East Asia Summer Monsoon (EASM) is the primary circulation affecting boreal summer precipitation in eastern China and is mainly dominated by the recession and extension of the Western Pacific Subtropical High (WPSH). Based on monthly datasets, previous studies have mainly focused on the intensity and variability of the WPSH, in order to obtain potential predictions of the EASM. Here, based on daily wind anomalies, in addition to the most common mode of WPSH, two additional modes are found in the summer circulation over China. The second mode (M2) seems irrelevant to the influence of WPSH over China. The positive phase of M2 favors precipitation in the areas south of the Yangtze River and the western Northeast China, but is unfavorable to precipitation in North China. M2 poses an India Ocean-East China (or west-east) dipole pattern. The positive phase of M2 seems associated with a strong, large, spatially continuous but southerly shifted subtropical high that connects the WPSH and the subtropical high over the India Peninsular/Indian Ocean, leading to a strong eastward wind flow from the northern India Ocean to the northwest Pacific. Accompanying with this large subtropical high system is a cyclonic circulation over the area of Southeastern China and the East China Sea. The positive phase of the third mode (M3) reflects a northward shifted WPSH, which favors precipitation in northern China and a small part of South China, but unfavorable to precipitation in the Yangtze River basin. M3 is associated with a strong south-north dipole structure of sea level pressure. The south side of this structure is over the Maritime Continent, and its north side is over the Asia continent, but the variation of sea level pressure over the Maritime Continent is small compared with that over the Asian continent and the western North Pacific, so this dipole structure can also be regarded as a uniform structure over the Asia continent. Comparatively, M3 has a more pronounced decreasing trend in the past decades, while M2 mainly poses decadal changes.
Research Article
Three modes of the east Asia summer monsoon influencing Eastern China
https://doi.org/10.21203/rs.3.rs-1952485/v1
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East Asia summer monsoon
western Pacific subtropical high
daily wind anomalies
west-east dipole structure
sea surface temperature
The precipitation in the southeastern China in boreal summer is regarded to be highly associated to the East Asia Summer Monsoon (EASM) and tropical cyclones (TCs), which are mainly influenced by the recession and the extension of the Western Pacific Subtropical High (WPSH)(Wang et al., 2013; Yang et al., 2022a). As a anticyclonal system, the WPSH is always present in the middle and lower troposphere of the north Western Pacific and becomes strong in the boreal summer. The northward or eastward wind at the west side of this anticyclone system can transport moisture from the tropics to East Asia, which dominating summer rainfall in these areas. This transportation of moisture is considered as the rain belt or the East Asia atmospheric river (Liang et al., 2022). During the month of May each year, the rain belt is mainly over the Huai River basin and the lower Yangtze River Basin in eastern China. This phenomenon is known as Meiyu in China. The WPSH/rain belt moves northward in early June, followed by more rainfall in northern China before its withdraws in August. The spatial extent and duration of the northward moving of the WPSH typically affects summer rainfall in arid northern China, including eastern Northwest China, North China and Northeast China, and thus the strength of WPSH is used as a major factor/indicator in studying EASM (Chen et al., 2020; Li et al., 2021; WANG et al., 2008; Yang et al., 2022b). Scientists found that a strong WPSH measured by certain metrics can cause more precipitation in the lower Yangtze River basin and the Huai River basin, but less precipitation in northern China((NIE et al., 2021). Weakened EASM triggers increased precipitation in northwest China(Chen et al., 2021). It is believed that the westward extension of the WPSH since the late 1970s has led to increased precipitation in eastern China along the lower Yangtze River basin, and deficient rainfall in northern China(Cherchi et al., 2018).
Some authors found that the WPSH has intensified during the past decades based on 850-hPa geopotential heights and SLP(MATSUMURA et al., 2015) and the 5880-gpm line (Liu et al., 2014), but with global warming, the geopotential height is also increasing, so the WPSH index obtained based on geopotential heights is definitely larger than before and is also expanding westward and northward. To avoid this drawback (He et al., 2015), the eddy geopotential height was suggested to measure the strength of the WPSH, but the obtained WPSH is weakening and retreating eastward in response to global warming.
