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: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Volume 10, issue 9
Geosci. Model Dev., 10, 3567–3589, 2017
https://doi.org/10.5194/gmd-10-3567-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 3567–3589, 2017
https://doi.org/10.5194/gmd-10-3567-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 28 Sep 2017

Development and technical paper | 28 Sep 2017

Calibrating climate models using inverse methods: case studies with HadAM3, HadAM3P and HadCM3

Simon F. B. Tett et al.
Related authors  
Can downwelling far-infrared radiances over Antarctica be estimated from mid-infrared information?
Christophe Bellisario, Helen E. Brindley, Simon F. B. Tett, Rolando Rizzi, Gianluca Di Natale, Luca Palchetti, and Giovanni Bianchini
Atmos. Chem. Phys., 19, 7927–7937, https://doi.org/10.5194/acp-19-7927-2019,https://doi.org/10.5194/acp-19-7927-2019, 2019
Short summary
Glacier change along West Antarctica's Marie Byrd Land Sector and links to inter-decadal atmosphere–ocean variability
Frazer D. W. Christie, Robert G. Bingham, Noel Gourmelen, Eric J. Steig, Rosie R. Bisset, Hamish D. Pritchard, Kate Snow, and Simon F. B. Tett
The Cryosphere, 12, 2461–2479, https://doi.org/10.5194/tc-12-2461-2018,https://doi.org/10.5194/tc-12-2461-2018, 2018
Short summary
Global evaluation of gross primary productivity in the JULES land surface model v3.4.1
Darren Slevin, Simon F. B. Tett, Jean-François Exbrayat, A. Anthony Bloom, and Mathew Williams
Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017,https://doi.org/10.5194/gmd-10-2651-2017, 2017
Using IASI to simulate the total spectrum of outgoing long-wave radiances
E. C. Turner, H.-T. Lee, and S. F. B. Tett
Atmos. Chem. Phys., 15, 6561–6575, https://doi.org/10.5194/acp-15-6561-2015,https://doi.org/10.5194/acp-15-6561-2015, 2015
Multi-site evaluation of the JULES land surface model using global and local data
D. Slevin, S. F. B. Tett, and M. Williams
Geosci. Model Dev., 8, 295–316, https://doi.org/10.5194/gmd-8-295-2015,https://doi.org/10.5194/gmd-8-295-2015, 2015
Related subject area  
Climate and Earth System Modeling
Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis
Patrick J. Bartlein and Sarah L. Shafer
Geosci. Model Dev., 12, 3889–3913, https://doi.org/10.5194/gmd-12-3889-2019,https://doi.org/10.5194/gmd-12-3889-2019, 2019
Short summary
TheDiaTo (v1.0) – a new diagnostic tool for water, energy and entropy budgets in climate models
Valerio Lembo, Frank Lunkeit, and Valerio Lucarini
Geosci. Model Dev., 12, 3805–3834, https://doi.org/10.5194/gmd-12-3805-2019,https://doi.org/10.5194/gmd-12-3805-2019, 2019
Short summary
CAM6 simulation of mean and extreme precipitation over Asia: sensitivity to upgraded physical parameterizations and higher horizontal resolution
Lei Lin, Andrew Gettelman, Yangyang Xu, Chenglai Wu, Zhili Wang, Nan Rosenbloom, Susan C. Bates, and Wenjie Dong
Geosci. Model Dev., 12, 3773–3793, https://doi.org/10.5194/gmd-12-3773-2019,https://doi.org/10.5194/gmd-12-3773-2019, 2019
Short summary
Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1
Allison C. Michaelis, Gary M. Lackmann, and Walter A. Robinson
Geosci. Model Dev., 12, 3725–3743, https://doi.org/10.5194/gmd-12-3725-2019,https://doi.org/10.5194/gmd-12-3725-2019, 2019
Short summary
The penultimate deglaciation: protocol for Paleoclimate Modelling Intercomparison Project (PMIP) phase 4 transient numerical simulations between 140 and 127 ka, version 1.0
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
Cited articles  
Bellprat, O., Kotlarski, S., Lüthi, D., and Schär, C.: Objective calibration of regional climate models, J. Geophys. Res.-Atmos., 117, d23115, https://doi.org/10.1029/2012JD018262, 2012.
Bellprat, O., Kotlarski, S., Lüthi, D., De Elía, R., Frigon, A., Laprise, R., and Schär, C.: Objective calibration of regional climate models: application over Europe and North America, J. Climate, 29, 819–838, https://doi.org/10.1175/jcli-d-15-0302.1, 2015.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, 2001.
Publications Copernicus
Download
Short summary
The paper shows it is possible to automatically calibrate the parameters in the atmospheric component of two climate models. The resulting atmosphere–ocean models are often, but not always, stable and realistic. The computational cost to do this is feasible. The implications are that it is possible to generate multiple configurations of a single model with different parameter values but which all look similar to the standard model and that the techniques could be used to calibrate other models.
The paper shows it is possible to automatically calibrate the parameters in the atmospheric...
Citation