1. Introduction
Central China lies to the east of the Tibetan Plateau, including the middle reaches of the Yangtze River and the middle and lower reaches of the Yellow River, constituting one of the major socioeconomic centers of China owing to its advantages of population, transportation, agriculture, and industry (Sun et al. 2010; Ren et al. 2013; Ke and Guan 2014; Hu et al. 2017, 2020; Chen et al. 2022; Chen and Li 2022). Floods, landslides, and mudslides brought by the heavy precipitation are the major natural disasters over central China (especially in July, which is the local peak rainy month), severely threatening the security of the local people’s lives and properties (Jiang et al. 2015; Hu et al. 2020). For example, in July 2021, Henan Province suffered torrential precipitation, causing heavy casualties of 73 people and direct economic losses of more than 80 billion CNY. All these suggest an increasing need for a better understanding of the underlying physical mechanisms that drive the variations of the central China July precipitation (CCJP).
What is already known is that the climate system over central China during July consists of two major atmospheric circulations: one is the low-level south flow associated with the western Pacific subtropical high and the other is the westerly jet from the mid- to high latitudes (Lu 2004; Lu and Lin 2009; Sampe and Xie 2010; Chen and Bordoni 2014a,b; Chiang et al. 2017, 2019, 2020; Hu et al. 2017, 2020; Kong and Chiang 2020a,b; Liu et al. 2020, 2022; X. Li et al. 2021; Ren et al. 2021; Zhou et al. 2021). The low-level south flow can supply abundant moisture to feed convection over central China (Sampe and Xie 2010; Jiang et al. 2015; Zhang et al. 2017; Gao et al. 2020a,b,c). The westerly jet tilts northward from the low levels to the high levels (Sampe and Xie 2010). On the one hand, the midtroposphere westerly jet can transport warm air from the eastern flank of the Tibetan Plateau to central China, inducing the local ascending motion that favors the central China precipitation (Sampe and Xie 2010; Chen and Bordoni 2014b; Hu et al. 2017, 2020; Zhou et al. 2021). On the other hand, the upper-level westerly jet can steer wave trains from the area upstream, which creates periods conductive to precipitation through convective instability and adiabatic updrafts (Molnar et al. 2010; Sampe and Xie 2010; Chen and Bordoni 2014a; Li and Lu 2017; Kong and Chiang 2020a). Apparently, the collaboration of the western Pacific subtropical high from the low latitudes with the westerly jet from the mid- to high latitudes largely controls the July precipitation over central China.
Some modes of large-scale climate variability can strongly mediate the interannual variabilities of these two major atmospheric circulations mentioned above and may thus influence the CCJP. For example, the El Niño–Southern Oscillation (ENSO) mode has been verified to significantly affect the central China wet season precipitation in the decaying stage by mediating both the intensity and location of the western Pacific subtropical high and influencing the low-level south flow (Wang et al. 2000; Chen 2002; B. Wu et al. 2009; Wu et al. 2010; Xie et al. 2009, 2016; Hu et al. 2017, 2019, 2020; Zhou et al. 2018; He et al. 2019; G. Li et al. 2021a,b; Wu et al. 2021). This provides a robust tropical predictor for the CCJP (Wang et al. 2000, 2013; Yang et al. 2007; Xie et al. 2009; Stuecker et al. 2013, 2015; Chen et al. 2016, 2019; Li et al. 2017; B. Wang et al. 2017; Wang 2019; Sun et al. 2021). Regarding the westerly jet, previous studies (Z. Wu et al. 2009; Wu et al. 2012; Zuo et al. 2013; Yim et al. 2014) reported that it can be significantly affected by the spring tripole sea surface temperature (SST) anomalies in North Atlantic, an outstanding regional mode of interannual variability induced by the North Atlantic Oscillation (NAO; Cayan 1992; Z. Wu et al. 2009; Zuo et al. 2013). Specifically, such spring North Atlantic tripole SST anomalies, which feature positive (negative) SST anomalies in the northwest Atlantic and negative (positive) SST anomalies in the subpolar and tropical oceans, can persist into the following summer and exert a zonal wave train over the Atlantic–Eurasia region (Z. Wu et al. 2009; Wu et al. 2012; Zuo et al. 2013; Yim et al. 2014). This zonal wave train pattern can be trapped by the westerly jet over Asia in its eastward propagation (Zuo et al. 2013). As a result, the active disturbance in the westerly waveguide may increase the probability of intense ascent and instability over East Asia (Sampe and Xie 2010). This suggests a possible influence of the North Atlantic SST anomalies on the East Asian summer climate (Z. Wu et al. 2009; Wu et al. 2012; Zuo et al. 2012, 2013). However, it remains unclear whether and how the spring North Atlantic SST anomalies would affect the July precipitation over central China. If there is an extratropical effect of the spring North Atlantic SST anomalies on the interannual July precipitation variation over central China, what are the extratropical teleconnection processes and mechanisms?
