To examine the relationship between the spring precipitation, circulation, and SST, we perform an SVD analysis to extract the dominant patterns of covariability between MAM 850-hPa vorticity and SST in spring and at a lead of two months based on the interannual and inter-member variability. The relationships between the spring 850-hPa wind, precipitation, and the first two coupled modes are further discussed.
Here, the MAM vorticity (0°–55°N, 70°–165°E) and SST (50°S–55°N, 40°E–90°W) anomalies are used as the left and right fields, respectively. In the Northern Hemisphere, positive and negative vorticities are indicators of low and high pressure systems, respectively. The vorticity anomalies in the region (0°–55°N, 70°–165°E) are closely related to the Northwest Pacific subtropical anticyclone activity, which influences the precipitation over East Asia significantly (Kosaka et al., 2013; Ma et al., 2017a). Figure 8 shows the first two SVD modes for the observations, which explains 40.5% and 15.3% of the total covariance, respectively. The vorticity field of the leading mode (Fig. 8a) is characterized by a negative correlation located in Northwest Pacific (NWP), which is noted as an anomalous anticyclone. Meanwhile, there is a positive correlation in the southern region of China. In the SST field of the first mode (Fig. 8b), positive SST correlations occur in the central and eastern equatorial Pacific with intensified equatorial westerlies, while negative correlations are located in the western Pacific (WP) and north of the central equatorial Pacific (NCP). In addition, there is a significant positive correlation in the equatorial Indian Ocean. In the vorticity field of the second mode (Fig. 8c), the negative vorticity moves southeastward compared with the leading mode. In the corresponding SST field (Fig. 8d), positive SST correlations mainly appear in the Maritime Continent, northern Indian Ocean (NIO), and NWP.
Figure 8. Heterogeneous fields (shading) of the observed (a, b) first and (c, d) second SVD modes of the interannual 850-hPa (a, c) vorticity and (b, d) SST anomalies in MAM. Correlation coefficients between the spring 850-hPa winds (vector; a–d), precipitation (contour; red solid for positive and blue dashed for negative), and PCs of the corresponding fields are computed. Shading, vector, and the bold contours indicate the correlation coefficients at the 90% confidence level.
The vectors shown in Fig. 8 indicate the correlation coefficients between the MAM 850-hPa winds and the first two SST PCs from the SVD analysis reaching at 90% confidence level with a t-test. For the first mode, the southeastern China is under the control of intensified southwesterlies, with significantly positive precipitation anomalies sitting in the eastern part of China. The significant negative precipitation anomalies are mainly located in southeastern Asia and NWP, with weak signals in southwestern China and east of the Tibetan Plateau. For the second mode, positive precipitation anomalies are mainly located in northwestern and northern China. Therefore, the observed first mode may play a major role in the spring precipitation anomaly in eastern China, while the second mode associates with the precipitation anomaly in northwestern and northern China.
Figure 9 shows the SVD results for the ensemble mean forecast with the November initialization. The first two modes account for 81.1% and 9.5% of the total covariance, respectively. Note a significant overestimation of the first variance contribution. Indeed, the first PC of the SVD mode is highly correlated with the Nino3.4 index with the correlation coefficients of above 0.9 (figure omitted), significant at the 99% confidence level, and the second SVD PC is in poor correlation with the Nino3.4 index with the correlation coefficients below 0.2, indicating that the large variance explained by the first mode in the MME may be caused by the dominant signal of the ENSO in the ENSEMBLES. The predicted SVD results resemble the observations, identifying the first mode as positive SST correlations over the Indian Ocean and the central and eastern equatorial Pacific with intensified westerly anomalies, negative SST correlations in the WP and NCP (Fig. 9b). Meanwhile, a negative vorticity anomaly exists over the NWP, and southeastern China is under the control of anomalous positive vorticity (Fig. 9a). The significant southwesterly wind and positive precipitation anomaly are located in southeastern China, while the negative precipitation anomaly mainly occurs in South Asia and the NWP, with a slight impact on southwestern China. Many previous studies have revealed that ENSO is one of the most important factors that influence precipitation anomalies in southern China, and the Philippine Sea anticyclone (PSAC) is the key system that bridges the remote ENSO forcing to East Asian climate variation (Wang et al., 2000; Xie et al., 2009; Jia et al., 2014), which can also be seen from the leading SVD mode in Fig. 9.
