1. Comparative Study of Performance of CMIP3 GCMs in Simulating the East Asian Monsoon Variability
SAHANA PAUL and H. H. HSU
Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan.
Taiwan Climate Change Information Platform. NCDR, Taiwan

2. Focus:
Comprehensive assessment of relative merits of CMIP3 models in simulating the East Asian summer (EASM) and winter monsoon (EAWM) variability using different kinds of monsoon indices and construction of Monsoon Matrix.

3. List of CMIP3 GCMs No. Model CMIP3 I.D. Resolution 1.
Bjerknes Centre for Climate Research
BCCR-BCM2.0
64x128 2.
Canadian Center for Climate Modeling and Analysis Canada
CGCM3.1(T63) 3.
CGCM3.1(T47)
48x96 4.
Australia's Commonwealth Scientific and Industrial Research Organization Australia
CSIRO-Mk3.0
96x196 5.
CSIRO-Mk3.5
96x192 6.
Geophysical Fluid Dynamics Laboratory USA
GFDL-CM2.0
90x144 7.
GFDL-CM2.1 8.
GISS USA
GISS-AOM
60x90 9.
GISS-EH
46x72
10.
GISS-ER
11.
Institute of Atmospheric Physics China
FGOALS-g1.0
60x148
12.
Institute for Numerical Mathematics Russia
INM-CM3.0
45x72
13.
National Institute of Geophysics and Volcanology, Bologna, Italy
INGV-SXG
160x320
14.
Institute Pierre Simon Laplace France
IPSL-CM4
72x96
15.
MIROC3.2(hires)
16.
MIROC3.2(medres)
17.
Meteorological Institute, University of Bonn, Germany Meteorological Research Institute of KMA, Korea Model and Data Group at MPI-M, Germany
ECHO-G
18.
Max-Planck-Institut for Meteorology Germany
ECHAM5/MPI-OM
19.
Meteorological Research Institute Japan
MRI-CGCM2.3.2
20.
National Centre for Atmospheric Research USA
CCSM3
21.
PCM
22.
UK Met. Office UK
UKMO-HadCM3
73x96
23.
UKMO-HadGEM1
145x192
24.
Centre National de Recherches Meteorologiques France
CNRM-CM3
List of CMIP3 GCMs

4. East Asian Summer Monsoon (1950-99)

5. Indices Used for East Asian Summer Monsoon (EASM):
Wang-Fan Index (Wang-Fan, 1999) :
Difference between U850 (5-15N, 90-130E) and U850 (22.5-32.5N, 100-140E)
2. Tripole pattern (Hsu et. al., 2007), which is the leading EOF of rainfall in both inter-annual and decadal time scales in East Asia, and the associated circulation during the northern summer.

6. BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
GISS-EH
GISS-ER
INM-CM3.0
INGV-SXG
IPSL-CM4
MIROC3.2(medres)
MRI-CGCM2.3.2
CCSM3
UKMO-HadGEM1
Time series of normalized monsoon index (IWF) of the Observed data and GCMs showing weakening.
NCEP
Weak and Strong monsoon decades with average standard deviation more than +/-.5 are chosen.

7. NCEP CGCM3.1(T63) CGCM3.1(T47) CSIRO-Mk3.0 GISS-EH GISS-ER INM-CM3.0
Comparison of Decadal Difference Between the Negative and Positive monsoon Decades for Wind field in between different GCMs and observation.
NCEP
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
GISS-EH
GISS-ER
INM-CM3.0
INGV-SXG
MIROC3.2(medres)
MRI-CGCM2.3.2
CCSM3
UKMO-HadGEM1
.63
.77
.62
.84
.68
.76

8. CRU CGCM3.1(T63) CGCM3.1(T47) CSIRO-Mk3.0 .25 .26 .12 GISS-EH GISS-ER
INM-CM3.0
INGV-SXG
-.00
-.15
.14
.02
MIROC3.2(medres)
MRI-CGCM2.3.2
CCSM3
UKMO-HadGEM1
-.05
.35
.06
.08
Comparison of Decadal Difference Between the Negative and Positive monsoon Decades for Precipitation in between different GCMs and observation

9. EOF1=23%
Comparison of Tri-pole pattern of inter-annual component of precipitation in between GCMs and observation.
CRU
EOF2=13.5%
EOF2=13.9%
EOF1=21.9%
EOF1=15.3%
EOF2=13.8%
EOF1=29.8%
EOF1= 42%
EOF1=17.7%
EOF2=18.3%
EOF2=13.4%
EOF1=31%
EOF1=33%
EOF1=21.5%
EOF2=17.5%
EOF2=15%
EOF1=18.6%
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
CSIRO-Mk3.5
GFDL-CM2.0
GFDL-CM2.1
GISS-AOM
GISS-EH
FGOALS-g1.0
INM-CM3.0
INGV-SXG
MIROC3.2(hires)
MIROC3.2(medres)
PCM
UKMO-HadCM3
UKMO-HadGEM1
-.54
-.56
-.13
.44
.45
.59
-.68
-.60
-.75
.42
.62
.43
-.42
.60

