Abstract

The period from April to June signifies the transition from spring to summer over the South China Sea (SCS). The present study documents two distinct processes for abnormal spring to summer transition over the SCS. One process is related to large-scale sea surface temperature (SST) anomalies in the tropical Indo-Pacific region. During spring of La Niña decaying years, negative SST anomalies in the equatorial central Pacific (ECP) and the southwestern tropical Indian Ocean (TIO) coexist with positive SST anomalies in the tropical western North Pacific. Negative ECP SST anomalies force an anomalous Walker circulation, negative southwestern TIO SST anomalies induce anomalous cross-equatorial flows from there, and positive tropical western North Pacific SST anomalies produce a Rossby wave–type response to the west. Together, they contribute to enhanced convection and an anomalous lower-level cyclone over the SCS, leading to an advanced transition to summer there. The other process is related to regional air–sea interactions around the Maritime Continent. Preceding positive ECP SST anomalies induce anomalous descent around the Maritime Continent, leading to SST increase in the SCS and southeast TIO. An enhanced convection region moves eastward over the south TIO during spring and reaches the area northwest of Australia in May. This enhances descent over the SCS via an anomalous cross-equatorial overturning circulation and contributes to further warming in the SCS. The SST warming in turn induces convection over the SCS, leading to an accelerated transition to summer. Analysis shows that the above two processes are equally important during 1979–2015.

1. Introduction

Climatologically, the South China Sea summer monsoon onset occurs around mid-May (e.g., Wu and Wang 2000). The period from April to June signifies the transition from spring to summer in the South China Sea and the adjacent regions. An advanced or a delayed transition may have important implication for weather and climate anomaly. First, it may indicate an early or a late start of summer season around the South China Sea. Second, it may imply an advanced or a delayed occurrence of severe weather events and active phases of intraseasonal oscillations over the South China Sea and the neighboring regions. Third, it may serve as an indicator for summer rainfall anomalies over the South China Sea. For example, Wu and Hu (2015) showed that the June-minus-April rainfall anomaly, which represents the pace of seasonal transition around May, has a correlation coefficient of 0.68 with summer rainfall anomalies averaged over the South China Sea for the period 1979–2010. Thus, it is of significance to understand the processes leading to early or late spring to summer transition.

In general, the advanced or delayed start of summer season may be attributed to two types of anomalies. One is the persistent anomaly from spring to early summer. The other is the change of anomaly in the transition season. The effects of these two types of anomalies on the spring to summer transition are illustrated in a schematic diagram shown in Fig. 1. Corresponding to a persistent positive anomaly, the state in the seasonal evolution appears earlier than climatology, leading to an early transition to summer. Corresponding to a positive change anomaly, the state before the transition could be below normal, but the change is much larger than the normal seasonal progress. The large change anomaly overcomes the anomaly at the start so that the anomaly at the end is above normal. This leads to an accelerated transition to summer. In reality, the abnormal transition in individual years may be due to the persistent anomaly or the change anomaly or a combination of both. Revealing the contribution of these two types of anomalies and the associated processes can advance our knowledge of factors and processes of abnormal spring to summer transition.

Fig. 1.

A schematic diagram illustrating the precipitation change in the early transition (dashed) and the accelerated transition (dotted) compared to that in the normal transition (solid). The horizontal line denotes the reference rainfall (Pc).

Fig. 1.

A schematic diagram illustrating the precipitation change in the early transition (dashed) and the accelerated transition (dotted) compared to that in the normal transition (solid). The horizontal line denotes the reference rainfall (Pc).

Wu and Hu (2015) and Hu and Wu (2016) analyzed in detail the climate anomalies during the spring to summer transition season over the north Indian Ocean and the South China Sea corresponding to the mean anomaly (the average of anomaly in April, May, and June) and the change anomaly (the difference of the anomaly in June minus the anomaly in April). They detected very different atmospheric and oceanic anomalies over the tropical Indo-Pacific Ocean corresponding to the mean rainfall anomaly and the rainfall change anomaly in the South China Sea region. The mean rainfall anomaly is associated with large-scale sea surface temperature (SST) anomaly pattern in the tropical Indo-Pacific region. The rainfall change anomaly is related to regional air–sea interaction processes in the South China Sea region, featuring a sequence of less rainfall, higher SST, more rainfall, and lower SST. Their analyses are based on regression with respect to the area-averaged rainfall mean anomaly and change anomaly. However, because of the co-occurrence of mean anomaly and change anomaly in some years, parts of the identified signals may be related to both types of anomalies. As such, the effects of these two anomalies are not completely separated from each other in these previous studies. Further, it is not investigated what initiates the rainfall anomalies over the South China Sea in the above sequence of anomalies corresponding to the change anomaly.

The present study separates the two types of years in the analysis of abnormal spring to summer transition in the South China Sea region. One type is dominated by the mean anomaly and the other type is dominated by the change anomaly. We investigate the processes leading to the two types of abnormal transitions respectively. Distinctive features are identified in the two types of years. In particular, we identify signals over the southeast tropical Indian Ocean in the transition corresponding to the change anomaly. In the following, we describe the datasets in section 2. In section 3, we present the classification of two types of years and contrast the evolution of rainfall anomalies. In section 4, we analyze the processes in the years dominated by persistent mean anomalies. In section 5, we investigate the processes in the years primarily due to change anomalies. Section 6 further analyzes the signals over the southeast tropical Indian Ocean associated with the transition due to change anomalies. A summary of main results is presented in section 7 along with some discussion.

2. Datasets

The present study used monthly precipitation of the Global Precipitation Climatology Project (GPCP) version 2.2 (Adler et al. 2003; Huffman et al. 2009). The GPCP precipitation data are available on 2.5° × 2.5° latitude–longitude grids from January 1979 to the present. The GPCP dataset is provided by the NOAA/OAR/ESRL Physical Science Department (PSD) (http://www.esrl.noaa.gov/psd/).

