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In this study, we used historical simulations from 34 CMIP5 CGCMs, which are forced by the observed history of greenhouse gases, aerosol concentrations, solar radiation, volcanic eruptions, and other climate forcings (all-forcing experiment; Taylor et al., 2012). Some of the models have more than one ensemble member available and only Run 1 from each model was used. To compare the models’ simulations at the same horizontal resolution, we interpolated monthly mean variables, including precipitation and horizontal wind, into a regular grid of 2.5° × 2.5° by the bilinear interpolation method. The period from 1900 to 2005 was used to examine the interannual variation. We also examined the period from 1979 to 2005, and the main results were similar. Table 1 lists the main information of these models, including the host centers and the atmospheric models’ resolutions. More details on the models and experiments can be found at http://cmip-pcmdi.llnl.gov/cmip5/availability.html.
Model Lat. × Lon. Host center/country ACCESS1.0 145 × 192 Commonwealth Scientific and Industrial Research
Organization (CSIRO) and Bureau of Meteorology
(BoM)/AustraliaACCESS1.3 145 × 192 Commonwealth Scientific and Industrial Research
Organization (CSIRO) and Bureau of Meteorology
(BoM)/AustraliaBCC_CSM1.1(m) 160 × 320 Beijing Climate Center/China BCC_CSM1.1 64 × 128 Beijing Climate Center/China BNU-ESM 64 × 128 Beijing Normal University/China CanESM2 64 × 128 Canadian Centre for Climate Modelling and
Analysis/CanadaCCSM4 192 × 288 National Center for Atmospheric Research/USA CESM1(CAM5) 192 × 288 National Center for Atmospheric Research/USA CMCC-CMS 96 × 192 Centro Euro-Mediterraneo sui Cambiamenti
Climatici/ItalyCMCC-CM 240 × 480 Centro Euro-Mediterraneo sui Cambiamenti
Climatici/ItalyCNRM-CM5 128 × 256 Centre National de Recherches Météorologiques,
Centre Européen de Recherche et de Formation
Avancée en Calcul Scientifique/FranceCSIRO Mk3.6.0 96 × 192 Commonwealth Scientific and Industrial Research
Organization/Queensland Climate Change Centre of
Excellence/AustraliaFGOALS-g2 60 × 128 Institute of Atmospheric Physics, Chinese Academy
of Sciences/ChinaFGOALS-s2 108 × 128 Institute of Atmospheric Physics, Chinese Academy
of Sciences/ChinaFIO-ESM 64 × 128 The First Institute of Oceanography, SOA/China GFDL CM3 90 × 144 Geophysical Fluid Dynamics Laboratory/USA GFDL-ESM2G 90 × 144 Geophysical Fluid Dynamics Laboratory/USA GFDL-ESM2M 90 × 144 Geophysical Fluid Dynamics Laboratory/USA GISS-E2-H 90 × 144 NASA/GISS (Goddard Institute for Space Studies)/USA GISS-E2-R 90 × 144 NASA/GISS (Goddard Institute for Space Studies)/USA HadGEM2-CC 145 × 192 Met Office Hadley Centre/UK HadGEM2-ES 145 × 192 Met Office Hadley Centre/UK INM-CM4.0 120 × 180 Russian Academy of Sciences, Institute of Numerical
Mathematics/RussiaIPSL-CM5A-LR 96 × 96 Institut Pierre Simon Laplace/France IPSL-CM5A-MR 143 × 144 Institut Pierre Simon Laplace/France IPSL-CM5B-LR 96 × 96 Institut Pierre Simon Laplace/France MIROC-ESM-CHEM 64 × 128 Atmosphere and Ocean Research Institute, National
Institute for Environmental Studies, and Japan
Agency for Marine-Earth Science and Technology/JapanMIROC-ESM 64 × 128 Atmosphere and Ocean Research Institute, National
Institute for Environmental Studies, and Japan
Agency for Marine-Earth Science and Technology/JapanMIROC5 128 × 256 Atmosphere and Ocean Research Institute, National
Institute for Environmental Studies, and Japan
Agency for Marine-Earth Science and Technology/JapanMPI-ESM-LR 96 × 192 Max Planck Institute for Meteorology/Germany MPI-ESM-MR 96 × 192 Max Planck Institute for Meteorology/Germany MRI-CGCM3 160 × 320 Meteorological Research Institute/Japan NorESM1-ME 96 × 144 Bjerknes Centre for Climate Research, Norwegian
Meteorological Institute/NorwayNorESM1-M 96 × 144 Bjerknes Centre for Climate Research, Norwegian
Meteorological Institute/NorwayTable 1. Details of the 34 CMIP5 CGCMs used in this study.
