Articles | Volume 17, issue 21
https://doi.org/10.5194/gmd-17-7835-2024
© Author(s) 2024. 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-17-7835-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
07 Nov 2024
Methods for assessment of models |
| 07 Nov 2024
| 07 Nov 2024
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Trude Eidhammer
CORRESPONDING AUTHOR
NSF National Center for Atmospheric Research, Boulder, CO, USA
Andrew Gettelman
NSF National Center for Atmospheric Research, Boulder, CO, USA
now at: Atmospheric, Climate and Earth Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
Katherine Thayer-Calder
NSF National Center for Atmospheric Research, Boulder, CO, USA
Duncan Watson-Parris
Scripps Institution of Oceanography and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
Gregory Elsaesser
Dept. of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
NASA Goddard Institute for Space Studies, New York, NY, USA
Hugh Morrison
NSF National Center for Atmospheric Research, Boulder, CO, USA
Marcus van Lier-Walqui
Center for Climate Systems Research, Columbia University, New York, NY, USA
NASA Goddard Institute for Space Studies, New York, NY, USA
Ci Song
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Daniel McCoy
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
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18 citations as recorded by crossref.
- Detection of potential structural deficiencies in a global aerosol model using a perturbed parameter ensemble L. Prévost et al. https://doi.org/10.5194/acp-26-2487-2026
- Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model W. Pringle et al. https://doi.org/10.1029/2024MS004337
- Recent Advances in the Observation and Modeling of Aerosol-Cloud Interactions, Cloud Feedbacks, and Earth’s Energy Imbalance: A Review T. Michibata et al. https://doi.org/10.1007/s40726-025-00382-6
- Quantification and parameterization of snowflake fall speeds in the atmospheric surface-layer S. Donovan et al. https://doi.org/10.5194/acp-25-16729-2025
- The coupled uncertainties in carbon dioxide removal and transient climate response to cumulative CO2 emissions C. Di Natale et al. https://doi.org/10.1088/1748-9326/ae20a5
- Uncertainty in aerosol effective radiative forcing from anthropogenic and natural aerosol parameters in ECHAM6.3-HAM2.3 Y. Bhatti et al. https://doi.org/10.5194/acp-26-269-2026
- Opinion: The importance and future development of perturbed parameter ensembles in climate and atmospheric science K. Carslaw et al. https://doi.org/10.5194/acp-26-4651-2026
- Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble A. Mikkelsen et al. https://doi.org/10.5194/acp-25-4547-2025
- Aircraft in-situ measurements from SOCRATES constrain the anthropogenic perturbations of cloud droplet number C. Song et al. https://doi.org/10.5194/acp-25-16063-2025
- Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling R. O'Loughlin et al. https://doi.org/10.5194/gmd-18-787-2025
- Enhanced climate reproducibility testing with false discovery rate correction M. Kelleher & S. Mahajan https://doi.org/10.5194/esd-17-23-2026
- Calibrating the GAMIL3-1° climate model using a derivative-free optimization method W. Liang et al. https://doi.org/10.5194/gmd-18-9293-2025
- Remaining aerosol forcing uncertainty after observational constraint and the processes that cause it L. Regayre et al. https://doi.org/10.5194/acp-26-2293-2026
- Developing Guidelines for working with Multi-Model Ensembles in CMIP A. Katzenberger et al. https://doi.org/10.5194/esd-17-495-2026
- JCM v1.1: a differentiable, intermediate-complexity atmospheric model E. Davenport et al. https://doi.org/10.5194/gmd-19-6451-2026
- Calibration of climate model parameterizations using Bayesian experimental design T. Reichelt et al. https://doi.org/10.1088/3049-4753/ae2edb
- Confronting Earth System Model trends with observations I. Simpson et al. https://doi.org/10.1126/sciadv.adt8035
- Parametric Sensitivity Analysis of ENSO‐Related Shortwave Feedback Simulations by PPE Experiments in CAM6 Y. Zhu et al. https://doi.org/10.1002/joc.70210
Saved (final revised paper)
Latest update: 16 Sep 2026
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.
We describe a dataset where 45 parameters related to cloud processes in the Community Earth...