The monthly mean SST used in the present study is the National Oceanic and Atmospheric Administration (NOAA) optimum interpolation (OI) version 2 (Reynolds et al. 2002). This SST dataset has a resolution of a 1° × 1° grid and is available for the period of December 1981 to present. The OI SST is obtained from http://www.esrl.noaa.gov/psd/.

The present study uses monthly mean winds at 10 m, 850 hPa, and 200 hPa from the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) Reanalysis 2 (Kanamitsu et al. 2002). The NCEP–DOE reanalysis is provided by the NOAA/OAR/ESRL PSD from the website at http://www.esrl.noaa.gov/psd/. The reanalysis variables are available from 1979 to the present. The 850- and 200-hPa winds are on a 2.5° × 2.5° grid and surface winds are on T62 Gaussian grid.

The monthly mean surface shortwave and longwave radiations and surface latent and sensible heat fluxes are from the TropFlux data (Praveen Kumar et al. 2012). The TropFlux data are available on a 1° × 1° grid starting from 1979 and obtained from the website at http://www.incois.gov.in/tropflux_datasets/data/monthly/. Note that positive shortwave radiation and latent heat flux anomaly denotes downward flux into the ocean in the present study.

3. Classification of two types of years

The classification of years is determined based on a comparison of the mean anomaly and the change anomaly of area-mean rainfall over the region 5°–20°N, 110°–120°E [the South China Sea (SCS)] in the transition season. Figure 2 shows normalized June minus April (denoted by JmA) and April–June (AMJ) as well as June–August (JJA) rainfall anomalies in the above region. The correlation coefficient of the JmA and AMJ rainfall anomaly with JJA rainfall anomaly in the same region is 0.70 and 0.40, respectively, for the period 1979–2015. The high correlation coefficient of 0.70 suggests that the change anomaly is a good indicator of summer rainfall anomalies over the South China Sea, consistent with Wu and Hu (2015). The correlation coefficient between the JmA and AMJ rainfall anomalies is 0.166 for the period 1979–2015.

Fig. 2.

Normalized area-mean June minus April (JmA) (green), April–June (AMJ) mean (blue), and June–August (JJA) mean (red) rainfall anomalies (mm day−1) over the South China Sea region (5°–20°N, 110°–120°E) for the period 1979–2015. The dotted lines denote ±0.5 standard deviation.

Fig. 2.

Normalized area-mean June minus April (JmA) (green), April–June (AMJ) mean (blue), and June–August (JJA) mean (red) rainfall anomalies (mm day−1) over the South China Sea region (5°–20°N, 110°–120°E) for the period 1979–2015. The dotted lines denote ±0.5 standard deviation.

The AMJ anomaly represents the part of anomalies that persist during the transition. A large AMJ anomaly indicates that the state is earlier or later than climatology. The JmA anomaly denotes the part of anomalies that change during the transition. A large JmA anomaly implies an accelerated or a decelerated switch from spring to summer. The JmA anomaly synthesizes the contribution of both April and June anomalies. In individual years, it is possible that the April or June anomaly alone may influence the transition. Based on the above, the following criteria are used in the classification of years.

  1. If the JmA (AMJ) rainfall anomaly exceeds ±0.5 standard deviations (std) and the AMJ (JmA) rainfall anomaly is within ±0.5 std, the year is classified as one in which the transition is due to the JmA (AMJ) anomaly.

  2. If both the JmA and AMJ rainfall anomalies exceed ±0.5 std and are of the same sign, the year is classified as one in which the transition is due to JmA (AMJ) if the JmA (AMJ) rainfall anomaly is larger, with exceptions for years 1998 and 2011 as explained below.

  3. When both JmA and AMJ rainfall anomalies exceed ±0.5 std and are of opposite sign, the year is excluded in the classification. These include 1999, 2000, 2005, 2008, and 2009. In these five years, the two types of rainfall anomalies in the South China Sea tend to be of the same sign in April, but opposite in June, leading to small anomalies in June.

The first criterion is a traditional one that categorizes the cases when only one anomaly contributes to the transition. The second criterion is used to take care of the cases when the two anomalies are both large, introducing a difficulty in separating the contribution of the two anomalies. In this situation, we determine the relative contributions of the two anomalies based on a comparison of their magnitudes. There are more cases when the two anomalies are both large than when only one anomaly is large, which is associated with the superposition of the two anomalies. Combining the two criteria allows us to increase the number of cases for each type of transitions in the composite analysis. For years 1998 and 2011, the magnitudes of JmA and AMJ rainfall anomalies are quite close with the JmA anomalies slightly larger. Inspection of the temporal evolutions of the SST anomalies in the tropical Indo-Pacific region in these two years (see Fig. 6 below) indicates that they deviate largely from those in other JmA dominant years, but resemble those in the AMJ dominant years. As such, we adjust the classification of these two years and include them in the AMJ dominant years. The final classification of years is displayed in Table 1. There are 13 years in both categories. Note that there are only 11 years available for the SST analysis in the change anomaly category.

Table 1.

List of the two types of years for abnormal spring to summer transition over the South China Sea during 1979–2015. The plus and minus signs denote advanced and delayed transitions, respectively.

List of the two types of years for abnormal spring to summer transition over the South China Sea during 1979–2015. The plus and minus signs denote advanced and delayed transitions, respectively.
List of the two types of years for abnormal spring to summer transition over the South China Sea during 1979–2015. The plus and minus signs denote advanced and delayed transitions, respectively.

