1. Introduction
El Niño exerts a distinct impact on global climate by modulating atmospheric circulation and convection. A weakened Walker circulation suppresses atmospheric convection over the tropical western Pacific, causing the lower-tropospheric anticyclonic anomaly over the Philippine Sea (Wang et al. 2000) associated with the Matsuno–Gill pattern (Matsuno 1966; Gill 1980). The resultant southerly wind anomalies enhance warm air advection over the western North Pacific, leading to a warm winter climate in East Asia (Zhang et al. 1996; Chen et al. 2000). Those features are well reproduced by the atmospheric general circulation models (AGCMs) with the tropical Pacific sea surface temperature (SST) forcing (Kusunoki et al. 2001; Kuramochi et al. 2021), suggesting a remote influence of El Niño on East Asian climate. Hereafter, the season will correspond to the Northern Hemisphere.
The tropical Indian Ocean (TIO) SST anomalies are another important forcing for the anomalous Walker circulation and associated convection. There are two types of the Indian Ocean dipole (IOD; Saji et al. 1999) modes that change the Walker circulation. One is associated with the intrinsic ocean–atmosphere interaction within the TIO, and the other is associated with El Niño (Saji et al. 1999; Fischer et al. 2005; Qiu et al. 2014). Regarding the latter type, El Niño weakens the Walker circulation and causes surface easterly to southeasterly wind anomalies over the equatorial Indian Ocean, intensifying surface evaporation and ocean upwelling in the eastern TIO from early summer to autumn. They form positive wind stress curl anomalies over the southeastern TIO, triggering a positive phase of IOD (pIOD) through the off-equatorial downwelling Rossby waves propagating westward. With the aid of the Indian monsoon reversal, the pIOD shifts into the Indian Ocean Basin warming in the following winter. The deepened thermocline sustains positive SST anomalies in the southwestern TIO (Xie et al. 2002), while the eastern TIO warms due to increased solar radiation and suppressed surface evaporation (Tokinaga and Tanimoto 2004). The TIO warming contributes to the development and maintenance of the lower-tropospheric anticyclonic circulation anomaly over the Philippine Sea (Watanabe and Jin 2002). Such tropical Indo-Pacific interaction is important for regional climate in the subtropical western North Pacific. However, a detailed mechanism for the tropical SST influence on the East Asian winter climate is yet to be elucidated.
Atmospheric teleconnections from the tropics, such as the western Pacific (WP) and Pacific–North American (PNA) patterns, have possible impacts on the East Asian winter climate by changing the East Asian winter monsoon (Wallace and Gutzler 1981; Horel and Wallace 1981; Hoskins and Karoly 1981). The WP pattern is characterized by a meridional dipole of 500-hPa geopotential height (Z500) anomalies in the western North Pacific, while the PNA is by a Rossby wave train from the North Pacific to North America. Analyzing atmospheric reanalysis data, the previous studies suggest that the negative phase of the WP pattern (positive Z500 anomalies in the south and negative anomalies in the north) brings warmer air into East Asia in winter (Wang et al. 2007; Wang and Chen 2014; Shiozaki et al. 2021). Shiozaki et al. (2021) also found that the early onset El Niño suppresses convection in the western Pacific and excites the WP pattern, while the late-onset El Niño excites only the PNA pattern. However, it remains unclear how TIO plays a role in the selective activation of these teleconnection patterns.
One of the keys to identifying the tropical influence on the East Asian winter climate is to suppress the effect of strong internal variability in the midlatitude atmosphere. Statistical analyses with atmospheric reanalysis products may provide typical teleconnection patterns observed during El Niño but cannot sufficiently remove the atmospheric internal variability in the midlatitude due to limited sampling numbers of El Niño events. For this purpose, the present study analyzes large-ensemble simulations with a high-resolution AGCM forced by observed SSTs. We aim to detect the atmospheric teleconnections in response to the tropical Indo-Pacific SST forcing by suppressing the atmospheric internal variability through composites of 100-member ensemble simulations. We also propose a formation mechanism for the WP pattern triggered by the tropical SST forcing.
The rest of this paper is organized as follows. Section 2 introduces the datasets and methods used in the present study. Section 3 shows the results from the composite analysis for the warm and cold winter in East Asia, and section 4 investigates the dominant patterns of atmospheric response to the TIO warming. Section 5 is a summary and discussion.
