Decadal variability of the IOD-ENSO relationship

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1 Chinese Science Bulletin 2008 SCIENCE IN CHINA PRESS ARTICLES Springer Decadal variability of the IOD-ENSO relationship YUAN Yuan 1,2 & LI ChongYin 1 1 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing , China; 2 Graduate University of Chinese Academy of Sciences, Beijing , China Using three kinds of over 100-year sea surface temperature (SST) datasets as well as three-dimensional wind data from NCEP/NCAR, this paper documents the decadal variability of the Indian Ocean Dipole (IOD)-El Niño/Southern Oscillation (ENSO) relationship. During , positive (negative) IOD and warm (cold) ENSO events were more independent of each other. But after 1970, they tended to occur in the same year. ENSO would influence the whole life span of IOD, and IOD also affects the developing phase of ENSO. Considering the climatological background SST, low-level winds and also equatorial vertical circulations, it is revealed that the decadal variability of the IOD-ENSO relationship may be caused by the enhanced Walker circulation with increased rising motion over the Maritime Continent after Warmer SST around the Maritime Continent gives rise to anomalous low-level convergence and intensified convection there, which apparently increases the SST linkage between the eastern Indian Ocean and the western Pacific and thereby the interaction between the IOD and ENSO event. IOD, ENSO, decadal variability The Indian Ocean Dipole (IOD) is a basin-scale mode of sea surface temperature (SST) and wind anomalies occurring on interannual timescales in the equatorial Indian Ocean [1,2]. Previous studies have proved that the dipole mode exerts a major impact on seasonal climatic conditions in nations around the Indian Ocean [3,4], and also on the atmospheric circulation and climate in other far regions, like East Asia [5,6], Europe, and North and South America [3]. A controversial issue concerning the dependence/independence of IOD and the El Niño/Southern Oscillation (ENSO) phenomena has recently been raised [7]. The correlation coefficient (r = 0.35) between monthly IOD index and Niño3 SST anomaly (SSTA) time series is insignificant [1,2]. Some extremely strong positive IOD events occur without an El Niño event, like 1961, 1967, and 1994 [8]. These results indicate that the IOD mode may not be related with the ENSO events, but forced by the internal dynamics confined in the Indian Ocean itself [9,10]. In contrast, there are also some positive IODs coinciding with major El Niño events, which appear in 1963, 1972, 1982, and A significant correlation coefficient of 0.56 is found between the boreal autumn (September-November) IOD and Niño3-SSTA indices, while in other seasons it is insignificant [7,11]. Therefore, IOD is suggested to be a part of ENSO evolution, being excited through the oceanic Rossby waves from the east [12], the Indonesian Throughflow [13,14], or the Walker circulation across the tropical Indo-Pacific Ocean [15 17]. The controversy has now come to an end that IOD is influenced by ENSO event in some years, but ENSO is not the only one triggering mechanism [18]. Existing researches have mainly talked about the IOD-ENSO relationship on the seasonal or interannual timescale. As will be discussed in our analyses, is it possible that their relationship actually changes with time, or in other words, it Received November 13, 2007; accepted February 20, 2008 doi: /s Corresponding author ( yuanyuan@mail.iap.ac.cn) Supported by the China National 973 Program (Grant No. 2006CB403600), the National Natural Science Foundation of China (Grant No ), and the Innovation Key Program of the Chinese Academy of Sciences (Grant No. ZKCX2-SW- 226) ATMOSPHERIC SCIENCES csb.scichina.com Chinese Science Bulletin June 2008 vol. 53 no

