Variations of Summertime SSTA Independent of ENSO in the Maritime Continent and Their Possible Impacts on Rainfall in the Asian–Australian Monsoon Region

Jing Zhu aCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), International Joint Laboratory on Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing, China

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Zhaoyong Guan aCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), International Joint Laboratory on Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing, China

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Xudong Wang bDepartment of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences, Fudan University, Shanghai, China

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Abstract

The sea surface temperature anomalies (SSTA) in the Maritime Continent (MC) region are mainly related to local variability, ENSO, and the Indian Ocean dipole. Using the reanalysis data from NOAA and NCEP–NCAR, by employing the empirical orthogonal function (EOF) analysis, we have explored the principal mode of ENSO-independent summertime SSTA in the MC and its associations with regional climate anomalies. After ENSO signals have been removed, the leading mode of SSTA in the MC exhibits a uniformly signed pattern, which mainly varies on an interannual time scale. The maintenance mechanisms of the ENSO-independent SSTA are different in different subregions, especially over the region south of Java and the tropical northwestern Pacific. When the time coefficient of the first leading EOF mode (EOF1) is positive, warmer SSTAs are observed in the area south of Java. The oceanic dynamic heating there facilitates the warmer SSTA. Thus, the Gill-type response of the atmosphere is found over the region south of Java. The diabatic cooling in the atmosphere is dominant over the tropical northwestern Pacific where the warmer SSTA is maintained by the absorption of solar radiation due to less cloud cover there. A tilted vertical circulation is hence formed, linking the tropical southeastern Indian Ocean with the tropical northwestern Pacific. The anomalous circulations in the Asian–Australian monsoon region are affected by this ENSO-independent SSTA mode, resulting in decreased summer rainfall anomaly in the region near the southeast coast of China and increased winter precipitation anomaly over the extratropical region of Australia.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Z. Guan, guanzy@nuist.edu.cn

Abstract

The sea surface temperature anomalies (SSTA) in the Maritime Continent (MC) region are mainly related to local variability, ENSO, and the Indian Ocean dipole. Using the reanalysis data from NOAA and NCEP–NCAR, by employing the empirical orthogonal function (EOF) analysis, we have explored the principal mode of ENSO-independent summertime SSTA in the MC and its associations with regional climate anomalies. After ENSO signals have been removed, the leading mode of SSTA in the MC exhibits a uniformly signed pattern, which mainly varies on an interannual time scale. The maintenance mechanisms of the ENSO-independent SSTA are different in different subregions, especially over the region south of Java and the tropical northwestern Pacific. When the time coefficient of the first leading EOF mode (EOF1) is positive, warmer SSTAs are observed in the area south of Java. The oceanic dynamic heating there facilitates the warmer SSTA. Thus, the Gill-type response of the atmosphere is found over the region south of Java. The diabatic cooling in the atmosphere is dominant over the tropical northwestern Pacific where the warmer SSTA is maintained by the absorption of solar radiation due to less cloud cover there. A tilted vertical circulation is hence formed, linking the tropical southeastern Indian Ocean with the tropical northwestern Pacific. The anomalous circulations in the Asian–Australian monsoon region are affected by this ENSO-independent SSTA mode, resulting in decreased summer rainfall anomaly in the region near the southeast coast of China and increased winter precipitation anomaly over the extratropical region of Australia.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Z. Guan, guanzy@nuist.edu.cn

1. Introduction

The Maritime Continent (MC) is a special region located in the Asian–Australian monsoon region and consisting of many islands and shallow marginal seas. It is defined as the area over 10°S–20°N, 90°–150°E (Ramage 1968; Fig. 1), where there are strong interactions among the atmosphere, ocean, and islands. In the east–west direction, the MC separates the tropical Pacific from the tropical Indian Ocean, while the two oceans are connected through the Indonesian Throughflow (Konda et al. 1996); in the north–south direction, the MC behaves as a bridge that links the East Asian monsoon and the Australian monsoon regions. It is also the critical region where the Northern and Southern Hemispheres interact with each other though the cross-equatorial flows (e.g., Findlater 1969; Moore 2013) and their coupling with circulations in the equatorial region (e.g., Chen and Guan 2017).

Fig. 1.
Fig. 1.

Map of the Maritime Continent and the key regions referred to in this study: the Indo-China Peninsula, the Philippines, Kalimantan, Sumatra, Java, and New Guinea.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

The sea surface temperature (SST) anomalies along with the climate in the MC vary on multiple time scales. With regards to the interannual variability, as well known, the SST anomalies (SSTAs) in the Indian Ocean side of the MC are mostly regulated by both the Indian Ocean basinwide mode (IOBM; e.g., Klein et al. 1999; Yang et al. 2007) and the Indian Ocean dipole mode (IOD; Saji et al. 1999). It is found that the IOBM is closely related to ENSO (El Niño–Southern Oscillation) for it is a result of the remote forcing of SSTA in the Pacific (Klein et al. 1999; Alexander et al. 2002; Ashok et al. 2003a). In the Pacific side of the MC, the SST anomalies in both regions around Indonesian islands and the tropical western Pacific are also strongly affected by the ENSO signal via the vertical circulations and equatorial waves. However, it is found that the variability of both ENSO and IOD are not able to account for all the variance of the SSTA variance; there is a lot of local variability of SSTA to be explained (Zhang et al. 2016; Wang and Guan 2017; Xu et al. 2019). Besides of SSTA, climatic variables such as rainfall and outgoing longwave radiation (OLR) in the MC exhibit pronounced interannual variability (e.g., Song et al. 2011; Yang et al. 2019).

Climate variations in the MC are closely related to ENSO (e.g., Ropelewski and Halpert 1987; McPhaden et al. 2006; Spencer and Braswell 2014; Ham et al. 2014; Zhang et al. 2016; Chen and Guan 2017; Zhang et al. 2018; Xu et al. 2019; Hu et al. 2020).It is observed that the largest interannual variability of OLR occurs in the MC, particularly over 10°S–10°N, 95°–145°E (Song et al. 2011) in boreal summer. The area 10°S–10°N, 95°–145°E is referred to as the key Maritime Continent (KMC) (Xu and Guan 2017). In the KMC, the ENSO signal can explain about 70% of the periodic 3–7-yr changes in OLR anomalies (Xu and Guan 2017). The impact of ENSO on precipitation is more pronounced in the relatively dry season (June–August) of the MC, whereas in boreal winter, when precipitation is abundant, the correlation between the ENSO signal and precipitation is weak (Lau and Chan 1983). It is reported that when El Niño occurs, the warm SSTAs in the central eastern Pacific can trigger the atmospheric teleconnection, which results in easterly anomalies in eastern Indonesia and decreased SST and precipitation there. As a result, cold SSTAs occur in the equatorial western Pacific, leading the Walker circulation to weaken (Haylock and McBride 2001; Hendon 2003). The cold SST in the MC region leads to higher sea level pressure and divergence, and precipitation decreases subsequently (Hackert and Hastenrath 1986), inducing drought there (Feng et al. 2010). When El Niño reaches its mature stage in the winter, the easterly anomaly and the corresponding convergence at the southern flank of the anomalous South China Sea (SCS) anticyclone promotes the atmospheric low-level ascending motion over the western MC. The above local convective instability process eventually leads to positive precipitation anomaly in the western MC (Jiang and Li 2018). Note that, since the central and eastern types of ENSO events have been explored, the SSTA as well as climate variations in the MC have been found to be affected by various types of ENSO. The vertical circulations in troposphere and the equatorial Kelvin/Rossby waves play important roles in the connections between two types of ENSO and MC climate anomalies (Tedeschi et al. 2013; Xiang et al. 2013; Zhang et al. 2013, 2014; Zhai et al. 2016; Fang et al. 2016; Wang and Guan 2017; W. Wang et al. 2018).

