1. Introduction
China is a typical monsoon region with complex and diverse terrain and climate characteristics. Affected by the East Asian summer monsoon advancement, the rain belt shifts from south to north in China during the rainy season (Chen et al. 2001; Ding and Chan 2005; Huang et al. 2012). Southern China (SC) is located south of the Yangtze River and east of the Tibetan Plateau (see the red box in Fig. 1a) and is one of the most densely populated regions in China, with developed agriculture and industry. Specifically, the precipitation over SC is concentrated mainly in April–June (AMJ), which is the first major flood season in China, also known as the pre–flood season (PFS) in SC (Yuan et al. 2010; Gao et al. 2016; Chu et al. 2018, 2020). During the PFS, SC experiences abundant precipitation attributed to the large-scale monsoon circulation, which contributes the majority (∼40%–50%) of the local annual precipitation (Yang and Sun 2005; Yuan et al. 2019). Meanwhile, most extreme precipitation events in China occur in SC, usually causing serious regional floods and resulting in great social impacts (Zhai and Eskridge 1997; Shi and Ding 2000; Tang et al. 2006; Bao 2007; Miao et al. 2015; Shi et al. 2021; Guo et al. 2022). For instance, in the PFS of 2019, Guangdong province experienced several heavy precipitation processes, leading to mountain torrents and urban waterlogging in multiple places, and causing severe casualties and major economic losses (Ji et al. 2021). Therefore, studying the interannual variability of precipitation in SC during the PFS and its underlying mechanisms is crucial for regional climate disaster prevention and mitigation (Luo et al. 2017).
(a) Mean precipitation (colors; units: mm day−1) and its standard deviation (contours; interval: 0.4 mm day−1) in the pre–flood season (PFS) [April–June (AMJ)] for 1961–2020; the red box denotes Southern China (SC; 22°–28°N, 109°–120°E). (b) Monthly precipitation amount (unit: mm) over SC during 1961–2020; the short lines denote the interannual variability (standard deviation; unit: mm).
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
As the dominant ocean–atmosphere interaction signal over the tropical Pacific on an interannual time scale, El Niño often exerts great impacts on the global climate via atmospheric teleconnections (Ropelewski and Halpert 1987; Philander 1990; Lau and Nath 2009; Wang et al. 2017; Luo and Lau 2020; Ren et al. 2020; Li et al. 2021a, 2023). Specifically, SC is located in the tropical and subtropical climate zones bordering the tropical western Pacific region, and local precipitation anomalies may be linked to El Niño events (Huang and Wu 1989; Wang et al. 2000; Wu et al. 2003; Lau and Nath 2009). For instance, the El Niño–induced northwestern Pacific anomalous anticyclone (NPAAC) can convey excessive atmospheric moisture to SC in favor of the local precipitation during the mature winter (Gong and Wang 1999; Wang et al. 2000; Xie et al. 2016). By contrast, SC often experiences a precipitation deficit during the El Niño decaying summer because of the strengthened and westward extension of the northwest Pacific subtropical high (Huang and Wu 1989; Chang et al. 2000; Gao et al. 2014; Huang et al. 2018). However, the specific effect of El Niño on the subsequent PFS precipitation over SC remains unclear, and the underlying mechanisms deserve a thorough investigation.
Against the background of global climate change, El Niño–related sea surface temperature (SST) anomalies have experienced decadal changes. Conventionally, the El Niño–related warm SST anomaly centers are located in the equatorial eastern Pacific (Ashok and Yamagata 2009; Kao and Yu 2009), but since the early 1990s these centers have often been observed in the equatorial central Pacific (Ashok et al. 2007; Kug et al. 2009). For the projected future with warming scenarios, such central-Pacific El Niño events would occur even more frequently (Yeh et al. 2009). As a result, El Niño has exhibited a decadal enhancement of the intensity of the central-Pacific warm SST anomalies with westward extension since the early 1990s, as suggested by satellite observational data analyses (Lee and McPhaden 2010; McPhaden et al. 2011). Some studies have shown that the Asian climate responses have exhibited evident decadal changes with this decadal change in El Niño activities since the early 1990s (Jin et al. 2016; Piao et al. 2020; Li et al. 2021b; Chen and Li 2022; Chen et al. 2022). Therefore, the following question is posed here: Has the effect of El Niño on the subsequent PFS precipitation over SC changed with the changed El Niño characteristics since the early 1990s, and if so, how?