2 has a decadal variability? 1 Data and methodology Atmospheric variables used in this study are derived from the National Centers for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/ NCAR) reanalysis, including monthly three-dimensional winds on twelve standard pressure levels, with a horizontal resolution of 2.5 latitude-longitude squares and a 56-year ( ) period [19]. SST data mainly come from the monthly Hadley Center sea ice and SST dataset (HadISST), with 1 o latitude/longitude resolution and a 134-year period of [20]. To testify the decadal variability of the IOD-ENSO relationship, we also examine two other over 100-year SST datasets: the extended reconstruction of global SST (ERSST) produced on Comprehensive Ocean-Atmosphere Data Set (COADS) from 1854 to 2005 [21], and the Kaplan SST data of [22]. Interannual anomalies are obtained by deviations from the climatological cycle based on the individual timescale of each dataset. The long-term linear trend of SSTA is removed at each grid point. IOD index is defined as SSTA difference between the western (50 E 70 E, 10 S 10 N) and southeastern (90 E 110 E, 10 S-equator) Indian Ocean [1]. Positive IOD means warm (cool) in the west (east), and the opposite pattern is negative IOD. Niño3 index, defined as SSTA area-averaged over 150 W 90 W, 5 S 5 N, is used to represent ENSO signal in the tropical Pacific. Based on the one standard deviation of the root mean square of normalized IOD and Niño3 indices (Figure 1), the active period of IOD is from July to November (JASON), and for Niño3 it is from October to the next January (ONDJ). Because of the tight phase-locking characteristic, we calculate the seasonal stratified IOD (JASON) and Niño3 (ONDJ) indices. In this study, we utilize the method proposed by Ashok et al. [10] to remove ENSO signal from the IOD I I r( I, I ) I, index IODM AIODM IODM NINO3 NINO3 where I NINO3 is the normalized Niño3 index ( I NINO3 ), is the standard deviation of the IOD index ( I IODM ), ri ( IODM, ININO3) denotes their correlation coefficient, and I AIODM is the remainder of I IODM with ENSO sig- Figure 1 Annual variations of the root mean square of the normalized IOD (closed circle) and Niño3 (open circle) index. Dashed line indicates one standard deviation. X axis is for the calendar months, with 0 ( 1 ) for the onset (following) year. nal removed. I NINO3 and I IODM can be exchanged so as to remove IOD signal from the Niño3 index. IOD years are selected based on one standard deviation (0.36 o C) of the seasonal mean (JASON) IOD index from 1948 to 2003, and ENSO years are determined by Wang and Gong [23]. 2 Decadal variability of the IOD-ENSO relationship Using HadISST, the 11-year running correlation between the seasonal mean IOD (JASON) and Niño3 (ONDJ) indices shows a clear decadal variability (Figure 2(a)): insignificant correlation during , whereas significant correlation from the 1900s to early 1920s and again after To verify such decadal variability, we also examine two other SST datasets over 100 years: ERSST and Kaplan SST. Except the inconsistent IOD- ENSO relationship before 1940, both of them show the similar low correlation during and high correlation above 95% confidence level after 1970 (Figure 2(b), (c)), suggesting that the decadal variability of the IOD-ENSO relationship is not subject to data at least after Note that the SST data before 1940 might have quality problems with more missing observations and the available atmospheric data only start from The following analyses will mainly focus on the period. Figure 3 shows the wavelet spectra and 1 8-year 1746 YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

3 ARTICLES Figure 2 11-year running correlation between IOD (JASON) and Niño3 (ONDJ) index during , using (a) HadISST, (b) ERSST, and (c) Kaplan SST data. The dashed line indicates the 95% confidence level (0.598) of the correlation coefficient by t-test. ATMOSPHERIC SCIENCES scale averaged time series of the monthly Niño3 and IOD indices using the Morlet wavelet [24]. In contrast with the strongest power of the Niño3 spectrum in 1950s, early 1970s, and 1980s 1990s (Figure 3(a)), the peak power in the IOD spectrum occurs during the 1960s and 1990s (Figure 3(c)). The 1 8-year time series confirm YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

