Journal article
Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?
- Abstract:
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Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC) methods, which directly adjust the model outputs of interest (e.g. precipitation) according to the available local observations, to more complex Perfect Prognosis (PP) ones, which indirectly derive...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Accepted manuscript, pdf, 2.8MB)
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- Publisher copy:
- 10.1007/s00382-017-3668-z
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Authors
Funding
+ MULTI-SDM
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Funding agency for:
Gutiérrez, J
Grant:
CGL2015-66583-R, MINECO/FEDER
Bibliographic Details
- Publisher:
- Springer Verlag Publisher's website
- Journal:
- Climate Dynamics Journal website
- Volume:
- 50
- Issue:
- 3-4
- Pages:
- 1161-1176
- Publication date:
- 2017-04-07
- Acceptance date:
- 2017-03-28
- DOI:
- EISSN:
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1432-0894
- ISSN:
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0930-7575
- Source identifiers:
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690824
Item Description
- Keywords:
- Pubs id:
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pubs:690824
- UUID:
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uuid:82f4069c-8dec-4a63-9426-0c06e4b61fa3
- Local pid:
- pubs:690824
- Deposit date:
- 2017-04-26
Terms of use
- Copyright holder:
- © Springer-Verlag Berlin Heidelberg 2017
- Copyright date:
- 2017
- Notes:
- This is the author accepted manuscript following peer review version of the article. The final version is available online from Springer Verlag at: 10.1007/s00382-017-3668-z
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