Furthermore, previous studies may only show an extratropical teleconnection pathway of the Atlantic SST anomalies affecting the East Asian summer climate (Z. Wu et al. 2009; Wu et al. 2012; Zuo et al. 2012, 2013; Yim et al. 2014). Recent studies (Li et al. 2016; L. Wang et al. 2017; Cai et al. 2019) have increasingly emphasized the role of the tropical Atlantic warming in forcing a pan-tropical climate change, for example, initiating a Pacific La Niña–like response on the interdecadal time scale. This suggests that the interannual Atlantic SST anomalies might also affect the East Asian summer climate through a tropical pathway. Theoretically, the tropical North Atlantic SST warming can drive a convective response and result in a local diabatic heating (Wang et al. 2009; L. Wang et al. 2017; Ham et al. 2013; Kucharski et al. 2014; McGregor et al. 2014; Wang 2019; Zhang and Li 2022), inducing a Gill-type response with easterly wind anomalies over the Indo-western Pacific as Kelvin waves and an anomalous cyclone over the subtropical eastern Pacific as Rossby waves (Ham et al. 2013; Hong et al. 2014; Chang et al. 2016; Li et al. 2016, 2018; L. Wang et al. 2017; Cai et al. 2019; Zuo et al. 2019). Through the wind–evaporation–SST (WES) feedback, the easterly wind anomalies cause the Indo-western Pacific to warm and the central Pacific to cool (Li et al. 2016). Through the WES footprinting mechanism, the northeasterlies in the western flank of the anomalous cyclone superimpose on the northeast trade winds, causing the equatorial eastern Pacific to cool (Vimont et al. 2001; Li et al. 2016). However, as the westerly wind anomalies in the southern flank of the cyclone would prevent the SST there from being cooled through suppressing the local upwelling (Ham et al. 2013; L. Wang et al. 2017; Cai et al. 2019), significant SST cooling mainly locates in the equatorial central Pacific. This SST cooling in the central Pacific (warming in the Indo-western Pacific) together with the original Atlantic SST warming would further intensify the easterly wind anomalies over the Pacific and accelerate the Walker circulation (Li et al. 2016), contributing to the La Niña–type responses in the central Pacific. Obviously, there is a positive feedback between the SST gradient in the equatorial Pacific and the Walker circulation, illustrating the importance of the North Atlantic SST warming for the central Pacific La Niña state. Considering the possible influence of the La Niña state on the western Pacific subtropical high, we guess that there might be also a tropical teleconnection pathway of the North Atlantic SST anomalies on the CCJP through modulating the pantropical climate, the western Pacific subtropical high as well as the low-level south flows.
The present study investigates the interannual relationship between the spring SST anomalies in North Atlantic and the following July precipitation over central China. Indeed, the results show that the spring North Atlantic SST anomalies, especially those in the tropical North Atlantic (TNA) and the subpolar North Atlantic (SNA), can persist into the following July and strongly affect the CCJP via the tropical and extratropical pathways. For the tropical pathway, the spring TNA SST anomalies induce an anomalous anticyclone over the northwest Pacific (NWP) through a series of air–sea interactions, causing increased CCJP by enhancing the low-level water vapor transportation. For the extratropical pathway, the spring TNA and SNA SST anomalies result in an anomalous anticyclone over North China, bringing the cold air to the south, which is conductive to the ascending motion over central China as a result of frontal activity. Our results highlight the two pathways of the spring North Atlantic SST anomalies affecting the following July precipitation over central China and are of great significance for improving the seasonal prediction of the regional climate.
The rest of this work is organized as follows. Section 2 describes the datasets and methods used in this study. Section 3 presents the subseasonal characters of the summer precipitation over central China. In section 4, we investigate the relationship between the spring North Atlantic SST anomalies and the following July precipitation over central China. In section 5, the possible physical mechanisms for the effect of the North Atlantic SST anomalies on the following July precipitation over central China are explored. Finally, conclusions and discussion are presented in section 6.
2. Datasets and methods
In this study, we use multiple datasets for the period 1979–2019. The monthly precipitation data are from the Global Precipitation Climatology Project (GPCP; 2.5° × 2.5°; Adler et al. 2003). The monthly SST data are taken from the Hadley Centre of the U.K. Met Office (HadISST; 1° × 1°; Rayner et al. 2006). The monthly atmospheric reanalysis datasets, including the zonal and meridional components of wind, geopotential height, specific humidity, relative humidity, air temperature, omega, surface latent heat flux, surface sensible heat flux, and surface net radiation, are derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5; 1° × 1°; Hersbach et al. 2020) and the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis (NCEP–NCAR; 2.5° × 2.5°; Kalnay et al. 1996). Note that the results from the two atmospheric reanalysis datasets are very similar, and only the results from the ERA5 atmospheric reanalysis dataset are shown in the present study. Fifteen atmosphere-only simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6/AMIP), which are forced with observed SST, are also used to validate our results (Table S1 in the online supplemental material; Eyring et al. 2016). Here, we examine the 1979–2014 period for all CMIP6/AMIP outputs and only the first-member run (r1i1p1) of each model is analyzed, unless otherwise specified. All CMIP6/AMIP outputs are interpolated to a uniform 2.5° × 2.5° horizontal grid. The methods of correlation and regression analyses are employed, and the significance level is examined by Student’s t test. All data are linearly detrended and the decadal variations are also removed before carrying out the statistical analyses.
To explore the relationship between the spring North Atlantic SST anomalies and the following July precipitation over central China, we define the CCJP index as the July precipitation anomalies averaged over the region of 28°–38°N, 100°–118°E. The TNA SST index is denoted as the SST anomalies averaged in the region of 0°–20°N, 83°–22°W, the subtropical North Atlantic SST index is denoted as the SST anomalies averaged in the region of 21°–39°N, 95°–28°W, and the SNA SST index is denoted as the SST anomalies averaged in the region of 45°–55°N, 48°–27°W (also see Fig. 3). The NAO index is also used in this study, which is defined as the difference of the zonally averaged (80°W–30°E) sea level pressures between 35° and 65°N (Li and Wang 2003).
Here, the weighting coefficients represent the relative roles of the spring TNA and SNA SST anomalies in affecting the CCJP.
