlantic thermohaline circulation in
response to changes in the hydrological cycle, Nature, 378, 145–149, 1995. a
Rahmstorf, S., Crucifix, M., Ganopolski, A., Goosse, H., Kamenkovich, I., Knutti, R., Lohmann,
G., Marsh, R., Mysak, L. A. and Wang, Z., and Weaver, A.J.:
Thermohaline circulation hysteresis: A model intercomparison, Geophys.
Res. Lett., 32, 23, https://doi.org/10.1029/2005GL023655, 2005. a
Ridley, J. K., Huybrechts, P., Gregory, J. M., and Lowe, J. A.: Elimination of
the Greenland Ice Sheet in a High CO2 Climate, J. Climate, 18,
3409–3427, https://doi.org/10.1175/JCLI3482.1, 2005. a
Rind, D., Peteet, D., and Kukla, G.: Can Milankovitch orbital variations
initiate the growth of ice sheets in a general circulation model?, J.
Geophys. Res.-Atmos., 94, 12851–12871,
https://doi.org/10.1029/JD094iD10p12851, 1989. a
Roberts, W. H. G., Valdes, P. J., and Payne, A. J.:
Topography's crucial role in Heinrich Events, P.
Natl. Acad. Sci. USA, 47, 16688–16693, https://doi.org/10.1073/pnas.1414882111, 2014. a
Roche, D. M., Dokken, T. M., Goosse, H., Renssen, H., and Weber, S. L.:
Climate of the Last Glacial Maximum: sensitivity studies and model-data
comparison with the LOVECLIM coupled model, Clim. Past, 3, 205–224,
https://doi.org/10.5194/cp-3-205-2007, 2007. a, b, c, d
Roche, D. M., Crosta, X., and Renssen, H.: Evaluating Southern Ocean sea-ice for
the Last Glacial Maximum and pre-industrial climates: PMIP-2 models and data
evidence, Quaternary Sci. Rev., 56, 99–106, 2012. a
Roche, D. M., Dumas, C., Bügelmayer, M., Charbit, S., and Ritz, C.: Adding a
dynamical cryosphere to iLOVECLIM (version 1.0): coupling with the GRISLI
ice-sheet model, Geosci. Model Dev., 7, 1377–1394,
https://doi.org/10.5194/gmd-7-1377-2014, 2014. a, b, c, d
Rossow, W. B.: International Satellite Cloud Climatology Project (ISCCP): New
radiance calibrations, World Meteorological Organization, 1996. a
Shaffer, G. and Bendtsen, J.: Role of the Bering Strait in controlling North
Atlantic ocean circulation and climate, Nature, 367, 354–357, 1994. a
Stokes, C. R., Tarasov, L., and Dyke, A. S.: Dynamics of the North American Ice
Sheet Complex during its inception and build-up to the Last Glacial Maximum,
Quaternary Sci. Rev., 50, 86–104, 2012. a
Stouffer, R. J., Yin, J., Gregory, J. M., Dixon, K. W., Spelman, M. J., Hurlin,
W., Weaver, A. J., Eby, M., Flato, G. M., Hasumi, H., Hu, A., Jungclaus,
J. H., Kamenkovich, I. V., Levermann, A., Montoya, M., Murakami, S., Nawrath,
S., Oka, A., Peltier, W. R., Robitaille, D. Y., Sokolov, A., Vettoretti, G.,
and Weber, S. L.: Investigating the Causes of the Response of the
Thermohaline Circulation to Past and Future Climate Changes, J.
