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dc.contributor.author
Solman, Silvina Alicia
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dc.date.available
2017-12-01T20:02:11Z
dc.date.issued
2016-04
dc.identifier.citation
Solman, Silvina Alicia; Systematic temperature and precipitation biases in the CLARIS-LPB ensemble simulations over South America and possible implications for climate projections; Inter-Research; Climate Research; 68; 2-3; 4-2016; 117-136
dc.identifier.issn
0936-577X
dc.identifier.uri
http://hdl.handle.net/11336/29502
dc.description.abstract
Within the framework of the CLARIS-LPB EU Project, a suite of 7 coordinated Regional Climate Model (RCM) simulations over South America driven by both the ERA-Interim reanalysis and a set of Global Climate Models (GCMs) were evaluated. The systematic biases in simulating monthly mean temperature and precipitation from the 2 sets of RCM simulations were identified. The Climate Research Unit dataset was used as a reference. The systematic model errors were more dependent on the RCMs than on the driving GCMs. Most RCMs showed a systematic temperature overestimation and precipitation underestimation over the La Plata Basin region. Model biases were not invariant, but a temperature-dependent temperature bias and a precipitation-dependent precipitation bias were apparent for the region, with the warm bias amplified for warm months and the dry bias amplified for wet months. In a climate change scenario, the relationship between model bias behaviour and the projected climate change for each individual model revealed that the models with the largest temperature bias amplification projected the largest warming and the models with the largest dry bias amplification projected the smallest precipitation increase, suggesting that models’ bias behaviour may affect the future climate projections. After correcting model biases by means of a quantile-based mapping bias correction method, projected temperature changes were systematically reduced, and projected precipitation changes were systematically increased. Though applying bias correction methodologies to projected climate conditions is controversial, this study demonstrates that bias correction methodologies should be considered in order to better interpret climate change signals.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Inter-Research
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dc.rights
info:eu-repo/semantics/embargoedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Regional Climte Models
dc.subject
Regional Climate Change
dc.subject
South America
dc.subject
Systematic Bias
dc.subject.classification
Meteorología y Ciencias Atmosféricas
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dc.subject.classification
Ciencias de la Tierra y relacionadas con el Medio Ambiente
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Systematic temperature and precipitation biases in the CLARIS-LPB ensemble simulations over South America and possible implications for climate projections
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-06-07T20:47:35Z
dc.journal.volume
68
dc.journal.number
2-3
dc.journal.pagination
117-136
dc.journal.pais
Alemania
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dc.description.fil
Fil: Solman, Silvina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina
dc.journal.title
Climate Research
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dc.rights.embargoDate
2021-05-01
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3354/cr01362
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.int-res.com/abstracts/cr/v68/n2-3/p117-136/
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