Here, P, a, Φ, and λ are the pressure, Earth radius, latitude, and longitude, respectively;
3. Subseasonal characters of the central China summer precipitation
The East Asian summer monsoon rainband has a prominent seasonal migration (Chen et al. 2004; Ding and Chan 2005; Ding 2007; Su and Xue 2010). To demonstrate that the central China summer precipitation suffers significant subseasonal variabilities with the migration of the rainband, the summer mean and monthly climatological precipitation together with the low-level (850 hPa) flows are shown in Fig. 1. Indeed, the climatic precipitation and 850-hPa winds over central China display prominent differences from June to August. In June, the low-level southwesterly only reaches south of the Yangtze River, with the precipitation center mainly located in South China. If using the 6 mm day−1 precipitation contours to outline the rainband (Lau and Yang 1997; Su and Xue 2010), it only reaches about 30°N, indicating less precipitation over central China in this time (Fig. 1b). By July, the southwesterly jumps northward to south of the Yellow River, with the rainband marching northward and covering the area south and southeast of central China, indicating that central China has suffered abundant precipitation in the midsummer (Fig. 1c). In August, the southwesterly monsoon retreats eastward and weakens, and it brings less influence to central China and causes less precipitation there (Fig. 1d). Apparently, the summer precipitation over central China experiences prominent subseasonal variations, with July suffering the heaviest precipitation among the summer months. The summer mean precipitation pattern is only similar to that in June (Figs. 1a,b), showing less precipitation over central China. This might explain why the relationship between the summer mean precipitation variability over central China and some well-known forces (such as ENSO) is not robust in the previous studies (Ye and Lu 2011; Hu et al. 2017).
Climatological precipitation (shaded; mm day−1) and 850-hPa wind fields (arrows; m s−1) in (a) summer, (b) June, (c) July, and (d) August during 1979–2019. Wind speed less than 2 m s−1 is removed. The boxed area denotes the region of central China (28°–38°N, 100°–118°E).
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Figure 2 exhibits the monthly climatologies of the central China precipitation during 1979–2019. This further shows that the central China summer precipitation is of significant seasonality and July is the peak rainy month for central China, accounting for about 18.34% of the annual precipitation. Considering the possible floods, landslides, and mudslides brought by the frequent precipitation during the wet season, we may need a better focus on the nature and causes of the interannual variabilities of the central China precipitation in July.
Monthly climatologies of the precipitation (mm day−1) averaged over central China during 1979–2019. The value over each bar is the percentage of the monthly precipitation in the annual total.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
4. Relationship between the July precipitation over central China and the spring North Atlantic SST anomalies
Previous studies suggested that the summer climate over East Asia is closely associated with the preceding spring North Atlantic tripole SST anomaly pattern, which is the dominant mode of the empirical orthogonal function analysis of the spring North Atlantic SST anomalies induced by the NAO (Fig. S1; Z. Wu et al. 2009; Wu et al. 2012; Zuo et al. 2013). On the subseasonal time scale, the July precipitation over central China might be also linked with the preceding spring SST anomalies in the North Atlantic. In Fig. 3a, we present the correlation maps of the CCJP index with the preceding spring SST anomalies. Indeed, there are remarkable correlations in North Atlantic, which feature a “+ − +” distribution pattern from the tropics to the high latitudes (i.e., the TNA, the subtropical North Atlantic, and the SNA), suggesting that the anomalous July precipitation over central China is closely associated with the preceding spring tripole SST anomalies in North Atlantic. Moreover, such close relationship between the North Atlantic SST anomalies and the CCJP still exists in July, albeit with a weaker magnitude in the correlation coefficients (Fig. 3b), implying a persistence of the spring North Atlantic SST anomalies, and thus a potential predictor for the CCJP.
Correlations of the central China July precipitation (CCJP) index with the sea surface temperature (SST) anomalies in (a) spring and (b) July. The dots indicate that the correlations are at the significance level of p < 0.05. The boxed areas from the tropics to the high latitudes denote the regions of tropical North Atlantic (TNA; 0°–20°N, 83°–22°W), subtropical North Atlantic (21°–39°N, 95°–28°W), and subpolar North Atlantic (SNA; 45°–55°N, 48°–27°W), respectively.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
However, it should be noted that the persistent as well as the significant correlations mainly appear in the TNA and the SNA, rather than the subtropical North Atlantic. When calculating the correlation coefficients between the CCJP index and the subtropical North Atlantic SST indices in both spring and July, the results are low and insignificant (Figs. 4b,e), indicating a weak relationship between the spring/July subtropical North Atlantic SST anomalies and the CCJP. But the results for the TNA SST and SNA SST indices in spring (July) are 0.40 (0.26) and 0.35 (0.37), at the significance levels of p < 0.01 (p < 0.05) and p < 0.1 (p < 0.05), respectively (Figs. 4a,c,d,f). The prominent difference between the subtropical North Atlantic and the other two poles suggests that even though the correlations in North Atlantic feature a tripole pattern in general, the North Atlantic SST anomalies that are significantly correlated with the CCJP mainly locate in the TNA and the SNA.
