Comparative Study of Performance of CMIP3 GCMs in Simulating the East Asian Monsoon Variability SAHANA PAUL and H. H. HSU Department of Atmospheric Sciences,

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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

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.

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

East Asian Summer Monsoon (1950-99)

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.

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.

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

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

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

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

East Asian Winter Monsoon (1950-99)

Indices Used for East Asian Winter Monsoon (EASM): ICHENW (average v wind component over East China Sea and South China Sea(10-25N,110-130E and 25-40N,120-140E). 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;125-145E) Sun and Li, (1997)) for the lower-troposphere temperature variability.

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.

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.

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

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

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

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.

Thank You！

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

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.

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

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

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. 20= spatial correlation between model observation according to ICHENW for mslp,21= Weakening of Siberian high.