Based on the above classification, we make composite anomalies for these two types of years respectively. This allows a separation of effects of the mean anomaly and the change anomaly in the spring to summer transition. We have examined composite anomalies corresponding to positive and negative mean anomaly and change anomaly years separately. The obtained anomalies are similar in most regions in positive and negative anomaly years (with opposite signs) although differences are present in some regions (figures not shown). To increase the number of cases for composite analysis and thus the robustness of composite anomalies, we reverse the sign of anomalies in delayed transition years and group them together with those in advanced transition years. Because of this, the composite anomalies only reveal those features common to both advanced and delayed transitions years (except for an opposite sign). The differences between the delayed and advanced transitions are not considered in the present analysis.

The standard deviation of individual anomalies with respect to the composite anomalies is calculated for the two groups of years respectively. This standard deviation represents a spread among the individual anomalies. The magnitude of composite anomalies is compared to the above standard deviation as a measure of the robustness of obtained composite anomalies. In the present study, when the ratio of the magnitude of composite anomalies over the standard deviation is larger than 0.5, which is approximately equivalent to a t value at the 10% significance level according to the Student’s t test, we denote the composite anomalies as significant.

The temporal evolutions of composite SCS rainfall anomalies between the two types of years are compared in Fig. 3. In the years dominated by persistent anomaly (denoting an early transition to summer), the SCS rainfall is above normal until June (Fig. 3a). The persistence of the rainfall anomalies from winter to spring suggests a precursory signal for this type of transitions. In the change anomaly controlled years (denoting an accelerated transition to summer), the SCS rainfall is below normal in and before May and above normal in June (Fig. 3b). A clear signal of accelerated transition from April to June is obvious. In both types of years, the rainfall anomaly turns to be small after June. A comparison of the temporal evolution between the composite mean and spread suggests that the composite SCS rainfall anomalies are less robust in May than in June and April.

Fig. 3.

Temporal evolution of composite monthly rainfall anomalies (mm day−1) over the South China Sea (5°–20°N, 110°–120°E) in the (a) early transition and (b) accelerated transition years. The thin curves denote the ranges of ±0.5 standard deviation (std) of individual anomalies with respect to composite anomalies. The marks denote that the magnitude of composite anomalies is larger than the 0.5 standard deviation.

Fig. 3.

Temporal evolution of composite monthly rainfall anomalies (mm day−1) over the South China Sea (5°–20°N, 110°–120°E) in the (a) early transition and (b) accelerated transition years. The thin curves denote the ranges of ±0.5 standard deviation (std) of individual anomalies with respect to composite anomalies. The marks denote that the magnitude of composite anomalies is larger than the 0.5 standard deviation.

4. Abnormal transition due to the persistent anomaly

In this section, we analyze the transition in years corresponding to the persistent anomaly. Wu and Hu (2015) documented anomalies corresponding to AMJ mean rainfall anomalies based on regression. As pointed out earlier, due to the co-occurrence of the same-sign mean anomaly and change anomaly, the regression analysis cannot distinguish the processes dominated by one type of anomaly. Here, a composite analysis is employed so that the respective effects of the mean anomaly and the change anomaly in the spring to summer transition can be separated. The sign of anomalies described below refers to that corresponding to the advanced transition years.

The composite fields display obvious SST anomalies in the tropical Indo-Pacific region in May (Fig. 4a). Significant negative SST anomalies are observed in the equatorial central and eastern Pacific and the southwestern tropical Indian Ocean, and significant positive SST anomalies extend from the tropical western North Pacific to the extratropical North Pacific. These features agree with those obtained by Hu et al. (2014), who performed a correlation analysis with respect to AMJ South China Sea rainfall anomalies.

Fig. 4.

Composite anomalies of (a) SST (°C), (b) rainfall (mm day−1; shading) and 850-hPa wind (m s−1; vector), and rainfall (mm day−1, shading) and (c) 200-hPa wind (m s−1; vector) in May of the early transition years. The thick contours denote anomalies of SST in (a) and rainfall in (b) and (c) with a magnitude larger than 0.5 std. The black vectors denote wind anomalies with magnitude larger than 0.5 std in (b) and (c). The scale for the wind vectors is shown at top right of the respective panel. The boxes in (a) denote the domains for calculating area-mean SST anomalies in Fig. 6.

Fig. 4.

Composite anomalies of (a) SST (°C), (b) rainfall (mm day−1; shading) and 850-hPa wind (m s−1; vector), and rainfall (mm day−1, shading) and (c) 200-hPa wind (m s−1; vector) in May of the early transition years. The thick contours denote anomalies of SST in (a) and rainfall in (b) and (c) with a magnitude larger than 0.5 std. The black vectors denote wind anomalies with magnitude larger than 0.5 std in (b) and (c). The scale for the wind vectors is shown at top right of the respective panel. The boxes in (a) denote the domains for calculating area-mean SST anomalies in Fig. 6.

Below-normal rainfall is observed over the equatorial central Pacific and the southwestern tropical Indian Ocean (Fig. 4b). Above-normal rainfall covers the tropical western Pacific and the South China Sea. Over the equatorial central Pacific, anomalous easterlies and westerlies are observed at lower and upper levels respectively (Figs. 4b,c). An anomalous lower-level cyclone covers the tropical western North Pacific, the South China Sea, and the Indochina Peninsula (Fig. 4b). A lower-level wind anomaly pattern asymmetric to the equator overlies the tropical Indian Ocean (Fig. 4b), similar to the asymmetric mode (Wu et al. 2008). Large upper-level easterly wind anomalies are observed over the tropical Indian Ocean (Fig. 4c).

