第一届未来大气科学论坛

Uneven economic impacts of climate change have been largely caused by differentiated warming rates across different geographical regions, affecting the lives of the majority of worlds’ population. Historical and future warming rates are commonly obtained from global climate models, which exhibit considerable spreads in terms of global mean and region-dependent warming rates. While the multi-model spread in global mean warming rate has been widely reported in past literature, the multi-model spread in terms of global warming pattern and its temporal evolution remain unclear. Here we diagnose the CMIP6 multi-model spread in simulated surface air temperature trend in historical and future periods under different emission scenarios, in comparison with the unforced, baseline multi-model spread in the piControl experiment. This study shows that the multi-model spread in the simulated global warming pattern depends closely on the level of warming. The simulated global warming pattern deviates substantially among CMIP6 models before 1985 and converges afterwards, as the greenhouse gases level rises and global mean warming rate accelerates. Moreover, the consistency of model-predicted future warming pattern varies by emission scenario, namely the future trajectory of GHG concentrations.. Models predict highly consistent warming patterns under the high emission scenario during the entire 21st century; whereas under low and intermediate emission scenarios, future warming patterns diverge among these models around middle of the 21st century, as the predicted concentration of carbon dioxide and other GHGs declines. Besides, such multi-model spread in the simulated local warming rate shows a delayed response in the mid-to-high latitude Southern Ocean, likely attributed to the ocean circulations and ocean-atmosphere interactions that postpone the trajectory of regional surface air temperature response to global warming. While our study detects an anthropogenic signal in the temporal evolution of multi-model consistency in the global warming pattern, the physical mechanisms underlying such varying multi-model consistency in the warming pattern merits further investigation.
 

Global Warmig Patterns, Global Warming Rate, Spatial Correlation, Multi-model Spread