Jeong, Dae Il; St-Hilaire, André; Ouarda, Taha B. M. J. et Gachon, Philippe (2012). CGCM3 predictors used for daily temperature and precipitation downscaling in Southern Québec, Canada. Theoretical and Applied Climatology , vol. 107 , nº 3-4. pp. 389-406. DOI: 10.1007/s00704-011-0490-0.
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This study provides some guidance on the choice of predictor variables from both reanalysis products and the third version of the Canadian Coupled Global Climate Model (CGCM3) outputs for regression-based statistical downscaling models (SDMs) for climate change application in southern Québec (Canada). Twenty CGCM3 grid points and four surface observation sites in the study area were employed. Twenty-five deseasonalized predictors and four deseasonalized predictands (daily maximum and minimum temperatures, precipitation occurrence and wet day precipitation amount) were used to investigate correlation coefficients among predictors and to evaluate their predictive ability when used in a multiple linear regression (MLR) downscaling model. The basic statistical characteristics of vorticity at 1,000-, 850- and 500-hPa levels, U-component of velocity at 1,000-hPa level, temperature at 2 m (T 2) and wind direction at 1,000- and 500-hPa level of CGCM3 showed a larger difference with those of the NCEP reanalysis data. Therefore, those seven variables require high caution to be included as predictors in statistical downscaling models. Specific humidity at 1,000-, 850- and 500-hPa levels, geopotential height at 850- and 500-hPa levels and T 2 were the most sensitive predictors for future climate conditions (i.e. A1B and A2 emission scenarios). Specific humidity and geopotential height at different levels and T 2 were important explainable predictors for the daily temperatures. Mean sea level pressure, specific humidity, U and V components and divergence showed potential as predictors for daily precipitation. Spatial explained variance of MLRs between predictors of every different CGCM3 grid points and the four predictands showed large values at the CGCM3 grid points located near the observation sites, whereas relatively small values were shown at the CGCM3 grid points located more than 400 km from the sites. The explained variance of the downscaled predictands by predictors of three or four CGCM3 grid points located near the observation site produced 2–5% larger R-squares than those by predictors of the nearest grid point. The results illustrated that the use of predictors from more than one AOGCM grid points located near the observation site can increase the skill of the MLR downscaling models.
Type de document: | Article |
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Mots-clés libres: | grid point; geopotential height; specific humidity; observation site; statistical downscaling |
Centre: | Centre Eau Terre Environnement |
Date de dépôt: | 11 janv. 2021 16:05 |
Dernière modification: | 11 janv. 2021 16:05 |
URI: | https://espace.inrs.ca/id/eprint/10646 |
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