Figure 9. As in Fig. 8, but for the MME interannual 850-hPa vorticity and SST anomalies in MAM based on the ensemble mean forecast with November initialization.
In the second mode, positive SST correlations are mainly located in the Maritime Continent, Bay of Bengal, and NWP, while negative SST correlations are in the central equatorial Pacific accompanied by anomalous northeasterly trade. The positive SST anomaly and corresponding weak westerlies in the eastern equatorial Pacific also exist (Fig. 9d). In addition, the anomalous anticyclone in the second mode shows an eastward and southward position compared with the first mode (Fig. 9c), which is consistent with the observations. However, there is a difference of the location between the predicted anomalous precipitation and observations, as the former shows a significantly positive signal of precipitation and corresponding positive vorticity in the southeastern coastal areas of China.
The MAM SVD results with the initialization of February (figure omitted) closely resemble those for the November initialization. Table 1 summarizes the correlation coefficients between the observed and ensemble mean SVD PCs. For the SVD from hindcasts in February and November, both PC1 and PC2 are correlated with the counterparts from observation, significant at the 90% confidence level. Thus, the coupled modes of the spring circulation and SST predicted by the MME are closely correlated with their counterparts from the observations, which give us confidence to use ENSEMBLES hindcasts to investigate the spring climate predictability. And the first mode may play a leading role in the climate variability over eastern China, though the predicted locations of anomalous southwesterlies and precipitation are generally biased toward the south compared to the observations.
Correlation coefficient FEB PC1 FEB PC2 NOV PC1 NOV PC2 OBS-PC1 0.92 0.45 OBS-PC2 0.59 0.43
Table 1. Correlation coefficients between the observed and ensemble mean SVD PCs. OBS-PC1 and OBS-PC2 represent the first and second PC of the SVD in MAM based on observations, respectively. FEB and NOV denote the SVD based on the hindcasts with February and November initializations, respectively
In the following, SVD analyses are conducted to extract the dominant coupled modes between the inter-member anomalies of MAM 850-hPa vorticity and SST. Figure 10 presents the first two SVD modes of the inter-member variability from the hindcasts initialized in November, which account for 33.4% and 22.6% of the total covariance, respectively. The vorticity fields resemble the first two SVD modes of ensemble mean interannual variability, identifying the anomalous anticyclone located over the NWP for the first mode and a southeastward position for the second mode (Figs. 10a, c). The SST field of the first mode features significant positive SST correlations in the equatorial Indian Ocean and central-eastern equatorial Pacific, while the second mode shows positive SST correlations in the NIO and NWP, as well as negative correlations in the central Pacific (Figs. 10b, d). Figures 10a and 10c present the correlation coefficients between the inter-member 850-hPa wind, precipitation, and SST PCs of the SVD analysis. For the first mode, intensified anomalous southwesterlies and positive precipitation occur over southeastern China, while the second mode presents weak northeasterlies with precipitation confined to the south of the mainland. The SVD modes between the inter-member vorticity and SST anomalies are similar to those between the interannual anomalies. It suggests that the prediction spread in the spring climate forecast of eastern China is mainly derived from the internal dynamics of ocean–atmosphere interaction over the tropical Pacific, NCP, and Indian Ocean. As we mentioned before, anomalous SST associated with El Niño in the central-eastern equatorial Pacific can induce anomalous descent over the Philippine Sea, favoring the development of an anomalous anticyclone. The anomalous anticyclone acts as a medium bridging remote El Niño forcing and climate variations in East Asia as it enhances southwesterlies to its northwest flank and generates positive precipitation over China. The anomalous anticyclone can persist through local air–sea interactions over the NWP, causing rainfall anomalies over eastern China in the ensuing spring.
