| DOI: | 10.1007/s00382-011-1168-0
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| Scopus记录号: | 2-s2.0-84862983660
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| 论文题名: | Artificial neural network assisted Bayesian calibration of climate models |
| 作者: | Hauser T.; Keats A.; Tarasov L.
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| 刊名: | Climate Dynamics
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| ISSN: | 9307575
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| 出版年: | 2012
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| 卷: | 39, 期:2017-01-02 | | 起始页码: | 137
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| 结束页码: | 154
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| 语种: | 英语
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| 英文关键词: | Bayesian calibration
; Emulation
; Probabilistic climate forecasting
; Structural error
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| 英文摘要: | We demonstrate and validate a Bayesian approach to model calibration applicable to computationally expensive General Circulation Models (GCMs) that includes a posterior estimate of the intrinsic structural error of the model. Bayesian artificial neural networks (BANNs) are trained with output from a GCM and used as emulators of the full model to allow a computationally efficient Markov Chain Monte Carlo (MCMC) sampling of the posterior for the GCM parameters calibrated against seasonal climatologies of temperature, pressure, and humidity. We validate the methodology by calibrating to targets produced by a model run with added noise. We then demonstrate a calibration of five GCM parameters against an observational data set. The approach accounts for both parametric and structural uncertainties of the model as well as uncertainties associated with the observational calibration data. This enables the generation of statistically rigorous probabilistic forecasts for future climate states. All calibration experiments are performed with emulators trained using a maximum of one hundred model runs, in accord with typical resource restrictions imposed by computationally expensive models. We conclude by summarizing remaining issues to address in order to create a complete and validated operational methodology for objective calibration of computationally expensive models. © 2011 Springer-Verlag. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/55220
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| Appears in Collections: | 过去全球变化的重建
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作者单位: | Physics-Physical Oceanography, Memorial University Newfoundland, St. John's, NL A1C 5S7, Canada
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| Recommended Citation: | |
Hauser T.,Keats A.,Tarasov L.. Artificial neural network assisted Bayesian calibration of climate models[J]. Climate Dynamics,2012-01-01,39(2017-01-02)
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