Projection of multi-site daily temperatures over the Montréal area, Canada

Abstract

This study presents a post-adjustment procedure for a multivariate multi-site statistical downscaling model (MMSDM) which can simultaneously downscale multiple predictands at multiple observation sites by combining multivariate multiple linear regression and the stochastic randomization procedure. In the post-adjustment procedure, bias and determinant adjustment factors correct the systematic bias on the downscaled series using atmosphere-ocean coupled global climate model (AOGCM) predictors, and prevent the propagation of systematic error to the projected future predictands. The MMSDM with the post-adjustment procedure is applied to project a realistic series of 2 predictands (daily Tmax and Tmin) for 10 observation sites in the region of Montréal (southern Québec, Canada). The Canadian CGCM3 reference outputs (1961-2000) and future outputs under the A1B and A2 SRES scenarios (2061-2100) were employed as AOGCM predictors. On average over the 10 observation sites, the monthly means of the daily Tmax and Tmin were increased by 2.0-4.7 and 2.7-5.4°C while seasonal 90th percentile of daily Tmax and 10th percentile of daily Tmin (Tmax90 and Tmin10) were increased by 2.1-4.5 and 2.7-5.8°C for the A1B and A2 scenarios with the MMSDM, respectively. Future Tmax and Tmin series showed higher increases in winter than in the other seasons, as anticipated from AOGCMs or regional climate models over the same area. The average diurnal temperature ranges of future series suggest small increases in spring and autumn. Finally, the projected series yielded frost seasons that are 23 and 28 d shorter, whereas 23 and 27 more days are projected for the length of the growing season than in the present-day climate series. © Inter-Research 2013.