Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/13771
An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment
Title: An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment
Authors: Gutiérrez, José ManuelMaraun, DouglasWidmann, MartinHuth, RadanHertig, ElkeBenestad, R.Roessler, O.Wibig, JoannaWilcke, R.Kotlarski, SvenSan-Martín, DanielHerrera García, SixtoBedia, JoaquínCasanueva, AnaManzanas, RodrigoIturbide, M.Vrac, M.Dubrovsky, MartinRibalaygua Batalla, JaimePórtoles, JavierRäty, O.Räisänen, J.Hingray, B.Raynaud, D.Casado Calle, María JesúsAutor AEMETRamos Calzado, PetraAutor AEMETZerenner, T.Turco, MarcoBosshard, T.Štěpánek, P.Bartholy, JuditPongracz, R.Keller, Daphne E.Fischer, Andreas M.Cardoso, Rita M.Soares, Pedro M. M.Czernecki, B.Pagé, C.
Keywords: Downscaling; Bias adjustment; Perfect prognosis; Weather gen33 erators; Model output statistics; CORDEX; Reproducibility
Issue Date: 2019
Publisher: Wiley; Royal Meteorological Society
Citation: International Journal of Climatology. 2019, 39(9), p. 3750-3785
Publisher version: https://doi.org/10.1002/joc.5462
Abstract: VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process-based, etc.). Here we describe the participating methods and first results from the first experiment, using “perfect” reanalysis (and reanalysis-driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques.
Sponsorship : J.M.G. and S.H. acknowledge partial funding from MULTI-SDM project (MINECO/FEDER, CGL2015-66583-R). B.H. and D.R. acknowledge COMPLEX project (FP7-ENV-2012, No: 308601). M.T. was supported by HOPE project (MINECO, CGL2014-52571-R).
URI: http://hdl.handle.net/20.500.11765/13771
ISSN: 0899-8418
1097-0088
Appears in Collections:Artículos científicos 2019-2022


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