Articles | Volume 6, issue 5
https://doi.org/10.5194/gmd-6-1447-2013
© Author(s) 2013. 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-6-1447-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
10 Sep 2013
Development and technical paper |
| 10 Sep 2013
An efficient method to generate a perturbed parameter ensemble of a fully coupled AOGCM without flux-adjustment
P. J. Irvine
Institute for Advanced Sustainability Studies IASS, Potsdam, Germany
L. J. Gregoire
School of Geographical Sciences, University of Bristol, UK
D. J. Lunt
School of Geographical Sciences, University of Bristol, UK
P. J. Valdes
School of Geographical Sciences, University of Bristol, UK
Viewed
Total article views: 7,118 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Feb 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,050 | 1,756 | 312 | 7,118 | 340 | 383 |
- HTML: 5,050
- PDF: 1,756
- XML: 312
- Total: 7,118
- BibTeX: 340
- EndNote: 383
Total article views: 6,263 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 10 Sep 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 4,689 | 1,292 | 282 | 6,263 | 321 | 377 |
- HTML: 4,689
- PDF: 1,292
- XML: 282
- Total: 6,263
- BibTeX: 321
- EndNote: 377
Total article views: 855 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Feb 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 361 | 464 | 30 | 855 | 19 | 6 |
- HTML: 361
- PDF: 464
- XML: 30
- Total: 855
- BibTeX: 19
- EndNote: 6
Cited
15 citations as recorded by crossref.
- GREB-ISM v1.0: A coupled ice sheet model for the Globally Resolved Energy Balance model for global simulations on timescales of 100 kyr Z. Xie et al. https://doi.org/10.5194/gmd-15-3691-2022
- How to reduce long-term drift in present-day and deep-time simulations? M. Brunetti & C. Vérard https://doi.org/10.1007/s00382-017-3883-7
- Palaeogeographic controls on climate and proxy interpretation D. Lunt et al. https://doi.org/10.5194/cp-12-1181-2016
- Empirical Run‐Time Bias Correction for Antarctic Regional Climate Projections With a Stretched‐Grid AGCM G. Krinner et al. https://doi.org/10.1029/2018MS001438
- Mid-latitude continental temperatures through the early Eocene in western Europe G. Inglis et al. https://doi.org/10.1016/j.epsl.2016.12.009
- Key factors governing uncertainty in the response to sunshade geoengineering from a comparison of the GeoMIP ensemble and a perturbed parameter ensemble P. Irvine et al. https://doi.org/10.1002/2013JD020716
- Calibrating climate models using inverse methods: case studies with HadAM3, HadAM3P and HadCM3 S. Tett et al. https://doi.org/10.5194/gmd-10-3567-2017
- A Caveat Note on Tuning in the Development of Coupled Climate Models D. Dommenget & M. Rezny https://doi.org/10.1002/2017MS000947
- Global climate system response to SOFIA Antarctic meltwater in HadCM3-M2.1 A. Mistry et al. https://doi.org/10.5194/tc-19-6989-2025
- Reducing climate model biases by exploring parameter space with large ensembles of climate model simulations and statistical emulation S. Li et al. https://doi.org/10.5194/gmd-12-3017-2019
- A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 2: global performance and future changes K. Yamazaki et al. https://doi.org/10.1007/s00382-020-05608-5
- ENSO probability forecasting by diffusing multi-intelligent models B. Mu et al. https://doi.org/10.1016/j.ocemod.2026.102838
- Climate change is an important predictor of extinction risk on macroevolutionary timescales C. Malanoski et al. https://doi.org/10.1126/science.adj5763
- Identifying sensitive ranges in global warming precipitation change dependence on convective parameters D. Bernstein & J. Neelin https://doi.org/10.1002/2016GL069022
- An Objective Approach to Generating Multi-Physics Ensemble Precipitation Forecasts Based on the WRF Model C. Shen et al. https://doi.org/10.1007/s13351-020-9198-3
15 citations as recorded by crossref.
- GREB-ISM v1.0: A coupled ice sheet model for the Globally Resolved Energy Balance model for global simulations on timescales of 100 kyr Z. Xie et al. https://doi.org/10.5194/gmd-15-3691-2022
- How to reduce long-term drift in present-day and deep-time simulations? M. Brunetti & C. Vérard https://doi.org/10.1007/s00382-017-3883-7
- Palaeogeographic controls on climate and proxy interpretation D. Lunt et al. https://doi.org/10.5194/cp-12-1181-2016
- Empirical Run‐Time Bias Correction for Antarctic Regional Climate Projections With a Stretched‐Grid AGCM G. Krinner et al. https://doi.org/10.1029/2018MS001438
- Mid-latitude continental temperatures through the early Eocene in western Europe G. Inglis et al. https://doi.org/10.1016/j.epsl.2016.12.009
- Key factors governing uncertainty in the response to sunshade geoengineering from a comparison of the GeoMIP ensemble and a perturbed parameter ensemble P. Irvine et al. https://doi.org/10.1002/2013JD020716
- Calibrating climate models using inverse methods: case studies with HadAM3, HadAM3P and HadCM3 S. Tett et al. https://doi.org/10.5194/gmd-10-3567-2017
- A Caveat Note on Tuning in the Development of Coupled Climate Models D. Dommenget & M. Rezny https://doi.org/10.1002/2017MS000947
- Global climate system response to SOFIA Antarctic meltwater in HadCM3-M2.1 A. Mistry et al. https://doi.org/10.5194/tc-19-6989-2025
- Reducing climate model biases by exploring parameter space with large ensembles of climate model simulations and statistical emulation S. Li et al. https://doi.org/10.5194/gmd-12-3017-2019
- A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 2: global performance and future changes K. Yamazaki et al. https://doi.org/10.1007/s00382-020-05608-5
- ENSO probability forecasting by diffusing multi-intelligent models B. Mu et al. https://doi.org/10.1016/j.ocemod.2026.102838
- Climate change is an important predictor of extinction risk on macroevolutionary timescales C. Malanoski et al. https://doi.org/10.1126/science.adj5763
- Identifying sensitive ranges in global warming precipitation change dependence on convective parameters D. Bernstein & J. Neelin https://doi.org/10.1002/2016GL069022
- An Objective Approach to Generating Multi-Physics Ensemble Precipitation Forecasts Based on the WRF Model C. Shen et al. https://doi.org/10.1007/s13351-020-9198-3
Saved (final revised paper)
Latest update: 19 Oct 2026
