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Regional climate downscaling with prior statistical correction of the global climate forcing
Author(s) -
Colette A.,
Vautard R.,
Vrac M.
Publication year - 2012
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2012gl052258
Subject(s) - downscaling , climatology , environmental science , climate model , forcing (mathematics) , precipitation , climate change , scale (ratio) , meteorology , geology , geography , oceanography , cartography
A novel climate downscaling methodology that attempts to correct climate simulation biases is proposed. By combining an advanced statistical bias correction method with a dynamical downscaling it constitutes a hybrid technique that yields nearly unbiased, high‐resolution, physically consistent, three‐dimensional fields that can be used for climate impact studies. The method is based on a prior statistical distribution correction of large‐scale global climate model (GCM) 3‐dimensional output fields to be taken as boundary forcing of a dynamical regional climate model (RCM). GCM fields are corrected using meteorological reanalyses. We evaluate this methodology over a decadal experiment. The improvement in terms of spatial and temporal variability is discussed against observations for a past period. The biases of the downscaled fields are much lower using this hybrid technique, up to a factor 4 for the mean temperature bias compared to the dynamical downscaling alone without prior bias correction. Precipitation biases are subsequently improved hence offering optimistic perspectives for climate impact studies.