The interannual variability of the WPSH is actually regulated by sea surface temperature (SST) anomalies over the tropical central pacific and the Maritime Continent (Cherchi et al., 2018). WPSH usually becomes stronger when El Nino in its early decaying stage and weaker when El Nino in its early development phase. Since the early 1990s, the WPSH becomes strong in years when El Nino is decaying or La Nina events are developing, such as 1998 and 2010. It is also believed that the WPSH has been strengthening since the late 1970s (Liu et al., 2014), which brings more precipitation to the Yangtze River basin but less to northern China (Huang et al., 2020). The WPSH is also associated to the dipole pressure pattern in western Pacific and India Ocean (Huang et al., 2020). The warming in the tropical area of India Ocean can cause an anticyclone of anomalies in the western Pacific and a cyclone of anomalies in the mid-latitude East Asia via Kelvin waves propagating from the India Ocean(Hu et al., 2011). This accompanying of anticyclone and the cyclone anomalies is known as the East Asia -Pacific (EAP)/Pacific Japan (PJ) pattern(Huang, 2004). This pattern can also be viewed as an enhanced WPSH. (Huang et al., 2020) found that the boreal summer WPSH underwent a pattern shift around the late 1990s, from a uniform Asia-Australian pattern to a India Ocean-West North Pacific dipole structure.
All these above previous studies mainly focused on the variability of WPSH, rather than the summer East Asia monsoonal circulation itself. The main reason may be that most of the previous studies rely on monthly/seasonally datasets other than daily datasets, and the former cannot reflect the characteristics on shorter time scales. This study aims to clarify how the variabilities of summer monsoon are associated with the variability of SST.
The datasets used in this study include: 1) daily atmospheric circulation datasets (1979– 2021, 2.5×2.5 degree) from the National Centers for the Environmental Prediction–National Center for the Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay and Coauthors, 1996); 2) daily circulation datasets (1951–2002) from ERA-40 (Uppala and Coauthors, 2005); 3) monthly precipitation (1901–2021) in high-resolution (0.5x0.5 degree) grids from the Climatic Research Unit (CRU) Time-series (TS) data version 4.00 ((Harris et al., 2013; Kevin et al., 2014); 4) the NOAA Extended Reconstructed Sea Surface Temperature (ERSST) dataset (monthly, 1800–2021, 2×2 degree) derived from the International Comprehensive Ocean-Atmosphere Dataset (Xue et al., 2003). Only the data in June, July and August (JJA) in the above datasets are used.
Empirical orthogonal function (EOF) decomposition is conducted on the daily composition of zonal and meridional JJA 850-hPa winds from the NCEP/NCAR reanalysis and the ERA-40 reanalysis. The EOF decomposition can obtain main spatial patterns and the intensity variations of these spatial patterns in time (the Principal Components, PC). In this study, the spatial patterns are denoted as EOF1, EOF2, … EOFn, while the corresponding timely intensity variations are denoted as PC1, PC2, …, PCn. Considering that the EOF analysis is highly sensitive to the selected domain, and in order to focus on the influence of the East Asia summer monsoon on precipitation in eastern China, the domain of 10N-48N and 90E-120E is selected for the EOF analysis. This domain does not cover the area of Northeast China, western Xinjiang, western Tibet and a small part of East China. Excluding these areas are just to avoid the disturbance of the circulations outside of China.
The WPSH index(PSHI) is calculated from the eddy geopotential height over 15°N-25°N, 120°E-150°E. Eddy geopotential height is defined as the geopotential height anomalies referenced to zonal mean geopotential height over 0–40°N, to eliminate the increase associated with global warming (He et al., 2015).
To analyze other potential influencing factors of SST, following indices are also collected: 1) the India Ocean Dipole (IOD) indices (https://sealevel.jpl.nasa.gov/overlay-iod)(Kumar et al., 2020a); 2) the multivariate ENSO Index version 2 (MEI.v2, https://psl.noaa.gov/enso/mei/)(Zhang et al., 2019).