2. Data and methods
a. d4PDF
We use the monthly mean data from the database for policy decision-making for Future climate change (d4PDF), available for 1951–2011. The d4PDF is a 100-member ensemble simulation using MRI-AGCM3.2 developed by the Meteorological Research Institute of the Japan Meteorology Agency (Mizuta et al. 2017). The MRI-AGCM3.2 has high skill in simulating regional-scale extreme climate including the monsoon precipitation over East Asia (Endo et al. 2012). While AGCMs cannot represent coupled ocean–atmosphere processes important for local SST-precipitation correlation (Kumar et al. 2013), the present study mainly focuses on the remote influence of the tropical Indo-Pacific SST on the East Asian winter climate. For validation, Fig. S1 in the online supplemental material compares the composite anomalies of Z500 for El Niño between the d4PDF and two reanalysis products. The d4PDF successfully reproduces the observed PNA and WP patterns quite well. The amplitude of d4PDF Z500 anomalies is slightly smaller near the WP southern center of action and larger near the Aleutian low. However, these differences from the observation presumably include both the model bias and the effect of atmospheric internal variability, as suggested by limited areas with statistically significant anomalies in reanalysis products.
The d4PDF large-ensemble simulation has been performed with a horizontal resolution of about 60 km, forced by observed SST and sea ice from the Centennial in situ Observation-Based Estimates of the Variability of SST and Marine Meteorological Variables, version 2 (COBE-SST2; Hirahara et al. 2014), greenhouse gas concentration, sulfate aerosol, ozone, and volcanic aerosol. Each ensemble is subject to almost the same SST and sea ice forcing but begins from a different initial atmospheric condition. By calculating the 100-member ensemble mean, we can largely counteract internal atmospheric variability and obtain atmospheric responses to the prescribed forcing. We analyze the following variables: SST, temperature, zonal and meridional winds, 10-m zonal and meridional winds, geopotential height, sea level pressure (SLP), and precipitation. To calculate wind stress, we use the bulk formula (Large and Pond 1981) based on 10-m winds, with constant atmospheric density (1.225 kg m−3) and the bulk coefficient for momentum flux (1.2 × 10−3).
b. Classification and indices
The monthly mean anomaly is defined as the departure from the 61-yr climatology for 1951–2011. All anomalies are detrended by removing the least squares linear trend on each grid. El Niño events are defined as the December–February (DJF)-mean Niño-3 (5°S–5°N, 90°–150°W) SST anomalies exceeding 0.5 standard deviation. The El Niño events are further classified into the warm and cold winters (DJF-mean) in East Asia (25°–40°N, 100°–140°E), based on ±0.5 standard deviation of the area-averaged air temperature anomalies at 850 hPa. This region has been used in previous studies (Takaya and Nakamura 2013; Shiozaki et al. 2021) as it can reflect the modulation of the East Asian winter monsoon (EAWM). Based on the ensemble mean indices, we extract 17 El Niño events between 1951 and 2011, of which eight events are classified as warm winters (1952, 1958, 1966, 1969, 1988, 1998, 2007, and 2010) and five events as cold winters (1970, 1977, 1983, 1987, and 1992). By using the ensemble mean for the warm and cold winter classification, we can suppress the atmospheric internal variability and detect SST-forced atmospheric response. While the cold winters in 1983 and 1992 occurred after the volcanic eruptions in the tropics (Liu et al. 2022), their cooling effect on East Asia is beyond the scope of the present study. We also use the Indian Ocean Basin warming (IOBW) index, which is defined as the area-averaged SST anomalies over the TIO (20°S–20°N, 40°–110°E). The statistical significance of composite anomalies is tested with Welch’s t test. For the probability density function (PDF) in section 4, the z test is applied. The 100-member ensemble mean is applied to all anomaly data unless otherwise noted.
c. Rossby wave source and wave activity flux
3. Warm and cold winters in East Asia
This section examines the typical atmospheric and oceanic patterns linked to the warm and cold East Asian winters during El Niño through the composite analysis.
a. Atmospheric teleconnections
Figure 1 shows the composite anomalies of 850-hPa temperature and Z500 over the Northern Hemisphere based on the classification described in section 2b. In the warm winter composite, positive temperature anomalies cover East Asia with its local maximum south of Japan (around 25°N, 135°E) (Fig. 1a). Both the negative phase of WP and the positive phase of PNA (the deeper Aleutian low) patterns are identified in the Z500 composite (Fig. 1d). The WP pattern intensifies warm air advection into East Asia by southerly wind anomalies along the western edge of anticyclonic anomaly over the western North Pacific.
