Near-Term Projections of Global and Regional Land Mean Temperature Changes Considering Both the Secular Trend and Multidecadal Variability

Near-term climate projections are needed by policymakers; however, these projections are difficult because internally generated climate variations need to be considered. In this study, temperature change scenarios in the near-term period 2017–35 are projected at global and regional scales based on a refined multi-model ensemble approach that considers both the secular trend (ST) and multidecadal variability (MDV) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. The ST and MDV components are adaptively extracted from each model simulation by using the ensemble empirical mode decomposition (EEMD) filter, reconstructed via the Bayesian model averaging (BMA) method for the historical period 1901–2005, and validated for 2006–16. In the simulations of the " medium” representative concentration pathways scenario during 2017–35, the MDV-modulated temperature change projected via the refined approach displays an increase of 0.44°C (90% uncertainty range from 0.30 to 0.58°C) for global land, 0.48°C (90% uncertainty range from 0.29 to 0.67°C) for the Northern Hemispheric land (NL), and 0.29°C (90% uncertainty range from 0.23 to 0.35°C) for the Southern Hemispheric land (SL). These increases are smaller than those projected by the conventional arithmetic mean approach. The MDV enhances the ST in 13 of 21 regions across the world. The largest MDV-modulated warming effect (46%) exists in central America. In contrast, the MDV counteracts the ST in NL, SL, and eight other regions, with the largest cooling effect (220%) in Alaska.