Figure 10. As in Fig. 8, but for the MME inter-member 850-hPa vorticity and SST anomalies in MAM with November initialization.
We find that the 2-month preceding SST is well coupled with the MAM circulation and precipitation in eastern China. Figure 11 shows the observed first two SVD modes of MAM vorticity and SST at a lead of two months, accounting for 39.4% and 18.7% of the total covariance, respectively. Note that the modes calculated by preceding SST resemble those in Fig. 8. For the first mode (Figs. 11a, b), the SST field presents positive SST correlations over the central-eastern equatorial Pacific and negative correlations in the WP and NCP, while the vorticity field shows an anomalous anticyclone over the NWP with a significant impact on the precipitation in eastern China. For the second mode (Figs. 11c, d), positive SST correlations occur over the NWP, Indian Ocean, and eastern equatorial Pacific. An anomalous anticyclone with a southeastward position compared with the leading mode is shown in the second vorticity field. Note that the second mode has little connection with the precipitation in eastern China, but gives a positive precipitation anomaly in the northwest.
Figure 11. As in Fig. 8, but for the interannual 850-hPa vorticity in spring and SST at a lead of two months.
For the predicted SVD results of the ensemble mean forecast with the November initialization (figure omitted), the first two modes account for 83.6% and 10.5% of the total covariance, respectively. Similar to the coupled modes in Fig. 9, the first mode features the anomalous anticyclone over the NWP with the corresponding intensified southwesterlies and positive precipitation anomaly in southeastern China. The related negative SST anomaly occurs in the WP and NCP, while the positive SST anomaly occurs in the central-eastern equatorial Pacific and Indian Ocean. The second mode features a southeastward position of the negative vorticity anomaly with the positive precipitation anomaly confined to the south of 25°N, and the positive SST anomaly mainly in the NIO and NWP.
Finally, the first two SVD modes between inter-member anomalies of MAM 850-hPa vorticity and SST at a lead of two months are calculated (figure omitted), which account for 33.5% and 27.0% of the total covariance, respectively. Note that the correlations for the inter-member variability in 850-hPa wind and precipitation resemble those for ensemble mean interannual anomalies, indicating that the first coupled mode plays a more important role in the climate variability of eastern China, with a significant precipitation anomaly located in the southeast. No more tautology here as the first two modes as well as the correlation fields of precipitation and 850-hPa winds are similar to those calculated by the contemporaneous SST. During positive ENSO events, though the positive SST anomalies in the eastern tropical Pacific decay rapidly, the anomalous anticyclone over NWP can be maintained in the ensuing spring and summer through local air–sea interactions. With regard to the ocean memory that maintains the anomalous anticyclone, Wang et al. (2003) emphasized the SST cooling in the easterly trade wind regime of the NWP. More specifically, on the east side of the anticyclone, anomalous northeastern winds strengthen trade winds, enhancing the latent heat flux from the ocean to the atmosphere and cooling the underlying SST. Negative SST anomalies excite westward propagating Rossby waves, which reinforce the anticyclone in return. Southerlies on western flank of the anticyclone transport warm air from low-latitude oceans and contribute to the positive SST anomalies over the South China Sea and surrounding regions. In addition, El Niño can induce the Indian Ocean warming, which persists into the following spring (Du et al., 2009). And modeling studies also support that the Indian Ocean can force the anomalous anticyclone over NWP (Huang et al., 2010; Chowdary et al., 2011). Thus, the SST anomalies in the leading SVD mode at a lead of two months may be a predictor for the spring climate variability in eastern China. Additionally, the forecast skill can mainly arise from the internal dynamics of the ocean–atmosphere interaction over the tropical Pacific, NCP, and Indian Ocean.