4 Figure 3 Wavelet analyses of monthly (a) Niño3 and (c) IOD indices. (b) Same as (a), but with IOD signal removed. (d) Same as (c), but with ENSO signal removed. Each diagram includes the wavelet power spectrum (top), with the thick solid curves as the 95% confidence level, and 1 8-year scale average (bottom) of the time series. the variation of the index intensity, which also agrees well with Saji and Yamagata [8]. In a further step, we remove the IOD (ENSO) signal from the original Niño3 (IOD) index, and then apply the Morlet wavelet again. As shown in Figure 3(b), little change occurs in the spectrum or time series of the Niño3 index before But after 1970, the leading period of the Niño3 index changes from years to 3 6 years, and the intensity of the time series is also reduced, especially during the 1990s. For the IOD index with ENSO signal removed, there are few differences before 1970, but significant decrease of intensity after 1970 (Figure 3(d)). Normalized seasonal mean IOD (JASON) and Niño3 (ONDJ) indices display a nearly out-of-phase correlation during , but almost in-phase variation during (Figure 4). This implies that positive (negative) IOD often takes place with negative (positive) or nearly zero SSTA in the equatorial eastern Pacific before 1970, but with positive (negative) SSTA there after Tables 1 and 2 list warm and cold ENSO years as well as positive and negative IOD years, separately in the and period. There Figure 4 Time series of the normalized seasonal mean IOD (JASON; open circle and solid line) and Niño3 (ONDJ; closed circle and dashed line) index during are very few co-occurrences of El Niño (La Niña) and positive (negative) IOD in the earlier period (Table 1). But after 1970, almost all El Niño events happen with a positive IOD and almost every positive IOD event occurs in an El Niño year. The same can be said for La Niña and negative IOD (Table 2) YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

5 Table 1 El Niño and La Niña years (according to Wang and Gong [23] ) and positive IOD (PIOD) and negative IOD (NIOD) years (based on one standard deviation of the IOD index averaged in JASON) during El Niño La Niña ARTICLES PIOD NIOD The years in bold indicate the co-occurrences of El Niño (La Niña) and positive (negative) IOD. Table 2 Same as Table 1, but during El Niño La Niña PIOD NIOD Figure 5 gives the IOD index composite in positive IOD years, Niño3 index composite in El Niño years, and also the same IOD (Niño3) index with ENSO (IOD) signal being removed. During , the IOD index Figure 5 (a) IOD index composite for positive IOD years during (solid and dashed curves) and (open and closed circles). The dashed and closed circles are the IOD index with ENSO signal removed. (b) Same as (a), but for Niño3 index and with IOD signal being removed. X axis is for the calendar months in two continuous years, with 2 12 for the onset year and for the following year. shows few differences before and after ENSO signal is removed. But during , the entire life span of the IOD index is significantly reduced when ENSO signal is removed, indicating that ENSO has a great impact on the development of IOD events during recent decades (Figure 5(a)). Similarly, if IOD signal is removed from the Niño3 index, there is also little change of the Niño3 index before But after 1970, the index is largely suppressed during its developing phase (Figure 5(b)). The reduced value of about 0.5 is even larger than that of the IOD index (about 0.2 decrease). Some important conclusions can be inferred from Figure 5: (1) IOD is not just a slave of ENSO, but can actively influence ENSO intensity, especially after 1970; (2) ENSO affects the whole life span of IOD, but IOD mainly influences the developing phase of ENSO; (3) IOD has almost the same strength before and after 1970, but ENSO shows a larger intensity after 1970, which also confirms a recent finding by Annamalai et al. [25] that the decadal increase of El Niño events may be caused by the interference of more positive IOD events in the latest decades. In agreement with the running correlation between IOD and Niño3 index (Figure 2), the above analyses reaffirm the decadal variability of the IOD-ENSO relationship: before 1970, IOD and ENSO events are more independent of each other, but after 1970, they are more interactive. Then, what is the reason for the decadal variability of their relationship? 3 Possible dynamics When a positive IOD and a warm ENSO event occur simultaneously, positive SSTA dominates the tropical ATMOSPHERIC SCIENCES YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

