期刊
JOURNAL OF CLIMATE
卷 22, 期 13, 页码 3540-3557出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/2008JCLI2533.1
关键词
-
资金
- Joint Defra and MoD Programme [GA01101 (MoD), CBC/2B/0417 Annex C5]
- U.K. Natural Environment Research Council (NERC)
- RAPID Directed Programme
- ESRC [ES/G021694/1] Funding Source: UKRI
- Economic and Social Research Council [ES/G021694/1] Funding Source: researchfish
- Natural Environment Research Council [NER/J/S/2002/00737] Funding Source: researchfish
Global climate models (GCMs) contain imprecisely defined parameters that account, approximately, for subgrid-scale physical processes. The response of a GCM to perturbations in its parameters, which is crucial for quantifying uncertainties in simulations of climate change, can-in principle-be assessed by simulating the GCM many times. In practice, however, such perturbed physics'' ensembles are small because GCMs are so expensive to simulate. Statistical tools can help in two ways. First, they can be used to combine ensembles from different but related experiments, increasing the effective number of simulations. Second, they can be used to describe the GCM's response in ways that cannot be extracted directly from the ensemble(s). The authors combine two experiments to learn about the response of the Hadley Centre Slab Climate Model version 3 (HadSM3) climate sensitivity to 31 model parameters. A Bayesian statistical framework is used in which expert judgments are required to quantify the relationship between the two experiments; these judgments are validated by detailed diagnostics. The authors identify the entrainment rate coefficient of the convection scheme as the most important single parameter and find that this interacts strongly with three of the large-scale-cloud parameters.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据