The above rainfall and wind anomalies are responses to the SST anomalies as demonstrated by previous studies. The equatorial central Pacific negative SST anomalies enhance convection over the South China Sea through an anomalous Walker circulation (Hu et al. 2014). The southwestern tropical Indian Ocean negative SST anomalies induce anomalous cross-equatorial flows and anomalous westerlies north of the equator (Wu et al. 2008; Hu et al. 2014) that extend eastward to the South China Sea. Annamalai et al. (2005) indicated that local negative SST anomalies in the southwest tropical Indian Ocean may enhance precipitation over the tropical west Pacific and Maritime Continent through an anomalous Indian Ocean Walker circulation, contributing to the development of a low-level cyclone over the Philippine and South China Seas. The tropical western North Pacific positive SST anomalies produce a Rossby wave–type response to the west (Wang et al. 2000; Wu et al. 2014; Hu et al. 2014). Wu and Wang (2000) showed that local warm SST anomalies in the tropical western North Pacific may play an important role in the generation of lower-level cyclonic wind anomalies and enhancement of convective instability. The effects of these SST anomalies on circulation and rainfall changes over the South China Sea during the spring to summer transition season have been confirmed by Hu et al. (2014) using numerical model experiments. The synergistic effects of these SST anomalies lead to enhanced convection over the South China Sea.

The above effects of SST anomalies are further illustrated using 850- and 200-hPa divergent wind anomalies shown in Fig. 5. Corresponding to the SST anomaly pattern in Fig. 4a, there are lower-level divergent winds and upper-level convergent winds over the equatorial eastern Pacific and the southwestern tropical Indian Ocean (Figs. 5a,b). These winds are linked to opposite-sign divergent and convergent winds over the tropical western North Pacific and the South China Sea.

Fig. 5.

Composite anomalies of velocity potential (10−6 m2 s−1; contour) and the associated divergent winds (m s−1; vector) at (a) 850 and (b) 200 hPa in May of the early transition years. The scale for the wind vectors is shown at top right of the respective panel.

Fig. 5.

Composite anomalies of velocity potential (10−6 m2 s−1; contour) and the associated divergent winds (m s−1; vector) at (a) 850 and (b) 200 hPa in May of the early transition years. The scale for the wind vectors is shown at top right of the respective panel.

The SST anomalies in the tropical Indo-Pacific region show persistence in this type of year. This is illustrated using Fig. 6, which displays the temporal evolution of area-mean SST anomalies averaged in the three domains: 5°S–10°N, 180°–140°W [the equatorial central Pacific (ECP)]; 15°S–0°, 50°–70°E [the southwestern Indian Ocean (SWI)]; and 10°–20°N and 130°–170°E [the western North Pacific (WNP)]. The locations of these domains are denoted by boxes in Fig. 4a. The equatorial central Pacific SST remains below normal until summer with decrease in the magnitude of anomalies (Fig. 6a). So does the southwestern tropical Indian Ocean SST (Fig. 6b). By contrast, the SST is above normal in the tropical western North Pacific until July (Fig. 6c). A comparison of the composite mean and spread indicates that the composite SST anomalies are more robust in the equatorial central Pacific than in the southwestern Indian Ocean and the western North Pacific before June. Indeed, during January–May, the area-mean ECP SST anomalies are of the same sign in all the years, but the area-mean SWI and WNP SST anomalies are opposite to the composite mean in a few years (figures not shown). The temporal evolution of SST anomalies indicates a decaying La Niña state in the tropical Pacific. In relation to the persistence of SST anomalies in the tropical Indo-Pacific regions, rainfall and wind anomalies in March and April (figures not shown) display features similar to those in May, consistent with Wu and Hu (2015). The persistence of the SST anomalies in the tropical western North Pacific supports the role of a local thermodynamic feedback mechanism in the maintenance of anomalous lower-level cyclone over the Philippine Sea and the South China Sea (Wang et al. 2000, 2003). Note that the SST anomalies in 1998 and 2011 in the above three regions (displayed as blue and green dashed lines, respectively) follow the composite anomalies, which justify the grouping of these two years in this category. The persistence of the large-scale SST anomaly pattern maintains the enhanced convection over the South China Sea, leading to an earlier transition to summer.

Fig. 6.

Temporal evolution of composite monthly SST anomalies (°C) in the (a) equatorial central Pacific (5°S–10°N, 180°–140°W), (b) southwest tropical Indian Ocean (15°S–0°, 50°–70°E), and (c) tropical western North Pacific 10°–20°N, 130°–170°E in the early transition years. The thin curves denote the ranges of ±0.5 std of individual anomalies with respect to composite anomalies. The marks denote that the magnitude of composite anomalies is larger than 0.5 std. The blue and green curves are SST anomalies in 1998 (sign reversed) and 2011, respectively.

Fig. 6.

Temporal evolution of composite monthly SST anomalies (°C) in the (a) equatorial central Pacific (5°S–10°N, 180°–140°W), (b) southwest tropical Indian Ocean (15°S–0°, 50°–70°E), and (c) tropical western North Pacific 10°–20°N, 130°–170°E in the early transition years. The thin curves denote the ranges of ±0.5 std of individual anomalies with respect to composite anomalies. The marks denote that the magnitude of composite anomalies is larger than 0.5 std. The blue and green curves are SST anomalies in 1998 (sign reversed) and 2011, respectively.

5. Anomalous transition due to the change anomaly

In this section, we analyze the transition in years corresponding to the change anomaly. In the regression analysis of Wu and Hu (2015), most prominent wind and rainfall anomalies corresponding to June minus April rainfall change anomaly are mainly confined to the South China Sea region. Here, we will show pronounced anomalies outside of the South China Sea, indicative of a connection of the change anomaly related abnormal seasonal transition in the South China Sea with other regions. Again, this difference occurs because the regression analysis cannot separate the effects of mean anomaly and change anomaly due to their co-occurrence.

The area-mean SST anomaly averaged in the region of 5°–20°N and 110°–120°E (SCS; denoted by the box in Fig. 8a) displays significant positive values in April and May (Fig. 7a) when the rainfall is below normal (Fig. 3b). Inspection of anomalies in individual years shows that the area-mean SCS SST anomalies are positive in 8 (9) out of 11 years in April (May) (figure not shown). The correspondence indicates an atmospheric forcing of SST change in the South China Sea, as noted by Wu and Hu (2015). On the other hand, the positive SST anomaly precedes the above-normal rainfall in June. This signifies an oceanic forcing of rainfall. The decrease of SST anomaly after May reflects a negative effect of the atmosphere (Wu and Hu 2015). The above temporal relationship between local rainfall and SST changes indicates a local air–sea interaction process starting from below-normal rainfall (Wu and Hu 2015). What initiates the below-normal rainfall over the South China Sea, however, was not addressed in Wu and Hu (2015).