Composite anomalies of (top) DJF-mean 850-hPa temperature (color; °C) and wind (vectors; m s−1), and (bottom) 500-hPa geopotential height (contours at 5-m interval) for (a),(d) the warm and (b),(e) cold winters in East Asia during El Niño. (c) Difference in the 850-hPa temperature anomaly between the warm and cold winter composites [(a) minus (b)]. (f) As in (c), but for the 500-hPa geopotential height anomaly [(d) minus (e)]. Color shading, vectors, and stippling indicate statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
In contrast, the WP pattern does not emerge and the PNA pattern still dominates in the cold winter composite (Fig. 1e). A deepened Aleutian low associated with the PNA pattern extends westward into the northeast Eurasian continent. This low pressure anomaly strengthens northwesterly winds of EAWM, leading to cold air advection over East Asia (Fig. 1b). The features of the warm and cold winter composites are in good agreement with those revealed in observational studies analyzing the Japanese 55-yr Reanalysis (JRA-55) and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis products (Shiozaki and Enomoto 2020; Shiozaki et al. 2021). Nevertheless, more robust forced responses are shown by the d4PDF large-ensemble simulation. The warm minus cold winter composite makes this difference more evident, highlighting the WP-induced warm winter in East Asia (Figs. 1c,f). The meridional dipole of the WP pattern becomes conspicuous in Z500 anomalies, accompanied by strong warm advection from the subtropical western North Pacific into East Asia. Assuming that El Niño’s influence and atmospheric internal variability are largely reduced in this composite difference, the WP pattern is likely to be caused by another SST forcing.
b. Tropical Indo-Pacific SST
Figure 2 shows a seasonal evolution of composite SST and 850-hPa wind anomalies for the warm East Asian winter. It is widely known that El Niño typically peaks in winter. However, a maximum of positive SST anomaly in the eastern equatorial Pacific already exceeds +1.8°–2.0°C in summer and autumn (Figs. 2a,b), suggesting an early development of El Niño. Interestingly, the Niño-3 SST anomalies reach a mature phase in autumn but not in winter (Fig. 2c). Tightly coupled with those SST anomalies, a weakened Walker circulation sustains strong westerly wind anomalies over the equatorial western Pacific from summer to winter. It also strengthens low-level divergent anomalies over the Maritime Continent during the same period, leading to easterly wind anomalies over the equatorial Indian Ocean and positive wind stress curl anomalies over the southeastern TIO (Fig. 3).
Composite anomalies of (a) JJA, (b) SON, and (c) DJF-mean SST (color; °C) and 850-hPa wind (vectors; m s−1) for the warm winter. Color shading and vectors indicate statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
Composite anomalies of SON-mean wind stress (vectors; N m−2) and its curl (color; ×10−9 N m−3) for the warm winter. Color shading and vectors indicate statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
In response to the wind anomalies, the pIOD develops from summer to autumn (Figs. 2a,b). The coastal upwelling off the Sumatra coast cools SST in the southeastern TIO, while Ekman downwelling by the positive wind stress curl anomalies contributes to warming the western TIO through Rossby waves (Fig. 3). The longitude-time section of the TIO SST anomalies along 10°S shows downwelling Rossby waves propagating westward from 90°E in June–July(−1) to 50°E in the following February(0) (Fig. 4a), consistent with previous studies (Xie et al. 2002; Hill et al. 2000; Heffner et al. 2008). Due to the resultant deepened thermocline, positive SST anomalies in the western TIO persist from autumn to winter. In winter, the easterly wind anomalies weaken the climatological monsoon westerly winds over the equatorial Indian Ocean (Fig. S2), acting to warm SST through suppressed surface evaporation (Tokinaga and Tanimoto 2004). Over the eastern TIO, the weakened Walker circulation increases solar radiation. As a result, the pIOD turns into IOBW in the following winter due to the weakened climatological monsoon in the Indian Ocean, a unique seasonal transition found during the rapid development of El Niño. This IOBW plays an important role in linking the El Niño influence and the warm East Asian winter, as described in section 4.