Indeed, the work reported herein reveals a decadal enhancement in the effect of El Niño on the subsequent PFS precipitation over SC. Before the 1990s, El Niño exhibited little connection to the subsequent PFS precipitation anomalies over SC, but since the early 1990s it has tended to induce a precipitation surplus over SC during the subsequent PFS. This is because of the stronger intensity and longer duration of El Niño–related warm SST anomalies over the equatorial central Pacific in the epoch after the early 1990s (1992–2020) than in the previous decades (1961–91), resulting in a westward shift of the NPAAC accompanied by an anomalous descending motion over the South China Sea since the early 1990s. Correspondingly, the regional Hadley circulation weakens with an abnormal upward ascending motion and excessive precipitation over SC during the PFS, and this has great implications for regional seasonal climate prediction in the future.
The rest of this paper is organized as follows. Section 2 introduces the data and methods. Section 3 presents the climatology and interannual variability of the SC precipitation during the PFS. Section 4 demonstrates the interannual relationship between El Niño and the subsequent PFS SC precipitation and the decadal enhancement of this relationship. Section 5 explores the underlying cause of the decadal enhancement in the effect of El Niño on the subsequent PFS precipitation over SC. Finally, section 6 presents conclusions and a discussion.
2. Data and methods
The monthly observed CN05.1 precipitation dataset with a high resolution of 0.25° × 0.25° was obtained from the China Meteorological Administration (CMA), covering the period of 1961–2020. Note that these gridded data could cause a strong bias toward the heavy precipitation events that contribute the majority of the PFS precipitation over SC (Han and Zhou 2012; Wu and Gao 2013), so we also used a daily precipitation dataset from over 2400 Chinese stations obtained from the CMA to double-check our main results. The monthly SST dataset with a resolution of 1° × 1° from 1870 to the present was obtained from the Hadley Center Sea Ice and SST dataset (Rayner et al. 2003). The Japan Meteorological Agency produces the Japanese 55-year Reanalysis dataset with a horizontal resolution of 1.25° × 1.25° and a time span of 1958–2020 (Kobayashi et al. 2015), which provided the monthly atmospheric fields, such as the three-dimensional wind velocities and humidity. The study period was taken as 1961–2020, which is a common period for all the datasets.
The intensity of El Niño events is denoted using the Oceanic Niño Index (ONI) from the Climate Prediction Center of the United States in mature winter. The ONI is based on the running SST anomalies over the Niño-3.4 region (5°S–5°N, 170°–120°W; see http://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php for more details). For composite analyses, we selected 20 El Niño events whose winter ONI exceeded 0.5 (Table 1), and we removed the long-term trends of all data before statistical analyses to reduce the possible influence of climate change. The significance level p is estimated based on Student’s t test. In particular, because the samples at neighboring time points are not independent, the degree of freedom of 29-yr moving correlation/standard deviations is estimated by n = N(1 − r2)/(1 + r2), where N is the sample number and r is the 1-yr lagged autocorrelation coefficient.
El Niño events during 1961–2020 used in composite analyses.
3. Climatology and interannual variability of pre–flood season SC precipitation
Figure 1 shows the climatology of the PFS precipitation over eastern China for 1961–2020. The precipitation amount generally decreases from south to north, with a range of more than 10 mm day−1 to less than 1 mm day−1 (Fig. 1a). During the PFS, the largest precipitation is located mainly in SC with a total amount of 6–10 mm day−1. Correspondingly, the interannual variability of precipitation over SC is also the strongest, with a standard deviation of precipitation of ∼2 mm day−1.
Normally, the rainy season in China is summer because of the influence of the East Asian summer monsoon system. The rain belt advances with the development of the monsoon system from south to north, so the rainy season starts earlier in SC, and the PFS precipitation is a major component of local monsoon precipitation (Yang and Sun 2005). As shown in Fig. 1b, during our study period, the regional average SC precipitation was concentrated mainly in AMJ, along with the largest interannual variabilities. The precipitation amount in SC was ∼200 mm day−1 in April to over 270 mm day−1 in June, and the three-month precipitation summation contributed approximately 43% of the local total annual precipitation. For our study area and period, the standard deviation of total precipitation in the PFS was ∼107 mm, accounting for about 15% of the AMJ precipitation amount.