6 western Indian Ocean and eastern Pacific, while negative anomalies extend from the equatorial eastern Indian Ocean to the western Pacific, which forms a tropical Pacific-Indian Ocean SSTA mode [26]. However, such a pattern tends to miss its western part in the tropical Indian Ocean (i.e. pure ENSO event) or its eastern part in the tropical Pacific (i.e. pure IOD event) before 1970, but becomes evident after As SST variation in the western Indian Ocean is closely related with that in the equatorial eastern Pacific 1), the decadal variability of the IOD-ENSO relationship might be caused by the variation of the SST connection between the eastern Indian Ocean and the western Pacific. Under this assumption, we investigate the differences of climatological background fields between and , including SST structure, low-level winds, and vertical winds along the equator. Variables averaged in JASON are illustrated, as it is the active phase of IOD and developing phase of ENSO with significant IOD impacts during (Figure 5(b)). As shown in Figure 6(a), most of the tropical Indian Ocean, Maritime Continent, western Pacific around the Philippines, and the southeastern Pacific exhibit a warming SST trend after In the low-level wind field, a significant difference is a cyclone (denoted by C ) identified around the Maritime Continent south of the Indo-China Peninsular (Figure 6(b)), which rightly overlies the extremely warmer water (Figure 6(a)). Climatologically, the warm pool region has the strongest upward motion with most intense convection in the tropical ocean, while subsidence dominates the relatively cold regions of the tropical western Indian Ocean and eastern Pacific. This forms two Walker circulations over the tropical Indo-Pacific Ocean and is well-known as atmospheric bridge [15]. In the difference diagrams of 850-hPa and 200-hPa potential velocity, low-level convergence and upper-level divergence are enhanced above the Maritime Continent and the tropical eastern Pacific after 1970, while low-level divergence and upper-level convergence are intensified over the western Indian Ocean and central Pacific (Figures not shown). These results imply increased Walker circulations with a stronger ascending motion over the Maritime Continent in than in , consistent with the warmer SST (Figure 6(a)) and an anomalous low-level cyclone (Figure 6(b)) there. The difference of the equatorial vertical winds between the later and the earlier period further confirms our results: negative values are observed to the west of the 120 o E longitude, indicating an enhanced upward motion there (Figure 6(c)). Therefore, warmer SST over the Maritime Continent gives rise to an anomalous low-level cyclone with increased convection and enhanced rising motion there after Associated with the intensified low-level convergence, the connection of the sea water between the eastern Indian Ocean and the western Pacific should be strengthened, so is the interaction between the IOD and ENSO events during recent decades. 4 Summary and discussion The present paper reveals the decadal variability of the IOD-ENSO relationship and further investigates possible reasons for it. Using three different SST datasets, it is found that the IOD-ENSO relationship changes with time: insignificant correlation during , but significant correlation during In the earlier period with few co-occurrences of positive (negative) IOD and warm (cold) ENSO event, little change occurs in the strength of the IOD mode when ENSO signal is removed, and the same can be said for ENSO events when IOD signal is subtracted. But after 1970, most El Niño events co-occur with positive IOD events, and almost every positive IOD happens in an El Niño year. During these co-occurrences, ENSO affects the whole life span of IOD, and IOD also influences the developing phase of ENSO. Considering the decadal variation of the climatological background SST, low-level winds as well as the equatorial vertical circulations between and , it is suggested that the increased inter- action between IOD and ENSO after 1970 may be caused by the enhanced linkage of the sea water between the eastern Indian Ocean and the western Pacific. Warmer SST around the Maritime Continent after 1970 would enhance the in situ convection and rising motion. Associated with the low-level anomalous convergence, westerly anomalies are identified over the equatorial eastern 1) Yuan Y, Zhou W, Yang H, Li C Y. Warming in the northwestern Indian Ocean associated with the El Niño event. Adv Atmos Sci, in press 1750 YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

7 ATMOSPHERIC SCIENCES ARTICLES Figure 6 Differences of the climatological (a) SST ( ), (b) 850-hPa winds (m/s), and (c) vertical winds (10 2 hpa/s) along the equator (5 S 5 N) between and All variables are averaged in JASON. Positive (negative) value means downward (upward) motion. YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