Climate variations in the MC are also affected by variability over the Indian Ocean, especially on the Indian Ocean side of the MC. During boreal summer, it is found that more (less) than normal precipitation is received in the western (eastern) part of the MC when the IOBM is in its warm phase (Wang and Guan 2017). When a positive IOD event occurs, it may be anomalously dry in the western part of MC whereas flooding occurs in the northern part of the MC (Guan and Yamagata 2003; Xu et al. 2019). Despite the significant influences of IOBM and IOD, it should be noted that the Indian Ocean variability is strongly linked to the variability in the Pacific through the Indonesian Throughflow (e.g., Godfrey 1996) and the atmospheric bridge (e.g., Alexander et al. 2002). Interestingly, it is reported that the mixed diversity of shifting IOD and El Niño is able to dominate the location of Maritime Continent autumn drought (Hu et al. 2020).

Variations of SSTA and other climate variables in the MC can have profound relations with interannual variability of summer precipitation in China. It is found that the large-scale convection in the MC may significantly affect precipitation anomaly in eastern China (e.g., Song et al. 2011; Xu and Guan 2017). The anomalous diabatic heating in the MC, especially in the KMC, may excite a teleconnection pattern from the MC northeastward to East Asia (Huang and Li 1987; Nitta 1987), inducing the anomalous circulation there. More than these, it is also found that the convection in the KMC region can modulate the meridional vertical circulation from the KMC to southwest China, significantly leading to anomalous precipitation there (Xia et al. 2020).

As mentioned above, the SSTA and climate anomalies in the MC vary with large interannual variabilities. They are strongly influenced by ENSO and Indian Ocean variability. The variations such as convective activity as indicated by OLR in MC are found to have strong impacts on East Asian summer climate. However, our previous studies demonstrate that both ENSO and the Indian Ocean signal can explain some parts of the interannual climate variability in the MC region (Xu and Guan 2017; Xu et al. 2019). Large portions of SST variability in the MC are not explained by ENSO as mentioned above. Therefore, it is very important for us to understand how the SSTA changes in the MC after the ENSO signal is filtered out. We hence explore the dominant mode of the MC SSTA independent of ENSO and its maintenance mechanism. Also, the possible impacts of this SSTA mode are investigated.

The present paper is organized as follows. After an introduction, the data and methods used in the present paper are briefly described in section 2. In section 3, the principal mode of the ENSO independent SSTA in the MC is explored and the associated anomalous atmospheric circulations are investigated. The mechanism of SSTA maintenance is revealed. In section 4, the influences of the principal mode of filtered SSTA on the local and regional climate are discussed. Following section 4 is the conclusion of the present work.

2. Data and method

a. Data

The data used in the present study are from the National Oceanic and Atmospheric Administration (NOAA) and include the following: 1) monthly mean sea surface temperature (SST) extracted from OISST, which has a resolution of 1.0° × 1.0° (Reynolds et al. 2002), and 2) monthly mean sea surface height (SSH), potential temperature in the subsurface of the ocean, and ocean current motion extracted from the Global Ocean Data Assimilation System (GODAS; the resolution of these data is 0.33° × 1.0°; Behringer and Xue 2004); 3) monthly mean precipitation from CMAP (Xie and Arkin 1997) and outgoing longwave radiation (OLR) (Liebmann and Smith 1996) in 2.5° × 2.5° grids; and 4) monthly mean winds (u, υ, ω), air temperature (T), and geopotential height (H) at different pressure levels extracted from the NCEP–NCAR reanalysis 1 product in global 2.5° × 2.5° grids, surface net longwave radiation, net shortwave radiation, sensible and latent heat net fluxes, and total cloud cover (Kalnay et al. 1996). The study period covers 1982–2016, and the Northern Hemisphere summer is defined as June–August (JJA). The anomaly of a given variable in the present study refers to the deviation of its JJA mean in a given year from its multiyear (1982–2016) mean JJA value. All time series of data have been detrended before being analyzed.

b. Methods

The empirical orthogonal function (EOF) analysis is implemented to obtain the first leading mode of SSTA. Composite analysis and regressions are also employed in the present study.

To explore the reason for the maintenance of ENSO-independent SSTA in the MC, simple linear regressions are performed of SSTA to filter out ENSO signals. Here, “ENSO-independent” means that the ENSO signals are mostly removed statistically from SSTA and all other time series of data in the present study. It is reported that variations of SSTA and other variables in the Indian Ocean lag the ENSO signal by about 6 months (Klein et al. 1999; Alexander et al. 2002; Ashok et al. 2003a). Hence, not only the JJA but also the preceding December–February (DJF) ENSO signals are all removed out to get the ENSO-independent components of these variables. Note that in the present study, the ENSO signals in JJA and DJF are indicated by the Niño-3 index, which is a time series of seasonal mean SSTA averaged over the Niño-3 region (5°S–5°N, 150°–90°W). It is worked out that the correlation of the JJA (DJF) Niño-3 index with the JJA (DJF) Niño-3.4 index is found to be 0.90 (0.97), suggesting that the canonical Niño-3 index is a good indicator of ENSO even though any given ENSO might be a central or eastern type. Let IN3JJA and IN3DJF be the Niño-3 indices for JJA and DJF, respectively. It is found that the preceding DJF ENSO index IN3DJF is uncorrelated with the following summer JJA ENSO index IN3JJA because the correlation coefficient is as small as 0.04. In contrast, IN3JJA is highly correlated with the following DJF Nino-3 index IN3DJF with a correlation value of 0.79 during 1982–2016. Based on the nature of ENSO in the Indo-Pacific as indicated by the time-lag correlations, we may do filtering using the partial regressions, which are widely used in climate research community (e.g., Cai et al. 2011; Ham et al. 2013). Therefore, suppose that Y′ is the time series of anomalies of a given variable. Then ENSO-independent component Yr can be written as
Yr=YαIN3JJAβIN3DJF,
where α and β are the regression coefficients. Figure 1 exhibits the regression coefficients and the ratio of variance after filtering the total variance of SSTA. It can be seen from Figs. 2a and 2b that a large part of the ENSO-related component is indeed removed from the SSTA in the MC region, especially in areas north of equator. After having the ENSO signals removed out, the ENSO-independent component of SSTA explains 40%–60% of the total SSTA variance in most parts of the MC (Fig. 2c). This means that there is still a large part of total variance that need to be explained.
Fig. 2.
Fig. 2.