4. Decadal change in effect of El Niño on SC precipitation
Being adjacent to the northwestern Pacific, the precipitation in SC is strongly linked with the tropical SST anomalies (Chen et al. 2014). Indeed, in the PFS over SC, the regional precipitation anomaly is tightly connected with the tropical ocean states, especially the tropical Pacific SST anomalies. As shown in Fig. 2a, the preceding-winter SST anomalies over the equatorial central-eastern Pacific had significant positive correlations with the PFS SC precipitation in 1961–2020, while there were negative correlations over the western Pacific. The spatial correlation distribution exhibits a typical El Niño–related SST anomaly pattern. Furthermore, the regional average PFS precipitation over SC and the preceding-winter ONI were closely linked by a significant (p < 0.05) correlation coefficient of 0.27 for the past six decades (Fig. 2b). In other words, when the equatorial central-eastern Pacific SST is abnormally warmer in preceding winter (i.e., an El Niño event occurs) there is usually a precipitation surplus over SC in the subsequent PFS. However, such an SST–precipitation relationship is unstable in our study period. The 29-yr moving correlation between the AMJ SC precipitation and the preceding-winter ONI is relatively weak for the early subperiod but strengthens rapidly in the latest 29 years: the correlation coefficient even exceeds the significance level of p < 0.01 for 1992–2020 (Fig. 3a). The 25- and 21-yr moving correlations also show a similar pattern: they are obviously enhanced when the moving window contains the early 1990s. To ascertain further the year of the abruption, we used different time spans with an initial year between 1986 and 1996 to 2020, and the results show that the correlation is strong for 1992–2020 and is even strengthened when the time span is narrowed (Fig. 3b).
(a) Correlation distribution of sea surface temperature (SST) anomalies in preceding winter with SC precipitation anomaly in AMJ for 1961–2020; the dotted areas are significant with p < 0.05. (b) Standardized precipitation anomaly over SC in AMJ and preceding-winter Oceanic Niño Index (ONI) during 1961–2020; r denotes their correlation coefficient.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
(a) The 29-, 25-, and 21-yr moving correlation coefficients between winter ONI and SC precipitation anomaly in subsequent AMJ for 1961–2020; the dashed lines denote the significance level of p < 0.05 for the different moving windows, and the years on the horizontal axis denote the central years. (b) Multiyear correlation coefficients for different time spans between the initial year and 2020; the solid circles are significant with p < 0.05.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
Based on the above results, we select the two subperiods of 1961–91 and 1992–2020 for our further analyses. Obviously, the relationship between El Niño SST and SC precipitation anomalies during these two subperiods exhibits a distinct discrepancy. In the early 31 years, the correlation coefficient for the AMJ SC precipitation and the preceding-winter ONI is only 0.19 (Fig. 4a), indicating a weak influence of El Niño on the SC precipitation in the PFS, whereas in 1992–2020 it increases to 0.44 (p < 0.05) (Fig. 4b), which suggests a strong influence of El Niño on the PFS SC precipitation. Noting that some super El Niño events may mislead the above findings, we additionally remove five decaying years with winter ONI > 1.5, which are also five well-known super El Niño events (i.e., 1972/73, 1982/83, 1991/92, 1997/98, and 2015/16). The results after removing the super El Niño events still show an evident decadal enhancement in the effect of El Niño on the PFS SC precipitation. The correlation coefficients for winter ONI and AMJ SC precipitation are 0.03 and 0.4 (p < 0.05) for the early and late subperiods (figure not shown), respectively, consistent with our main findings. In addition, considering that El Niño and La Niña exert asymmetric effects on the East Asian climate (Wu et al. 2021; Xu et al. 2021; Gao and Li 2023; Lin et al. 2023), we further divide the whole study period into two categories based on positive and negative ONIs. For the years with preceding-winter ONI > 0, the AMJ SC precipitation is significantly (p < 0.05) correlated with the ONI by ∼0.4 (figure not shown). For the years with preceding-winter ONI < 0, the correlation coefficients are only 0.14, 0.17, and 0.08 for the whole study period, 1961–91, and 1992–2020, respectively. This suggests that El Niño exerts an evident effect on the PFS SC precipitation, while the effect of La Niña is limited, and the interdecadal change in the response of the AMJ SC precipitation anomaly is attributed mainly to El Niño.