Scatterplots of the CCJP index and the spring (a) TNA SST index, (b) subtropical North Atlantic SST index, and (c) SNA SST index. (d)–(f) As in (a)–(c), but for the July SST indices. The black line and r in each panel denote the linear fit and the correlation coefficient, respectively. All data are standardized.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Previous studies suggested that the spring North Atlantic SST anomalies are closely related to the remote ENSO forcing, especially those in the TNA (Xie and Carton 2004; Ham et al. 2013). To better isolate the ENSO effect, we remove the preceding winter Niño-3.4 (5°S–5°N, 170°–120°W) SST-related signals in the following analysis. After removing the ENSO effect, the relationship between the spring North Atlantic SST anomalies and the CCJP anomalies is still statistically significant and the correlation coefficient between the spring TNA (SNA) SST anomalies and the CCJP anomalies is 0.34 at p < 0.05 (0.32 at p < 0.05) against 0.40 at p < 0.01 (0.35 at p < 0.05) before removing the ESNO effect. This suggests that the relationship between the spring North Atlantic SST anomalies and the CCJP anomalies is robust regardless of the ENSO forcing.
Figure 5 further presents the correlations of the spring TNA and SNA SST indices with the July precipitation over East Asia. Clearly, the TNA and SNA SST indices are both closely related to the July precipitation over central China, with significant correlations occupying most areas of central China, implying that when the TNA and SNA SST anomalies are abnormally warmer in spring, most areas of central China would suffer surplus precipitation in the following July. All this further suggests that there is a close relationship between the spring TNA and SNA SST anomalies and the CCJP.
Correlations of the spring (a) TNA SST index and (b) SNA SST index with the July precipitation over East Asia. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the correlations are at the significance level of p < 0.05. The boxed area denotes the region of central China.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
5. Linking mechanisms of the spring North Atlantic SST with the following July precipitation over central China
a. Tropical pathway
The interannual variations of the July precipitation over central China are closely associated with the preceding spring tripole SST anomalies in the North Atlantic, especially those in the TNA and the SNA, with significant correlations persisting from spring into the following July, implying a strong effect of the spring North Atlantic SST anomalies on the CCJP. The question is how the spring North Atlantic SST anomalies affect the central China precipitation in the following July. Recently, research has increasingly suggested that the TNA warming on the interdecadal time scale plays a key role in forcing a pantropical climate change through the atmospheric bridges, for instance, initiating a Pacific La Niña–like response (Li et al. 2016; Cai et al. 2019). Obviously, the La Niña state can affect the East Asian summer climate vigorously. Thus, there might be also a similar tropical pathway linking the spring North Atlantic SST anomalies and the following July precipitation anomalies over central China through modulating the pantropical climate on the interannual time scale.
To explore the above hypothesis, the regression maps of the spring and July SST anomalies and low-level wind anomalies onto the spring TSNA SST index are presented in Fig. 6. Indeed, there is a prominent pan-tropical air–sea interaction from spring to July in response to the SST anomalies in North Atlantic. Specifically, in response to the interannual spring TNA warming, there are anomalous easterlies over the tropical western Pacific as the Kelvin wave responses and an anomalous low-level cyclone over the eastern Pacific as the Rossby wave responses (Fig. 6a). On the one hand, the interannual easterly wind anomalies over the equatorial western Pacific can cause the Indo-western Pacific to warm and the central Pacific to cool through the WES feedback (Li et al. 2016; Lu and Ren 2020). On the other hand, the northeasterly wind anomalies in the western flank of the cyclone over the subtropical eastern Pacific can superimpose on the northeast trade winds, cooling the surface temperature there and further causing the equatorial eastern Pacific to cool through the WES footprinting mechanism (Vimont et al. 2001; Li et al. 2016). As the westerly wind anomalies over the eastern Pacific would prevent the SST there from being cooled through suppressing local upwelling (Ham et al. 2013; L. Wang et al. 2017; Cai et al. 2019), significant interannual SST cooling mainly locates in the equatorial central Pacific. As a result, there is a prominent July SST warming in the Indo-western Pacific and cooling in the central Pacific (Fig. 6b).
Regressions of the (a) spring and (b) July SST anomalies (shaded; °C) and 850-hPa wind anomalies (arrows; m s−1) onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed SST anomalies are at the significance level of p < 0.05. The arrows are shown with the zonal or meridional component of the wind anomalies exceeding the significance level of p < 0.1. The boxed area denotes the region of central China.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Such a strengthened SST gradient along the equatorial Pacific together with the persistent TNA SST warming would intensify the Walker circulation, thus further contributing to the La Niña–type ocean dynamical responses (Li et al. 2016). In Fig. 7, the regression pattern of the vertical wind and troposphere temperature onto the spring TSNA SST index during July further supports this pan-tropical interaction. In response to the prominent SST cooling in the central Pacific and warming in the Indo-western Pacific and the TNA, there is a strengthened Walker circulation with anomalous descending motions over the central Pacific and ascending motions over the Maritime Continent and Atlantic. Such an intensified Walker circulation would in turn enhance the equatorial easterly wind anomalies over the Indo-western Pacific and thus further contribute to the anomalous SST warming in the Indo-western Pacific and cooling in the central Pacific. Obviously, there is a positive feedback between the SST gradient and the Walker circulation in the equatorial Pacific.
