Statistical Downscaling and Projection of Future Air Temperature Changes in Yunnan Province, China

Abstract

The SDSM was employed for downscaling of daily mean temperature of 32 meteorological stations (1954–2014) and future scenarios were generated up to 2100. The data were daily NCEP/NCAR reanalysis data and the daily mean climate model outputs for the RCP2.6, RCP4.5, and RCP8.5 scenarios from the MRI of Japan. Periodic features were obtained by wavelet analysis. The results showed the following. (1) The pattern of change and the numerical values of the air temperature could be reasonably simulated, with the average R2 between observed and generated data being 0.963 for calibration and 0.964 for validation. (2) All scenarios projected increases of different degrees of temperature in all seasons, except for spring in the 2020s. Annually, the most remarkable changes in the 2020s, 2050s, and 2080s were 0.27, 1.00, and 1.84°C, respectively. Seven dominant periods appeared under RCP4.5 and RCP8.5 from 1954 to 2100; however, an additional period appeared under RCP2.6. (3) In future periods, especially the 2020s, decreases in temperature were significantly located in the center of Yunnan under all three scenarios, whereas there were distinct increases in northwest and southeast Yunnan in most future periods. Besides, the RCP8.5 scenario showed the greatest increase in the 2080s.