Scatter relationship between winter ONI and SC precipitation anomaly in AMJ for (a) 1961–91 and (b) 1992–2020; r and p denote the correlation coefficient and its significance level, respectively. The straight line is the linear fitted line, and only the solid line indicates a statistically significant relationship.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
To clarify further the interdecadal changes in the effect of El Niño on the AMJ precipitation over SC, the correlation distributions of precipitation anomalies in AMJ with the preceding-winter ONI for different periods are shown in Fig. 5. During 1961–91, the significant positive correlations were generally located to the north of the study region near the lower reach of the Yangtze River valley (Fig. 5a). Most of the SC region shows a weak or insignificant correlation between the precipitation and ONI. This suggests a relatively weak influence of El Niño on the subsequent PFS precipitation over SC. By contrast, the correlation of winter ONI and AMJ precipitation strengthened dramatically over SC in 1992–2020 (Fig. 5b), with the region of positive correlation coefficient increasing over SC and even expanding to the upper and middle reaches of the Yangtze River valley.
Distribution of correlation between AMJ precipitation anomaly and preceding-winter ONI for (a) 1961–91 and (b) 1992–2020; the dotted areas are significant with p < 0.05, and the red box denotes the SC region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
To avoid possible biases from using the monthly interpolated dataset, we checked our results by using original daily observation data from over 2400 meteorological stations. First, the regional average SC precipitation anomalies in AMJ for the station and grided datasets are highly correlated with a correlation coefficient of 0.996 during 1961–2020 (figure not shown). Second, the decadal enhancement of El Niño SST anomaly affecting the AMJ SC precipitation is also shown by the correlation distributions of ONI with AMJ precipitation in the station dataset during the two subperiods (Figs. 6a,c).
Correlation distribution of AMJ precipitation anomaly in station observations with preceding-winter ONI for (a) 1961–91 and (c) 1992–2020. (b),(d) As in (a) and (c), but with the PFS defined by daily station data according to Gu et al. (2018). The stations denoted by triangles are statistically significant with p < 0.05, and the red box denotes the SC region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
In addition, we note that results from Gu et al. (2018) suggested using daily station data to define the length of the PFS because of the large interannual variation of the start and end dates. Therefore, we recalculated the start and end dates of the PFS for each year based on the stations in the four provinces of south coastal China (Guangdong, Guangxi, Fujian, and Hainan) during 1961–2020 [see Gu et al. (2018) or National Climate Center (2017) for the detailed criteria]. As a result, the average start and end dates of the PFS were 9 April and 4 July during 1961–2020, respectively, despite their obvious interannual variations (Fig. S1 in the online supplemental material). The average length was 87 days, which were mainly in AMJ. For our study region, the regional precipitation anomalies in the AMJ and year-to-year PFS were also highly correlated with each other with a correlation coefficient of 0.71 (p < 0.001) during the past six decades (Fig. S2). This indicates that the precipitation in AMJ is the major component of total precipitation in the PFS. Figures 6b and 6d further show the correlation distribution of the preceding-winter ONI with precipitation amount in year-to-year PFS during the two subperiods. In 1961–91, there was barely a robust relationship between El Niño SST and precipitation anomalies over SC. For 1992–2020, significant positive correlations mainly dominated the north of the SC region. In the south coastal area, the El Niño SST anomaly still exerted limited effects on the PFS precipitation. This highly resembles the results from the monthly grided data and is similar to the findings of Gu et al. (2018), who revealed a loose link between PFS precipitation over SC (mainly the south coastal provinces) and El Niño SST anomaly. The above results further support the assertion that the effect of El Niño on the SC precipitation during the subsequent PFS has experienced an interdecadal change, being evidently enhanced during recent decades.