Hovmöller diagram of composite SST anomalies (color; °C) averaged in 7.5°–12.5°S for (a) the warm and (b) cold winters. The El Niño developing year is denoted as Year(−1), and the following year is denoted as Year(0). Stippling indicates statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
In the cold winter composite, on the other hand, the TIO easterly wind anomalies are weak from autumn to winter, reducing the magnitude of TIO warming (Fig. 5). This difference from the warm winter composite is probably due to a one-season late development of the Pacific El Niño: El Niño peaks in winter, not in autumn as in the warm winter composite. In fact, the SONDJF-mean 850-hPa zonal wind anomaly averaged in the equatorial Indian Ocean exhibits a significant negative correlation with the JJASON-mean Niño-3 SST anomalies (r = 0.65), and the DJF-mean IOBW index also shows a significant positive correlation (r = 0.76; Fig. 6). These correlations with the summer-to-autumn Niño-3 SST indicate that the early El Niño effectively warms the TIO SST in winter through the weakening of the Walker circulation. In the cold winter composite, SST anomalies in the southwestern TIO are much weaker than those in the warm winter composite, consistent with an unclear westward propagation of warm Rossby waves in the southern TIO (Fig. 4b). In DJF, the TIO warming is limited in the subtropical southern Indian Ocean (IOBW index = 0.062°C), whereas it occurs over a wide area of the basin in the warm winter composite (IOBW index = 0.244°C) (Figs. 2c and 5c). The zonal gradient of equatorial Indian Ocean SST anomalies in DJF is also opposite between the two composites, implying a significant impact on the Walker circulation and atmospheric convection over the TIO.
As in Fig. 2, but for the cold winter.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
(a) Scatterplot of the JJASON-mean Niño-3 SST (°C) and SONDJF-mean 850-hPa zonal wind anomaly averaged in the equatorial Indian Ocean (5°S–5°N, 60°–100°E; m s−1). (b) As in (a), but for the same Niño-3 SST and DJF-mean IOBW index (°C). Regression lines and correlation coefficients are included in the figure.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
c. Precipitation and SLP
The precipitation and SLP composites illustrate a modulation of atmospheric convection and circulation coupled with the anomalous SST patterns over the tropical Indo-Pacific. Warm and cold winter composites show negative (positive) precipitation anomalies over the off-equatorial western (the equatorial central) Pacific (Fig. 7). The negative precipitation anomalies in the western Pacific induce the Matsuno–Gill response (positive SLP anomalies) over the tropical western Pacific, a common feature found during El Niño. In the warm winter composite, however, the positive SLP anomalies extend from the tropical western North Pacific to the higher latitudes due to the southern part of the WP pattern. As shown by the latitude-height section of the geopotential height anomaly (Fig. 8a), a meridional dipole of the WP pattern dominates in the middle and upper troposphere and its southern positive anomalies extend down to the surface. The moisture transport northwest of the positive SLP anomalies increases precipitation over southeastern China, consistent with Zhang et al. (2022). Positive precipitation anomalies are also more pronounced over the western TIO in the warm winter composite, weakening the climatological Walker circulation over the TIO. A zonal tripole pattern is distinct in precipitation anomalies with enhanced (suppressed) atmospheric convection over the equatorial western Indian Ocean and the equatorial central Pacific (the Maritime Continent).
Composite anomalies of DJF-mean precipitation (color; mm day−1) and SLP (contours at 0.4-hPa interval; dashed for negative values) for (a) the warm and (b) cold winters. Color shadings and contours indicate statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
Cross section of geopotential height anomaly averaged 120°–150°E (colors; m) for (a) the warm and (b) cold winters. Color shading indicates statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
In the cold winter composite, by contrast, the positive SLP anomalies over the tropical western Pacific do not extend northeastward due to the absence of the WP pattern (Figs. 7b and 8b). Compared to the warm winter composite, the positive SLP anomalies are zonally elongated in the Philippine Sea. They intensify the westerly wind anomalies associated with EAWM, leading to cold winters in East Asia (Figs. 1b, 7b, and 8b). This SLP pattern does not largely contribute to the moisture transport from the tropics to southeastern China. In the tropics, the zonal tripole pattern of precipitation anomalies is also unclear, probably due to the weak TIO warming. Compared to the observational analysis (Shiozaki et al. 2021), the amplitude of negative SST anomalies in the western Pacific is large in the cold winter composite (Fig. 5c) but the Indian–Pacific SLP anomalies are similar to this composite (Fig. 7). While El Niño creates similar circulation anomalies over the tropical western Pacific, the atmospheric response over the TIO is quite different between the two composites, suggesting the importance of TIO for the excitation of the WP pattern and thus the warm winter in East Asia.
