Articles | Volume 8, issue 4
https://doi.org/10.5194/gmd-8-1221-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-1221-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
29 Apr 2015
Development and technical paper |
| 29 Apr 2015
The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations
K. Alexander
Department of Computer Science, University of Toronto, 10, King's College Rd, Toronto, Ontario, Canada
now at: Climate Change Research Centre and ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney NSW 2052, Australia
S. M. Easterbrook
CORRESPONDING AUTHOR
Department of Computer Science, University of Toronto, 10, King's College Rd, Toronto, Ontario, Canada
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- Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models S. Hashimoto et al. https://doi.org/10.5194/gmd-10-1321-2017
- Linking cumulative carbon emissions to observable climate impacts C. Nzotungicimpaye & H. Matthews https://doi.org/10.1088/2752-5295/ad3fda
- Mapping future water scarcity in a water abundant nation: Near-term projections for Scotland A. Visser-Quinn et al. https://doi.org/10.1016/j.crm.2021.100302
- Using paleoecological data to inform decision making: A deep-time perspective H. Dowsett et al. https://doi.org/10.3389/fevo.2022.972179
- OpenArray v1.0: a simple operator library for the decoupling of ocean modeling and parallel computing X. Huang et al. https://doi.org/10.5194/gmd-12-4729-2019
- Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0) E. Weng et al. https://doi.org/10.5194/gmd-15-8153-2022
- FaIRv2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration N. Leach et al. https://doi.org/10.5194/gmd-14-3007-2021
- Neural emulator based on physical fields for accelerating the simulation of surface chlorophyll in an Earth System Model B. Wu et al. https://doi.org/10.1016/j.ocemod.2024.102491
- Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States E. Massoud et al. https://doi.org/10.1175/JHM-D-19-0258.1
- Toward modular in situ visualization in Earth system models: the regional modeling system RegESM 1.1 U. Turuncoglu https://doi.org/10.5194/gmd-12-233-2019
- Climate Model Code Genealogy and Its Relation to Climate Feedbacks and Sensitivity P. Kuma et al. https://doi.org/10.1029/2022MS003588
- Data Science of the Natural Environment: A Research Roadmap G. Blair et al. https://doi.org/10.3389/fenvs.2019.00121
- Fighting big data and ensemble fatigue in climate change impact studies: Can we turn the ensemble cascade upside down? E. Van Uytven et al. https://doi.org/10.1002/joc.6696
- CPMIP: measurements of real computational performance of Earth system models in CMIP6 V. Balaji et al. https://doi.org/10.5194/gmd-10-19-2017
- Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework V. Balaji et al. https://doi.org/10.5194/gmd-9-3605-2016
- Bitwise identical compiling setup: prospective for reproducibility and reliability of Earth system modeling R. Li et al. https://doi.org/10.5194/gmd-9-731-2016
- Thematic domain analysis for ocean modeling R. Jung et al. https://doi.org/10.1016/j.envsoft.2022.105323
- Software development processes in ocean system modeling R. Jung et al. https://doi.org/10.1142/S1793962322300023
- Taking climate model evaluation to the next level V. Eyring et al. https://doi.org/10.1038/s41558-018-0355-y
- Global Climate Model Ensemble Approaches for Future Projections of Atmospheric Rivers E. Massoud et al. https://doi.org/10.1029/2019EF001249
- Open Science Expectations for Simulation-Based Research G. Mullendore et al. https://doi.org/10.3389/fclim.2021.763420
- Software Architecture Evaluation of Earth System Models W. Hasselbring et al. https://doi.org/10.4236/jsea.2025.183008
- Software sustainability of global impact models E. Nyenah et al. https://doi.org/10.5194/gmd-17-8593-2024
- Optimized thread-block arrangement in a GPU implementation of a linear solver for atmospheric chemistry mechanisms C. Guzman Ruiz et al. https://doi.org/10.1016/j.cpc.2024.109240
- Toward more robust net primary production projections in the North Atlantic Ocean S. Doléac et al. https://doi.org/10.5194/bg-22-841-2025
- Modular System for Shelves and Coasts (MOSSCO v1.0) – a flexible and multi-component framework for coupled coastal ocean ecosystem modelling C. Lemmen et al. https://doi.org/10.5194/gmd-11-915-2018
- Crossing the chasm: how to develop weather and climate models for next generation computers? B. Lawrence et al. https://doi.org/10.5194/gmd-11-1799-2018
- An Efficient Ice Sheet/Earth System Model Spin‐up Procedure for CESM2‐CISM2: Description, Evaluation, and Broader Applicability M. Lofverstrom et al. https://doi.org/10.1029/2019MS001984
- A SPATIOTEMPORAL-AWARE WEIGHTING SCHEME FOR IMPROVING CLIMATE MODEL ENSEMBLE PREDICTIONS M. Fan et al. https://doi.org/10.1615/JMachLearnModelComput.2022046715
Saved (final revised paper)
Latest update: 24 Jun 2026
Short summary
This paper describes an analysis of the software architecture of global climate models. The analysis provides a visualization of the structure of these models, and reveals interesting differences between the models developed at different research labs.
This paper describes an analysis of the software architecture of global climate models. The...
