Articles | Volume 6, issue 5
https://doi.org/10.5194/gmd-6-1715-2013
© 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-6-1715-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
The potential of an observational data set for calibration of a computationally expensive computer model
D. J. McNeall
Met Office Hadley Centre, Exeter, UK
P. G. Challenor
College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
J. R. Gattiker
Los Alamos National Laboratory, Los Alamos, New Mexico, NM 87545, USA
E. J. Stone
School of Geographical Sciences, University of Bristol, Bristol, UK
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- Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode A. Beddows et al. 10.1021/acs.est.6b05873
- Reducing climate model biases by exploring parameter space with large ensembles of climate model simulations and statistical emulation S. Li et al. 10.5194/gmd-12-3017-2019
- Correcting a bias in a climate model with an augmented emulator D. McNeall et al. 10.5194/gmd-13-2487-2020
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- Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques D. Pollard et al. 10.5194/gmd-9-1697-2016
- Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties W. Chang et al. 10.5194/gmd-7-1933-2014
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- Impacts of Land Cover and Soil Texture Uncertainty on Land Model Simulations Over the Central Tibetan Plateau J. Li et al. 10.1029/2018MS001377
- Quantifying Spatio-Temporal Boundary Condition Uncertainty for the North American Deglaciation J. Salter et al. 10.1137/21M1409135
- Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking W. Chang et al. 10.1007/s00382-018-4294-0
- Tuning without over-tuning: parametric uncertainty quantification for the NEMO ocean model D. Williamson et al. 10.5194/gmd-10-1789-2017
- Parameter optimization for carbon and water fluxes in two global land surface models based on surrogate modelling J. Li et al. 10.1002/joc.5428
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- Identifying and removing structural biases in climate models with history matching D. Williamson et al. 10.1007/s00382-014-2378-z
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- The impact of structural error on parameter constraint in a climate model D. McNeall et al. 10.5194/esd-7-917-2016
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