Distributions of regression coefficients (a) α and (b) β (unit: °C) for JJA mean SSTA during 1982–2016, and (c) the ratios (%) of variance of filtered SSTA (Yr) to total variance of SSTA (Y′). The black rectangular frames indicate the Maritime Continent region (10°S–20°N, 90°–150°E).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

To understand the atmospheric response to the diabatic heating in the MC region, we compute the apparent atmospheric heat source Q1 (Yanai 1973; Luo and Yanai 1984). Let 〈Q1〉 be the vertical integral of Q1 from the Earth surface Ps up to the top isobaric level Pt (Pt = 300 hPa), which is expressed as Q1=(1/g)PtPsQ1dp. Then the equation for computing 〈Q1〉 can be written as
Q1=CP[Tt+VT+(PP0)kωθP].
On the right-hand side of Eq. (2), the vertically integrated local change, horizontal advection, and vertical advection of atmospheric temperature are presented, respectively. Note that 〈Q1〉 = (LPr + LCLE) + Qs + 〈Qr〉, with L being the latent heat of condensation, Pr the amount of precipitation, E the evaporation of cloud drops in the column, C the total amount of liquid water from water vapor condensation, Qs the surface sensible heat flux, and 〈Qr〉 the vertically integrated radiative heating (cooling).
The wave activity flux (WAF) is calculated to diagnose the Rossby wave energy propagations in the present study, which follows Takaya and Nakamura (2001). The horizontal component of the WAF is in pressure coordinates is expressed as
W=Wr+CUM,
Wr=12|V¯|[U¯(ψx2ψψxx)+V¯(ψxψyψψxy)U¯(ψxψyψψxy)+V¯(ψy2ψψyy)],
where V¯ is the background flow (V¯=U¯i+V¯j), CU the phase speed relative to the background flow (CU=CPV¯/|V¯|), W the wave activity flux (TN fluxes hereafter) parallel to the group velocity, Wr the wave disturbance energy flux excluding CUM, and ψ′ the perturbation of quasigeostrophic streamfunction. Wave activity intensifies (weakens) in places where the WAF Wr converges (diverges) for quasi-stationary waves.
Thermal diagnostic analysis of the oceanic mixed layer is conducted in the present study to reveal the mechanism for SST changes in the MC. The thermodynamic diagnosis equation of the mean mixed layer (Su et al. 2010, 2014; Chen et al. 2015; Jin et al. 2017; Chen and Li 2018) is expressed as
Tot=AadvAupw+μ(S w+L w+S h+L h)+Rs,
where Aadv and Aupw are expressed as
Aadv=(uoT¯ox+u¯oTox+uoTox)+(υoT¯oy+υ¯oToy+υoToy),
Aupw=woT¯oz+w¯oToz+woToz.
In Eqs. (5)(7), T and (u, υ, w) represent the ocean mixed layer temperature and three-dimensional oceanic current velocity, respectively. Variables Sw, Lw, Sh, and Lh represent shortwave and longwave radiation and sensible and latent heat fluxes, respectively. The quantity μ = 1/(ρHCP) with ρ, Cp, and H being the seawater density, seawater specific heat, and mixed layer thickness, respectively The term Rs represents the residual. The subscript o is for ocean while the prime (′) is for the anomaly. The quantity Aadv represents the dynamic heating due to horizontal advection whereas Aupw represents the dynamic heating due to upwelling/downwelling.

3. ENSO-independent SSTAs in the MC and their relations with circulation

a. The principal mode of SSTA independent of ENSO

EOF decomposition is performed for the filtered SSTA (Yr) and two leading EOF modes are obtained. These two EOF modes (hereafter EOF1 and EOF2) of SSTAs that exclude ENSO signals in the MC are well separated from each other (North et al. 1982). EOF1 accounts for 42.4% of the total variance, which is much larger than that accounted for by EOF2 (12.0%).

EOF1 exhibits almost uniformly positive SSTA over the entire MC (Fig. 3a). When the time coefficient (PC1) of EOF1 is positive, SSTA warming is found in the South China Sea and southern MC. The time series of ENSO-independent SSTA averaged over the MC region (Fig. 3b) looks to be in agreement with the time series of PC1; the correlation between these two time series is 0.96, indicating that EOF1 is indeed a major mode of filtered SSTA in the MC region. Because of the high correlation between PC1 and filtered SSTA averaged over the MC, here we use the PC1 as the index of ENSO-independent SSTA averaged over the entire MC for composite analysis. Spectral analysis of PC1 (Fig. 3b) reveals that the EOF1 has significant periods ranging from 3 to 5.5 years (Fig. 3c). The spatial pattern of simultaneous correlation between PC1 and filtered SSTA resembles EOF1 (Fig. 3d). As the EOF1 mode is so significant even though ENSO signals are removed, we therefore consider that the SSTA components independent of ENSO in the MC may play important roles in the atmosphere–ocean coupling in the MC region.

Fig. 3.
Fig. 3.

(a) Spatial pattern of the leading EOF mode (EOF1) of JJA mean SSTA in the MC during 1982–2016 with ENSO signals being filtered out and (b) the normalized time series of PC1 (filled bars) and ENSO-independent SSTA averaged over the MC (black curve). (c) Power spectrum of PC1 (solid thick line) and red noise spectrum at 60% (long-dashed line) and at 90% (short-dashed line) confidence levels. (d) Simultaneous correlations of PC1 with filtered SSTA. Only correlation coefficients exceed 90% confidence level are shown.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

Note that the ENSO influences are mainly dominant in regions north of equator in MC as seen in Fig. 2c. More than 50% of SSTA variance cannot be well explained by ENSO signals in regions south of the equator. Both spatial patterns as seen in Figs. 3a and 3d exhibit large values in regions south of equator, consistent with larger percentages in southern part of MC as displayed in Fig. 2c. Additionally, if we examine the spatial pattern of correlations between PC1 and the original SSTA without removing the ENSO signals (not shown), it is found that the spatial pattern looks very similar to that seen in Fig. 3d, suggesting that there are still large SSTA variations independent of ENSO in the MC (Fig. 2c). Further, if we check the correlation between PC1 and the domain-averaged original SSTA in MC, it is found that correlation coefficient amounts to 0.73, suggesting that about 53.3% of the total variance of domain-averaged original SSTA can be explained by PC1. This all further confirms that the EOF1 as derived from the filtered SSTA is also an important mode of SSTA in addition to the ENSO-related variability.

b. Relations with atmospheric circulation anomalies

To reveal the mechanisms of the ENSO-independent SSTA variations, composite analysis is conducted for circulations in the upper and lower troposphere based on some years with large positive and negative PC1 values. Those years are selected when the values of normalized PC1 (Fig. 3b) are larger than 0.75 or smaller than −0.75 (Table 1). Note that some selected years are very similar to those in Table 1 if using the time series of filtered MC-averaged SSTA (Fig. 3b). Besides, some selected years are IOD years such as 1994, 2004, and 2007. Indeed, the PC1 is strongly related to IOD with the correlation amounting to −0.75. However, the spatial pattern in Fig. 3d suggests that the temporal correlation between PC1 and IOD might be spurious since the SSTA in the tropical western Indian Ocean is insignificant. Only the eastern pole of IOD is related to the leading ENSO-independent mode in the MC.