3.1 Three EOF modes
Based on the NCEP/NCAR reanalysis (1979–2021), three modes of the wind anomalies at the pressure level of 850hpa are obtained through EOF decomposition. The first three leading PCs explains 21%, 10% and 8% of the total variance, respectively. These EOF modes extracted from the daily wind anomalies are different to that obtained from the monthly wind anomalies. The first PC from both the daily dataset and the monthly dataset both corresponds to the west part of WPSH (Fig. 1(a) based on daily dataset). The first two PCs extracted from the monthly wind anomalies explain 44% and 10% of the total variance, and the second EOF is a complex pattern and seems almost meaningless since it is very difficult to explain.
The first EOF pattern/mode (M1) features two aspects: the first is an anticyclone of wind anomalies over the South China Sea and South China, and the second is the westward wind anomalies from the South-China Sea to the India Ocean (Fig. 1(a)). This anticyclonic pattern reflects the western part of the typical WPSH in boreal summer. This pattern also implies a weak eastward summer monsoon wind blowing from the India Ocean to China. PC1 (the strength of M1) is positively correlated with summer precipitation over most of central China (including in the middle Yangtze River basin, the Huai River basin, the lower Yellow River basin, and the southern part of the Hai River basin in North China). This large area covers the Meiyu area (the lower Yangtze River and the Huai River) which is influenced by monsoonal precipitation from May to July. PC1 is significantly negatively correlated with summer precipitation in southern China, and also has negative but weak correlations to the precipitation in the upper Yellow River basin, eastern Northwest China and Northeast China (Fig. 1(g)). The outer boundary of the WPSH usually corresponds to the East Asia rain belt, so the negative correlation in South China and the positive correlation in Central China are reasonable. The correlation between PC1 and the WPSHI based on eddy geopotential height at 850-hPa is 0.8. Considering this correlation is not very large, therefore, PC1 cannot be simply recognized as an equivalent to the WPSHI.
The second EOF pattern/mode (M2) features an eastward wind anomaly blowing from the India Ocean to the South China Sea, and a southward wind dominating mainland China, forming a semi-cyclonal circulation in South China (Fig. 1(b)). The dry continental southerly winds over the mainland China definitely lead to less precipitation over a large area of North China north of the Yangtze river. The correlations between PC2 (the strength of M2) and summer precipitation in China shows a tri-polar pattern: positive correlation in southern China, negative correlation in North China and weak positive correlation in Northeast China(Fig. 1(h)). Actually, there is also a weak positive correlation area in western Xinjiang, but we will not discuss more about this region considering that the circulation for precipitation in Xinjiang is very complicated.
The third EOF pattern/mode (M3) mainly displays an anti-cyclone of wind anomalies over southeastern China. The winds in the southeastern half of China blows in such a circulation(Fig. 1(c)): from the South China Sea and the western Pacific to northern China. This anti-cyclonal pattern can be regarded as a representation of eastern and northern WPSH patterns. Correspondingly, this circulation may bring more moisture to northern China and northeastern China. The correlations between M3’s strength (PC3) and precipitation over China also shows a tri-polar pattern: positive correlation in southern China, negative correlation in south of the Yangtze river, and positive correlation in North China and northeastern China (Fig. 1(i)). Nevertheless, the most significant positive correlation in northern China lies in the eastern corner of Northeast China.
In summary, M1’s strength is positively correlated with precipitation in central China (the middle and lower Yangtze River basin, upper Huai River basin and the middle Yellow River basin). M2 strength is positively correlated with precipitation in South China and the western and central parts of Northeast China. M3’s strength is positively correlated with precipitation in eastern Northeast China. Thus, summer precipitation over eastern China can be considered as modulated by the three modes. M1 corresponds to the most commonly existed pattern of WPSH, M3 corresponds to a northern and eastern WPSH, while M2 corresponds to a very weak and broken WPSH over China. Besides this association to WPSH, the monsoonal wind between the north India Ocean and China plays another role and cannot be simply regarded as a feature of WPSH.