10. C M G Main features of EASM 1 2
Summer Monsoon Matrix(24x11) 1 2
1=Corrl. Betn. obs. and gcms for mean rainfall pattern.
2= Corrl. Betn. Obs. and gcms for rainfall variability pattern. 3
3=showing weakening for IWF 5 4
4=spatial. Corrl. Betn. gcms and obs. for Dec. diff of rainfall according to IWF.
5= decrease of rainfall over Central China due to weakening 6 7 8 9 11 12
6=spatial correlation between model observation according to IWF for streamfunction,
7= Showing anti-cyclonic circulation over western north Pacific.
8= tripole pattern of rainfall for decadal component ,
9=spatial correlation between observation and gcm,
10= tripole pattern of rainfall for inter-annual component, 11=spatial correlation between observation and gcm.
BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
CSIRO-Mk3.5
GFDL-CM2.0
GFDL-CM2.1
GISS-AOM
GISS-EH
GISS-ER
FGOALS-g1.0
INGV-SXG
INM-CM3.0
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHO-G
ECHAM5/MPI-OM
MRI-CGCM2.3.2
CCSM3
PCM
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3 .6 Y - .5 N .4 .3
-.5 .1
-.1 .7 .8
-.6
-.4
+.3
-.7 .2
-.2
-.8
-.3

11. East Asian Winter Monsoon (1950-99)

12. Indices Used for East Asian Winter Monsoon (EASM):
ICHENW (average v wind component over East China Sea and South China Sea(10-25N, E and 25-40N, E).
IGONGDY (mean SLP over the centre of Siberian High (40-60N,70-120E))(Gong et. al.(1997)) for the Siberian High variability.
ISUNBM (Average Normalized 500 hpa Geo-potential Height over (35-40N; E) Sun and Li, (1997)) for the lower-troposphere temperature variability.

13. GCMs showing weakening of EAWM according to ISUNBM
BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
GISS-AOM
GISS-EH
GISS-ER
INM-CM3.0
INGV-SXG
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHAM5/MPI-OM
MRI-CGCM2.3.2
PCM
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3
GCMs showing weakening of EAWM according to ISUNBM
NCEP
Weak and Strong monsoon decades with standard deviation more than +/-.5 are chosen. Here we considered three parameter, geo. potl. ht, mslp, temp.

14. NCEP BCCR-BCM2.0 CGCM3.1(T63) CGCM3.1(T47) CSIRO-Mk3.0 GISS-AOM
-.30
.45
.54
.75
.71
.43
.24
.64
.39
.42
-.51
.58
-.39
.77
.51
.61
.28
GISS-AOM
GISS-EH
GISS-ER
INM-CM3.0
INGV-SXG
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHAM5/MPI-OM
MRI-CGCM2.3.2
PCM
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3
Decadal Difference Between the Negative and Positive monsoon Decades for 500 hpa geopotential height.

15. NCEP
BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
-.48
.42
-.36
.55
.02
-.08
.44
.24
.15
.78
-.39
.49
-.12
.52
.41
GISS-AOM
GISS-EH
GISS-ER
INM-CM3.0
INGV-SXG
MIROC3.2(medres)
ECHAM5/MPI-OM
MRI-CGCM2.3.2
IPSL-CM4
MIROC3.2(hires)
PCM
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3
Decadal Difference Between the Negative and Positive monsoon Decades for Surface Air Temperature

16. NCEP
Decadal Difference Between the Negative and Positive monsoon Decades for MSLP
BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
GISS-AOM
GISS-EH
GISS-ER
INM-CM3.0
INGV-SXG
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHAM5/MPI-OM
MRI-CGCM2.3.2
PCM
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3
-.19
.75
.60
.20
.69
-.20
.25
.65
.64
.41
.35
.78
-.36
.57
.17
.52

17. Similar kind of study is done for other two indices.
1. IGONDGY, 2. ICHENW
Winter Monsoon Matrix (24x21) is constructed just like summer:
Main features of EAWM G C M

18. Conclusions:
Both the Summer and Winter Monsoon Matrix are robust in nature, reflecting quantitative and qualitative features of EASM and EAWM.
The main features of Summer Monsoons are mostly well simulated by CISRO-Mk3.0,MRI-CGCM2.3.2, UKMO-hadGEM1.
Winter Monsoon Matrix gives a very clear picture for relative performances of the GCMs. Good performances of CGCM3.1(T63), GISS-AOM, INGV-SXG, INM-CM3.0, MIROC3.2(medres), MRI-CGCM2.3.2, UKMO-HadGEM1, and CNRM-CM3.

