摘要

The Coupled Model Inter-comparison Project Phase 5 (CMIP5) contains a group of state-of-the-art climate models and represents the highest level of climate simulation thus far. However, these models significantly overestimated global mean surface temperature (GMST) during 2006-2014. Based on the ensemble empirical mode decomposition (EEMD) method, the long term change of the observed GMST time series of HadCRUT4 records during 1850-2014 was analyzed, then the simulated GMST by 33 CMIP5 climate models was assessed. The possible reason that climate models failed to project the recent global warming hiatus was revealed. Results show that during 1850-2014 the GMST on a centennial timescale rose with fluctuation, dominated by the secular trend and the multi-decadal variability (MDV). The secular trend was relatively steady beginning in the early 20th century, with an average warming rate of 0.0883A degrees C/decade over the last 50 years. While the MDV (with a similar to 65-year cycle) showed 2.5 multi-decadal waves during 1850-2014, which deepened and steepened with time, the alarming warming over the last quarter of the 20th century was a result of the concurrence of the secular warming trend and the warming phase of the MDV, both of which accounted one third of the temperature increase during 1975-1998. Recently the slowdown of global warming emerged as the MDV approached its third peak, leading to a reduction in the warming rate. A comparative analysis between the GMST time series derived from HadCRUT4 records and 33 CMIP5 model outputs reveals that the GMSTs during the historical simulation period of 1850-2005 can be reproduced well by models, especially on the accelerated global warming over the last quarter of 20th century. However, the projected GMSTs and their linear trends during 2006-2014 under the RCP4.5 scenario were significantly higher than observed. This is because the CMIP5 models confused the MDV with secular trend underlying the GMST time series, which results in a fast secular trend and an improper MDV with irregular phases and small amplitudes. This implies that the role of atmospheric CO2 in global warming may be overestimated, while the MDV which is an interior oscillation of the climate system may be underestimated, which should be related to insufficient understanding of key climatic internal dynamic processes. Our study puts forward an important criterion for the new generation of climate models: they should be able to simulate both the secular trend and the MDV of GMST.