3.2 Variation and trends of the modes
M1 strength is mostly in negative phase in August (Fig. 2 (a)). In certain years, the M1 strength keeps in high peaks in all JJA months, such as 1988, 1995–1996, 1998, 2010 and 2020. These years corresponds to the time when ENSO shifts from positive phase to its negative phase (the decaying stages of the EL Nino events). There is a very weak downward trend during 1961–2021. Separated by the large shifts in 1971, 1998 and 2020, comparatively, the variations of M1 strength can be divided into three periods: the highest level period in 1961–1970, the second level period in 1971–1997 and the lowest level period in 1999–2019. The peaks in 1998, 2010 and 2020 make the downward trends less pronounced.
M2 strength is mostly in positive phase in June and July, and in negative phase in August (Fig. 2(b)). M2 strength is in higher positive levels during 1961–1977 and in negative levels during 1978–1986. During 1987–1998, the variations are in large amplitude and mostly in positive phases. From 1999 to 2021, the variations show an upward trend. Except for the decadal variations, there is no significant decreasing/increasing trend during 1961–2021.
M3 strength is mostly in positive phase in July, and negative phase in August. There is a decreasing trend in M3 during 1961–2021 (Fig. 3(c)). The variations of M2 and M3 do not present significant extreme peaks/valleys in those summers of decaying El Nino events.
3.3 Variabilities associated with the SST
M1 is positively correlated with the SST at the Maritime Continent and the tropical Atlantic Ocean (R > 0.39), and is negatively correlated with the SST of the central-eastern Pacific (Fig. 3(a)). The largest correlations were found in the central South China Sea and the adjacent area in Northwest Pacific. These two neighboring areas are separated by the Luzon Island of Philippine, and the correlations are 0.49 and 0.475 respectively. The most negatively correlated area generally corresponds to the Nino4 area (160°E − 150°W, 5°S − 5°N), with a correlation of -0.40. Such a SST pattern implies colder SST in central-eastern Pacific and warmer SST in West Pacific when M1 strength is in its positive phase, which is a typical pattern of La Nina events.
M2 is positively correlated with SST in the central-eastern Pacific and western India Ocean and negatively correlated with SST in the southern part of the Maritime Continent (Fig. 3(b)). There are two high-correlation centers in the tropical Pacific: the central Pacific (around longitude 160W and the equator) and the eastern Pacific (80W-120W, 10S-10N), with correlations of 0.36 and 0.40 respectively. The correlation between PC2 and SST in the southern part of the Maritime Continent is -0.27. It is also noticeable that the correlation is weak over the northern part of the Maritime Continent (the South China Sea and the northwestern Pacific). The SST pattern associated with the positive phase of M2 shares the similar warmer eastern Pacific as that during standard El Nino events, but does not display cold status in the warm pool of west Pacific. Figure 3 shows that warm SST in West India Ocean favors positive M2, which means a positive India Ocean Dipole(IOD) is positively correlated with M2 strength. By referencing to the IOD index (https://sealevel.jpl.nasa.gov/overlay-iod) (Kumar et al., 2020b) averaged annually, the correlation obtained is 0.51.
M3 is negatively correlated with SST across the whole Maritime Continent, and positively correlated with SST in the central North Pacific region.
3.4 Circulation related to the PC2 and PC3
M1 is a direct reflection of common WPSH over China. Here we focus on the circulations related to M2 and M3.