Table 1

Years with high and low values of normalized PC1 (Fig. 2b) of ENSO-independent SSTA in the MC region.

Table 1

The EOF1 mode-related anomalous atmospheric circulations are formed as a response of the atmosphere to the thermal forcing associated with the filtered SSTA in the zonal region around 5°–10°S. The composite circulations (Fig. 4) show that at the lower troposphere above the MC, the atmosphere diverges over the northwestern Pacific (Fig. 4a), whereas it converges into oceanic regions of the MC south of the equator. An anomalous cyclonic circulation at 850 hPa is observed over the northeastern tropical Indian Ocean, which can be explained by the Gill-type response (Gill 1980) in addition to some Kelvin wave–related zonal wind anomalies over the equatorial MC region. At 200 hPa (Fig. 4b); however, a significant convergence anomaly occurs above the northwestern Pacific where the significant anomalous velocity potential at 200 hPa is observed (not shown), while pronounced divergence can be found over the equatorial southeastern Indian Ocean and oceanic belt region between Indonesia and the northern part of Australia, exhibiting an opposite anomalous circulation pattern in the upper troposphere as compared to that in the lower troposphere. Corresponding to the divergence anomalies, a strong cyclonic circulation (significant above 90% level of confidence; not shown) is observed at 850 hPa over northern Indian Ocean, and two anticyclonic circulations (marginally significant at 90% level of confidence, in the northern and southern portions of the Pacific side of the MC, respectively; not shown) (Fig. 4a).

Fig. 4.
Fig. 4.

(a) The composite differences of SSTA (shaded; unit: °C), anomalous divergent winds (arrows; unit: m s−1), and circulations (streamlines) at 850 hPa in JJA over the MC between selected positive and negative PC1 years (positive minus negative). (b) Shaded contours show the anomalous vertical velocity ω at 500 hPa, which is arbitrarily amplified by −100 Pa s−1. (c) Cross section of vertical circulation along the tilted line from 10°S, 92.5°E to 15°N, 152.5°E, as displayed in (a). (d) The meridional vertical circulation averaged over 90°–150°E. Red arrows in (a)–(d) as well as stippling in (a) and (b) indicate that values are significant at or above 90% level of confidence for the divergent wind components and SSTA, respectively. In (c) and (d), the vertical circulations are displayed with horizontal component of divergent wind anomalies and vertical component of the anomalous vertical velocity ω multiplied arbitrarily by −100. The vertical velocities in (c) and (d) above 90% level of confidence are shaded.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

The atmosphere responds to the anomalous thermal forcing in region south of Java Island (Fig. 5d), significantly inducing westerly anomalies over the equatorial Indian Ocean (Fig. 4a) between two anomalous cyclonic circulations that appear respectively over the northern and southern Indian Oceans. As the anomalous heating south of Java is not symmetric about equator, the Kelvin wave is excited, resulting in the weak easterly winds in the equatorial western Pacific (Gill 1980). Meanwhile, the anomalous diabatic cooling (Fig. 5d) in the atmosphere occurs over the western equatorial Pacific, which excites a pair of anomalous anticyclone near 10°N, 140°E over the tropical northwestern Pacific and near 5°S, 140°E over New Guinea. The weak anomalous easterly winds over the equatorial region east of the Philippines also result from the Gill-type atmospheric response to the diabatic cooling (Fig. 5d). Consequently, the anomalous westerly winds are observed in the southern flank of the anomalous anticyclone near New Guinea. The anomalous anticyclonic circulation near New Guinea in the Southern Hemisphere facilitates the maintenance of the warmer SSTA in region under this anomalous anticyclone because of the equatorward Coriolis force exerted on the sea surface, as is well known. Moreover, the anomalous westerly winds occur from Java all the way southeastward to the east coast of Australia. Due to the anomalous equatorward Coriolis force acting on the surface water in the westerly wind region, the warmer water converges into the sea area between Indonesia and Australia. Therefore, the circulation pattern as seen in Fig. 4a in turn favors the formation and maintenance of warm SSTAs from Java to northern Australia.

Fig. 5.
Fig. 5.

The composite mean differences of (a) anomalous sensible heat fluxes (unit: W m−2), (b) latent heat fluxes (unit: W m−2), (c) total cloud coverage (%), and (d) the diabatic heating rate (unit: W m−2) between larger positive and negative PC1 years. Negative values in (a) are for the upward sensible fluxes while positives for downward fluxes. Stippled areas are for values at/above 90% level of confidence using a t test.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

In the northwestern Pacific, the formation and maintenance of the anomalous anticyclonic circulation is associated with the significant downward motion and weak divergence around 5°N, 155°E (Figs. 4a,b). Besides, the warmer SSTA (Fig. 4a) and the related upward motion at 500 hPa (Fig. 4b) in the south of Java Island also excite an anomalous anticyclone over the tropical northwestern Pacific through the Kelvin wave–induced Ekman divergence. The anomalous northeasterlies weaken the southwesterly monsoon wind. As a result, the SSTA in the northwestern Pacific is increased (Wang et al. 2006; Xie et al. 2009, 2016). The northern part of the South China Sea (SCS) is under the influence of the anomalous anticyclonic circulation at 850 hPa (Fig. 4a) whereas the Bay of Bengal along with the southern part of the SCS is under the anomalous cyclonic circulation. In these two regions, the maintenance of the warmer SSTA may attribute to different mechanisms, which will be discussed later.

The PC1-related anomalous vertical circulations (Figs. 4c,d) demonstrate the interactions between the northwestern Pacific and the southeastern Indian Ocean and between oceanic regions in the Southern and Northern Hemispheres via atmospheric bridges in the MC sector. It is seen from Fig. 4a that the ENSO-independent SSTAs vary in spatial extent although the sign of EOF1-SSTA is almost uniformly positive over the MC when PC1 is positive. A distinct SSTA gradient is observed from the northwestern Pacific to Java. Such an SSTA gradient can induce vertical atmospheric circulation between the northwestern Pacific (15°N, 152.5°E) and south of Sumatra (15°S, 92.5°E) (Fig. 4c).

