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.
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
No articles found.
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
Short summary
Short summary
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
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
An abnormally warm period around 400,000 years ago is thought to have resulted in a large melt event for the Greenland Ice Sheet. Using a sequence of climate model simulations connected to an ice model, we estimate a 50 % melt of Greenland compared to today. Importantly, we explore how the exact methodology of connecting the temperatures and precipitation from the climate model to the ice sheet model can influence these results and show that common methods could introduce errors.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Related subject area
Climate and Earth system modeling
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
ICON-HAM-lite: simulating the Earth system with interactive aerosols at kilometer scales
Reducing Time and Computing Costs in EC-Earth: An Automatic Load-Balancing Approach for Coupled ESMs
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
Short summary
Short summary
A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
Short summary
Short summary
In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
Short summary
Short summary
The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
Short summary
Short summary
We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
Short summary
Short summary
We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
Short summary
Short summary
In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
Short summary
Short summary
We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
Short summary
Short summary
The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
Short summary
Short summary
The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
Short summary
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
Short summary
Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
Short summary
Short summary
Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
Short summary
Short summary
A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
Short summary
Short summary
This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
Short summary
Short summary
We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
Short summary
Short summary
Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
Short summary
Short summary
We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
Short summary
Short summary
We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
Short summary
Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
Short summary
Short summary
We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
Short summary
Short summary
We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
Short summary
Short summary
The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
Short summary
Short summary
We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
Short summary
Short summary
The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
Short summary
Short summary
In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
Short summary
Short summary
This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Philipp Weiss, Ross Herbert, and Philip Stier
EGUsphere, https://doi.org/10.5194/egusphere-2024-3325, https://doi.org/10.5194/egusphere-2024-3325, 2024
Short summary
Short summary
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 log-normal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of five kilometers. It captures key aerosol processes like dust storms or tropical cyclones.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-155, https://doi.org/10.5194/gmd-2024-155, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This work presents an automatic tool to enhance the performance of climate models by optimizing how computer resources are allocated. Traditional methods are time-consuming and error-prone, often resulting in inefficient simulations. Our tool improves speed and reduces computational costs without needing expert knowledge. The tool has been tested on European climate models, making simulations up to 34 % faster while using fewer resources, helping to make climate simulations more efficient.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
Short summary
Short summary
We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
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...