d. Rossby wave sources and propagation
This section analyzes the Rossby wave sources at the 250-hPa level over the Indo-Pacific domain to investigate a linkage between the tropical convection and the WP pattern. In the warm winter composite (Fig. 9a), the divergent winds converge (diverge) over the tropical western Pacific (western Indian Ocean), where the atmospheric convection is strongly suppressed (enhanced) due to the weakening of the Walker circulation. The equatorward divergent wind anomalies over the tropical western North Pacific correspond to decreased (increased) precipitation east of the Philippines (north of Taiwan) (Fig. 7a). The divergence over East Asia causes negative Rossby wave source anomalies. These Rossby wave source anomalies are balanced with positive geopotential height anomalies around Japan, contributing to the formation of the southern center of the WP pattern [Figs. 1d and 9a, and Eq. (2)]. This result is consistent with the observational analysis by Shiozaki et al. (2021), supporting that the WP pattern during El Niño is excited by remote forcing from the tropics but not by internal variability in the midlatitude atmosphere. Meanwhile, the divergence over the equatorial central Pacific is associated with increased precipitation due to El Niño. This divergence causes positive Rossby wave source anomalies, deepening the Aleutian low associated with the PNA pattern.
Composite anomalies of the DJF-mean Rossby wave source (color; ×10−10 s−2), geopotential height (contours at 10 m interval; dashed for negative values), and divergent wind (vectors; m s−1) at 250 hPa for (a) the warm and (b) the cold winters. (c) Difference between the warm and cold winter composites [(a) minus (b)]. Only vectors exceeding the 99% confidence level are shown.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
A striking difference between the warm and cold winter composites is found over the tropical Indo-western Pacific and East Asia. In contrast to the warm winter, the divergence (convergence) over the eastern (western) TIO suggests a strengthening of the Indian Ocean Walker circulation in the cold winter, consistent with the precipitation anomaly patterns (Figs. 7b and 9b). The intensified Indian Ocean Walker circulation weakens the anomalous convergence over the tropical western Pacific. As a result, the divergence over East Asia is much weaker in the cold winter, leading to unclear correspondence between the Rossby wave source and geopotential height anomalies. In fact, the difference in the two composites highlights not only the weakening of both the local meridional circulation over the western North Pacific and the Walker circulation over the Indian Ocean but also the WP pattern (Fig. 9c). Therefore, the difference in atmospheric diabatic heating over the tropical Indo-western Pacific is key to the emergence of the WP pattern. The East Asian cold winters during El Niño are probably attributable to the absence of WP and the presence of PNA patterns. While the former impedes cold air advection into East Asia, the latter enhances it through the deepening of the Aleutian low.
The wave activity flux supports that the WP pattern originates from the suppressed atmospheric convection over the tropical western North Pacific in the warm winter (Fig. 10a). Northward wave activity fluxes are generated around 10°N, 100°–130°E corresponding to the negative precipitation anomalies associated with the weakened Walker circulation (Figs. 7a and 9a). These fluxes converge around 35°N, 110°–150°E, decelerating westerly winds associated with the WP pattern. This EAWM weakening causes the warm winter in East Asia through reduced cold advection from the Eurasian continent (Fig. 1a). The other northward fluxes found over the Sea of Okhotsk and near the Bering Sea (50°N, 150°–180°E) correspond to the negative height anomalies of the northern part of the WP pattern.
As in Fig. 7, but for the wave activity flux (vectors; ×10−6 m2 s−2) and their divergence (color: ×10−6 m s−2) at 250 hPa. Only vectors exceeding the 99% confidence level are shown.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
In the cold winter composite, the northward fluxes from the tropical western North Pacific and their convergence over East Asia are less dominant (Fig. 10b). The amplitude of the convergence is less than half of that in the warm winter composite while the divergence around 30°N, 100°E is stronger and statistically significant. This divergence of the wave activity fluxes corresponds to the acceleration of westerly wind, consistent with negative temperature anomalies over eastern China (Fig. 1b).
4. TIO influence on East Asian winter
The pattern of TIO SST anomalies appears to be a key factor to give rise to differences in atmospheric convection over the tropical Indo-western Pacific. To further illustrate the importance of TIO for the East Asian winter climate, this section presents the regression analysis based on the first empirical orthogonal function mode (EOF1) for the DJF-mean TIO SST anomalies over TIO (20°S–20°N, 40°–110°E). The EOF modes and regressed anomalies are calculated from 6100-yr length anomaly data (61 years × 100 members) of the d4PDF.