Regressed height–longitude cross section of the July vertical wind (arrows; m s−1) and troposphere temperature (shaded; °C) anomalies averaged between 0° and 10°N onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed troposphere temperature anomalies are at the significance level of p < 0.05. The black arrows indicate that the zonal or vertical component of the wind anomalies exceed the significance level of p < 0.1. Wind speeds less than 1 m s−1 are not shown.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Such air–sea conditions in the equatorial Pacific are conductive to maintain an anomalous anticyclone over the NWP. On the one hand, the prominent SST cooling in the tropical central Pacific can emanate a downwelling Rossby wave that propagates to the west, favoring the anomalous anticyclone over the NWP (Wang et al. 2013; B. Wang et al. 2017; Li et al. 2017). On the other hand, the enhanced Walker circulation can enhance the meridional Hadley circulation, strengthening the descending motion over the NWP, which is also conductive to the maintenance of the anomalous anticyclone there (Weng et al. 2007; Yuan and Yang 2012; Wang et al. 2013; Li et al. 2017; Huang et al. 2018). Figure 8 shows the zonal averaged (100°–118°E) July vertical wind and zonal wind anomalies regressed onto the spring TSNA SST index. Indeed, corresponding to the enhanced Walker circulation with significant ascending motion over the Maritime Continent, there are strengthened Hadley circulations with prominent sinking motion off the equator. This helps maintain an anomalous anticyclone over NWP. As a result, the zonal wind anomalies also exhibit negative values in the tropics and positive values in the subtropics, exceeding the significance level of p < 0.05.
Regressed height–latitude cross section of the July vertical wind (arrows; m s−1) and zonal wind (shaded; m s−1) anomalies averaged between 100° and 118°E onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed zonal wind anomalies are at the significance level of p < 0.05. The black arrows indicate that the meridional or vertical component of the wind anomalies exceed the significance level of p < 0.1. Wind speeds less than 0.5 m s−1 are not shown.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Such an anomalous northwest Pacific anticyclone (NWPAC) could enhance the summer monsoon, transporting more water vapor to the mainland of China. In Fig. 9, we exhibit the regression map of the full layer (1000–300 hPa) integrated water vapor flux and its divergence anomalies on the spring TSNA SST index. Indeed, there is abundant moisture delivering to the north, resulting in prominent convergence over central China. The water vapor transportation is also highly consistent with the anomalous 850-hPa wind fields, indicating the critical role of the anomalous NWPAC in mediating the central China summer climate.
Regressions of the July water vapor flux (arrows; kg m−1 s−1) and its divergence (shaded; 1 × 105 kg m−2 s−1) anomalies integrated from 1000 to 300 hPa onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed divergence anomalies are at the significance level of p < 0.05. The black arrows indicate that the meridional or vertical component of the water vapor flux anomalies exceed the significance level of p < 0.1. Vector speeds less than 30 kg m−1 s−1 are not shown. The boxed area denotes the region of central China.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
In general, the anomalous NWPAC affects the CCJP a lot by strengthening the East Asian summer monsoon and providing abundant moisture to this region. Through adjusting the location and strength of the anomalous NWPAC, some well-known climate modes can control the central China precipitation. Here, we demonstrate that the spring NAO-induced North Atlantic SST anomalies can significantly affect the central China precipitation through affecting the NWPAC. In Fig. 10, we further present these processes. The spring North Atlantic SST anomalies, especially the tropical SST anomalies, can cause a pan-tropical SST pattern with cooling in the equatorial central Pacific and warming in the Indo-western Pacific and Atlantic in the following July. Here, we quantitatively describe the pan-tropical SST index as the difference between the regional-mean SST anomalies in the central Pacific (5°S–5°E, 170°–120°W) and the sum of regional-mean SST anomalies in the Indo-western Pacific (0°–20°N, 60°–130°E) and the TNA. Clearly, its correlation coefficient with the spring TNA SST index is high (0.71, exceeding the significance level of p < 0.001; Fig. 10a). This pan-tropical SST during July is conductive to enhance the Walker circulation, which further enhances the Hadley circulation with an anomalous anticyclone appearing over the NWP. As a result, the anomalous anticyclone over the NWP can transport more water vapor to central China and cause increased precipitation there. When we define the Walker circulation index as the difference between the 850-hPa zonal wind anomalies averaged in the eastern Pacific (120°–60°W) and the western Pacific (90°E–180°) and the NWPAC index as the difference in the regional-averaged 850-hPa zonal winds between the north (25°–32.5°N, 110°–140°E) and south (5°–15°N, 100°–130°E) of the NWPAC, the correlation coefficients among the pan-tropical SST index, the Walker circulation index, and the NWPAC index are 0.72 and 0.69, both exceeding the significance levels of p < 0.001 (Figs. 10b,c). The correlation coefficient between the NWPAC index and the CCJP index is 0.45, exceeding the significance level of p < 0.01 (Fig. 10d). All these suggest that there is a tropical pathway of the spring North Atlantic SST anomalies affecting the CCJP.
Scatterplots of (a) the spring TSNA SST index and the July pan-tropical SST index, (b) the July pan-tropical SST index and the simultaneous July Walker circulation index, (c) the July Walker circulation index and the July northwest Pacific anticyclone (NWPAC) index, and (d) the July NWPAC index and CCJP index. The preceding winter Niño-3.4 SST-related signals are removed. The black line and r in each panel denote the linear fit and the correlation coefficient, respectively. All data are standardized.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
b. Extratropical pathway
In the above section, we have demonstrated that the spring North Atlantic SST anomalies can significantly affect the CCJP through mediating the NWPAC. However, we notice that there is also an anomalous anticyclone over North China. Such an anomalous anticyclone with the northeasterly winds in its southeastern flank can bring the cold air to central China, conductive to the local ascending motion and increased precipitation (Fig. 6b). Yet, it remains unclear how this anomalous North China anticyclone is formed. Previous studies have also shown that the spring North Atlantic tripole SST anomalies can persist into the following summer and emanate a zonal wave train over the Atlantic and Eurasia, thus influencing the East Asian summer climate (Z. Wu et al. 2009, 2012; Zuo et al. 2013). On subseasonal time scale, can the spring North Atlantic SST anomalies persist into the following July and force a similar teleconnection affecting the CCJP? If so, is the anomalous North China anticyclone the result of the wave train?