Fig. 7.

Temporal evolution of composite monthly SST anomalies (°C) in the (a) South China Sea (5°–20°N, 110°–120°E), (b) southeast tropical Indian Ocean (15°–5°S, 110°–130°E), and (c) equatorial central Pacific (5°S–10°N, 180°–140°W) in the accelerated transition years. The thin curves denote the ranges of ±0.5 std of individual anomalies with respect to composite anomalies. The marks denote that the magnitude of composite anomalies is larger than 0.5 std.

Fig. 7.

Temporal evolution of composite monthly SST anomalies (°C) in the (a) South China Sea (5°–20°N, 110°–120°E), (b) southeast tropical Indian Ocean (15°–5°S, 110°–130°E), and (c) equatorial central Pacific (5°S–10°N, 180°–140°W) in the accelerated transition years. The thin curves denote the ranges of ±0.5 std of individual anomalies with respect to composite anomalies. The marks denote that the magnitude of composite anomalies is larger than 0.5 std.

It is interesting to note that the SST anomalies in May are positive in both the South China Sea and northwest of Australia (Fig. 8a). Area-mean SST anomalies averaged in the region of 15°–5°S, 110°–130°E [the southeast tropical Indian Ocean (SEIO)] in May (Fig. 7b) are of a magnitude close to those in the SCS (Fig. 7a). Among the 11 years, there are 9 (10) years in which the area-mean SCS (SEIO) SST anomalies are positive in May (figure not shown). By contrast, the rainfall is above normal over the southeast tropical Indian Ocean and north of Australia but below normal over the South China Sea, featuring an antisymmetric distribution about the equator along the longitude of the Maritime Continent (Fig. 8b). This signifies a distinct local rainfall–SST relationship in the above two regions. The lower-level wind anomalies feature a C-shaped distribution over the eastern Indian Ocean and the Maritime Continent, with easterly and westerly north and south of the equator, respectively, and northerly winds near the equator (Fig. 8b). There is anomalous lower-level convergence over the southeast tropical Indian Ocean and north of Australia and anomalous lower-level divergence over the South China Sea. Opposite anomalous divergence appears at upper levels (Fig. 8c). The above feature indicates a different air–sea relationship in May in the above two regions. Over the southeast tropical Indian Ocean and north of Australia, the local SST anomaly appears to induce enhanced convection. Over the South China Sea, the local SST anomaly appears to be a result of atmospheric change.

Fig. 8.

As in Fig. 4, but for the accelerated transition years. The boxes denote the domains for calculating area-mean SST anomalies in Figs. 7a,b.

Fig. 8.

As in Fig. 4, but for the accelerated transition years. The boxes denote the domains for calculating area-mean SST anomalies in Figs. 7a,b.

The wind and rainfall anomalies in the above regions appear to be connected by an anomalous cross-equatorial overturning circulation. This is illustrated by anomalous divergent winds shown in Fig. 9. There are lower-level northerly winds (Fig. 9a) and upper-level southerly winds (Fig. 9b) over the Maritime Continent. Lower-level divergence is overlaid by upper-level convergence over the South China Sea, whereas lower-level convergence is overlaid by upper-level divergence northwest of Australia, indicative of downward motion and upward motion over the two regions, respectively. The above results suggest a role of the SST anomalies northwest of Australia in suppressing rainfall over the South China Sea. Such a cross-equatorial overturning circulation was proposed by Wu et al. (2012) to play an important role in the influence of the southeastern tropical Indian Ocean SST anomalies on summer rainfall variability over southern China during 1980s and 1990s.

Fig. 9.

As in Fig. 5, but for the accelerated transition years.

Fig. 9.

As in Fig. 5, but for the accelerated transition years.

To verify the impacts of SST anomalies northwest of Australia, we perform numerical experiments with an atmospheric general circulation model. The model used is the atmospheric component of the Community Earth System Model version 1.0.4 (Vertenstein et al. 2011). The atmosphere model is coupled with the Community Land Model component with prescribed sea ice and ocean data. The atmospheric model is configured with 26 hybrid sigma levels on a 1.9° × 2.5° finite volume grid. Two experiments were conducted in this study. In the first experiment (control), climatological annual cycle of SST forcing is specified and the model is integrated for 30 years. In the second experiment (sensitivity), a patch of positive SST anomalies is added northwest of Australia. The distribution of specified SST anomalies, as shown in Fig. 10a, follows the observations (Fig. 8a). The magnitude of SST anomalies is multiplied by 2 to obtain a robust response over atmospheric internal variability. The model is integrated for 15 years and the last 10 years are analyzed. The difference between the sensitivity and control integrations represents the atmospheric response to the specified SST anomalies.

Fig. 10.

(a) SST anomalies (°C) specified in the sensitivity experiment of the atmospheric general circulation model, (b) precipitation (mm day−1; shading) and velocity potential (10−6 m2 s−1; contour) and associated divergent winds (m s−1; vector) at 1000 hPa, and (c) precipitation (mm day−1; shading) and velocity potential (10−6 m2 s−1; contour) and associated divergent winds (mm s−1; vector) at 200 hPa in the model in response to the specified SST anomalies. The scale for the wind vector is shown at top right of the respective panel.

Fig. 10.