We first compare the PDFs of the area-averaged precipitation anomalies in the western TIO (10°S–10°N, 40°–60°E) between the warm and cold winters in East Asia during El Niño (Fig. 11). This precipitation is positively correlated with SST anomaly in the same region, which serves as a measure of the anomalous Walker circulation modulated by TIO. Note that the analysis here classifies into the warm and cold winters for each ensemble member, not for the ensemble mean, based on the 0.5 standard deviation of the 850-hPa temperature anomalies in East Asia and the Niño-3 index. As a result, 588 (431) samples are extracted for warm (cold) winter. The shape of the PDF in the warm winter is clearly shifted to the positive side compared to that of the cold winter, supporting the influence of enhanced atmospheric convection over the western TIO. 62.6% (44.1%) of the warm (cold) winter samples occur when the precipitation anomaly is positive. On the other hand, 55.9% (37.4%) of the cold (warm) winter samples occur when the precipitation anomaly is negative. The PDF difference is statistically significant for both positive and negative sides of precipitation anomalies. These PDFs provide strong support for the remote influence of TIO on the East Asian winter climate.
The PDFs (%) of the area-averaged precipitation anomalies in the western Indian Ocean (10°S–10°N, 40°–60°E) using 100 members of the d4PDF. The red and transparent bars indicate the warm and cold winter samples, respectively.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
The EOF1, which accounts for 44.8% of the total SST variance, features the TIO basinwide warming, with vestiges of IOD in the preceding autumn. The regressed SST anomalies also show an El Niño pattern, resembling the SST composite for the warm winter (Figs. 2c and 12a). In fact, the time series of the EOF1 principal components is strongly correlated with the Niño-3 index (r = 0.96). Tightly coupled with those SST anomalies, the regressed precipitation anomalies (Fig. 12b) are characterized by a zonal tripole pattern with enhanced (suppressed) atmospheric convection over the western TIO and equatorial central-to-eastern Pacific (eastern TIO and tropical western Pacific). While the regressed SST anomalies exhibit the basinwide warming in TIO, enhanced atmospheric convection over the western TIO is more crucial for the weakening of the Walker circulation over the tropical Indo-Pacific. On the other hand, the second EOF mode (EOF2) is linked to the meridional gradient of TIO SST anomalies, explaining only 9.4% of the total SST variance (not shown). Because of a weak and insignificant correlation between the EOF2 and Niño-3 index (r = 0.23), this section focuses on the EOF1 and its relevance to atmospheric teleconnection.
Regression coefficients of DJF-mean (a) SST (°C) and (b) precipitation (mm day−1) anomalies onto the EOF1 PC time series. The EOF domain is indicated with a solid line square. Color shading indicates statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
To test our hypothesis that the basinwide warming of TIO contributes to the formation of the WP pattern during El Niño, we look into regressed anomalies of Z500 and divergent wind, the Rossby wave source, and the wave activity flux at 250 hPa. The Z500 regression exhibits a WP-like meridional dipole over the western North Pacific as well as the PNA pattern (Fig. 13), consistent with the result from the composite analysis (Fig. 1d). The regression of 250-hPa divergent winds supports the weakening of the Walker circulations over TIO (Fig. 14a), which is important for the WP pattern not seen or weak in the cold winter composite (Fig. 9b). The 250-hPa convergence around the Philippines due to the weakened Walker circulation is accompanied by a divergence over East Asia (near 35°N, 120°E), leading to negative Rossby wave source anomalies balanced with positive height anomalies over Japan.
As in Fig. 12, but for DJF-mean 500-hPa geopotential height anomalies (contours at 2-m interval; dashed for negative values). Stippling indicates statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
As in Fig. 12, but for (a) the Rossby wave source (color; ×10−10 s−2), geopotential height (contours at 5-m interval; dashed for negative values), and divergent wind anomalies (vectors; m s−1), and (b) the wave activity flux (vectors; m2 s−2) and their divergence (color shades; ×10−6 m s−2) at the 250-hPa surface in the DJF.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
The 250-hPa wave activity flux suggests the Rossby wave propagation from the Maritime Continent around 10°N to Japan (Fig. 14b). The convergence of the wave activity fluxes around 35°N, 110°–150°E corresponds to the deceleration of the westerly winds. Therefore, the convergence of the wave activity fluxes near Japan indicates the weakening of the EAWM. These patterns are similar to those of the warm winter composite (Figs. 1d, 2c, 9a, and 10a), emphasizing the importance of the TIO warming.