To explore these, the spring to July surface net heat flux (here positive downward) as well as 10-m wind anomalies regressed onto the spring TSNA SST index are first analyzed (Fig. 11). The surface net heat fluxes consist of surface turbulent heat fluxes and radiation heat fluxes. The positive surface net heat flux anomalies into the ocean imply that the atmosphere forces the ocean and vice versa (Wu and Kirtman 2005; Li et al. 2011; Wu et al. 2011). Results show that the ocean–atmospheric relationships are opposite during spring and July. During spring, corresponding to a negative phase of NAO, with an anomalous cyclone over the midlatitude of North Atlantic, there is reduced evaporation in both the TNA and SNA as a result of the weakened climatological winds. As a result, this leads to a “+ − +” downward surface net heat flux into North Atlantic and favors “+ − +” tripole SST anomalies in this region (Figs. 6a and 11a; Zuo et al. 2012; Zhang et al. 2022). By contrast, in July, the upward net heat fluxes in both the tropical and subpolar regions of North Atlantic hint that it is the North Atlantic SST anomalies that could potentially trigger the anomalous atmospheric circulation responses (Fig. 11b).
Regressions of the (a) spring and (b) July surface net heat flux anomalies (shaded; 1 × 106 J m−2) as well as 10-m wind anomalies (vectors; m s−1) onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed surface net heat flux anomalies are at the significance level of p < 0.05. The black arrows indicate that the zonal or meridional component of the wind anomalies exceed the significance level of p < 0.1. Wind speeds less than 0.5 m s−1 are not shown.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Such ocean-forced atmospheric circulation anomalies in the local would further emanate a remote atmospheric circulation by the energy dispersion of Rossby waves (Trenberth et al. 1998; Zuo et al. 2013). To demonstrate it, we present the regression map of the wave activity flux together with the streamfunction anomalies at 200 hPa onto the spring TSNA SST index in Fig. 12a. Clearly, corresponding to the anomalous warming in the TNA and the SNA, there is a significant wave train propagating eastward over the mid- to high latitudes. It extends from the SNA through Europe, western Russia, and West Asia to China, going especially along the Asian jet in the downstream (Fig. 12a). For convenience, we refer this wave train pattern as the North Atlantic–Eurasia–China (NAEC) teleconnection pattern in the remainder of the paper. Such a wave train pattern is quite different from the Silk Road pattern, one major wavelike circulation pattern along the Asian jet that can strongly affect the East Asian summer climate (Lu et al. 2002; Kosaka et al. 2009, 2012; Li and Ruan 2018; Li et al. 2019). Their pattern correlation of anomalous geopotential height is only 0.15. In Fig. 12b, the regressed meridional wind anomalies at 200 hPa onto the spring TSNA SST index, which features a prominent wave train pattern extending from North Atlantic to China, further supporting the existence of the NAEC teleconnection pattern. The existence of this NAEC teleconnection pattern reveals that there may be an extratropical pathway of the spring North Atlantic SST anomalies affecting the following July circulation anomalies over North China.
Regressions of the July 200-hPa (a) streamfunction (shaded; 5 × 105 m2 s−1) and wave activity flux anomalies (arrows; m2 s−2) and (b) meridional wind (shaded; m s−1) anomalies onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The blue solid lines are the 200-hPa zonal wind larger than 12 m s−1, with interval of 4 m s−1, which denotes the jet stream. In (a), vector speeds less than 1 m2 s−2 are not shown. The dots in (b) indicate that the regressed meridional wind anomalies are at the significance level of p < 0.05. The boxed area denotes the region of central China.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
In Fig. 13, we present the July wind anomalies together with the geopotential height anomalies at different vertical levels (700, 500, and 200 hPa) obtained by regressions on the spring TSNA SST index, which can provide a better understanding of the structure of the NAEC teleconnection pattern. In the high level, the 200-hPa geopotential height anomalies are highly consistent with the streamfunction anomalies, also exhibiting the NAEC teleconnection pattern, with three positive centers over the SNA, western Russia, and China and two negative centers over Europe and West Asia. Accompanied with the “+ − + − +” geopotential height anomalies, anomalous anticyclones and cyclones exist alternately from the SNA to China (Fig. 13a). Obviously, in the downstream of the wave train, there is an anomalous anticyclone over North China. At 500 and 700 hPa, albeit with a smaller amplitude than that of 200 hPa, such a NAEC pattern still exists (Figs. 13b,c), exceeding the significance level of p < 0.1. All this indicates that the NAEC teleconnection pattern features an equivalent barotropic structure in the entire troposphere and explains why there are low-level anticyclonic circulation anomalies over North China.
