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dc.contributor.author
Schwalm, Christopher R.
dc.contributor.author
Huntinzger, Deborah N.
dc.contributor.author
Michalak, Anna M.
dc.contributor.author
Fisher, Joshua B.
dc.contributor.author
Kimball, John S.
dc.contributor.author
Mueller, Brigitte
dc.contributor.author
Zhang, Ke
dc.contributor.author
Zhang, Yongqiang
dc.date.accessioned
2018-04-27T06:20:29Z
dc.date.available
2017-06-10T19:41:04Z
dc.date.available
2018-04-27T06:20:29Z
dc.date.issued
2013
dc.identifier.issn
1748-9326
dc.identifier.issn
1748-9318
dc.identifier.other
10.1088/1748-9326/8/2/024028
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/69986
dc.identifier.doi
10.3929/ethz-b-000069986
dc.description.abstract
Confrontation of climate models with observationally-based reference datasets is widespread and integral to model development. These comparisons yield skill metrics quantifying the mismatch between simulated and reference values and also involve analyst choices, or meta-parameters, in structuring the analysis. Here, we systematically vary five such meta-parameters (reference dataset, spatial resolution, regridding approach, land mask, and time period) in evaluating evapotranspiration (ET) from eight CMIP5 models in a factorial design that yields 68 700 intercomparisons. The results show that while model–data comparisons can provide some feedback on overall model performance, model ranks are ambiguous and inferred model skill and rank are highly sensitive to the choice of meta-parameters for all models. This suggests that model skill and rank are best represented probabilistically rather than as scalar values. For this case study, the choice of reference dataset is found to have a dominant influence on inferred model skill, even larger than the choice of model itself. This is primarily due to large differences between reference datasets, indicating that further work in developing a community-accepted standard ET reference dataset is crucial in order to decrease ambiguity in model skill.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Institute of Physics
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/
dc.subject
Climate models
en_US
dc.subject
Model validation
en_US
dc.subject
Evapotranspiration
en_US
dc.subject
CMIP5
en_US
dc.title
Sensitivity of inferred climate model skill to evaluation decisions: A case study using CMIP5 evapotranspiration
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 3.0 Unported
dc.date.published
2013-05-23
ethz.journal.title
Environmental Research Letters
ethz.journal.volume
8
en_US
ethz.journal.issue
2
en_US
ethz.journal.abbreviated
Environ. res. lett.
ethz.pages.start
024028
en_US
ethz.size
9 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
005253059
ethz.publication.place
Bristol, UK
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2017-06-10T19:43:59Z
ethz.source
ECIT
ethz.identifier.importid
imp593650d793a0845736
ethz.ecitpid
pub:110867
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-17T08:14:57Z
ethz.rosetta.lastUpdated
2018-08-03T06:47:51Z
ethz.rosetta.versionExported
true
ethz.COinS
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