5. Summary and discussion
We have investigated the atmospheric teleconnections from the tropical Indo-Pacific during El Niño that influence the East Asian winter climate using the AGCM large-ensemble simulations (d4PDF). In the warm winters, the Indian Ocean basinwide warming, which co-occurs with El Niño, strongly suppresses atmospheric convection around the Philippines, weakening the Walker circulation (Figs. 2 and 9a). The associated divergence in East Asia makes negative Rossby wave source anomalies balanced with positive geopotential height anomalies in the southern part of the WP pattern (Figs. 1d and 9a). This WP pattern weakens the EAWM and thus cold advection from the Eurasian continent, leading to the warm winter in East Asia (Figs. 1a,d, and 7a). By contrast, the Indian Ocean basinwide warming tends to be weak or rather negative during the cold winters (Figs. 1b and 5). As a result, El Niño weakens only the Pacific Walker circulation and excites only the PNA pattern (Figs. 1e and 9b). These results underscore the importance of the El Niño-induced TIO warming for the East Asian winter climate.
The early development of El Niño is a possible factor that can make a prominent difference in the TIO SST warming and the East Asian winter climate. As illustrated in Fig. 6, the early development of El Niño effectively warms TIO in winter by causing surface easterly wind anomalies over the equatorial Indian Ocean from summer to autumn. Figure 15a compares the composite seasonal evolutions of Niño-3 and IOBW indices for the warm and cold winters. In the warm winter composite, the Niño-3 SST rapidly develops from early spring and exceeds its monthly standard deviations (SDNINO.3) for 9 months from June(−1) to February(0) (Fig. 15a). In response to this early El Niño, the IOBW rises with a few months lag (Klein et al. 1999; Xie et al. 2009; Schott et al. 2009) and peaks in February (0). The IOBW enhances atmospheric convection over the TIO, contributing to the weakened Walker circulation. In addition to the emergence of the WP pattern, this early El Niño development contributes to warm atmospheric temperature globally (Fig. 1c), consistent with the previous studies (e.g., Trenberth et al. 2002). In the cold winter composite, on the other hand, the Niño-3 SST slowly develops from the late summer and gets larger than SDNINO.3 for the first time after November(−1). Presumably due to this relatively late development of El Niño, the IOBW remains weak throughout autumn to winter.
Composite time series of (a) Niño-3 SST (solid lines; °C) and the IOBW index (dashed lines; °C); and (b) 250-hPa velocity potential anomaly (solid lines; m−2 s−1) averaged in the tropical WP (20°S–20°N, 110°–150°E) and precipitation anomaly (dashed lines; mm day−1) averaged in the western TIO (10°S–10°N, 40°–60°E) for the warm (red) and cold (black) winters, as a function of calendar month. The gray line in (a) indicates the monthly one standard deviation of Niño-3 SST. The dots on the lines indicate statistically significant anomalies exceeding the 99% confidence level.
Citation: Journal of Climate 37, 15; 10.1175/JCLI-D-23-0627.1
The composite anomalies of the 250-hPa velocity potential over the tropical western Pacific and precipitation over the western TIO are consistent with these SST variations (Fig. 15b). The former is an indicator of the modulated Walker circulation, while the latter is an atmospheric response to the TIO SST. From autumn to winter, positive velocity potential anomalies are larger in the warm winter composite than in the cold one. Similarly, positive precipitation anomalies are larger in the warm winter composite. Interestingly, the major and secondary peaks are found in both the velocity potential and precipitation anomalies in the warm winter composite. While the Niño-3 SST anomalies have a single peak in December(−1), the velocity potential (precipitation) anomaly reaches the first peak in October(−1) [November(−1)] and the second one in February(0). The first peak is probably caused by the pIOD in autumn, while the second one is caused by the IOBW in winter. Similar double peaks are also found in the velocity potential anomaly of the cold winter composite. However, its amplitude is much weaker than those of the warm winter composite, especially during autumn and winter, consistent with the Niño-3 and IOBW indices. Therefore, the early development of both El Niño and IOBW may be a precursor that improves a seasonal prediction for the East Asian winter climate.
