Articles | Volume 8, issue 9
https://doi.org/10.5194/gmd-8-2829-2015
© 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-8-2829-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1.0)
The National Center for Atmospheric Research, Boulder, CO, USA
D. M. Hammerling
The National Center for Atmospheric Research, Boulder, CO, USA
M. N. Levy
The National Center for Atmospheric Research, Boulder, CO, USA
H. Xu
The National Center for Atmospheric Research, Boulder, CO, USA
J. M. Dennis
The National Center for Atmospheric Research, Boulder, CO, USA
B. E. Eaton
The National Center for Atmospheric Research, Boulder, CO, USA
J. Edwards
The National Center for Atmospheric Research, Boulder, CO, USA
C. Hannay
The National Center for Atmospheric Research, Boulder, CO, USA
S. A. Mickelson
The National Center for Atmospheric Research, Boulder, CO, USA
R. B. Neale
The National Center for Atmospheric Research, Boulder, CO, USA
D. Nychka
The National Center for Atmospheric Research, Boulder, CO, USA
J. Shollenberger
The National Center for Atmospheric Research, Boulder, CO, USA
J. Tribbia
The National Center for Atmospheric Research, Boulder, CO, USA
M. Vertenstein
The National Center for Atmospheric Research, Boulder, CO, USA
D. Williamson
The National Center for Atmospheric Research, Boulder, CO, USA
Viewed
Total article views: 4,178 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 May 2015)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,589 | 1,428 | 161 | 4,178 | 212 | 172 |
- HTML: 2,589
- PDF: 1,428
- XML: 161
- Total: 4,178
- BibTeX: 212
- EndNote: 172
Total article views: 3,496 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 09 Sep 2015)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,267 | 1,092 | 137 | 3,496 | 199 | 166 |
- HTML: 2,267
- PDF: 1,092
- XML: 137
- Total: 3,496
- BibTeX: 199
- EndNote: 166
Total article views: 682 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 May 2015)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
322 | 336 | 24 | 682 | 13 | 6 |
- HTML: 322
- PDF: 336
- XML: 24
- Total: 682
- BibTeX: 13
- EndNote: 6
Cited
24 citations as recorded by crossref.
- Semi‐Automatic Tuning of Coupled Climate Models With Multiple Intrinsic Timescales: Lessons Learned From the Lorenz96 Model R. Lguensat et al. 10.1029/2022MS003367
- Bitwise identical compiling setup: prospective for reproducibility and reliability of Earth system modeling R. Li et al. 10.5194/gmd-9-731-2016
- The GPU version of LASG/IAP Climate System Ocean Model version 3 (LICOM3) under the heterogeneous-compute interface for portability (HIP) framework and its large-scale application P. Wang et al. 10.5194/gmd-14-2781-2021
- Optimizing high-resolution Community Earth System Model on a heterogeneous many-core supercomputing platform S. Zhang et al. 10.5194/gmd-13-4809-2020
- Acceleration of the Parameterization of Unified Microphysics Across Scales (PUMAS) on the Graphics Processing Unit (GPU) With Directive‐Based Methods J. Sun et al. 10.1029/2022MS003515
- Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0) A. Baker et al. 10.5194/gmd-9-2391-2016
- Asynchronous communication in spectral-element and discontinuous Galerkin methods for atmospheric dynamics – a case study using the High-Order Methods Modeling Environment (HOMME-homme_dg_branch) B. Jamroz & R. Klöfkorn 10.5194/gmd-9-2881-2016
- Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso M. Krock et al. 10.1080/10618600.2023.2174126
- Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale S. Mahajan et al. 10.1016/j.procs.2017.05.259
- Evaluating lossy data compression on climate simulation data within a large ensemble A. Baker et al. 10.5194/gmd-9-4381-2016
- Characterizing uncertainties of Earth system modeling with heterogeneous many-core architecture computing Y. Yu et al. 10.5194/gmd-15-6695-2022
- A new and inexpensive non-bit-for-bit solution reproducibility test based on time step convergence (TSC1.0) H. Wan et al. 10.5194/gmd-10-537-2017
- Ensemble-based statistical verification of INM RAS Earth system model M. Tarasevich et al. 10.1515/rnam-2023-0014
- Towards Characterizing the Variability of Statistically Consistent Community Earth System Model Simulations D. Milroy et al. 10.1016/j.procs.2016.05.489
- Crossing the chasm: how to develop weather and climate models for next generation computers? B. Lawrence et al. 10.5194/gmd-11-1799-2018
- Ongoing solution reproducibility of earth system models as they progress toward exascale computing S. Mahajan et al. 10.1177/1094342019837341
- On Preserving Scientific Integrity for Climate Model Data in the HPC Era A. Baker 10.1109/MCSE.2021.3119509
- A Containerized Mesoscale Model and Analysis Toolkit to Accelerate Classroom Learning, Collaborative Research, and Uncertainty Quantification J. Hacker et al. 10.1175/BAMS-D-15-00255.1
- Replicability of the EC-Earth3 Earth system model under a change in computing environment F. Massonnet et al. 10.5194/gmd-13-1165-2020
- Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0) D. Milroy et al. 10.5194/gmd-11-697-2018
- Effects of Model Resolution, Physics, and Coupling on Southern Hemisphere Storm Tracks in CESM1.3 G. Meehl et al. 10.1029/2019GL084057
- An ensemble-based statistical methodology to detect differences in weather and climate model executables C. Zeman & C. Schär 10.5194/gmd-15-3183-2022
- A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean H. Kang et al. 10.1029/2020MS002238
- KGEN: A Python Tool for Automated Fortran Kernel Generation and Verification Y. Kim et al. 10.1016/j.procs.2016.05.466
23 citations as recorded by crossref.