(a) SST anomalies (°C) specified in the sensitivity experiment of the atmospheric general circulation model, (b) precipitation (mm day−1; shading) and velocity potential (10−6 m2 s−1; contour) and associated divergent winds (m s−1; vector) at 1000 hPa, and (c) precipitation (mm day−1; shading) and velocity potential (10−6 m2 s−1; contour) and associated divergent winds (mm s−1; vector) at 200 hPa in the model in response to the specified SST anomalies. The scale for the wind vector is shown at top right of the respective panel.

In response to positive SST anomalies northwest of Australia, positive rainfall, lower-level convergence, and upper-level divergence are produced there (Figs. 10b,c). The model also simulated lower-level northerly and upper-level southerly cross-equatorial divergent winds, in agreement with the observations. Opposite divergence is simulated over the South China Sea, consistent with the observations. The rainfall response displays some deviations from the observations. Reduced rainfall over the South China Sea is located somewhat northward compared to the observations and rainfall along the northwest and southeast coasts of Borneo is enhanced and reduced, respectively (Fig. 10b). Nevertheless, the model results support the impacts of SST anomalies northwest of Australia on the circulation and rainfall over the South China Sea. This result is consistent with He and Wu (2014), who conducted atmospheric model experiments with negative SST anomalies specified in the southeastern tropical Indian Ocean and north of Australia in the northern summer.

The warmer SST in the South China Sea in May induces anomalous lower-level convergence and above-normal rainfall in June (Figs. 11b,c). This leads to an accelerated transition to summer there. This also turns around the anomalous overturning circulation over the Maritime Continent as indicated by cross-equatorial anomalous southwesterly winds at lower levels and northeasterly winds at upper levels over the Maritime Continent (Figs. 11b,c and 12). The large suppressed shortwave radiation and enhanced upward latent heat flux over the South China Sea (not shown) immediately reduce the SST locally (Fig. 7a). An enhanced convection region appears over the equatorial western Pacific in June (Figs. 11b,c), invigorated by warmer SST in the equatorial central Pacific (Fig. 11a). This is accompanied by anomalous lower-level westerlies and upper-level easterlies over the equatorial western Pacific (Figs. 11b,c).

Fig. 11.

As in Fig. 8, but for June.

Fig. 11.

As in Fig. 8, but for June.

Fig. 12.

As in Fig. 9, but for June.

Fig. 12.

As in Fig. 9, but for June.

An important advance of the present analysis over Wu and Hu (2015) is the identification of the role of SST anomalies northwest of Australia in the suppression of convection over the South China Sea that in turn contributes to the SST increase there. This suggests that abnormal spring to summer transition over the South China Sea is not an isolated phenomenon. Instead, changes in other regions are involved through anomalous circulation, such as the cross-equatorial overturning circulation over the Maritime Continent.

6. Source of anomalous convection northwest of Australia

A key element for the cross-equatorial overturning circulation is higher SST and associated enhanced convection over the southeastern tropical Indian Ocean. What causes the SST increase and convection enhancement northwest of Australia? To address this question, we examine the temporal changes of anomalies in March and April. Figure 13 shows anomalous rainfall, SST, and surface and upper-level wind in March and April. Figure 14 shows 850- and 200-hPa velocity potential and divergent winds in March and April. Figure 15 shows surface net shortwave radiation and latent heat flux anomalies, the two largest terms in surface heat flux over the tropical ocean, in March and April.

Fig. 13.

Composite anomalies of (left) rainfall (mm day−1; shading) and wind at 10 m (m s−1; vector) and (right) SST (°C, shading) and wind at 200 hPa (m s−1, vector) in (a),(b) March and (c),(d) April of the accelerated transition years. The thick contours denote anomalies of rainfall in (a) and (c) and SST in (b) and (d) with magnitude larger than 0.5 std. The black vectors denote wind anomalies with magnitude larger than 0.5 std in (b) and (c). The scale for the wind vector is shown at top.

Fig. 13.

Composite anomalies of (left) rainfall (mm day−1; shading) and wind at 10 m (m s−1; vector) and (right) SST (°C, shading) and wind at 200 hPa (m s−1, vector) in (a),(b) March and (c),(d) April of the accelerated transition years. The thick contours denote anomalies of rainfall in (a) and (c) and SST in (b) and (d) with magnitude larger than 0.5 std. The black vectors denote wind anomalies with magnitude larger than 0.5 std in (b) and (c). The scale for the wind vector is shown at top.

Fig. 14.

Composite anomalies of velocity potential (10−6 m2 s−1; contour) and the associated divergent winds (m s−1; vector) at (left) 850 and (right) 200 hPa in (a),(b) March and (c),(d) April of the accelerated transition years. The scale for the wind vector is shown at top.

Fig. 14.

Composite anomalies of velocity potential (10−6 m2 s−1; contour) and the associated divergent winds (m s−1; vector) at (left) 850 and (right) 200 hPa in (a),(b) March and (c),(d) April of the accelerated transition years. The scale for the wind vector is shown at top.

Fig. 15.

Composite anomalies of (left) surface net shortwave radiation (W m−2) and (right) latent heat flux (W m−2) in (a),(b) March and (c),(d) April of the accelerated transition years. The thick contours denote anomalies with magnitude larger than 0.5 std.

Fig. 15.

Composite anomalies of (left) surface net shortwave radiation (W m−2) and (right) latent heat flux (W m−2) in (a),(b) March and (c),(d) April of the accelerated transition years. The thick contours denote anomalies with magnitude larger than 0.5 std.

