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1 Jour. Korean Earth Science Society, v. 29, no. 1, p , February 2008 (w ) w w» ½ 1, *Á 1 Á «2 1 w y w, w w w / w, ƒ The Interdecadal Variation of Relationship between Indian Ocean SeaG Surface Temperature and East Asian Summer Monsoon Won-Mo Kim 1, *, Jong-Ghap Jhun 1, and Byung-Kwon Moon 2 1 School of Earth and Environmental Sciences, Seoul National University, Seoul , Korea 2 Division of Science Education/Institute of Science Education, Chonbuk National University, Jeonju , Korea Abstract: This study aims to analyze the interdecadal variation of relationship between Indian Ocean sea surface temperature (SST) and East Asian summer monsoon (EASM) during the period of In the pre-period, which is from 1948 to 1975, the relationship between Indian Ocean SST and East Asian summer rainfall anomaly (EASRA) is very weak. However, in the post-period, which is from 1980 to 2005, Indian Ocean SST is significantly positively correlated with EASRA. The equatorial Indian Ocean SST has a significantly positive correlation with EASM in spring, while Indian Ocean SST near the bay of Bengal has a positive relationship in summer for the post-period. Also the interdecadal variation of the correlation between Indian Ocean SST and EASRA is significant, but that between EASRA and the El Niño-Southern Oscillation (ENSO) is not. Atmospheric general circulation model (AGCM) test results show the pattern of increased precipitation in the zonal belt region including South Korea and Japan and the pattern of decreased precipitation in the northeastern part of Asia, which are similar to the real climate. The increase of the precipitation in August from the model run is also similar to the real climate variation. Model results indicate that the Indian Ocean SST warming could intensify the convection over the vicinity of the Philippines and the Bay of Bengal, which forces to move northward the convection center. This warming strengthens the EASM and weakens the WNPM.,FZXPSET East Asian Monsoon, Interdecadal Variation, Indian Ocean Sea Surface Temperature : w 1970 Áz z y w.» w r (EASRA), ks (WNPMI) ƒ z ƒ j ƒw. w ƒƒ.. w» ENSO r ùkùš ENSO w j w. w w» (z» w» w ) š AGCM x w w w. x Áz» ql, w û ƒ, û ƒ ql. p 8 ks š» y w ƒ»z y ùkü. w ƒ w» y - *Corresponding author: koom2@snu.ac.kr Tel: Fax:

2 46 ½ Á Á «ks» y j w w ks š»» y jš»» y j w w. w» k. w ƒ z ks y y j w wš. w x ks» yw w.,», w w y ƒ»z p w wš. v e, y, û ¾ w eš mw x. ù w w š mw w w e š w o C w. w ùy w w ùkùš p 1970 Áz» w ƒ j ƒƒ ks ùkû (Wang, 1995; Zhang et al., 1997; Nitta and Yamada, 1989). w Hadley y yw û w w y»wš(wang et al., 2001), ks š» y k (Watanabe and Jin, 2002). w 1970 Áz z ks š» û w (Nitta and Hu, 1996). ¾ l 1970 Áz z w ùw yƒ» y y j w. w w s w w 1 j ƒ (Annamalai et al., 2005), w w š» r jš ûks š» t (Wang et al., 2001). w ks ƒ y š d (Webster et al., 1998; Kumar et al., 1999). w ENSO w Walker y e (Kumar et al., 1999), w ƒ w y(kumar et al., 1999), p (Chang et al., Fig. 1. Areas for defining various indices.

