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Impacts of climate change may depend more on changes in mean daily minimum temperature (Tmin) or maximum temperature (Tmax) than on average temperature (Tavg). In this study, we apply a statistical downscaling model (SDSM) for estimating the average length of spells with temperature values greater than Tmax = 30°C (ALS30), Tmax, and diurnal temperature range (DTR) for the present period (1961–1990) and the future period (2071–2099) climate conditions. The outputs of two GCMS (HadCM3 and CGCM3) are used to show the potential applicability of SDSM. Scenarios A2, A1B and B2 are used by the SDSM to construct climate scenario information over the Shikoku region. The results showed that: (1) The SDSM model is able to capture the major part of the temperature change signals, with a plausible climatic regime for higher warming; (2) From June to August, the average DTR changes in northern Shikoku would be positive; but in southern Shikoku, the changes would be negative under A2, A1B, and B2 scenarios using HadCM3 and CGCM3. The most important finding is that the DTR trend will be different at the local scale and these results highlight the importance of separately considering projections for Tmin and Tmax, when evaluating climate change impact for hydrological and agricultural applications.

Introduction of daily minimum and maximum temperature change signals in the Shikoku region using the statistical downscaling method by GCMs