In fact, over the region south of Sumatra and Java, the surface air anomalously converges (Fig. 4a) and the atmosphere at 200 hPa anomalously diverges (Fig. 4b). This anomalous convergence in the lower troposphere (Fig. 4a) is triggered by the anomalous diabatic heating due to the anomalously warmer sea surface there (Figs. 4a,b), inducing the anomalous upward motions (Fig. 4b) over the region south of Java. Particularly, the sensible heat fluxes are significantly negative over the oceanic region south of Java Island (Fig. 5a), indicating that the atmosphere is anomalously heated there. Correspondingly, large negative latent heat fluxes are also observed in region south of Java (Fig. 5b) along with increase of clouds there (Fig. 5c). These indicate that the atmosphere is possibly heated by the latent heat release as long as the anomalous upward motion occurs there. In fact, the anomalous convergence in the region south of Sumatra and Java intrinsically induces the anomalous upward motion there (Figs. 4b,c), which results in more latent heat release in the region south of Java. Further, more latent heat release will induce stronger upward motion there. In this way, a positive feedback relationship establishes between the upward motion and the anomalous vapor condensation-induced diabatic heating (e.g., Kuo et al. 1991).

However, in the northwestern Pacific where the downdraft of atmosphere is observed the ocean surface also warms, although it is not as strong as it is in area south of Java Island. This warmer SSTA may result from the absorption of more than normal solar radiation due to significantly less cloud cover (Fig. 5c). As seen in Fig. 5d, the atmosphere is significantly heated (positive 〈Q1〉) over southwestern part of the MC while it is cooled (negative 〈Q1〉) over the western Pacific, resulting in the anomalous upward motions in the regions around Java and Sumatra and downward motions in the northwestern Pacific. This may relate to the positive feedback mechanism between anomalous latent heat release and vertical motion (e.g., Kuo et al. 1991). Although marginally diabatic cooling is observed over South China Sea, similar explanations can still be made for the meridional circulations (Fig. 4d).

Note that circulations related to the ENSO-independent SSTA mode over the entire MC (Fig. 4) are dominated by the diabatic heating (Fig. 5d) in the southeastern Indian Ocean far away from the equator and the relative diabatic cooling in the northwestern Pacific. If positive SSTA occurs near equator in the KMC and heats the atmosphere, then Kevin waves would develop in the equatorial region via the Gill-type response (Gill 1980). In our case, the anomalous diabatic heating locates in region south of Sumatra, which is asymmetric about equator. The Kelvin wave in equatorial region is still developed, which is indicated by some easterly wind anomalies in 130°–150°E. Interestingly, these anomalous easterly winds facilitate the formation of two anomalous anticyclonic circulations at 850 hPa respectively over both sides of the equator (Fig. 4a) in the eastern part of the MC (Xie et al. 2009, 2016). Note that the pattern with a pair of anticyclonic circulations over the eastern part of the MC looks similar to the mixed wave pattern that corresponds to the case n = 1 as proposed by Matsuno (1966).

c. Relations with oceanic circulation anomalies

The first leading mode of SSTA is intrinsically associated with oceanic circulation anomaly. The simultaneous correlation coefficients of PC1 with the sea surface height anomaly and oceanic circulation anomaly averaged over 5°S–5°N and 10°–5°S are displayed in Fig. 6. It can be seen in Fig. 6a that a positive sea surface height anomaly appears to the west of the MC with the largest value located at the southwestern MC, suggesting that warm seawater is advected to this region. This is in agreement with the anomalous westerly winds near equatorial Indian Ocean in the lower troposphere (Fig. 4a). In fact, the westerly winds lead to a Coriolis force that drives water parcels near the sea surface to move toward the equator while the wind-driven sea current causes the seawater to converge into regions around Sumatra and Java. In this process, the oceanic Kelvin waves are excited in the equatorial Indian Ocean. As a result, the subsurface of the ocean deepens more in this region than in other places, favoring maintenance of warm SSTAs on the Indian Ocean side of the MC (Cai et al. 2009; Du et al. 2012).

Fig. 6.
Fig. 6.

(a) Simultaneous correlations of PC1 with sea surface height, and subsurface sea temperature averaged over (b) 5°S–5°N and (c) 10°–5°S. Arrows in (b) and (c) represent the circulation related to PC1 with the averaged zonal and vertical ocean flows. Shaded areas are for values at or above 90% confidence level using a t test. Green arrows in (b) and (c) show the subsurface currents at or above the 90% level of confidence.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

The oceanic subsurface temperature anomalies and anomalous ocean current distribution zonally averaged over 5°S–5°N (Fig. 6b) agree well with the sea surface height anomaly. Note that warm water above 50-m depth climatologically distributes uniformly in the equatorial Indian Ocean (not shown). In the layer from 50 m down to 150 m, the temperature changes greatly in vertical, showing the thermocline layer there. The oceanic currents are dominantly westward in the layer above 150 m. In the equatorial western Pacific above 150 m, the temperatures change in a similar way as in the Indian Ocean but the direction of the currents reverses (not shown). Under this climatological background, the abnormal eastward subsurface ocean current above 100 m in the area between 60° and 90°E and the abnormal westward ocean current between 125° and 150°E (Fig. 6b) are consistent with the distribution of 850-hPa zonal wind anomalies. Both the anomalous oceanic currents on the Indian and Pacific sides are favorable for the surface seawater to converge into the MC, leading to the maintenance of positive anomalies of subsurface temperature, and henceforth being favorable for the positive anomalies of SST. It is seen from Fig. 6b that, between 90° and 150°E, the subsurface temperature anomalies are positive above 100-m depth. For depths of 100 m downward, the anomalous subsurface temperature is positive between 85° and 100°E and weakly negative below 200 m, while the ocean current moves abnormally westward between 60° and 100°E and eastward between 120° and 140°E. In the region south of 5°S, warmer temperatures are observed between 95° and 150°E above 80-m depth (Fig. 6c). This scenario looks a little different from that in Fig. 6b. It is noticeable that in the equatorial region, the warmer subsurface temperatures in both the Indian Ocean and the Pacific are induced by oppositely oriented ocean currents (Fig. 6b). In the equatorial Indian Ocean, the maintenance of the positive subsurface temperature anomaly is strongly related to the eastward anomalous ocean currents that lead to warmer water parcel moving to the western boundary along Sumatra. However, in the equatorial western Pacific east of 120°E, the anomalous easterly winds (Fig. 4a) along with the westward ocean currents tend to make the water diverge poleward, not facilitating the warmer subsurface water to be in the equatorial region. The maintenance of positive SSTA and anomalous subsurface temperature may contribute to both the warmer water moving westward to the west boundary near the Kalimantan Island and absorption of more solar radiation there. That is to say, the ocean current must play an important role in the formation and maintenance of the first leading mode of SSTA in the MC region. To further explore the mechanism for the maintenance of the EOF1 in the MC, the thermodynamic equation of the oceanic mixed layer is implemented for diagnostic analysis.