We also used observational or reanalysis data. The horizontal wind was obtained from the National Centers for Environmental Prediction–Department of Energy Reanalysis-2 datasets (Kanamitsu et al., 2002). The precipitation came from the Global Precipitation Climatology Project (Adler et al., 2003). The horizontal resolutions were 2.5° in longitude and latitude and the period spanned 38 years from 1979 to 2016. Some other datasets, including the Climate Prediction Center Merged Analysis Precipitation (Xie and Arkin, 1997) and ERA-Interim (Dee et al., 2011), were also examined and showed similar results.
Our analyses focus on boreal summer (June–July–August, JJA), when the East Asian monsoon region has abundant precipitation over the year. Before the calculation of the interannual variation in observations and models, the component of time scale greater than nine years, including the long-term linear trend, was eliminated. Empirical orthogonal function (EOF) decomposition was employed to acquire the dominant modes associated with the interannual variation in the EAJ.
Model | Lat. × Lon. | Host center/country |
ACCESS1.0 | 145 × 192 | Commonwealth Scientific and Industrial Research Organization (CSIRO) and Bureau of Meteorology (BoM)/Australia |
ACCESS1.3 | 145 × 192 | Commonwealth Scientific and Industrial Research Organization (CSIRO) and Bureau of Meteorology (BoM)/Australia |
BCC_CSM1.1(m) | 160 × 320 | Beijing Climate Center/China |
BCC_CSM1.1 | 64 × 128 | Beijing Climate Center/China |
BNU-ESM | 64 × 128 | Beijing Normal University/China |
CanESM2 | 64 × 128 | Canadian Centre for Climate Modelling and Analysis/Canada |
CCSM4 | 192 × 288 | National Center for Atmospheric Research/USA |
CESM1(CAM5) | 192 × 288 | National Center for Atmospheric Research/USA |
CMCC-CMS | 96 × 192 | Centro Euro-Mediterraneo sui Cambiamenti Climatici/Italy |
CMCC-CM | 240 × 480 | Centro Euro-Mediterraneo sui Cambiamenti Climatici/Italy |
CNRM-CM5 | 128 × 256 | Centre National de Recherches Météorologiques, Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique/France |
CSIRO Mk3.6.0 | 96 × 192 | Commonwealth Scientific and Industrial Research Organization/Queensland Climate Change Centre of Excellence/Australia |
FGOALS-g2 | 60 × 128 | Institute of Atmospheric Physics, Chinese Academy of Sciences/China |
FGOALS-s2 | 108 × 128 | Institute of Atmospheric Physics, Chinese Academy of Sciences/China |
FIO-ESM | 64 × 128 | The First Institute of Oceanography, SOA/China |
GFDL CM3 | 90 × 144 | Geophysical Fluid Dynamics Laboratory/USA |
GFDL-ESM2G | 90 × 144 | Geophysical Fluid Dynamics Laboratory/USA |
GFDL-ESM2M | 90 × 144 | Geophysical Fluid Dynamics Laboratory/USA |
GISS-E2-H | 90 × 144 | NASA/GISS (Goddard Institute for Space Studies)/USA |
GISS-E2-R | 90 × 144 | NASA/GISS (Goddard Institute for Space Studies)/USA |
HadGEM2-CC | 145 × 192 | Met Office Hadley Centre/UK |
HadGEM2-ES | 145 × 192 | Met Office Hadley Centre/UK |
INM-CM4.0 | 120 × 180 | Russian Academy of Sciences, Institute of Numerical Mathematics/Russia |
IPSL-CM5A-LR | 96 × 96 | Institut Pierre Simon Laplace/France |
IPSL-CM5A-MR | 143 × 144 | Institut Pierre Simon Laplace/France |
IPSL-CM5B-LR | 96 × 96 | Institut Pierre Simon Laplace/France |
MIROC-ESM-CHEM | 64 × 128 | Atmosphere and Ocean Research Institute, National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology/Japan |
MIROC-ESM | 64 × 128 | Atmosphere and Ocean Research Institute, National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology/Japan |
MIROC5 | 128 × 256 | Atmosphere and Ocean Research Institute, National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology/Japan |
MPI-ESM-LR | 96 × 192 | Max Planck Institute for Meteorology/Germany |
MPI-ESM-MR | 96 × 192 | Max Planck Institute for Meteorology/Germany |
MRI-CGCM3 | 160 × 320 | Meteorological Research Institute/Japan |
NorESM1-ME | 96 × 144 | Bjerknes Centre for Climate Research, Norwegian Meteorological Institute/Norway |
NorESM1-M | 96 × 144 | Bjerknes Centre for Climate Research, Norwegian Meteorological Institute/Norway |