5. Underlying cause of decadal enhancement in the effects of El Niño on SC precipitation
The above analyses show that a positive SST anomaly over the central-eastern Pacific would induce a precipitation surplus over the SC during the PFS. Specifically, the 29-yr moving ONI standard deviation and El Niño SST–precipitation correlation are closely correlated to each other with a correlation coefficient of 0.57, which exceeds the significance level of p < 0.1 (Fig. S3). This hints at the SST–SC precipitation relationship being linked to El Niño variability for a certain period. To explore further the underlying mechanisms, we first look into the interdecadal changes in El Niño SST anomalies. Figure 7 shows the composite El Niño SST anomalies during decaying phases in each subperiod. In the mature winter, it is obvious that El Niño events in the late subperiod have a larger abnormal SST center with over 1°C than the ones in the early subperiod (Figs. 7a,b). Specifically, the warm SST anomaly over the equatorial central Pacific was stronger during 1992–2020. In the decaying spring to early summer, such differences between the two subperiods are more evident (Fig. S4). El Niño warm SST anomalies over the central Pacific were stronger, lasted for longer, and extended westward in the late subperiod compared with the ones in the early subperiod (Figs. 7c–f). This implies that El Niño events have enhanced and shifted to the central Pacific since the early 1990s. In addition, for the mature winter and decaying spring, because of the Rossby wave response to the warm El Niño SST anomaly, there was an anomalously colder SST anomaly over the northwestern Pacific region (Figs. 7a–d) (Wang et al. 2000). Such a local cold SST anomaly could motivate a low-level anticyclone over the northwestern Pacific (i.e., the NPAAC). Furthermore, the summer monsoon wind over the Indian Ocean is weakened because of the anomalous easterly wind in the southern rim of the NPAAC. This prevents local evaporation and thus warms the SST during the El Niño decaying phase. The abnormally warmer Indian Ocean basin (IOB) and colder northwestern Pacific along with the NPAAC form a positive feedback loop, which maintains the NPAAC until the summer (Figs. 7e,f) (Kosaka et al. 2013; Hu et al. 2014; Li et al. 2017). This IOB warming mode is also known as the Indian Ocean capacitor effect (Xie et al. 2009, 2016; Tao et al. 2015). More importantly, associated with the enhanced and westward extended warm El Niño SST anomaly over the central Pacific, the cold SST anomaly over the northwestern Pacific also shifted westward during 1992–2020 compared to the early period. Thus, the center of the NPAAC excited by the cold SST anomaly shifted from east to west across the Philippines.
Composite anomalies of 850-hPa wind (arrows; only wind anomalies that are significant with p < 0.05 are shown; units: m s−1) and SST (colors; the dotted areas are significant with p < 0.05; unit: °C) in (a) January–February, (c) March–April, and (e) May–June for the El Niño events during 1961–91. (b),(d),(f) As in (a), (c), and (e), but for the El Niño events during 1992–2020. The letter A roughly denotes the center of the anomalous low-level anticyclone over the northwestern Pacific region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
The above results are further supported by the monthly evolution of the SST anomalies over the Niño-3.4, Niño-3, Niño-4, and IOB regions in El Niño events for the two subperiods (Fig. 8). Generally speaking, the El Niño SST anomalies were stronger and lasted for longer during the late subperiod than before (Fig. 8a). For the equatorial eastern Pacific, the warm SST anomalies were stronger in the mature winter during late subperiod, but this difference vanished in early spring (Fig. 8b). By contrast, over the equatorial central Pacific, the SST anomalies were higher during the El Niño mature winter to the decaying spring for 1992–2020 than before (Fig. 8c). This difference in SST anomalies between the two subperiods was even enlarged during the PFS. In addition, the significant (p < 0.05) central Pacific warm SST anomalies during 1961–91 only lasted until April, whereas those during 1992–2020 lasted until May, suggesting a longer duration of El Niño in the late subperiod. The response of the IOB SST anomaly lags behind the El Niño SST anomaly, lasting until the PFS (Fig. 8d). In summary, El Niño events since the early 1990s have apparently intensified, especially over the equatorial central Pacific. Besides, the warm SST anomalies lasted for longer over the central Pacific in the late subperiod, suggesting a decadal westward shift of El Niño–related SST anomalies. From this perspective, the anomalous atmospheric circulation responses to El Niño–related SST anomalies are expected to extend westward correspondingly.