Regressions of the July (a) 200-, (b) 500-, and (c) 700-hPa geopotential height anomalies (shaded; m) and wind anomalies (arrows; m s−1) onto the spring TSNA SST index. The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed geopotential height anomalies are at the significance level of p < 0.05. The black arrows indicate that the zonal or meridional component of the wind anomalies exceed the significance level of p < 0.1. In (a), (b), and (c), wind speeds less than 1, 0.75, and 0.5 m s−1 are not shown, respectively. The boxed area denotes the region of central China.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
So far, we have illustrated the teleconnection pathway of the spring North Atlantic SST anomalies affecting the downstream circulation anomalies. Actually, the spring North Atlantic SST anomalies can persist into the following July and then emanate a wave train pattern propagating eastward, resulting in the anomalous circulation responses over North China that might also affect the precipitation anomalies over central China. In Fig. 14, we further present this process. Indeed, there is a persistent TNA and SNA SST warming from spring to the following July, with the correlation coefficient between the spring and July TSNA indices of 0.75 at the significance level of p < 0.001 (Fig. 14a). Corresponding to this persistent TNA and SNA SST warming from spring to the following July, an anomalous wave train appears over the mid- to high latitudes, which we called the NAEC teleconnection pattern. When we define the NAEC teleconnection index as the difference of the averaged “+” (A: 47.5°–57.5°N, 45°–30°W), “−” (B: 70°–75°N, 15°–30°E), “+” (C: 55°–60°N, 45°–65°E), “−” (D: 35°–42.5°N, 70°–80°E), and “+” (E: 37.5°–47.5°N, 102.5°–117.5°E) centers of the midsummer 500-hPa geopotential height anomalies from the SNA to China (NAECI = H500A + H500C + H500E − H500B − H500D), the correlation coefficient of the July TSNA SST index with the NAEC teleconnection index is 0.55, exceeding the significance level of p < 0.001 (Fig. 14b). The prominent NAEC teleconnection pattern features alternate anticyclonic and cyclonic circulations in its eastward propagation and an equivalent barotropic structure from the high levels to the low levels. As a result, in the downstream of the NAEC teleconnection pattern, an anomalous anticyclone appears over North China, which is significant in the entire troposphere. Such an anomalous North China anticyclone exhibits significant northeasterly winds in its southeastern flank, which can bring the cold air to central China at a low level, conductive to the local frontal activity and precipitation. When defining the North China anticyclone index as the zonal wind anomalies averaged in the southeastern part of the North China (32.5°–37.5°N, 102.5°–117.5°E) that can deliver cold air to the north, the correlation coefficient between the NAEC teleconnection index and the North China anticyclone index is 0.59, exceeding the significance level of p < 0.001 (Fig. 14c). And the correlation coefficient between the North China anticyclone index and the CCJP index is 0.37, exceeding the significance level of p < 0.05 (Fig. 14d). Therefore, we suggest that there is such an extratropical pathway of the spring North Atlantic SST anomalies that can largely affect the CCJP.
Scatterplots of (a) the spring TSNA SST index and the July TSNA SST index, (b) the July TSNA SST index and the July North Atlantic–Eurasia–China (NAEC) teleconnection index, (c) the July NAEC teleconnection index and the July North China anticyclone index, and (d) the July North China anticyclone index and the CCJP index. The preceding winter Niño-3.4 SST-related signals are removed. The black line and r in each panel denote the linear fit and the correlation coefficient, respectively. All data are standardized.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
c. Combination of the tropical and extratropical pathways
In sections 5a and 5b, we show that the July precipitation over central China is closely associated with the spring SST anomalies in North Atlantic, especially those in the TNA and the SNA. The SST anomalies in these two poles can persist into the following July and mediate the CCJP through different pathways: one is the tropical pathway and the other is the extratropical pathway. Through the tropical pathway, the spring TNA SST warming induces an anomalous anticyclone over the NWP in the following July, which can enhance the East Asian summer monsoon and transport more warm humid flows to central China. Through the extratropical pathway, the persistent TNA and SNA SST warming results in an anomalous anticyclone over North China in July, which can bring the cold air to central China. Obviously, the warm humid flows from the south against the cold air from the north are further conductive to the ascending motion as a result of frontal activity (Chen et al. 2004; Ding and Chan 2005; Ding 2007; Su and Xue 2010; Chiang et al. 2020), leading to increased precipitation over central China. To further demonstrate it, we present the regression map of the 850-hPa wind and equivalent potential temperature (θe) together with the precipitation anomalies onto the spring TSNA SST index in Fig. 15. Here, the θe is determined by both temperature and humidity, with a higher θe value reflecting a warmer and more humid atmosphere. Climatologically, the July θe decreases northward over China and shows a strong meridional gradient over central China, which favors the enhanced precipitation through the frontal activity. Under the combination of the tropical and extratropical pathways, such a frontal activity as well as precipitation would be further strengthened. Specifically, the northwest flank of the anomalous NWPAC can transport more warm humid flows to the north with significant positive θe values covering the south part of central China and the southeast flank of the North China anticyclone can bring more cold air to the south with significant negative θe values covering the north part of central China. This results in a larger θe gradient over central China. As a result, it is conductive to the frontal activity and thus more prone to heavy precipitation over central China.
(left) Regressions of the July precipitation (contour; mm day−1), 850-hPa equivalent potential temperature (θe; shaded; K), and wind anomalies (arrows; m s−1) onto the spring TSNA SST index. (right) The corresponding zonal averaged (100°–118°E) meridional gradient anomalies of θe (black line; 2 × 10−6 K m−1) and the climatology of the θe gradient (red line; 10−5 K m−1). The preceding winter Niño-3.4 SST-related signals are removed. The dots indicate that the regressed θe anomalies exceed the significance level of p < 0.1. The precipitation and wind anomalies are only shown at the significance level of p < 0.1.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
6. Conclusions and discussion
July is the peak rainy month of central China as a result of the seasonal migration of the East Asian summer monsoon. Floods, landslides, and mudslides brought by the heavy precipitation in this period often cause serious impacts on the local society and economy. The present study identifies that the CCJP is closely associated with the preceding spring SST anomalies in North Atlantic induced by the NAO, especially those in the TNA and the SNA. Warm SST anomalies in these two poles can induce surplus precipitation over central China in the following July.