d. Thermodynamic features of the oceanic mixed layer

The temperature change in the oceanic mixed layer is affected by the local oceanic current and heat flux as explained clearly by the mixed layer thermodynamic equation Eq. (3). The ocean current influences are determined by the temperature advection term Aadv and vertical transport term Aupw. Particularly, the temperature advection term includes the zonal term Tu and meridional term Tυ. The heat fluxes depend on the shortwave radiation μSw′, longwave radiation μLw′, sensible heat flux μSh′ and latent heat flux μLh′. To further explore the maintenance mechanism of the ENSO-independent SSTAs that distribute with the same sign in the MC, individual terms of the mixed layer thermodynamic equation are diagnosed (Table 2) over six subregions where the warm SSTA values are relatively larger. It is seen from Fig. 7 that the distribution of composite SSTAs exhibits two belts with large values in and around the MC. One is in the northern MC in the Northern Hemisphere from the Bay of Bengal, southeastward to South China Sea, and then to the northwestern Pacific near the equator. The other belt is in the Southern Hemisphere from the region south of Sumatra, southeastward to the northern coast of Australian continent and then to northeastern coast of the continent. We roughly define six subregions along these two larger SSTA belts for different geographic areas. These six subregions are referred to as box A for the area south of Java (5°–15°S, 100°–117.5°E), box B for the Bay of Bengal (10°–20°N, 80°–100°E), box C for the South China Sea (5°–18°N, 110°–120°E), box D for the northwestern Pacific (0°–12.5°N, 132.5°–145°E), box E for the southern MC (7°–15°S, 125°–140°E), and box F for oceanic area near eastern Australia (12°–30°S, 150°–165°E) (Fig. 7). Note that boxes A and B are on the Indian Ocean side, boxes B and D on the Pacific side, and boxes E and F in the middle area of the southern and northern belts of larger SSTAs. The primary factors that lead to the warm SSTA in each subregion are analyzed, especially for boxes A and D.

Fig. 7.
Fig. 7.

Illustration of boxes for different subregions as indicated by blue rectangular frames. Shaded contours indicate the composite mean differences of SSTA (unit: °C). Stippled areas indicate values at or above the 90% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

Table 2

Individual terms (×10−8 K s−1) of the mixed layer thermodynamic diagnostic equation over subregions in the MC region. The downward (upward) surface flux is defined as positive (negative) for ocean components in Eq. (5).

Table 2

The variations of SSTA are dominated by different factors in different areas of the MC region. As seen from Table 2, in all six boxes the SSTAs tend to increase with different tendencies when PC1 is positive.

In box A near Java Island, temperature advection makes positive contributions to the mixed layer SST change due to the joint effects of the positive zonal ocean current anomaly and positive meridional ocean current anomaly, consistent with the eastward oceanic currents (Fig. 6c) that tend to drive warmer water to move equatorward in this region. The anomaly of vertical transport is also positive (Table 2), suggesting a possible downwelling that relates to the convergence of surface warm water and positive anomalous sea surface height there (Fig. 6). However, the total heat flux is −5.25, which tends to cancel the SSTA to increase although the net longwave radiation (1.55) that reaches the ocean surface is more than normal due to more clouds there (Fig. 5c). The net shortwave radiation, the sensible heat flux, and the latent heat flux are all negative, suggesting that the ocean area in box A loses heat. On the contrary, the atmosphere over box A gets heat from the ocean. The anomalous diabatic heating forces the atmosphere to respond and hence produce stronger than normal updraft, inducing more clouds in this region. Note that, as seen in Table 2, the residual part in the box A region amounts to 5.43 × 10−8 K s−1, which looks to play a more important role in maintaining the SSTA tendency to be positive in the box A region. However, it is not easy to estimate the residual term by computing and analyzing the different processes in the residual part although we know it consists of effects from the subgrid oceanic processes and the errors induced by model bias, computational errors, and the observational data discrepancies. This needs to be investigated in the future.

The mechanism of maintaining higher than normal SST in the box D region is much different from that in box A. In box D over the northwestern Pacific, besides the dynamic heating due to both horizontal and vertical advection, the anomalous sea surface warming is mainly due to anomalous absorption of the shortwave radiation; the μSw′ amounts to 2.00 (×10−8 K s−1). This is in agreement with the anomalously less cloud covers there (Fig. 5c). The other components of diabatic heating including μLw′, μSh′, and μLh′ are all negative (Table 2), suggesting that these three negative diabatic heatings lead to the ocean surface to cool, which cancels the warming tendency due to μSw′. Note that over the western Pacific around box D the atmosphere is cooled rather than heated, which is clearly observed in the negative anomalies of apparent diabatic heating source there (Fig. 5d). Because of the anomalous descent of atmosphere, fewer clouds are observed over box D, inducing more absorption of solar radiation there (Table 2). Besides, the ocean in box D is heated due to dynamic process of ocean currents in this region. In other regions in the MC, the maintenance of positive SSTA is due to different heating processes, which are more or less similar to those in boxes A and D as seen in Table 2.

In box B, in addition to the residual part, the positive anomalous horizontal advections play a dominant role in the warmer SSTA in the Bay of Bengal (Table 2). However, the positive anomalous zonal advection along with the positive anomalous shortwave radiation dominates the warmer SSTA in the South China Sea region (box C). In the southern MC (box E) and region east of Australia (box F), the warm SSTAs are dominantly induced by the heat flux anomalies, especially the positive anomalous longwave radiation and latent heat fluxes. In fact, because the sea region east of Java is covered by the northern half of the anomalous cyclonic circulation centered at the south coast of Australia (Fig. 4a), marginally more clouds (Fig. 5c) prevent longwave radiation from going out the atmosphere (Table 2 for box E), which also favors the SST to be higher than normal (Fig. 4a).

Therefore, the ocean current and diabatic heating flux have different impacts on the maintenance of SSTA in these six boxes. More than this, it is found that the process of ocean influences the atmosphere in the southern MC whereas the process of atmosphere influences the ocean in the northern MC.

4. Climate anomalies related to ENSO-independent SSTA in the MC and monsoon regions

The leading mode of ENSO-independent SSTA in the MC significantly influences local and regional precipitation. In the warm phase of the EOF1, significantly increased and decreased precipitation anomalies occur in some parts of the southwestern and northeastern MC region, respectively. These can be seen from distributions of both anomalous precipitation (Fig. 8a) and OLR (Fig. 8b). The positive center is located to the south of Sumatra, which corresponds to the convergence center in the lower troposphere and divergence center in the upper troposphere (Figs. 4a,b). Pronounced ascending motion in this region (Figs. 4b,c) promotes convective activities and favors positive precipitation there. This anomalous ascent of air results from the anomalous diabatic heating over the warmer ocean south of Sumatra (Fig. 5d) and is enhanced by the anomalous latent heat release for the positive feedback relation between latent heat release and vertical motion (e.g., Kuo et al. 1991). On the contrary, the anomalous low-level divergence and upper-level convergence above the northwestern Pacific, which is partly a response of atmosphere to the diabatic cooling, result in descending motion in this region, prohibiting more precipitation there.

