Extreme temperature and precipitation changes associated with four degree of global warming above pre-industrial levels

In 2012, the World Bank released a report and stated that a 4 degrees C increase in global temperature relative to the pre-industrial levels would be devastating. However, there is a lack of scientific literature on the changes in climate associated with a 4 degrees C temperature increase. Based on the daily temperature and precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we project the global terrestrial changes in the extreme values of temperature and precipitation in association with a warming of 4 degrees C above the pre-industrial levels using the Representative Concentration Pathways 8.5 (RCP8.5) scenario. The results indicated that cold extremes will decrease and warm extremes will increase. More remarkable signals in temperature extremes based on daily minimum temperature are expected, and local changes in temperature extremes generally extend beyond the natural internal variability. Significant signals in the frequency of temperature extremes appear in low latitudes, while the temperature changes of the coldest and hottest days are great in northern high latitudes. Large signal-to-noise ratios for warm extremes mainly occur in low latitudes, while those of cold extremes are not uniformly distributed. More intense and frequent heavy precipitation is also projected. Signals in high-precipitation extremes are prominent in high latitudes and usually exceed the local natural internal variability. Changes in extreme dry events are high in the extratropics and generally lie within the background noise. Relative to the 1.5 degrees C global warming scenario, there would be more violent temperature and precipitation extremes with the 4 degrees C warming level, and these extremes would pose more threats to natural and human systems. Additionally, small inter-model uncertainty occurs in the regions with remarkable signals for high precipitation-related extremes and cold days and nights, while the opposite trend is seen for extreme dry events and other temperature extremes.