- Semi‐Automatic Tuning of Coupled Climate Models With Multiple Intrinsic Timescales: Lessons Learned From the Lorenz96 Model R. Lguensat et al. 10.1029/2022MS003367
- Bitwise identical compiling setup: prospective for reproducibility and reliability of Earth system modeling R. Li et al. 10.5194/gmd-9-731-2016
- The GPU version of LASG/IAP Climate System Ocean Model version 3 (LICOM3) under the heterogeneous-compute interface for portability (HIP) framework and its large-scale application P. Wang et al. 10.5194/gmd-14-2781-2021
- Optimizing high-resolution Community Earth System Model on a heterogeneous many-core supercomputing platform S. Zhang et al. 10.5194/gmd-13-4809-2020
- Acceleration of the Parameterization of Unified Microphysics Across Scales (PUMAS) on the Graphics Processing Unit (GPU) With Directive‐Based Methods J. Sun et al. 10.1029/2022MS003515
- Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0) A. Baker et al. 10.5194/gmd-9-2391-2016
- Asynchronous communication in spectral-element and discontinuous Galerkin methods for atmospheric dynamics – a case study using the High-Order Methods Modeling Environment (HOMME-homme_dg_branch) B. Jamroz & R. Klöfkorn 10.5194/gmd-9-2881-2016
- Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso M. Krock et al. 10.1080/10618600.2023.2174126
- Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale S. Mahajan et al. 10.1016/j.procs.2017.05.259
- Evaluating lossy data compression on climate simulation data within a large ensemble A. Baker et al. 10.5194/gmd-9-4381-2016
- Characterizing uncertainties of Earth system modeling with heterogeneous many-core architecture computing Y. Yu et al. 10.5194/gmd-15-6695-2022
- A new and inexpensive non-bit-for-bit solution reproducibility test based on time step convergence (TSC1.0) H. Wan et al. 10.5194/gmd-10-537-2017
- Ensemble-based statistical verification of INM RAS Earth system model M. Tarasevich et al. 10.1515/rnam-2023-0014
- Towards Characterizing the Variability of Statistically Consistent Community Earth System Model Simulations D. Milroy et al. 10.1016/j.procs.2016.05.489
- Crossing the chasm: how to develop weather and climate models for next generation computers? B. Lawrence et al. 10.5194/gmd-11-1799-2018
- Ongoing solution reproducibility of earth system models as they progress toward exascale computing S. Mahajan et al. 10.1177/1094342019837341
- On Preserving Scientific Integrity for Climate Model Data in the HPC Era A. Baker 10.1109/MCSE.2021.3119509
- A Containerized Mesoscale Model and Analysis Toolkit to Accelerate Classroom Learning, Collaborative Research, and Uncertainty Quantification J. Hacker et al. 10.1175/BAMS-D-15-00255.1
- Replicability of the EC-Earth3 Earth system model under a change in computing environment F. Massonnet et al. 10.5194/gmd-13-1165-2020
- Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0) D. Milroy et al. 10.5194/gmd-11-697-2018
- Effects of Model Resolution, Physics, and Coupling on Southern Hemisphere Storm Tracks in CESM1.3 G. Meehl et al. 10.1029/2019GL084057
- An ensemble-based statistical methodology to detect differences in weather and climate model executables C. Zeman & C. Schär 10.5194/gmd-15-3183-2022
- A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean H. Kang et al. 10.1029/2020MS002238
1 citations as recorded by crossref.
Saved (final revised paper)
Saved (final revised paper)
Saved (preprint)
Latest update: 21 Nov 2024
Short summary
Climate simulation codes are especially complex, and their ongoing state of development requires frequent software quality assurance to both
preserve code quality and instil model confidence. To formalize and simplify this previously subjective and expensive process, we
have developed a new tool for evaluating climate consistency.
The tool has proven its utility in detecting errors in software and hardware
environments and providing rapid feedback to model developers.
Climate simulation codes are especially complex, and their ongoing state of development requires...