Fig. 8.
Fig. 8.

(a) Composite anomalous rainfall (unit: mm) and (b) the corresponding OLR (unit: W m−2) in the summer (JJA) over the MC and its surrounding regions. Stippled areas indicate anomalies exceeding the 90% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

Note that the climate anomalies on the Pacific side are strongly associated with the anomalous anticyclonic circulation over box D. This anomalous anticyclonic circulation over box D is probably a result from the box A heating-induced Kelvin wave that produces the easterly equatorial winds (Xie et al. 2009, 2016) as aforementioned. As the easterly winds at 850 hPa weaken zonally from Sumatra eastward toward 170°E in the equatorial western Pacific (∂u′/∂x > 0), the anomalous positive divergence may be induced in the equatorial western Pacific due to both the zonally weakening easterly winds and the poleward Coriolis force associated with these easterly winds. This anomalous divergence henceforth yields the anomalous downward motion there. Furthermore, the diabatic cooling is generated in the region where anomalous descent of air occurs (Fig. 5d), which in turn forces the atmosphere to respond (Gill 1980), reinforcing the anomalous anticyclonic circulation northwest of the cooling center. In this way, the descent of air over box D is then intensified due to the well-known Ekman pumping in the anomalous anticyclonic circulation in the lower troposphere.

The ENSO-independent SSTA in the MC region may have impacts on the East Asian summer monsoon climate. It is found that more than normal precipitation occurs in eastern China (marginally significant at 90% level of confidence) and northeastern Japan (Fig. 8a). The dynamics behind this impact on East Asian summer monsoon are similar to the Pacific–Japan (PJ) or East Asia–Pacific (EAP) teleconnection patterns (Nitta 1987; Huang and Li 1987). This kind of teleconnection was also discussed in the context of a significant IOD event in 1994 (Saji et al. 1999), displaying an anomalous cyclonic circulation over the southern China along with an anomalous anticyclonic circulation over Yangtze River Valley where the record-breaking hot summer occurred in 1994 (Guan and Yamagata 2003). Recently, we have investigated the influences of the MC SSTA variability on the East Asian summer monsoon, also exhibiting the teleconnection pattern from the northwestern Pacific northeastward to regions around Japan (Xu and Guan 2017; Xu et al. 2019) based on the variations of anomalous OLR. Here, it is seen from Fig. 9a for 850 hPa that the wave activity fluxes (WAFs) emanate from the northern part of the Philippines and the South China Sea northeastward to the Korean Peninsula, triggering an anomalous anticyclonic circulation over southeast coast of China and an anomalous cyclonic circulation over the Korean region. The anomalous anticyclonic (cyclonic) circulation leads to the marginally significant dryer climate condition over parts of regions from the Philippines northeastward to the south of Japan (wetter climate in eastern China and northeastern Japan) (Fig. 8a). Note that the anomalous circulations over the southeastern part of China display a baroclinic vertical structure (Fig. 9b). Further, WAFs at 200 hPa demonstrate that the East Asian climate is affected by the disturbances from upstream in the westerlies (Fig. 9b).

Fig. 9.
Fig. 9.

Composite anomalous vorticity (shading; unit: s−1) and TN fluxes (red arrows; unit: m2 s−2) at (a) 850 and (b) 200 hPa in the summer (JJA) over the MC and its surrounding regions. Stippled areas indicate anomalies exceeding the 90% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-21-0783.1

The Australian winter climate is also influenced by the ENSO-independent SSTA in the MC. When the PC1 is in its positive phase, more than normal rainfall is significantly observed in the extratropical Australian continent (Fig. 8a), corresponding to the anomalous vertical motion (Fig. 4b) that extends from the southeast equatorial Indian Ocean southeastward to area near 35°S, 150°E. This pattern of influence on Australian climate looks somewhat similar to the influence of IOD (Ashok et al. 2003b) if a negative IOD event occurs. The reason why more precipitation is received in extratropical Australia is that the Australian winter monsoon at 850 hPa is significantly weakened due to both the positive SSTA in region south of Java (Fig. 4a) and the anomalous apparent cooling in the equatorial western Pacific. An anomalous cyclonic circulation is generated over the south Indian Ocean southwest of Java. The anomalous westerly winds in the northern flank of this anomalous cyclonic circulation extend into northwestern Australia. Meanwhile, an anomalous anticyclonic circulation is excited over New Guinea (Fig. 4a). The anomalous westerly winds in the southern flank of this anticyclonic circulation also extend into northern Australia. The anomalous westerly winds over the north Australian region facilitate a weak Australia winter monsoon. This anomalous cyclonic circulation over southeast tropical Indian Ocean extends toward Australia (Fig. 4a), causing Australian rainfall to increase directly (Fig. 8). The WAFs in Fig. 9b indicate that the associated Rossby wave energy propagates from the tropical southeastern Indian Ocean into Australia, facilitating the maintenance of the anomalous cyclonic circulation, inducing more precipitation there. Note that the Rossby wave energy from the westerly in the southern midlatitudes (Fig. 9b) also propagates into the Australian region, influencing the Australian monsoon anomalies.

5. Conclusions and discussion

The SSTA variations in the MC region during boreal summer are strongly influenced by ENSO. After having the signals of preceding wintertime and concurrent summertime ENSO removed from MC SSTA, the principal mode of ENSO-independent SSTA is extracted using the EOF analysis. The maintenance mechanisms of the principal mode of ENSO-independent SSTA in the MC and its influences on local and regional climate are investigated in the present study. The main conclusions are as follows.

The first leading mode of the ENSO-independent SSTA in boreal summer over the MC region exhibits a uniformly signed feature over the entire MC and has significant periodic 3–5.5-yr variability on the interannual time scale. The composited SSTA in the MC exhibits two belts with large SSTA values in and around the MC. One is in the northern MC in the Northern Hemisphere from the Bay of Bengal, southeastward to South China Sea, and then to the northwestern Pacific near the equator. The other belt is in the Southern Hemisphere from the region south of Sumatra, southeastward to the northern coast of the Australian continent and then to northeastern coast of the continent. Particularly, relatively larger positive SSTAs are found in regions near Sumatra and Java, the channel area between the Indonesian archipelagos and Australia, the oceanic area northeast of Australia, the Bay of Bengal, the South China Sea, and the tropical northwest Pacific when this uniformly signed ENSO-independent SSTA mode is in its positive phase. In general, this mode exhibits a very interesting feature in air–sea interactions; it mainly relates to the process of ocean influencing the atmosphere in the southern MC whereas it mainly relates to the process of atmosphere influencing the ocean in the northern MC.