3 w w» ) ƒ ƒ š y x.» z e w 1970 Áz» ƒwš. p» y w ƒ w. w ƒ p ey(index)w t xw. (110 o E-145 o E, 30 o N-50 o N) r œ s³w r ƒ (Lee et al., 2005) ks (5 o N- 15 o N, 100 o E-130 o E) û (20 o N-30 o N, 110 o E- 140 o E) 850 hpa œ s³w k s ƒ (Wang et al., 2001). ƒ w SST r œ s³ w ww. w w 1970 z z» w ƒ w p 8 ƒ p yƒ š (Yun et al., 2001, Ho et al., 2003, Ha et al., 2005).»z w w w AGCM w x š û w w w q w (Annamalai et al., 2005). ù w x w z Fig. 2. Sliding correlations with 15-year window between Indian Ocean SST and EASRA (Black curve)/wnpmi (Grey curve) from 1948 to 2005 for (a) DJF, (b) MAM, and (c) JJA. Those between Nino 3 index and EASRA (Black curve)/wnpmi (Grey curve) for (d) DJF, (e) MAM, and (f) JJA.

4 48 ½ Á Á «z ƒ z w ù r. w» wš r k w w ƒ ù w q wš w. w»z l l(ncdc) Extended Reconstructed Sea Surface Temperature(ERSST), ƒƒ 2.0 o (Smith and Reynolds, 2004). National Centers for Environmental Prediction(NCEP) Precipitation REConstruction(PREC), ƒƒ 2.5 o (Chen et al., 2002).» (,, 500 hpa š )» l(ecmwf) 40 (ERA-40), ƒƒ 2.5 ƒ o (Uppala et Table 1. Correlation coefficient between EASRA and SST for specifically defined area in MAM. ** means that 95% confidence level is satisfied, while * means 90% satisfied. 1948~ ~ ~2005 IO ** 0.271** TIO ** 0.293** SWIO ** 0.248** NEIO ** 0.168** Nino3 (MAM) ** 0.258** al., 2005). WNPMI (850 hpa ) NCEP ECMWF w w w (Kalnay et al., 1996). w w (110 o E-145 o E, 30 o N-50 o N) (20 o S-20 o N, 30 o E-100 o E). p r» w (NEIO), (TIO), û (SWIO) w w. TIO SWIO w EASRA 90% w š NEIO w EASRA Fig. 3. Same as Fig. 2 except for Indian Ocean SST of areas (a) IO (20 o S-20 o N, 40 o E-100 o E), (b) TIO (10 o S-10 o N, 50 o E-90 o E), (c) SWIO (15 o S-Eq, 50 o E-70 o E), and (d) NEIO (Eq-20 o N, 80 o E-100 o E) in MAM.

5 w w» 49 90% w. ƒ Fig. 1 NEIO( -20 o N, 80 o E-100 o E), TIO(10 o S-10 o N, 50 o E- 90 o E), SWIO(10 o S-, 50 o E-70 o E). w» s³ Fig. 2 w r ( )/ ks (z ) w s³(sliding) w. w w š Tao and Chen, 1987; Zhang and Sumi, 1999) ks w š (Wu and Wang, 2002). ƒƒ 1970 Áz» EASRA ƒwš WNPMI w z»»z ƒ. w»z y ENSO ƒ s³ ùkùš (Wu and Wang, 2002; Nitta and Hu, 1996). l ¾»z (Jumping) š Nino3 EASRA Fig. 2e 1970»z ƒ ùkù ù Fig. 2f 95% w ùkù» w Áz z Nino3 ks ks j ƒ wš. wr z» w Nino3 ƒƒ EASRA j š 1985~1990» s³ ƒ Fig. 4. Correlation maps between SST of DJF (a, b) and East Asia summer rainfall anomaly (EASRA/JJA), SST of MAM (c, d) and EASRA/JJA, and SST of JJA (e, f) and EASRA/JJA. Dark shading areas represent 95% confidence level and light shading area 90% confidence level.