19. Thank You！

20. BCCR-BCM2.0 CSIRO-Mk3.0 GFDL-CM2.1 GISS-AOM FGOALS-g1.0 INGV-SXG
EOF1=21%
EOF2=21.6%
EOF1=24%
EOF1=44.9%
EOF1=42%
EOF2=14.8%
EOF2=18.4%
EOF2=11.2%
EOF2=18.2%
EOF1=28%
EOF2=24%
BCCR-BCM2.0
CSIRO-Mk3.0
GFDL-CM2.1
GISS-AOM
FGOALS-g1.0
INGV-SXG
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
UKMO-HadCM3
UKMO-HadGEM1
EOF1=22.2%
Comparison of Tripole pattern of decadal component of precipitation in between GCMs and observation.
CRU
.45
.12
.46
.74
-.46
-.39
-.43
-.53
-.59
-.78
.60

21. GCMs showing weakening of EAWM according to IGONGDY
HADLEY
BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
GFDL-CM2.1
GISS-AOM
GISS-ER
INM-CM3.0
INGV-SXG
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHO-G
MRI-CGCM2.3.2
PCM
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3
Decadal difference of Weak and Strong monsoon decades considered for mslp, temp.

22. Decadal Difference Between the Negative and Positive monsoon Decades for MSLP
HADLEY
CGCM3.1(T63)
CGCM3.1(T47)
CSIRO-Mk3.0
GFDL-CM2.1
.83
.69
.64
.59
.73
.68
.50
.61
.56
.76
.75
.39
.70
GISS-AOM
GISS-ER
INM-CM3.0
INGV-SXG
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHO-G
MRI-CGCM2.3.2
UKMO-HadCM3
UKMO-HadGEM1
CNRM-CM3

23. GCMs showing weakening of EAWM according to ICHENW
BCCR-BCM2.0
CGCM3.1(T63)
CGCM3.1(T47)
GFDL-CM2.1
GISS-AOM
GISS-ER
INM-CM3.0
IPSL-CM4
MIROC3.2(hires)
MIROC3.2(medres)
ECHO-G
ECHAM5/MPI-OM
PCM
UKMO-HadCM3
CNRM-CM3
GCMs showing weakening of EAWM according to ICHENW
NCEP

24. Table 4: Winter monsoon matrix.1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
BCCR-BCM2.0
.98
.87
.95
.83 Y
-.30
-.48 N
-.19 -
.07
.35
.03
CGCM3.1(T63)
.97
.81
.94
.86
.45
.42
.75
.67
CGCM3.1(T47)
.96
.82
.84
.54
.60
.69
.21
-.05
-.07
CSIRO-Mk3.0
.91
.78
-.36
.20
.64
.48
CSIRO-Mk3.5
.99
.85
.79
GFDL-CM2.0
.92
GFDL-CM2.1
.90
.77
.59
.55
GISS-AOM
.80
.71
.57
.33
GISS-EH
.76
.43
.02
-.20
GISS-ER
.89
.24
-.08
.25
.73
.30
-.28
.23
FGOALS-g1.0
INGV-SXG
.39
.44
.50
.29
INM-CM3.0
.65
.68
.66
.13
.41
IPSL-CM4
.61
-.01
-.10
.31
.58
MIROC3.2(hires)
-.51
.15
.56
-.11
.36
.32
MIROC3.2(medres)
.70
.74
.05
ECHO-G
.93
-.61
.40
-.69
ECHAM5/MPI-OM
-.39
MRI-CGCM2.3.2
.53
CCSM3
PCM
.88
.49
-.44
.19
UKMO-HadCM3
.51
-.12
.17
.63
UKMO-HadGEM1
.52
CNRM-CM3
.28
Table 4: Winter monsoon matrix.
1= spatial corr. Of avg tmp, 2= spatial corr. Of tmp variability, 3= spatial corr. Of avg mslp, 4= spatial corr. Of mslp variability, 5=showing weakening according to ISUNBM.6= spatial correlation between model observation according to ISUNBM for geopotential height. 7= spatial correlation between model observation according to ISUNBM for temp. 8= rise of temperature ISUNBM, 9= spatial correlation between model observation according to ISUNBM for mslp, 10= Weakening of Siberian high. 11=showing weakening according to IGONGDY.12= spatial correlation between model observation according to IGONGDY for mslp.13 = spatial correlation between model observation according to IGONGDY for temp. 14= rise of temperature over north EA according to IGONGDY , 15=showing weakening according to ICHENW. 16= spatial correlation between model observation according to ICHENW for temp.17= rise of temperature ICHENW,18=spatial corr. between gcm and obs. according to ICHENW for strmline, 19= showing less north-easterly flow = spatial correlation between model observation according to ICHENW for mslp,21= Weakening of Siberian high.