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Journal article

Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

Abstract:

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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Publisher copy:
10.1007/s00382-017-3668-z

Authors


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Institution:
University of Oxford
Oxford college:
University College
Role:
Author
More from this funder
Funding agency for:
Gutiérrez, J
Grant:
CGL2015-66583-R, MINECO/FEDER
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:
1432-0894
ISSN:
0930-7575
Source identifiers:
690824
Keywords:
Pubs id:
pubs:690824
UUID:
uuid:82f4069c-8dec-4a63-9426-0c06e4b61fa3
Local pid:
pubs:690824
Deposit date:
2017-04-26

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