A Stepwise Regression and Statistical Downscaling Approach for Projecting Temperature Variations under Multiple RCP Scenarios

With the rapid development of Central China, temperature in this region is continuously increasing. Extreme weather events (e.g., high-temperature for many consecutive days) are becoming frequent. In order to provide future theoretical guidance on direction local and prevention extreme natural disasters, daily datasets 12 meteorological stations three provinces were collected. The corresponding predictors from 25 large-scale climatic factors then screened using stepwise regression. A regression statistical downscaling (SRSD) approach was developed establish relationship. results projected by generator, probability occurrence analyzed values. indicate that China shows an increasing trend 2036 2065 2066 2095, with representative concentration pathway 4.5 (RCP4.5) scenario showing a greater increase than 8.5 (RCP8.5) scenario. Hunan Province has largest increase, followed Hubei Henan Province. average annual duration heat waves 74.7 days.