Abstract:

China’s regional low temperature events were studied with multi-model ensembles based on CMIP5 daily minimum temperature data. China’s regional low temperature events were recognized with historical data. Results show that multi-model ensembles undervalue the change tendency of China’s regional low temperature events, but the temporal change with multi-model ensembles shows same weaken tendency as the observation, the result is also more stable than any single model, and the spatial distribution of China’s regional low temperature events is very similar as the observation. Furthermore, China’s regional low temperature events under different GHG emission scenarios (RCP2.6, RCP4.5, RCP8.5) were projected. Results show that all indices are decreasing slowly under RCP2.6 scenario. Under RCP4.5 and RCP8.5 scenarios, all indices have marked drop trends from early stage to late stage, but the drop trends of all indices under RCP8.5 is more sharply than that under RCP4.5. GHG emissions may play an important role on intensity and frequency of China’s regional low temperature events, but have little influence on the spatial distribution.

Key words: China’s regional low temperature events, multi-model ensemble, simulation and projection, temporal and spatial change