Composite monthly anomalies of SST (unit: °C) over (a) Niño-3.4 (5°S–5°N, 170°–120°W), (b) Niño-3 (5°S–5°N, 90°–150°W), (c) Niño-4 (5°S–5°N, 160°E–150°W), and (d) the Indian Ocean Basin (IOB; 20°S–20°N, 40°E–100°W) from developing autumn to decaying summer for El Niño events during 1961–91 and 1992–2020. The solid bars are significant with p < 0.05, and the dashed box denotes the months of the PFS.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
Figure 9 further shows the SST and 850-hPa wind anomalies during the PFS for El Niño events in the different subperiods. For 1961–91, El Niño warm SST anomalies persisted in AMJ over the central Pacific and were flanked by cold SST anomalies over the western Pacific (Fig. 9a). In this case, the atmospheric circulation responses reflected by the abnormal 850-hPa wind field are generally located over the central and western Pacific regions during the PFS. Especially over the northwestern Pacific, an obvious NPAAC forms that would exert evident effects on the East Asian climate (Wang et al. 2000, 2003; Yang et al. 2007; Xie et al. 2009, 2016; Chen et al. 2019, 2021; Li et al. 2019; Gao et al. 2020a,b). In comparison, the warm SST anomalies over the central Pacific during the PFS in 1992–2020 were stronger, with a warm center and significant cold SST situated more westward than in 1961–91 (Fig. 9b). Accordingly, the anomalous 850-hPa wind field responding to the SST anomaly moved westward over the northwestern Pacific, and the tropical Indian Ocean warming anchored this significant wind anomaly. This situation shows a clear decadal westward extension of the El Niño–related SST and atmospheric circulation anomalies. Note that there were two extreme El Niño events (i.e., 1997/98 and 2015/16) after the early 1990s and one extreme El Niño event (i.e., 1982/83) before the early 1990s. To verify whether such extreme El Niño events would affect our aforementioned results, we checked the decadal changes in El Niño SST anomalies and circulation responses after removing the three extreme El Niño decaying years (figure not shown). The new results are generally the same and still indicate that the enhanced warm SST anomaly over the tropical central Pacific with longer duration in El Niño events for the late subperiod led to a westward extension of the atmospheric circulation responses, which further supports our above findings.
Composite anomalies of 850-hPa wind (arrows; only wind anomalies that are significant with p < 0.05 are shown; units: m s−1) and SST (colors; the cross symbols mark areas that are significant with p < 0.05; unit: °C) in AMJ following the El Niño events during (a) 1961–91 and (b) 1992–2020. The red box denotes the SC region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
As mentioned above, the El Niño–induced NPAAC plays a key role in regulating the East Asian climate states in decaying phases. Therefore, we further illustrate the streamfunction and rotational wind anomalies at the 850-hPa layer during the PFS under different cases in Fig. 10. In 1961–91, the abnormal rotational wind shows that the main body of the El Niño–induced NPAAC was generally located to the east of the Philippines (Fig. 10a), and SC was impacted by the southwesterly flow in the northwestern rim. By comparison, during 1992–2020, such an NPAAC evidently shifted westward across the Indo-China Peninsula to the northern Indian Ocean (Fig. 10b). Under this circumstance, SC was located in the northern flank and was also affected by an abnormal southwesterly wind.
Composite anomalies of 850-hPa rotational wind (arrows; only wind anomalies that are significant with p < 0.05 are shown; units: m s−1) and streamfunction (contours; the dashed and solid lines denote the negative and positive values; the contour interval is 0.4; the zero contour is thickened; units: m2 s−1) in AMJ following El Niño events during (a) 1961–91 and (b) 1992–2020. The red box denotes the SC region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
Anomalous precipitation is commonly attributed to abnormal moisture transporting and ascending motion. The low-level wind plays the decisive role in tropospheric air moisture transporting due to the vertical distribution of the water vapor (more and less moisture at lower and higher atmospheric layers), which is the major source for regional precipitation. Therefore, the abnormal southwesterly wind provides a necessary but not sufficient condition for SC precipitation. Besides, it is well known that the NPAAC is always accompanied by a strong abnormal descending motion. As shown in Fig. 11a, the positive AMJ 500-hPa vertical velocity anomalies over the tropical area related to El Niño in 1961–91 were located mainly to the east of the Philippines. Accordingly, the regional Hadley circulation was also affected with an abnormal ascending movement to the east of SC (Fig. 11a). Thus, for 1961–91, the vertical circulation over the SC was barely affected in the PFS following El Niño. On the other hand, the abnormal downward motion extended westward during AMJ in 1992–2020, covering from the Philippines to the southern Indo-China Peninsula (Fig. 11b). Meanwhile, the abnormal ascent in the regional Hadley circulation also extended westward to SC for the late subperiod correspondingly. As a result, this induces the anomalous ascending motion over South China, although the regional Hadley circulation response over the northwestern Pacific to Southern China is only confined in a limited longitude band.