In March, moderate positive SST anomalies are observed in the equatorial central Pacific (Figs. 13b and 7c). This induces anomalous lower-level wind convergence, upper-level wind divergence, and above-normal rainfall over the equatorial central Pacific. Area-mean rainfall anomalies averaged in the region of 5°S–5°N and 160°E–160°W are positive in March in 12 out of 13 years (figure not shown). Negative rainfall anomalies are observed in both the eastern equatorial Indian Ocean/South China Sea and northwest of Australia (Fig. 13a), which is associated with anomalous lower-level diverging winds and upper-level converging winds (Figs. 13a,b). The rainfall and wind anomalies over the above regions appear to be a response to the equatorial central Pacific positive SST anomalies. This is illustrated by anomalous divergent winds shown in Figs. 13a and 13b. We observe anomalous lower-level convergence and upper-level divergence over the equatorial central Pacific and opposite divergence and convergence over the eastern tropical Indian Ocean and the Maritime Continent. Anomalous westerly and easterly divergent winds are observed over the western equatorial Pacific at lower and upper levels, respectively. These indicate that the response is attributed to an anomalous Walker circulation induced by SST anomalies in the equatorial central Pacific.

In March, the SST anomalies are very weak in the South China Sea (Fig. 13b). Positive SST anomalies appear in the southeastern equatorial Indian Ocean and north of Australia. Thus, there appears to be an earlier development of SST anomalies northwest of Australia compared to the South China Sea. This is confirmed by comparing the temporal evolution of area-mean SST anomalies in the SCS and the SEIO (Figs. 7a,b). As both the South China Sea and northwest of Australia are under the influence of anomalous descent, net surface shortwave radiation increases significantly in both regions (Fig. 15a), which favors the development of positive SST anomalies. Latent heat flux contributes to the SST change in the two regions as well. Off the northwest coast of Australia, upward latent heat flux is reduced (Fig. 15b). This reduction may be explained by the wind speed decrease as anomalous southeasterly winds (Fig. 13a) are against climatological westerly winds in this region. As such, shortwave radiation and latent heat flux act together to contribute to the SST increase northwest of Australia. There may also be contribution from suppressed vertical oceanic mixing due to the weakened surface winds. Over the South China Sea, the decrease in upward latent heat flux is observed over the northern part (Fig. 15b) where anomalous and climatological mean winds are opposite. In comparison, shortwave radiation and latent heat flux anomalies are larger over the southern and northern South China Sea, respectively (Figs. 15a,b).

A northeast–southwest contrasting feature is notable over the Indian Ocean in March. Rainfall is below normal over northern Sumatra and southern Malaysia and above normal over the subtropical central Indian Ocean (Fig. 13a). Lower-level divergence extends westward from the southern South China Sea to the southern Bay of Bengal and lower-level convergence exists over the subtropical central Indian Ocean with northerly divergent winds in between (Fig. 14a). Opposite anomalous divergence and winds are observed at upper levels (Fig. 14b) with some eastward shift in the location compared to those at lower levels.

From March to April, the SST anomalies in the South China Sea increase quickly (Figs. 13d and 7a). The positive SST anomaly region expands in the southeast tropical Indian Ocean and north of Australia as well. Such an SST anomaly increase is contributed by downward shortwave radiation increase and upward latent heat flux decrease as discussed above. The positive SST anomalies in the equatorial central Pacific change little (Figs. 13d and 7c). A weakening along with a shrink in the areal extent is observed in anomalous rainfall over the equatorial central Pacific (Fig. 13c). Consequently, anomalous divergent winds between the equatorial central Pacific and the Maritime Continent become weaker in April (Figs. 14c,d) compared to March (Figs. 14a,b). This indicates a reduced influence of anomalous heating over the equatorial central Pacific on the South China Sea and northwest of Australia in April.

The contrasting features in rainfall and divergent winds over the tropical Indian Ocean become more pronounced in April. Compared to March, the below-normal rainfall region appears to move westward to the north Indian Ocean and the above-normal rainfall region over the south Indian Ocean extends northeastward, forming a prominent north–south contrast (Fig. 13c). At lower levels, anomalous northwesterly winds blow from suppressed to enhanced rainfall regions (Fig. 13c). At upper level, anomalous southwesterly winds are observed over the equatorial Indian Ocean (Fig. 13d). The north-south contrasting anomalies are very prominent in divergent winds over the tropical Indian Ocean, which are opposite at lower level and upper level (Figs. 14c,d). These features indicate an anomalous cross-equatorial overturning circulation over the Indian Ocean.

With the approach of enhanced convection, surface net shortwave radiation turns to decrease and upward surface latent heat flux turns to increase off the west coast of Sumatra (Figs. 15c,d). These lead to a decrease of positive SST anomalies there from April to May (Figs. 13d and 8a). Northwest of Australia, the SST anomalies keep increasing due to the maintenance of enhanced downward net shortwave radiation and reduced upward latent heat flux (Figs. 14c,d). The maintenance of increased downward shortwave radiation and reduced upward latent heat flux over the northern South China Sea (Figs. 15c,d) favors the increase of positive SST anomalies in the South China Sea as well (Figs. 13d, 8a, and 7a). The anomalous meridional overturning circulation over the tropical Indian Ocean appears to move eastward to the Maritime Continent from April to May (Figs. 14c,d and 9). This eastward move may be related to the SST warming northwest of Australia (Figs. 13d and 8a) that may induce anomalous lower-level convergence (Lindzen and Nigam 1987) and thus enhance convection there.

7. Summary and discussion

An abnormal spring to summer transition may be indicative of summer climate anomaly. The present study distinguishes two types of years during which the abnormal spring to summer transitions over the South China Sea are associated with the mean anomaly and the change anomaly respectively. Analysis reveals distinct processes leading to abnormal spring to summer transition over the South China Sea in these two types of years. Advancing the results of Wu and Hu (2015), the present study identifies that the advanced transition in relation to the change anomaly involves changes over the tropical Indian Ocean and north of Australia.

In years with persistent rainfall anomalies, the negative SST anomalies in the equatorial central Pacific maintain their roles in inducing anomalous cooling with their magnitude decreasing somewhat from preceding winter to early summer. The coexisting negative SST anomalies in the southwestern tropical Indian Ocean induce cross-equatorial flows and anomalous easterly winds extending from the north Indian Ocean to the South China Sea. The accompanying positive SST anomalies in the tropical western North Pacific produce a Rossby wave–type response to the west. Together, they lead to persistent enhanced convection and an earlier transition to summer over the South China Sea.