The maintenance of the principal mode of the ENSO-independent SSTA in the MC region is closely associated with ocean current and sea surface heat flux anomalies, but roles of the currents and fluxes are different in different subregions in the MC. When the PC1 in its positive phase, the anomalous dynamic heating due to advections by both horizontal and vertical motion of seawater is all positive in subregions including box A near Java, box B in the Bay of Bengal, box C in the South China Sea, and box D in the northwest tropical Pacific. The positive dynamic heating anomalies are favorable for the warmer SSTA maintenance in these subregions. However, the negative anomalous total diabatic heating is not favorable for the increase and maintenance of a warmer than normal mixed layer of the ocean in the above subregions. Particularly, larger dynamic heating tendency in box A south of the Java Island is canceled by a larger negative tendency due to both shortwave radiation and sensible heat fluxes in the box A area, suggesting that the atmosphere over box A is anomalously heated. However, in box D in the tropical northwest Pacific the ocean mixed layer is heated by more absorption of anomalous shortwave radiation in addition to weak positive dynamic heating, suggesting that the warmer SSTA results mainly from absorbing more solar radiation, which is in contrast to that in box A south of Java.

The ocean–atmosphere interactions in the MC region occur differently over different subregions. When the PC1 is in its positive phase, the warmer ocean near Java forces the atmosphere to respond (Matsuno 1966; Gill 1980), resulting in the anomalous convergence over the tropical southeastern Indian Ocean and henceforth facilitating an anomalous cyclonic circulation southwest of Java Island. The anomalous westerly wind in lower troposphere on the northern flank of this anomalous cyclonic circulation in turn drives the ocean surface water to converge into oceanic region south of Java, facilitating the higher than normal sea surface height and warmer SSTA there by the Coriolis force and SST advections. Meanwhile, an anomalous convergence center at 850 hPa and an anomalous divergence center at 200 hPa are generated over box A near Java. On the contrary, over box D in the tropical northwestern Pacific, an anomalous divergence center at 850 hPa and an anomalous convergence center at 200 hPa are generated due to the diabatic cooling there. A positive feedback mechanism between anomalous vertical motion and anomalous latent heat release works in these regions. As a result, a tilted vertical circulation is generated with the ascending branch over the tropical southeastern Indian Ocean and the descending branch over the tropical northwestern Pacific. Therefore, the southeastern part and the northeastern part of the MC are connected with each other during the interaction between the northwest Pacific and the east Indian Ocean in the tropical region.

The ENSO-independent SSTA mode in the MC region may induce local and regional precipitation anomalies. During the positive phase of PC1, precipitation decreases in the northeastern MC region with the center located above the northwestern Pacific including the Philippines and New Guinea. Meanwhile, increased rainfall is found in the southwestern MC with the center located south of Sumatra and Java. Moreover, the East Asian summer monsoon is influenced to some extent, inducing anomalously dry climate conditions in regions near the southeast coast of China. The Australian winter monsoon is also affected, leading to more than normal precipitation in the extratropical Australian continent during the positive phase of PC1.

Since the SSTA variations are very complicated in association with ENSO, fully filtering out the influences of ENSO signal from SSTA in the MC is not reasonable. However, it is still possible to remove most of the ENSO signal as we do in the present paper. The simultaneous correlation between the Niño-3 and Niño-3.4 indices is 0.97 for boreal winter whereas it is 0.90 for boreal summer, suggesting that it is rational to use the Niño-3 index when doing filtering. The correlation of the Niño-3 index in boreal winter with that in the following spring (the former fall) is 0.96 (−0.07), suggesting that employing the DJF and JJA mean Niño-3 indices would also be reasonable when we carry out the filtering. It is noticed that ENSO is found to have different patterns, especially the eastern equatorial Pacific type (E type) and central equatorial Pacific type (C type) (e.g., Ashok et al. 2007; Kao and Yu 2009; Kug et al. 2009; Hu et al. 2016; M. Wang et al. 2018). There are several pairs of indices are put forward to describe the E and C types of ENSO. Because different types of ENSO have different influences on the MC climate, it seems to be necessary to look into the variations of MC SSTA after the ENSO signals are filtered out using the different ENSO indices or hybrid index. This deserves future work. Moreover, because the location of the eastern pole of the IOD is just in the MC region, it is reasonable to expect that the IOD can also have impacts on the SSTA in the MC region (e.g., Guan and Yamagata 2003; Xu et al. 2019). In the present study, the leading ENSO-independent SSTA mode in the MC (Fig. 3d) looks to be related to the eastern pole of the IOD. As the IOD index describes the variations of zonal gradients of SSTA, it is reasonable to expect that there is a significant simultaneous correlation between PC1 and the IOD index. In fact, when we have both the ENSO and IOD signals removed from the SSTA, we find that the ratios of variance of filtered SSTA (not shown) show obvious decreases in SSTA variance in the eastern tropical Indian Ocean southwest of Sumatra, indicating that the IOD does really affect this principal mode of the ENSO-independent SSTA. As both ENSO and the IOD have impacts on MC SSTA (e.g., Hu et al. 2020), what does the principal mode of MC-SSTA independent of both ENSO and the zonal gradient including the IOD signal appear to be? This problem deserves further investigation. Furthermore, in the present study, we only explored the associated atmospheric and oceanic circulation anomalies, which can explain the maintenance mechanism of MC SSTA to some extent. The formation mechanisms are not discussed. Although the contributions of different thermal and dynamic terms affecting MC SSTA in the mean mixed layer is diagnosed using the thermodynamic diagnosis equation, the external forcing factors that trigger MCSSTA are not deeply discussed. This is worthy of further study in the future.

Acknowledgments.

This work is jointly supported by the National Key Research and Development Program of China (2019YFC1510201), the project of Natural Science Foundation of China (41330425), and the PAPD project of Jiangsu Province. Data services are provided by Nanjing Atmospheric Information Center of Department of Earth Science (Nanjing University of Information Science and Technology). Figures are plotted using the NCL software packages.

Data availability statement.

All data are openly available from the NOAA/OAR/ESRL PSL, Boulder, Colorado, USA, including OISST data from their web site at https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.html as cited in Reynolds et al. (2002), NCEP Global Ocean Data Assimilation System (GODAS) data from their web site at https://psl.noaa.gov/data/gridded/data.godas.html as cited in Behringer and Xue (2004), precipitation data from their web site at https://psl.noaa.gov/data/gridded/data.cmap.html as cited in Xie and Arkin (1997), OLR data from their web site at https://psl.noaa.gov/data/gridded/data.olrcdr.interp.html as cited in Liebmann and Smith (1996), and NCEP–NCAR Reanalysis data from their web site at https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.derived.html as cited in Kalnay et al. (1996).

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