Physics – Geophysics
Scientific paper
Jun 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009georl..3611708m&link_type=abstract
Geophysical Research Letters, Volume 36, Issue 11, CiteID L11708
Physics
Geophysics
11
Global Change: Regional Climate Change, Mathematical Geophysics: Probabilistic Forecasting (3238), Global Change: Instruments And Techniques
Scientific paper
A statistical method is developed to generate local cumulative distribution functions (CDFs) of surface climate variables from large-scale fields. Contrary to most downscaling methods producing continuous time series, our “probabilistic downscaling methods” (PDMs), named “CDF-transform”, is designed to deal with and provide local-scale CDFs through a transformation applied to large-scale CDFs. First, our PDM is compared to a reference method (Quantile-matching), and validated on a historical time period by downscaling CDFs of wind intensity anomalies over France, for reanalyses and simulations from a general circulation model (GCM). Then, CDF-transform is applied to GCM output fields to project changes in wind intensity anomalies for the 21st century under A2 scenario. Results show a decrease in wind anomalies for most weather stations, ranging from less than 1% (in the South) to nearly 9% (in the North), with a maximum in the Brittany region.
Loukos H.
Michelangeli P.-A.
Vrac Mathieu
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