Atmospheric teleconnections modulated by the tropical interbasin interaction and various ENSO types are the other factors affecting the East Asian climate. A strong pIOD in 2019, co-occurred with the preexisting El Niño Modoki/central Pacific El Niño, enhanced atmospheric convection over the western TIO and excited the Rossby waves propagating from the Indian subcontinent to East Asia (Doi et al. 2020a,b). The Rossby waves displaced the subtropical jet northward over East Asia, leading to an extremely warm winter in Japan. SST anomalies in the southern TIO are also affected by the remote forcing from ENSO (Xie et al. 2002). They can excite the Rossby wave source over the Mediterranean, causing a large meander of the subtropical jet from Europe to East Asia (Liu et al. 2014). While these studies suggest a TIO impact on the upstream subtropical jet, our results highlight the importance of the WP teleconnection triggered by the strongly weakened Walker circulation due to the TIO warming during the eastern Pacific El Niño. Some previous studies suggest that the interbasin connection between ENSO and TIO is time varying (e.g., Schott et al. 2009; Ham et al. 2017). Ham et al. (2017) pointed out that the recent ENSO–IOD coupling is weaker compared to before 2000. Our results mainly reflect the era with a strong linkage between ENSO and IOD. It remains to be explored how the East Asian winter climate is affected by interdecadal variations in the tropical Indo-Pacific basin interaction.
Strong internal atmospheric variability has hampered the understanding of the WP pattern forced by the tropical SST although it has been an important teleconnection with diverse effects on the East Asian winter climate (Takaya and Nakamura 2013; Park and Ahn 2016; Tanaka et al. 2016; Sekizawa et al. 2021). To suppress the effects of the internal variability in the midlatitude atmosphere, we have applied the composite analysis for the 100-member ensemble simulation of d4PDF. Our results show that the PNA and WP patterns emerge in response to the tropical Indo-Pacific SST forcing consistent with the observational studies (Sakai and Kawamura 2009; Shiozaki and Enomoto 2020; Shiozaki et al. 2021; Kuramochi and Ueda 2023). The WP pattern triggered by the strong TIO warming associated with El Niño is one of the major factors that warm the East Asian winter climate.
On the other hand, it has remained unclear to what extent the SST-forced WP pattern can explain the interannual variations in the East Asian winter temperature relative to the atmospheric internal variability. To answer this question, we compare the signal-to-noise ratio (SNR) for several composite cases of the East Asian winter temperature using the d4PDF (Table 1). For the SNRs, the signal and noise are defined as the ensemble mean and standard deviation of the 100-member temperature anomalies, respectively. All SNRs fall below 1, suggesting that the atmospheric internal variability is still larger than the SST-forced signal for any composite cases. In particular, the SNR for the neutral winters is close to 0 and that for all El Niño winters is 0.163, indicative of strong atmospheric internal variability. However, the SNRs for all El Niño warm winters and the 1997/98 El Niño warm winter case reach 0.46 and 0.69, respectively. Similarly, the SNRs for the cold winter cases are also larger than that for the neutral case. This SNR increase strongly supports a significant and nonnegligible impact of the tropical Indo-Pacific SST on the East Asian winter temperature.
The signal, noise, and SNR for each category of the East Asian winter temperature anomaly. The signal and noise are defined as the ensemble mean and standard deviation of 100-member ensembles of the d4PDF, respectively. Both El Niño and La Niña years are excluded from the neutral winter category, while all El Niño winter category includes both the warm and cold winter years.
A TIO warming trend has been a focus of attention over the past decades (Roxy et al. 2014, 2019). In observations, the TIO SST has warmed steadily since the 1950s and shows the largest warming trend in the tropical oceans (Du and Xie 2008). Sharma et al. (2023) indicate that the nonuniform TIO warming in the future simulated by coupled general circulation models reduces the zonal SST gradient, acting to weaken the Walker circulation over the tropical Indo-Pacific. Given that the WP pattern and the East Asian winter climate are affected by a warmer TIO and a weaker Walker circulation, the midlatitude atmospheric responses during El Niño may change under global warming. The present study has focused on the interannual variability in the past climate simulation, but its future changes affected by the TIO warming pattern need further investigation.
Acknowledgments.
This work was supported by the Japan Society for the Promotion of Science KAKENHI Grants JP19H05703, JP19H05704, JP23K22563, JP23K22570, JP23K25946, JP24H02229, and JP24H00261.
Data availability statement.
The database for policy decision-making for future climate change (d4PDF) is available in the Data Integration and Analysis System Program (DIAS) website at http://www.diasjp.net/en/.
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