Quantifying the importance of interannual, interdecadal and multidecadal climate natural variabilities in the modulation of global warming rates

Meng (Matt) Wei1, Fangli Qiao1, Yongqing Guo2, Jia Deng3, Zhenya Song1, Qi Shu3 and Xiaodan Yang1, (1)First Institute of Oceanography, Ministry of Natural Resources of the People's Republic of China, Qingdao, China, (2)Marine Science and Technology College, Zhejiang Ocean University, China, (3)First Institute of Oceanography, Ministry of Natural Resources of the People's Republic of China, China
Abstract:
Despite the monotonically rising greenhouse gas emission, global warming rate changes again and again, especially the slowdown during 1998-2013, challenging the current global temperature change mechanisms. Recently, different-scale natural climate variabilities have been individually recognized as the potential causes of global warming rate change, particularly the recent warming slowdown, but disagreements still exist on their relative importance. Here we quantify the contribution of interannual, interdecadal and multidecadal variabilities (IAV, IDV and MDV) in modulating the global warming rate during the period 1850-2017 via decomposing the global mean temperature timeseries derived from 12 datasets into several quasi-periodic fluctuations and a monotonical secular trend (ST) using the ensemble empirical mode decomposition method. Our results show that the IAV, IDV and MDV dominate the global warming rate change together, rather than one-scale variability alone. For example, during 1998-2013 both the IAV and IDV present obvious negative trends and combine to cut 59 ± 22% of global mean surface temperature (GMST) and 65 ± 38% of sea surface temperature (SST) positive trends which are caused by the steadily warming ST and the warming phase of MDV, thus causing an apparent warming slowdown during this period. Furthermore, we illustrate that the IAV, IDV and MDV mainly originate from the El Niño-Southern oscillation (ENSO), Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO), respectively. Our work partly reconciles the controversy over the importance of different-scale natural variabilities, and provides some insights for climate change attribution and prediction research.