Composite anomalies of 500-hPa vertical velocity (colors; units: 1 × 10−2 Pa s−1; negative values denote upward motion) in AMJ for the El Niño events during (a) 1961–91 and (b) 1992–2020. The white-line-enclosed and dotted areas are significant with p < 0.1 and p < 0.05, respectively. The red box denotes the SC region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
To clarify the above findings, the longitude–height cross section of vertical wind anomaly averaged over 109°–120°E (covering the SC region) is shown in Fig. 12. For the PFS following El Niño in 1961–91, the regional Hadley circulation anomaly over SC was relatively weak (Fig. 12a). Specifically, there was barely any abnormal ascending motion above SC. In contrast, there was an obvious anomalous regional Hadley circulation in the El Niño decaying AMJ during 1992–2020, featuring strong descending and ascending motions over the tropical and SC regions, respectively (Fig. 12b). This indicates that El Niño in 1992–2020 provided more-favorable conditions for the SC precipitation during the subsequent PFS.
Composite anomalies of vertical velocity averaged over 109°–120°E (arrows and colors; the shown arrows are significant with p < 0.05; units: 1 × 10−2 Pa s−1) in AMJ following the El Niño events during (a) 1961–91 and (b) 1992–2020. The red box is above the SC region.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
In summary, local ascending motion is a crucial condition for regional precipitation. For SC, the abnormal vertical movement is tightly linked to local precipitation anomaly in the PFS. Nevertheless, El Niño exerted distinctly different effects on the SC vertical motion during the subsequent PFS for the two subperiods. In the early subperiod (1961–91), the correlation coefficient of preceding-winter ONI with the AMJ SC vertical velocity anomaly was only −0.19 (Fig. 13a), implying that El Niño exerted little influence on the PFS SC precipitation as reflected in Fig. 4a, whereas in 1992–2020 it reached approximately −0.38 (p < 0.05; Fig. 13b), indicating a strong effect of El Niño on the SC vertical circulation. As a result, an abnormally warmer SST over the central Pacific led to evident ascending motion over SC during the PFS in the three most recent decades, thus causing excessive local precipitation (Fig. 4b).
Scatter relationships between preceding-winter ONI and AMJ 500-hPa vertical velocity anomaly over SC for (a) 1961–91 and (b) 1992–2020; r and p denote the correlation coefficient and its significance level, respectively. The straight line is the linear fitted line, and only the solid line indicates a statistically significant relationship.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
6. Conclusions and discussion
The PFS precipitation over SC contributes ∼40%–50% of the local annual precipitation and has serious regional socioeconomic impacts. This study investigated the effect of El Niño on the subsequent PFS precipitation over SC for 1961–2020. The results showed a decadal enhancement in the effect of El Niño on the subsequent PFS precipitation over SC: whereas there were no significant PFS precipitation anomalies over SC following El Niño before the 1990s, El Niño has tended to induce a strong abnormal upward motion and excessive PFS precipitation over SC since the early 1990s.
