Climate Indicators of Pace and Perception of Projected Changes Using CMIP5 Simulations

Abstract:

In most studies, climate change is approached by focusing on the evolution between a fixed current baseline and a future period, emphasizing stronger warming as me move further from the current climate. This long-term vision is used in order to characterize quantitatively the magnitude and expected effects of mitigation policies across the globe, but is not well suited to discuss coming generations’ experience. In this study, we propose an alternative approach that considers indicators of pace and perception of changes using projections of a Global Climate Model ensemble. First, it consists in tracking changes with a running baseline over periods of 20 years, defining the time evolution of the rate at which climate changes. Then, distributions of the following and previous 20 years are compared for each year. A 20-year baseline also enables to estimate the memory that a generation can have. We are mainly interested on mean and variability of surface air temperature and daily precipitation amounts.

Under the strongest emission scenario (RCP8.5), pace and perception will become far stronger over the 21st century, with a maximum reached around 2060. While northern high-latitudes will witness a higher temperature rise, southern mid-latitudes will witness the largest warming rate increase resulting in a tripling by the end of the 21st century. They will also show a 45%-increase of drying rate by that time. In the tropics, a 64%-increase of moistening rate is displayed and indicators of perception are at their highest value, especially in West Africa and South-East Asia. Drying regions being globally fewer than moistening ones and drying rate being weaker than moistening one, a continuous modification of the hydrological cycle is confirmed. Besides, their spatial fraction over the globe appears to remain unchanged (about 60% of regions are moistening). Only the strongest mitigation scenario (RCP2.6) leads to a global return to historical regime. This approach shows that, under strong emissions, one should be prepared for higher adaptation rates in the coming decades.