Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year
    4.890
  • CiteScore value: 4.49 CiteScore
    4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 51 Scimago H
    index 51
Volume 9, issue 7
Geosci. Model Dev., 9, 2391-2406, 2016
https://doi.org/10.5194/gmd-9-2391-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 2391-2406, 2016
https://doi.org/10.5194/gmd-9-2391-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 12 Jul 2016

Development and technical paper | 12 Jul 2016

Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0)

Allison H. Baker et al.
Related authors  
Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0)
Daniel J. Milroy, Allison H. Baker, Dorit M. Hammerling, and Elizabeth R. Jessup
Geosci. Model Dev., 11, 697-711, https://doi.org/10.5194/gmd-11-697-2018,https://doi.org/10.5194/gmd-11-697-2018, 2018
Short summary
Evaluating lossy data compression on climate simulation data within a large ensemble
Allison H. Baker, Dorit M. Hammerling, Sheri A. Mickelson, Haiying Xu, Martin B. Stolpe, Phillipe Naveau, Ben Sanderson, Imme Ebert-Uphoff, Savini Samarasinghe, Francesco De Simone, Francesco Carbone, Christian N. Gencarelli, John M. Dennis, Jennifer E. Kay, and Peter Lindstrom
Geosci. Model Dev., 9, 4381-4403, https://doi.org/10.5194/gmd-9-4381-2016,https://doi.org/10.5194/gmd-9-4381-2016, 2016
Short summary
P-CSI v1.0, an accelerated barotropic solver for the high-resolution ocean model component in the Community Earth System Model v2.0
Xiaomeng Huang, Qiang Tang, Yuheng Tseng, Yong Hu, Allison H. Baker, Frank O. Bryan, John Dennis, Haohuan Fu, and Guangwen Yang
Geosci. Model Dev., 9, 4209-4225, https://doi.org/10.5194/gmd-9-4209-2016,https://doi.org/10.5194/gmd-9-4209-2016, 2016
Short summary
A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1.0)
A. H. Baker, D. M. Hammerling, M. N. Levy, H. Xu, J. M. Dennis, B. E. Eaton, J. Edwards, C. Hannay, S. A. Mickelson, R. B. Neale, D. Nychka, J. Shollenberger, J. Tribbia, M. Vertenstein, and D. Williamson
Geosci. Model Dev., 8, 2829-2840, https://doi.org/10.5194/gmd-8-2829-2015,https://doi.org/10.5194/gmd-8-2829-2015, 2015
Short summary
Related subject area  
Climate and Earth System Modeling
The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model
Salomon Eliasson, Karl Göran Karlsson, Erik van Meijgaard, Jan Fokke Meirink, Martin Stengel, and Ulrika Willén
Geosci. Model Dev., 12, 829-847, https://doi.org/10.5194/gmd-12-829-2019,https://doi.org/10.5194/gmd-12-829-2019, 2019
Short summary
The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET v1.0): an efficient and user-friendly model of city cooling
Ashley M. Broadbent, Andrew M. Coutts, Kerry A. Nice, Matthias Demuzere, E. Scott Krayenhoff, Nigel J. Tapper, and Hendrik Wouters
Geosci. Model Dev., 12, 785-803, https://doi.org/10.5194/gmd-12-785-2019,https://doi.org/10.5194/gmd-12-785-2019, 2019
Short summary
GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems
Katherine Calvin, Pralit Patel, Leon Clarke, Ghassem Asrar, Ben Bond-Lamberty, Ryna Yiyun Cui, Alan Di Vittorio, Kalyn Dorheim, Jae Edmonds, Corinne Hartin, Mohamad Hejazi, Russell Horowitz, Gokul Iyer, Page Kyle, Sonny Kim, Robert Link, Haewon McJeon, Steven J. Smith, Abigail Snyder, Stephanie Waldhoff, and Marshall Wise
Geosci. Model Dev., 12, 677-698, https://doi.org/10.5194/gmd-12-677-2019,https://doi.org/10.5194/gmd-12-677-2019, 2019
Short summary
Limitations of the 1 % experiment as the benchmark idealized experiment for carbon cycle intercomparison in C4MIP
Andrew Hugh MacDougall
Geosci. Model Dev., 12, 597-611, https://doi.org/10.5194/gmd-12-597-2019,https://doi.org/10.5194/gmd-12-597-2019, 2019
Short summary
Computing climate-smart urban land use with the Integrated Urban Complexity model (IUCm 1.0)
Roger Cremades and Philipp S. Sommer
Geosci. Model Dev., 12, 525-539, https://doi.org/10.5194/gmd-12-525-2019,https://doi.org/10.5194/gmd-12-525-2019, 2019
Short summary
Cited articles  
Baker, A. H., Xu, H., Dennis, J. M., Levy, M. N., Nychka, D., Mickelson, S. A., Edwards, J., Vertenstein, M., and Wegener, A.: A Methodology for Evaluating the Impact of Data Compression on Climate Simulation Data, in: Proceedings of the 23rd International Symposium on High-performance Parallel and Distributed Computing, HPDC '14, 203–214, 2014.
Baker, A. H., Hammerling, D. M., Levy, M. N., Xu, H., Dennis, J. M., Eaton, B. E., Edwards, J., Hannay, C., Mickelson, S. A., Neale, R. B., Nychka, D., Shollenberger, J., Tribbia, J., Vertenstein, M., and Williamson, D.: A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1.0), Geosci. Model Dev., 8, 2829–2840, https://doi.org/10.5194/gmd-8-2829-2015, 2015.
Box, G. E. P. and Draper, N. R.: Response Surfaces, Mixtures, and Ridge Analyses, Second Edition, John Wiley and Sons, 2007.
Carson, II, J. S.: Model Verification and Validation, in: Proceedings of the 2002 Winter Simulation Conference, 52–58, 2002.
Clune, T. and Rood, R.: Software Testing and Verification in Climate Model Development, IEEE Software, 28, 49–55, https://doi.org/10.1109/MS.2011.117, 2011.
Publications Copernicus
Download
Short summary
Software quality assurance is critical to detecting errors in large, complex climate simulation codes. We focus on ocean model simulation data in the context of an ensemble-based statistical consistency testing approach developed for atmospheric data. Because ocean and atmosphere models have differing characteristics, we develop a new statistical tool to evaluate ocean model simulation data that provide a simple, subjective, and systematic way to detect errors and instil model confidence.
Software quality assurance is critical to detecting errors in large, complex climate simulation...
Citation