Climate, 19, 1365–1387, https://doi.org/10.1175/JCLI3689.1, 2006. a
Tarasov, L. and Peltier, W. R.: A high-resolution model of the 100 kyr Ice Age
cycle, Ann. Glaciol., 25, 58–65, 1997. a
Tarasov, L. and Peltier, W. R.: Greenland glacial history and local
geodynamic consequences, Geophys. J. Int., 150, 198–229, 2002. a
Tarasov, L. and Peltier, W. R.: A calibrated deglacial drainage chronology for
the North American continent: Evidence of an Arctic trigger for the
Younger Dryas, Quaternary Sci. Rev., 25, 659–688, 2006. a
Tarasov, L. and Peltier, W. R.: The Co-evolution of continental ice cover and
permafrost extent over the last glacial-interglacial cycle in North
America, J. Geophys. Res.-Earth Surf., 112, F02S08, https://doi.org/10.1029/2006JF000661, 2007.
a
Thomas, R. H., Abdalati, W., Frederick, E., Krabill, W. B., Manizade, S., and
Steffen, K.: Investigation of surface melting and dynamic thinning on
Jakobshavn Isbræ, Greenland, J. Glaciol., 49, 231–239,
https://doi.org/10.3189/172756503781830764, 2003. a
Timmermann, A., Gildor, H., Schulz, M., and Tziperman, E.: Coherent Resonant
Millennial-Scale Climate Oscillations Triggered by Massive Meltwater Pulses,
J. Climate, 16, 2569–2585,
https://doi.org/10.1175/1520-0442(2003)016<2569:CRMCOT>2.0.CO;2, 2003. a
van den Broeke, M., Smeets, P., Ettema, J., and Munneke, P. K.: Surface
radiation balance in the ablation zone of the west Greenland ice sheet,
J. Geophys. Res.-Atmos., 113, D13105, https://doi.org/10.1029/2007JD009283, 2008. a
Van Meerbeeck, C. J., Renssen, H., and Roche, D. M.: How did Marine Isotope
Stage 3 and Last Glacial Maximum climates differ? – Perspectives from
equilibrium simulations, Clim. Past, 5, 33–51,
https://doi.org/10.5194/cp-5-33-2009, 2009. a
Walsh, J., Chapman, W., and Fetterer, F.: Gridded Monthly Sea Ice Extent and
Concentration, 1850 Onward, Version 1, Tech. rep., NSIDC: National Snow and
Ice Data Center, Boulder, Colorado USA, https://doi.org/10.7265/N5833PZ5, 2015. a, b
Widmann, M., Goosse, H., van der Schrier, G., Schnur, R., and Barkmeijer, J.:
Using data assimilation to study extratropical Northern Hemisphere climate
over the last millennium, Clim. Past, 6, 627–644,
https://doi.org/10.5194/cp-6-627-2010, 2010. a
Xu, Y., Rignot, E., Fenty, I., Menemenlis, D., and Flexas, M. M.: Subaqueous
melting of Store Glacier, west Greenland from three-dimensional,
high-resolution numerical modeling and ocean observations, Geophys.
Res. Lett., 40, 4648–4653, https://doi.org/10.1002/grl.50825, 2013. a
Xun, G., Gregor, K., Gerrit, L., and Xu, Z.: Dependence of abrupt Atlantic
meridional ocean circulation changes on climate background states,
Geophys. Res. Lett., 40, 3698–3704, https://doi.org/10.1002/grl.50701, 2013. a
Yin, Q., Berger, A., Ganopolski, A., Goelzer, H., Guo, Z., and
Huybrechts, P.: Ice sheets, insolation and CO2 during the interglacial
MIS-13, in: EGU General Assembly Conference Abstracts, Vol. 16, EGU
General Assembly Conference Abstracts, p. 2910, 2014. a
Short summary
We describe a new coupling between the Glacial Systems Model and the
LOVECLIM intermediate complexity climate model. The coupling is
distinguished from that of previous studies by greater completeness
and accuracy, with the intent of capturing the major feedbacks between
ice sheets and climate on glacial cycle timescales. The fully coupled
model will be used to examine the ice/climate phase space of past
glacial cycles.
We describe a new coupling between the Glacial Systems Model and the
LOVECLIM intermediate...