6 50 ½ Á Á «90% eš. ù» (interdecadal) y» 1970 Áz š w Table 1 l ¾» w» 95% wš.» 28, z» 26,» 58 m w (N-1) ƒƒ 27, 25, 57. w w 90% 0.313, 0.331, % 0.373, 0.388, Table 1 ** 95% * 90% ùkü. w w w w, w ƒ z» EASRA, š WNPMI w š (Table ). EASRA WNPMI e w (Lee et al., 2005). Fig. 3 p ù w ùkù. TIO SWIO w ƒ EASRA NEIO. Fig. 3a 1970 Á z»» Fig. 3b Fig. 3c w ùkù. p w ƒ w û (Klein et al., 1999) w» ƒ ùkùš. Áz» w ƒ Table l 2005 ¾» 1948 l 1975 ¾» EASRA Fig. 5. Correlation maps between SST of DJF (a, b) and western North Pacific monsoon index (WNPMI/JJA), SST of MAM (c, d) and WNPMI/JJA, and SST of JJA (e, f) and WNPMI/JJA. Dark shading areas represent 95% confidence level and light shading areas 90% confidence level.

7 w w» 51 w ƒƒ % e 1980 l 2005 z»» 95% wš. w Nino3 w Nino3 90% e w.»z w y w w» z» 1976 ~1979 wš 1948 l 1975 ¾», 1980 l 2005 ¾ z» w x w. œ Fig. 4 (DJF) (MAM) w EASRA w œ s.» w EASRA z» j ƒw. w Áz» y (JJA) w œ ql š. Figs. 4c 4d w w EASRA j š Fig. 6. The first three EOF modes in MAM for (left panels) and for (right panels). Units are nondimensional and the contour intervals is 0.02.

8 52 ½ Á Á «EASRA ks w w ë. Figs. 4e 4f œ ql š. z» p w w j ùkùš. ks v v wì ew œ (Wang and Fan, 1999). z y y w š w ks j w š q. w z ƒ w w 5 e x mw w. wr ù w z» w. wr»z p EASRA w ks w œ ùkû (Fig. 5). p z» WNPMIƒ w ƒ j. ks ENSO w» w» w j w š w. x w mw» w x w Fig. 7. Same as Fig. 6 except for JJA.

9 w w» 53 (EOF) w (basin), w, û w ƒ. Fig. 6 w Áz» w ql š ù ë ùkù. w ƒ z» w EOF y p y w ƒ. z» w w w. Áz» EOF ql j yƒ (Fig. 7).» w û e z» w û ùkùš. w» w ƒ z» ùkù Áz z s³ y Fig hpa sl š š 5850 gpm~5880 gpm š ùkü gpm š š ks š»» w z» 6, 8 ks š» y w ùk ùš, 5850 gpm š ks š» w«6, 7, 8 y w.» z» ks š» w j w. ks š» y ql, -, û ƒƒ,, (Wu and Wang, 2002). w ks š» y» w z» ql w ùkù. Fig. 9 û l w y yƒ, w. Table 2 (30 o N-50 o N, 110 o E-145 o E) Áz» ù r ƒ j. y j p ü ƒ ƒw w Fig hPa geopotential height fields for (a) June, (b) July, (c) August, and (d) JJA from observations. Solid black contours are for the post-period and dashed gray contours for the pre-period.

10 w w» 54 Fig. 9. Differences of precipitation between the post-period and the pre-period for (a) June, (b) July, (c) August, and (d) JJA. Fig. 10. Same as Fig. 8 except from IO forcing experiments.

11 w w» 55 Table 2. Precipitation averaged for EASRA region of (30 o N-50 o N, 110 o E-145 o E). Unit is mm/day. June July August JJA 1948~ ~ ù. w w ƒ z» j ƒw š d w t z» j ƒw ( ). w y y (Kumar et al., 1999) w ƒ w (Lee et al., 2005). p d t û w û e j ƒw. e x w» y x w» y x(snuagcm) Kim (1999) w. x T42 s w (~2.8Ü2.8) ƒ rp. 20 (σ)d h w CCSR/NIES AGCM» wš» (NCAR) t non-local PBL/vertical diffusion scheme ƒ.» w Kim(1999) ùkù. y (twostream) k s w w, yw Arakawa-Shubert,, z ù, x q w, w t sw. x x Fig. 1 w (forcing) w. š» y w w z» w» w. w ƒw œ» y w w w w w AGCM x Fig. 11. Precipitation differences (model run minus control run) for (a) June, (b) July, (c) August, and (d) JJA. Unit is mm/day.