In years dominated by the rainfall change anomaly, the equatorial central Pacific positive SST anomalies produce large above-normal rainfall there around March. The associated anomalous heating over the equatorial central Pacific suppresses convection around the Maritime Continent via an anomalous Walker circulation, which contributes to the SST increase in the South China Sea. After April, although the SST anomalies are maintained in the equatorial central Pacific, rainfall anomalies are weak there. As such, the equatorial central Pacific SST effect becomes small. A large north–south contrasting pattern of wind and rainfall anomalies develops over the tropical Indian Ocean. This pattern moves eastward to the Maritime Continent. With the weakening of anomalous heating over the equatorial central Pacific, anomalous heating northwest of Australia takes a leading role in further suppressing convection over the South China Sea via an anomalous cross-equatorial overturning circulation, sustaining the SST increase in the South China Sea. Thus, the SST warmings in the equatorial central Pacific and northwest of Australia play a combined role in relay in suppressing the convection and maintaining the warming of the upper ocean in the South China Sea region. In turn, the South China Sea SST warming enhances the convection in June, leading to an accelerated transition to summer.

One prominent difference between the two types of years is that there are opposite SST anomalies in the equatorial central Pacific in preceding winter and spring. In the first type, large negative SST anomalies persist with their magnitude decreasing during spring and summer. These SST anomalies induce regional SST anomalies in the tropical Indian Ocean and western North Pacific through the atmospheric changes as demonstrated in previous studies (e.g., Klein et al. 1999; Alexander et al. 2002; Lau and Nath 2003; Wang et al. 2000, 2003). The large-scale SST anomaly pattern in the tropical Indo-Pacific region induces enhanced convection over the South China Sea that persists from previous winter to early summer. In the second type, moderate positive SST anomalies are maintained in the equatorial central Pacific. Their roles are manifested in suppressing convection and initiating the SST warming in the South China Sea and northwest of Australia around March. After regional SST warms up, the roles of equatorial central Pacific SST anomalies weaken and the regional air–sea coupled processes in the eastern tropical Indian Ocean take a leading role in maintaining the reduced convection and sustaining the SST warming in the South China Sea until May. The present analysis shows that advanced spring to summer transition over the South China Sea can occur corresponding to both positive and negative SST anomalies in the equatorial central Pacific through different processes.

In the early transition years, large and significant negative SST anomalies persist from winter to early summer in the equatorial central Pacific. This indicates a good seasonal predictability of abnormal spring to summer transition over the South China Sea, which may be attributed to the effect of ENSO-related large-scale SST anomaly pattern in the tropical Indo-Pacific region. In the accelerated transition years, the composite SST anomalies in the equatorial central Pacific are moderate with relatively large spread among individual years. In such years, the lower boundary forcing is not so strong and the atmospheric internal variability is relatively large, and thus the seasonal predictability is not high for abnormal spring to summer transition over the South China Sea. During the present analysis period, the number of the two types of transition years is the same, indicative of a nearly equal importance of the two types of anomalies in the abnormal spring to summer transition over the South China Sea. Jang et al. (2016) noted a change in the local precipitation–SST relationship over the South China Sea around the late 1990s. This indicates a possibility that the relative importance of the two types of anomalies may have low-frequency changes, which is an issue worthy of further study.

The temporal evolution of the equatorial central Pacific SST anomalies indicates a different association of the two types of abnormal transitions with ENSO. The accelerated transitions are related to moderate warm events in the equatorial central Pacific. The early transitions occur during the La Niña decaying years with a large-scale SST anomaly pattern in the tropical Indo-Pacific Ocean. The anomalies in this type of transitions display features similar to the Indo-western Pacific ocean capacitor (IPOC) mode that is a seasonally evolving coupled mode (Xie et al. 2016) unifying the local air–sea interaction mechanism in the tropical western North Pacific (Wang et al. 2000, 2003) and the Indian Ocean capacitor effect (Xie et al. 2009). However, there is an obvious difference during the transition in the equatorial central Pacific where the IPOC mode has weak anomalies, but large anomalies are present there in the early transition years. This difference occurs because the IPOC mode does not distinguish the two types of cases that have opposite SST anomalies in the equatorial central Pacific. Such difference is related to the inter-ENSO variability discussed in Lee et al. (2014). The present study illustrates a case of interevent difference in the impacts of equatorial Pacific SST anomalies.

The anomalies in the accelerated transition years display a relatively quick month-to-month change. This suggests a plausible contribution of intraseasonal variations to the accelerated transitions. Indeed, analysis using GPCP daily rainfall data that are available after October 1996 (retrieved from https://climatedataguide.ucar.edu/climate-data/gpcp-daily-global-precipitation-climatology-project) shows that the monthly mean rainfall anomalies constructed based on 10–60-day intraseasonal component have a large contribution to the total JmA rainfall anomalies over the South China Sea in some years (figure not shown). The distribution of rainfall anomalies in May indicates that the low-frequency (>60 days) and intraseasonal components have a larger contribution to the total anomalies in different regions. Further analysis is needed to understand the contribution of intraseasonal oscillations to this type of transitions.

Acknowledgments

The authors appreciate comments of three anonymous reviewers. This study is supported by National Key Basic Research Program of China Grant 2014CB953902, National Key Research and Development Program of China Grant 2016YFA0600603, and National Natural Science Foundation of China Grants 41530425, 41475081, 41275081, and 41506003. The GPCP rainfall data and NOAA OI SST data were provided by the NOAA/OAR/ESRL Physical Science Department (PSD) (http://www.esrl.noaa.gov/psd/). The NCEP–DOE reanalysis 2 data were obtained from ftp://ftp.cdc.noaa.gov/.

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Footnotes

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