8 Indian Ocean, while easterly anomalies dominate the equatorial western Pacific (Figure 6(b)). Therefore, the connection between the two tropical oceans may be increased through the Indonesian Throughflow [13,14] or some other thermodynamic processes. As illustrated in Figure 5(b), IOD is not just a slave of ENSO, but can actively influence ENSO intensity during Moreover, the increased strength of the ENSO event after 1970 may also be caused by the interference of more positive IOD events [25]. Questions are: through what physical processes would IOD influence the developing phase of ENSO, and what about the significance of the IOD effects? Our further studies have suggested that the impacts IOD on ENSO may be realized based on the atmospheric bridge theory [15]. Through changing the upward motion above the Maritime Continent and the low-level zonal winds over the western-central Pacific, IOD could increase the intensity of ENSO with its impacts at least above the 85% confidence level. Nevertheless, more statistical analyses or numerical simulations are still required to testify our results and further investigate other dynamic or thermodynamic mechanisms. The authors highly thank two anonymous reviewers for their useful suggestions and comments on improving this paper. 1 Saji N H, Goswami B N, Vinayachandran P N, et al. A dipole mode in the tropical Indian Ocean. Nature, 1999, 401: Webster P J, Moore A M, Loschnigg J P, et al. Coupled ocean- atmosphere dynamics in the Indian Ocean during Nature, 1999, 401: Saji N H, Yamagata T. Possible impacts of Indian Ocean dipole mode events on global climate. Clim Res, 2003, 25: Wang X, Li C Y, Zhou W. Interdecadal variation of the relationship between Indian rainfall and SSTA modes in the Indian Ocean. Int J Climatol, 2006, 26: Li C Y, Mu M Q. Influence of the Indian Ocean dipole on atmospheric circulation and climate. Adv Atmos Sci, 2001, 18: Xiao Z N, Yan H M, Li C Y. The relationship between Indian Ocean SSTA dipole index and the precipitation and temperature over China. J Trop Meteor, 2002, 18: Allan R, Chambers D, Drosdowsky W, et al. Is there an Indian Ocean dipole, and is it independent of the El Niño-Southern Oscillations? CLIVAR Exchanges, 2001, 6: Saji N H, Yamagata T. Structure of SST and surface wind variability during Indian Ocean dipole mode events: COADS observations. J Clim, 2003, 16(16): Yamagata T, Behera S K, Rao S A, et al. The Indian Ocean dipole: a physical entity. CLIVAR Exch, 2002, 24: Ashok K, Guan Z, Yamagata T. A look at the relationship between the ENSO and the Indian Ocean dipole. J Meteor Soc Japan, 2003, 81: Baquero-Bernal A, Latif M, Legutke S. On dipolelike variability of sea surface temperature in the tropical Indian Ocean. J Clim, 2002, 15: Xie S P, Annamalai H, Schott F A, et al. Structure and mechanisms of south Indian Ocean climate variability. J Clim, 2002, 15: Meyers G. Variation of Indonesian throughflow and El Niño/Southern Oscillation. J Geophys Res, 1996, 101(C5): Wang D X, Liu Q Y, Liu Y, et al. Connection between interannual variability of the western Pacific and eastern Indian Oceans in the El Niño event. Prog Nat Sci, 2004, 14(5): Klein S A, Soden B J, Lau N C. Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. J Clim, 1999, 12: Li C Y, Mu M Q, Pan J. Indian Ocean temperature dipole and SSTA in the equatorial Pacific Ocean. Chin Sci Bull, 2002, 47: Shinoda T, Alexander M A, Hendon H H. Remote response of the Indian Ocean to interannual SST variations in the tropical Pacific. J Clim, 2004, 17(2): Saji N H, Xie S, Yamagata T. Tropical Indian Ocean variability in the IPCC twentieth-century climate simulations. J Clim, 2006, 19(17): Kistler R, Kalnay E, Collins W, et al. The NCEP-NCAR 50-year reanalysis: Monthly means CD-ROM and documentation. Bull Am Meteor Soc, 2001, 82: Rayner N A, Parker D E, Horton E B, et al. Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J Geophy Res, 2003, 108 (D14): 4407, DOI: / 2002JD Smith T M, Reynolds R W. Extended reconstruction of global sea surface temperatures based on COADS data ( ). J Clim, 2003, 16: Kaplan A, Cane M, Kushnir Y, et al. Analyses of global sea surface temperature J Geophy Res, 1998, 103: Wang S W, Gong D Y. ENSO events and their intensity during the past century. Meteorology (in Chinese), 1999, 25: Torrence C, Compo G P. A practical guide to wavelet analysis. Bull Am Meteor Soc, 1998, 79: Annamalai H, Xie S P, Mccreary J P, et al. Impact of Indian Ocean sea surface temperature on developing El Niño. J Clim, 2005, 18: Yang H, Jia X L, Li C Y. The tropical Pacific-Indian Ocean temperature anomaly mode and its effect. Chin Sci Bull, 2006, 51: YUAN Yuan et al. Chinese Science Bulletin June 2008 vol. 53 no

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