12 56 ½ Á Á «Fig. 12. P-velocity (upper panels) and differences of p-velocity (lower panels) for two convection centers (80 o E-90 o E, 20 o N- 30 o N) and (120 o E-130 o E, 10 o N-20 o N) for IO forcing from the model run.. AMP(Atmospheric Model Intercomparison Project)» 3 1 l 8 31 ¾» w w 6. x Fig hpa sl š 5880 gpm w w ks š» 8 y w»z y ql w. w y w w wù š ƒ. p gpm š xkƒ š 5850 gpm š d w. w y p 8»z j w ƒ. Fig. 11 Áz» w w w z p 6 8 ù ƒ j» w. 4 Áz» ql z (Fig. 9) w ù z y jš û w, š 8 ƒ q l 1970 Áz»»z y ql w. 8 ƒ ks kt ƒ kt w ƒ. w ƒƒ kt ƒ ƒ w ƒ v w. Fig. 12 p- w w y š x ks v v y (Wang and Fan, 1999). w - ks f y y š ks - w y y z y w (Kawamura et al., 2001; Wang et al., 2001; Lee et al., 2005). w y z w» y y w p w û

13 w w» 57 Fig. 13. Same as fig. 12 except for TIO forcing. û w s ƒ j ùkûš w w» w z ƒ û y w ( ). Fig. 13 (80 o E-90 o E, 10 o N-25 o N) w z y w š w ks (120 o E- 130 o E, 10 o N-20 o N) y. w w e z ƒ w ùkû. ù ks y w j w ks xk ƒ š ƒ (Wang et al., 2001). w 1970 Áz z ks j.» w r, ks ƒ z ƒ j ƒw. w ƒ ƒ.. w» ENSO r ùkùš. ENSO w j w ƒ. d Áz» ks š» y y. ks y w ƒ û -w - û ƒw š w. w» (z» w minus» w ) š AGCM x ww w. x Áz» ql, w û ƒ, û

14 58 ½ Á Á «ƒ ql. p 8 ks š» y w ƒ»z y ùkü. w ƒ d ƒ j w w w ƒ z ƒ ùkú š q. w w ƒ ƒ - ks y j w w ks š»» y jš»» y j w w. w w ƒ j. ù x w AGCM w w ƒ w z e w w w». CGCM w w ƒ w w f q w» w ¾ ƒ v w.»»» (CATER ) w 21 w. mw w Ì. š x Annamalai, H., Liu, P., and Xie, S., 2005, Southwest Indian Ocean SST variability: Its local effect and remote influence on Asian monsoons. Journal of Climate, 18, Chang, C., Harr, P., and Ju, J., 2001, Possible roles of Atlantic circulations on the weakening Indian monsoon rainfall-enso relationship. Journal of Climate, 14, Chen, M., Xie, P., Janowiak, J.E., and Arkin, P.A., 2002, Global land precipiation: A 50-yr monthly analysis based on gauge observations. Journal of Hydrome teorology, 3, Ha, K.J., Park, S.K., and Kim, K.Y., 2005, On interannual characteristics of climate prediction center merged analysis precipitation over the Korean peninsula during the summer monsoon season. International Journal of Climatology, 25, Ho, C.H., Lee, J.Y., Ahn, M.H., and Lee, H.S., 2003, A sudden change in summer rainfall characteristics in Korea during the late 1970s. International Journal of Climatology, 23, Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, B., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Jenne, R., Joseph, D., 1996, The NCEP/NCAR 40-year reanalysis project. Bulletin of American Meteorological Society, 77, Kawamura, R., Matsuura, T.I., and Iizuka, S., 2001, Role of equatorially asymmetric sea surface temperature anomalies in the Indian Ocean in the Asian summer monsoon and El Nino Southern Oscillation coupling. Journal of Geophysical Research, 106, Kim, J.K., 1999, Parameterization of land surface processes in an atmospheric general circulation model. Ph. D. thesis, Seoul National University, Seoul, Korea, 178 p. Klein, S.A., Soden, B.J., and Lau, N.C., 1999, Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. Journal of Climate, 12, Kumar, K.K., Rajagopalan, B., and Cane, M.A., 1999, On the weakening relationship between the Indian monsoon and ENSO. Science, 284, Lee, E.J., Jhun, J.G., and Park, C.K., 2005, Remote connection of the northeast Asian summer rainfall variation revealed by a newly defined monsoon index. Journal of Climate, 18, Nitta, T. and Yamada, S., 1989, Recent warming of tropical sea surface temperature and its relationship to the Northern Hemisphere circulation. Journal of Meteorological Society of Japan, 67, Nitta, T. and Hu, Z.Z., 1996, Summer climate variability in China and its association with 500 hpa height and tropical convection. Journal of Meteorological Society of Japan, 74, Smith, T.M. and Reynolds, R.W., 2004, Improved Extended Reconstruction of SST ( ). Journal of Climate, 17, Tao, S.Y. and Chen, L.X., 1987, A review of recent research on the East Asian summer monsoon in China. In Chang, C.P. and Krishnamurti, T.N. (eds.), Monsoon Meteorology. Oxford University Press, UK, Uppala, S.M., Kållberg, P.W., Simmons, A.J., Andrae, U., da Costa Bechtold, V., Fiorino, M., Gibson, J.K., Haseler, J., Hernandez, A., Kelly, G.A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R.P., Andersson, E., Arpe, K., Balmaseda, M.A., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Caires, S., Cheval-