This decadal enhancement in the effect of El Niño on the subsequent PFS precipitation over SC is due to the stronger intensity and longer duration of El Niño–related warm SST anomalies over the equatorial central Pacific after the early 1990s than before. The El Niño–related SST anomalies could force an NPAAC in the subsequent PFS. On one hand, the northwestern flank of the NPAAC features southwesterly wind anomalies, which could transport water vapor from the South China Sea. On the other hand, accompanying the NPAAC, an abnormal descending motion exists over the tropical western Pacific, resulting in a weakened regional Hadley circulation with an abnormal ascending motion over subtropical East Asia. Before the early 1990s, this abnormal ascending motion was located mainly to the east of SC, exerting no significant impact on the PFS precipitation over SC. By contrast, after the early 1990s, El Niño–related warm SST anomalies over the equatorial central Pacific were stronger and longer lasting with a westward extension, leading to a westward shift of the abnormal cold SST over the northwest Pacific. This enhances the NPAAC with a decadal westward extension. As a result, since the early 1990s, the anomalous regional Hadley circulation has been more evident over SC during the El Niño decaying AMJ, causing a strong abnormal upward motion and excessive PFS precipitation there. In this process, the Indian Ocean SST anomaly contributes to the formation of the feedback loop in the sea–atmosphere interaction over the northwestern Pacific and anchors the NPAAC until the subsequent summer (Li et al. 2017). As shown in Fig. 14, the IOB warming in AMJ is tightly linked to the preceding-winter El Niño SST anomalies and has an evident effect on the SC precipitation (Figs. 14a,b). After removing the IOB AMJ SST signal, the correlation coefficient of the winter ONI with the AMJ SC precipitation anomaly is only −0.07. This further confirms that the Indian Ocean plays a key role in conveying the El Niño signal from the mature winter to the subsequent PFS.
Scatter relationships of (a) preceding-winter ONI with AMJ IOB SST anomaly, (b) IOB SST with SC precipitation anomalies in AMJ, and (c) ONI removing IOB signal (based on regression approach) with AMJ SC precipitation anomaly for 1992–2020. All data are standardized; r and p denote the correlation coefficient and its significance level, respectively. The straight line is the linear fitted line, and only the solid lines indicate statistically significant relationships.
Citation: Journal of Climate 36, 23; 10.1175/JCLI-D-22-0864.1
Monsoon precipitation is a major source of water in China and, coupled with the advance of the monsoon system, the rain belt in China moves from south to north during the rainy season. For SC, the PFS precipitation provides the majority of the local annual precipitation and is crucial for the agrarian-based socioeconomic livelihood in this densely populated region, including agriculture, water resources, food security, ecosystems, disaster mitigation, infrastructure construction, and human health. Our results highlight a decadal enhancement in the effect of El Niño on the SC precipitation during the PFS since the early 1990s, and they improve our understanding of the interannual variation of the PFS precipitation over SC. In summer, SC still suffers from heavy precipitation events, and Wu et al. (2010) reported that it also experienced a decadal increment in summer precipitation around 1992/93 partly due to an increase in SST in the equatorial Indian Ocean. A recent study revealed that El Niño has exerted a stronger effect on the Indian Ocean warming in the decaying phase during recent decades (Zhang and Li 2023), which is also implied in our results (Figs. 7 and 8). This indicates that such decadal-intensified SC summer precipitation may be related to the interdecadal changes in the variability of El Niño as well, and it is worth investigating further.
Furthermore, El Niño diversity is also important for regional climate predictions and exerts different effects on the East Asian climate (Gao et al. 2020; Luo and Lau 2020; Wen et al. 2020). Previous studies have revealed a higher frequency and stronger intensity of El Niño against the background of global warming, with El Niño tending to develop and mature in the tropical central Pacific with prolonged lifetime (Lee and McPhaden 2010; Cai et al. 2014; Xia et al. 2017). This could plausibly explain the increased occurrence of the central Pacific El Niño warming under the projected future warming scenarios (Yeh et al. 2009). A question is whether such El Niño diversity can have different effects on the subsequent PFS SC precipitation, and if so how. This could be explored thoroughly in the future.
Acknowledgments.
This work was supported by the National Natural Science Foundation of China (41831175), the Fundamental Research Funds for the Central Universities (B210201029), the Independent Research Project of the National Key Laboratory of Water Disaster Prevention (5230248D2), the Joint Open Project of KLME and CIC-FEMD (KLME202202), and the Key Scientific and Technological Project of the Ministry of Water Resources, China (SKS-2022001).
Data availability statement.
The precipitation data were provided by the Climate Change Research Center of China (https://ccrc.iap.ac.cn/resource/detail?id=228) and the China Meteorological Administration (http://data.cma.cn), the SST data were obtained from the HadISST dataset (https://www.metoffice.gov.uk/hadobs/hadisst/data/download.html), the atmospheric reanalysis data were obtained from the Japan Meteorological Agency (https://jra.kishou.go.jp/JRA-55/index_en.html), and the Oceanic Niño Index was obtained from the Climate Prediction Center of the United States (http://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php).
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