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Geophysical Research Letters
Supporting Information for
Projected changes of wintertime synoptic-scale transient eddy activities in the East
Asian eddy-driven jet from CMIP5 experiments
Chuliang Xiao* and Yaocun Zhang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
*Current affiliation: Cooperative Institute for Limnology and Ecosystems Research, University of Michigan, Ann Arbor,
Michigan, USA
Contents of this file
Figures S1 to S4
Tables S1
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Table S1.
CMIP5 models used in the study
No. Model
1 BCC-CSM-1.1
2 BCC-CSM-1.1m
3 BNU-ESM
4 CanCM4
5 FGOALS-g2
6 GFDL-CM3
7 GFDL-ESM2G
8 GFDL-ESM2M
9 HadGEM-CC
10 INM-CM4
11 IPSL-CM5-LR
12 MIROC-ESM
Institute
BCC
BCC
GCESS
CCCMA
LASG-CESS
GFDL
GFDL
GFDL
MOHC
INM
IPSL
MIROC
Country
China
China
China
Canada
China
USA
USA
USA
UK
Russia
France
Japan
Atmosphere
Gaussian
Gaussian
Gaussian
Gaussian
Hybrid
Gaussian
Gaussian
Gaussian
1.25
× 1.875
1.5
× 2
Hybrid
Gaussian
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13 MPI-ESM-LR MPI German Gaussian
14 NorESM1-M NCC Norway Hybrid
BCC-CSM-1.1
: Beijing Climate Center-Climate System Model version 1.1
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BCC-CSM-1.1m
: Beijing Climate Center-Climate System Model version 1.1 moderate resolution
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BNU-ESM : Beijing Normal University-Earth System Model, developed by College of Global
Change and Earth System Science (GCESS)
Grid
64 × 128
160 × 320
64 × 128
64 × 128
60 × 128
90 × 144
90 × 144
90 × 144
144 × 192
120 × 180
96 × 96
64 × 128
96 × 192
96 × 144
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CanCM4 : Canada Climate Model version 4, developed by Canadian Centre for Climate

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Modelling and Analysis (CCCMA)
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FGOASL-g2 : The Flexible Global Ocean-Atmosphere-Land System Model, Gridded Version 2,
32 developed by The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and
33 Geophysical Fluid Dynamics (LASG) -Center for Earth System Science (CESS)
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GFDL-CM3 : Geophysical Fluid Dynamics Laboratory-Coupled Model version 3
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GFDL-ESM2G : Geophysical Fluid Dynamics Laboratory-Earth System Model version 2, with
Generalized Ocean Layer Dynamics
37
GFDL-ESM2M : Geophysical Fluid Dynamics Laboratory-Earth System Model, with Modular
38 Ocean Model version 4.1
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HadGEM2-CC : Hadley Centre Global Environmental Model version 2–Carbon Cycle configuration, developed by Met Office Hadley Centre (MOHC)
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INM-CM4 : Institute of Numerical Mathematics-Coupled Model version 4
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IPSL-CM5 : L’Institut Pierre-Simon Laplace Coupled Model version 5-Low Resolution
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MIROC-ESM : Model for Interdisciplinary Research on Climate Earth System Model
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MPI-ESM-LR : Max Planck Institute Earth System Model-Low Resolution
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NorESM1-M : The Norwegian Earth System Model version 1- Moderate resolution

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Jet locations in East Asia
In East Asia, the intensity of the time-mean wind gradually decreases from the westerly jet axis to the polar-front region. The EASJ is persistent and dominant in both the time-mean and high-frequency fields. Thus, in time-mean wind field, the EAEJ can hardly be distinguished from the EASJ. Therefore, the daily or higher-frequency data should be used for a detailed description of the EAEJ seasonal variation. In previous studies, three methods are used to define upper-level jets from the perspective of jet occurrence. (This section is adapted from Xiao and Zhang, On the concurrent existence of East Asian subtropical and polar-front jets in winter, to be submitted to
Journal of Climate , 2015)
(a) Jet Occurrence Percentage (JOP) [ Koch et al.
, 2006],
When the speed is equal or larger than 30 m s -1 at one grid, a jet occurrence is defined at this gird. The jet occurrence number is counted at every grid. Then, the JOP is calculated in the following equation,
JOP =
𝐽𝑒𝑡 𝑂𝑐𝑐𝑢𝑟𝑟𝑒𝑛𝑐𝑒 𝑁𝑢𝑚𝑏𝑒𝑟
× 100%
𝐴𝑙𝑙 𝑇𝑖𝑚𝑒 𝑁𝑢𝑚𝑏𝑒𝑟
(b) Horizontal Jet Core Number (hJCN) [ Zhang et al 2008; Ren et al.
2010, 2011],
In horizontal x-y plane, a jet core occurrence is defined if one specific grid satisfies the following conditions: (1) the wind speed at this grid equal or larger than 30 m s -1 ; (2) the wind speeds at surrounding eight grids are smaller than this grid. Those procedures are applied with every time, and then the hJCN is calculated.
(c) Vertical Jet Core Number (vJCN) [ Schiemann et al.
2009; Pena-Ortiz et al.
2013]
The vJCN is defined the same as the hJCN, but in the vertical y-p plane. In this method, vJCN is counted on every vertical level.
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Figure S1.
Climatological distributions of (a) jet occurrence percentage, (b) horizontal jet core number at 300 hPa and (c) vertical jet core number (see the text above for the detailed definitions). The contours indicate the zonal winds (m s -1 ) at 300 hPa. The 3000-m orographic outline of the Tibetan Plateau is denoted by the thick solid contour. The maxima of zonal wind in the meridional direction are presented in two thick lines, corresponding to the axis of EAEJ and
EASJ, respectively.

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Figure S2.
The vertical cross section of eddy kinetic energy (EKE, m 2 s -2 ) zonally averaged in the East Asian landmass (60-120°E). The contours denote the zonal mean zonal wind (m s -1 ).
The bottom is masked by the Tibetan Plateau. The climatological locations of EASJ and EAEJ are marked by the sun cross.
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Figure S3.
Climatological distribution of eddy kinetic energy (EKE) at 300 hPa (contour, m 2 s -2 ) and 1000-850 hPa vertical mean EGRM (Eady growth rate maximum, shading, day -1 ) in winter from NCEP/NCAR reanalysis. The closed curve denotes the 3000 m outline of Tibetan Plateau.
The blue rectangle is the area of East Asian eddy-drive jet and area-mean is averaged in this region.
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Figure S4.
The projected change (2071–2100 minus 1971–2000) of eddy kinetic energy (EKE) zonally averaged in different section: (a) East Asia, (b) North Pacific, (c) North Atlantic. The thick black line indicates the multi-model ensemble mean. The dots on each line indicate the latitude of the maximum EKE for 1971–2000 climatology; when the dot is at a latitude where the
EKE change is increasing towards the pole, there will be a poleward shift of EKE location (as
Figures. b and c); when the dot is at a latitude where the EKE change is reaching the peak, there will be a strengthening of EKE intensity.

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Reference
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