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

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Journal of Meteorological Research 2018年第3期32卷 337-350页

作者： Yajie QI Zhongwei YAN Cheng QIAN Ying SUN CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of Sciences(CAS)Beijing 100029 Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089 University of Chinese Academy of Sciences Beijing 100049 Laboratory for Climate Studies National Climate CenterChina Meteorological AdministrationBeijing 100081 Joint Center for Global Change Studies Beijing Normal UniversityBeijing 100875

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℃(90% uncertainty range from 0.30 to 0.58℃) for global land, 0.48℃(90% uncertainty range from 0.29 to 0.67℃) for the Northern Hemispheric land(NL), and 0.29℃(90% uncertainty range from 0.23 to 0.35℃) 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.

关键词： near-term projection multidecadal variability multi-model ensemble method ensemble empirical mode decomposition(EEMD) Bayesian model averaging(BMA)

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