The analyses reveal that there are two pathways of the spring TNA and SNA SST anomalies affecting the CCJP: one is the tropical pathway and the other is the extratropical pathway. To better understand the mechanisms, we establish a schematic diagram summarizing the tropical and extratropical pathways of the spring North Atlantic SST anomalies linking the CCJP in Fig. 16. For the tropical pathway, the spring TNA warming can cause pan-tropical SST anomalies with the cooling in central equatorial Pacific and the warming in the Indo-western Pacific and Atlantic in the following July. This pan-tropical SST anomalies can strength the Walker circulation and shift its rising branch farther to the west, thus enhancing the sinking motion over the NWP through the meridional Hadley circulation. As a result, the NWPAC gets enhanced and can transport more warm humid flows to central China. For the extratropical pathway, the spring TNA and SNA SST anomalies can persist into the following July, emanating a wave train extending from the SNA throughout the Eurasian continent to China that we called the NAEC teleconnection pattern in this study. The NAEC teleconnection pattern exhibits an equivalent barotropic structure from the high levels to the low levels with alternate anticyclonic and cyclonic circulations in its eastward propagation. In the downstream, the NAEC teleconnection pattern is trapped by the westerly jet over Asia and displays an anomalous anticyclone over North China from the high levels to the low levels. As a result, the southeast flank of this anticyclone can transport the cold air to central China. Moreover, such cold air from the north can collaborate with the warm humid flows from the south, causing a sharp gradient in the θe over central China, which is further conductive to the local ascending motion and favors the enhanced precipitation there.
Schematic diagram describing the tropical and extratropical pathways of the North Atlantic SST anomalies affecting the CCJP. The tropical pathway refers to the spring TNA SST anomalies resulting in a pan-tropical climate response in July, which favors an anomalous anticyclone (green anticyclone) over the northwest Pacific and transport more warm humid flows (wavy green arrows) to central China. The extratropical pathway refers to the spring TNA and SNA SST anomalies persisting into the following July and emanating a wave train extending from the SNA throughout the Eurasian continent to East Asia, which induces an anomalous anticyclone over North China with its southeast flank transporting more cold air (blue arrows) to central China. The zonal and meridional black solid lines with arrows denote the anomalous Walker circulation and Hadley circulation, respectively. The blue and red dotted circles with the letters H and L denote the wave train. The green arrows over the mid- to high latitudes denote the propagation path of the wave train.
Citation: Journal of Climate 35, 20; 10.1175/JCLI-D-21-1012.1
Here, we reveal two pathways of the spring North Atlantic SST anomalies affecting the CCJP. Our results improve the understanding of the influence of the spring North Atlantic tripole SST anomalies on the central China climate. However, it should be noted that the dynamical models still show large biases in simulating the remote influence of the North Atlantic SST anomalies, especially for the extratropical pathway. For the 15 models from the CMIP6/AMIP, almost no models can well reproduce the extratropical wave train (Fig. S2), which might be partly due to the low ability of dynamical models in simulating the atmospheric responses to the oceanic forcing in the mid- to high latitudes (Jing et al. 2020; Chen et al. 2021). For example, we notice that there exist large biases of the models in simulating the strength and location of the midlatitude westerly jet (Fig. S2; Chen et al. 2021). For the tropical pathway, the situation is better; more than half of them can reproduce the effect of spring TNA warming on the anomalous anticyclone over the NWP in the following July via the Gill response, although the strength and location of the anomalous NWPAC may still need further improvement (Fig. S3). All this suggests that if the dynamical models can reflect the remote influence of the North Atlantic SST anomalies reasonably, there may be a higher prediction skill for the central China climate. Owing to the enormous impact of the central China precipitation on the local livelihood of millions of people, the improvement of the seasonal prediction of the CCJP is of great potential benefit.
It should be also noted that the NAO tends to feature a more dominant negative phase since the late 1980s or the early 1990s (Kim et al. 2014; Cohen et al. 2014, 2020). Considering the close relationships among the spring NAO, the tripole SST anomalies in North Atlantic, and the CCJP [the correlation coefficients among them are −0.56 (p < 0.001), 0.35 (p < 0.05), and −0.39 (p < 0.05), respectively; Fig. S1], this implies an interdecadal strengthened summer precipitation over central China. While some studies attribute this negative trend of the NAO to a warmer Arctic in responses to global warming (Kim et al. 2014; Barnes and Polvani 2015; Kug et al. 2015; Coumou et al. 2018; Cohen et al. 2020), others believe that it is a result of the internal variability of the climate system (Blackport and Kushner 2017; Blackport and Screen 2020; Cohen et al. 2020). More specific and in-depth work may need to be done in the future.
Acknowledgments.
This work is supported by the National Key Research and Development Program of China (2021YFA0718000), the Fundamental Research Funds for the Central Universities (B220203002, B210201015, and B210202135), and the National Natural Science Foundation of China (41831175, 42076208, and 42141019), the Natural Science Foundation of Jiangsu Province (BK20211209), and the Joint Open Project of Key Laboratory of Meteorological Disaster, Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology (KLME202202).
Data availability statement.
The precipitation data are provided by the Global Precipitation Climatology Project (https://psl.noaa.gov/data/gridded/data.gpcp.html), the SST data are provided by the Hadley Centre of the U.K. Met Office (https://www.metoffice.gov.uk/hadobs/hadisst/data/download.html), the atmospheric reanalysis datasets are obtained from the European Centre for Medium-Range Weather Forecasts reanalysis v5 (https://doi.org/10.24381/cds.6860a573) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html), and the CMIP6/AMIP model data are obtained from Earth System Grid Federation server (https://esgf-node.llnl.gov/projects/cmip6).
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