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16 Jour. Korean Earth Science Society, v. 29, no. 1, p , February 2008 (w ) w w» ½ 1, *Á 1 Á «2 1 w y w, w w w / w, ƒ The Interdecadal Variation of Relationship between Indian Ocean SeaG Surface Temperature and East Asian Summer Monsoon Won-Mo Kim 1, *, Jong-Ghap Jhun 1, and Byung-Kwon Moon 2 1 School of Earth and Environmental Sciences, Seoul National University, Seoul , Korea 2 Division of Science Education/Institute of Science Education, Chonbuk National University, Jeonju , Korea Abstract: This study aims to analyze the interdecadal variation of relationship between Indian Ocean sea surface temperature (SST) and East Asian summer monsoon (EASM) during the period of In the pre-period, which is from 1948 to 1975, the relationship between Indian Ocean SST and East Asian summer rainfall anomaly (EASRA) is very weak. However, in the post-period, which is from 1980 to 2005, Indian Ocean SST is significantly positively correlated with EASRA. The equatorial Indian Ocean SST has a significantly positive correlation with EASM in spring, while Indian Ocean SST near the bay of Bengal has a positive relationship in summer for the post-period. Also the interdecadal variation of the correlation between Indian Ocean SST and EASRA is significant, but that between EASRA and the El Niño-Southern Oscillation (ENSO) is not. Atmospheric general circulation model (AGCM) test results show the pattern of increased precipitation in the zonal belt region including South Korea and Japan and the pattern of decreased precipitation in the northeastern part of Asia, which are similar to the real climate. The increase of the precipitation in August from the model run is also similar to the real climate variation. Model results indicate that the Indian Ocean SST warming could intensify the convection over the vicinity of the Philippines and the Bay of Bengal, which forces to move northward the convection center. This warming strengthens the EASM and weakens the WNPM.,FZXPSET East Asian Monsoon, Interdecadal Variation, Indian Ocean Sea Surface Temperature : w 1970 Áz z y w.» w r (EASRA), ks (WNPMI) ƒ z ƒ j ƒw. w ƒƒ.. w» ENSO r ùkùš ENSO w j w. w w» (z» w» w ) š AGCM x w w w. x Áz» ql, w û ƒ, û ƒ ql. p 8 ks š» y w ƒ»z y ùkü. w ƒ w» y - *Corresponding author: koom2@snu.ac.kr Tel: Fax: