Articles | Volume 11, issue 3
https://doi.org/10.5194/cp-11-425-2015
© 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/cp-11-425-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 3: Practical considerations, relaxed assumptions, and using tree-ring data to address the amplitude of solar forcing
Department of Physical Geography, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
R. Sundberg
Division of Mathematical Statistics, Department of Mathematics, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
H. Grudd
Department of Physical Geography, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
A. Hind
Department of Physical Geography, Stockholm University, Stockholm, Sweden
Division of Mathematical Statistics, Department of Mathematics, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
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Cited
11 citations as recorded by crossref.
- Reconstructed and simulated temperature asymmetry between continents in both hemispheres over the last centuries H. Goosse https://doi.org/10.1007/s00382-016-3154-z
- Comparing CMIP6 Climate Model Simulations of Annual Global Mean Temperatures to a New Combined Data Product P. Craigmile & P. Guttorp https://doi.org/10.1029/2022EA002468
- Evaluation of simulated responses to climate forcings: a flexible statistical framework using confirmatory factor analysis and structural equation modelling – Part 1: Theory K. Lashgari et al. https://doi.org/10.5194/ascmo-8-225-2022
- The PMIP4 contribution to CMIP6 – Part 3: The last millennium, scientific objective, and experimental design for the PMIP4 past1000 simulations J. Jungclaus et al. https://doi.org/10.5194/gmd-10-4005-2017
- On Discriminating between GCM Forcing Configurations Using Bayesian Reconstructions of Late-Holocene Temperatures* M. Tingley et al. https://doi.org/10.1175/JCLI-D-15-0208.1
- Continental-scale temperature variability in PMIP3 simulations and PAGES 2k regional temperature reconstructions over the past millennium https://doi.org/10.5194/cp-11-1673-2015
- Challenges and perspectives for large‐scale temperature reconstructions of the past two millennia B. Christiansen & F. Ljungqvist https://doi.org/10.1002/2016RG000521
- Centennial-Scale Temperature Change in Last Millennium Simulations and Proxy-Based Reconstructions F. Ljungqvist et al. https://doi.org/10.1175/JCLI-D-18-0525.1
- Evaluation of simulated responses to climate forcings: a flexible statistical framework using confirmatory factor analysis and structural equation modelling – Part 2: Numerical experiment K. Lashgari et al. https://doi.org/10.5194/ascmo-8-249-2022
- Testing the consistency between changes in simulated climate and Alpine glacier length over the past millennium H. Goosse et al. https://doi.org/10.5194/cp-14-1119-2018
- Views on grand research challenges for Quaternary geology, geomorphology and environments S. Forman & G. Stinchcomb https://doi.org/10.3389/feart.2015.00047
11 citations as recorded by crossref.
- Reconstructed and simulated temperature asymmetry between continents in both hemispheres over the last centuries H. Goosse https://doi.org/10.1007/s00382-016-3154-z
- Comparing CMIP6 Climate Model Simulations of Annual Global Mean Temperatures to a New Combined Data Product P. Craigmile & P. Guttorp https://doi.org/10.1029/2022EA002468
- Evaluation of simulated responses to climate forcings: a flexible statistical framework using confirmatory factor analysis and structural equation modelling – Part 1: Theory K. Lashgari et al. https://doi.org/10.5194/ascmo-8-225-2022
- The PMIP4 contribution to CMIP6 – Part 3: The last millennium, scientific objective, and experimental design for the PMIP4 past1000 simulations J. Jungclaus et al. https://doi.org/10.5194/gmd-10-4005-2017
- On Discriminating between GCM Forcing Configurations Using Bayesian Reconstructions of Late-Holocene Temperatures* M. Tingley et al. https://doi.org/10.1175/JCLI-D-15-0208.1
- Continental-scale temperature variability in PMIP3 simulations and PAGES 2k regional temperature reconstructions over the past millennium https://doi.org/10.5194/cp-11-1673-2015
- Challenges and perspectives for large‐scale temperature reconstructions of the past two millennia B. Christiansen & F. Ljungqvist https://doi.org/10.1002/2016RG000521
- Centennial-Scale Temperature Change in Last Millennium Simulations and Proxy-Based Reconstructions F. Ljungqvist et al. https://doi.org/10.1175/JCLI-D-18-0525.1
- Evaluation of simulated responses to climate forcings: a flexible statistical framework using confirmatory factor analysis and structural equation modelling – Part 2: Numerical experiment K. Lashgari et al. https://doi.org/10.5194/ascmo-8-249-2022
- Testing the consistency between changes in simulated climate and Alpine glacier length over the past millennium H. Goosse et al. https://doi.org/10.5194/cp-14-1119-2018
- Views on grand research challenges for Quaternary geology, geomorphology and environments S. Forman & G. Stinchcomb https://doi.org/10.3389/feart.2015.00047
Saved (final revised paper)
Latest update: 04 Jun 2026
Short summary
Experiments with climate models can help to understand causes of past climate changes. We develop a statistical framework for comparing data from simulation experiments with temperature reconstructions for the last millennium. A combination of several external factors is found to explain a significant part of the observed variations, but our selection of data cannot tell which of two alternative choices of past solar forcing gives the best fit between simulations and reconstructions.
Experiments with climate models can help to understand causes of past climate changes. We...