3.4.1 Circulation related to PC2
The circulation associated to M2 has an India-East China (or west-east) dipole structure. During the high positive phase of M2, the average wind anomalies at the 850hPa level greater than 3.0 (a normalized value during JJA months) is calculated here(Fig. 4(a)). It shows an anticyclone in a region of western North Pacific (140E-180E, 20N-38N). The circulation over the India Peninsular, Northwest India Ocean, Bay of Bengal and South China Sea is also generally in a anticyclonal pattern. This anticyclonic circulation of anomalies implies a strong, large and persistent southerly subtropical high, which connected the WPSH and the subtropical high over the India and the Indian Ocean. This large subtropical high system causes a strong eastward wind flow from the India Peninsular/North India Ocean to the South China Sea, then to the Northwest Pacific. A cyclonic circulation exists over the area from Southeastern China to the East China Sea. In mainland China, strong wind anomaly blowing southwestward, implying a very weak summer monsoon. Meanwhile, in the northern part of Northeast China, there is a westward wind anomaly associated to a large anti-cyclone centered on the Sea of Okhotsk, which can transport moisture to Northeast China. Such circulations can easily explain the tripolar correlation pattern between M2 and boreal summer precipitation in South China and Northeast China. In summary, during the positive phase of M2, Southeastern China and the East China Sea are under a relatively low pressure system, while the North India Ocean and the India Peninsular are under a relatively high pressure phase. The WPSH centered at 150E-160E, 24N-28N is very weak during the positive phase of M2. This pressure gradient can enhance the eastward subtropical winds along India, Bay of Bengal, Indochina Peninsula, South China Sea and the Northwest Pacific/East China Sea. This pattern has similar effects of dipole pressure patterns with the opposite signs in northwest Pacific and India Ocean (Huang et al., 2020; Wang et al., 2013). This dipole pressure pattern actually has an explanation: warm SST (low pressure) in the India Ocean can emanate warm tropospheric Kelvin waves propagating into the West Pacific, causing anomalous anticyclonic circulation (high pressure)(Hu et al., 2011; XIE et al., 2008).
During the strong negative phase of M2 with normalized M2 values smaller than − 3.0, the wind anomalies were averaged here (Fig. 4(b)). This averaged circulation poses a very different pattern: a strong westward wind anomaly flowing from the Northwest Pacific to the South China Sea and the India Peninsular, implying a very weak subtropical high. A northward wind anomaly exists in eastern mainland China, implying a strong summer monsoon over the large area north of the Yangtze River. Meanwhile, an anticyclone exists in South China, which can create less precipitation. Comparatively, the Southwest part of Northeast China is under an anticyclonic anomaly system, which also lead to less precipitation. In general, during the negative phase of M2, southeastern half of China is under a relatively high-pressure system, which is also associated to the strong WPSH centered at 146E-156E, 30N-37N. Meanwhile, the northern India Ocean, India Peninsular and Bay of Bengal are under a relatively low-pressure system. This gradient of SLP anomaly also enhances the westward wind anomaly, implying that the monsoon becomes weak. It is worthy to note that the correlation coefficient between M2 and WPSHI is very small (less than 0.05), which may imply that the strength of WPSH is not the primary influencing factor of M2.
3.4.2 Circulations related to M3
M3 corresponds to a north-south dipole structure. During the positive phase of M3 (PC3 > 3), the whole Asia continent and the Northwest Pacific is under a relative low-pressure and cyclonic pattern, leading to an enhanced eastward monsoon (blowing from the India ocean to the South China Sea) on the southern side of the Asia continent (Fig. 5(a)). There is a anticyclonic circulation centered at the East China Sea (between East China, Korean Peninsular and South Japan), which transports moisture to Northeast China. The low pressure pattern in most areas of China favors precipitation in the interior of China, including the upper Yellow River and western Inner Mongolia. Northwest Pacific which is usually occupied by the WPSH is under low-pressure anomalies, which implying a very weak WPSH. Comparatively, the SLP over the southern Maritime Continent with latitudes less than 5°N and the eastern tropical India Ocean is in high-pressure anomalies. This pattern may be related to the cold phase of SST in the warm pool of west Pacific, considering there is a negative correlation pattern of PC3 with SST of this area(Fig. 3(c)).
During the negative phase of M3 (PC3<-3), the typical wind anomalous patterns and SLP patterns show that the Northwest Pacific and the Asia continent (except western China) are under high pressure and anticyclonic anomalies. This pattern gives rise to westward wind from Northwest Pacific to India/India Ocean, implying a very weak summer monsoon. Comparatively, the SLP over the southern Maritime Continent with latitudes less than 5°N and the eastern tropical India Ocean is in low-pressure anomalies, which corresponds to the warm phase of SST in the warm pool of West Pacific(Fig. 5(c)).
3.4.3 Association to the SLP patterns
Two EOF patterns based on JJA daily SLP (in the NCEP/NCAR reanalysis) are also obtained. The first SLP-EOF is a north-south dipole structure that explains 20% of the total variance, while the second SLP-EOF is a west-east dipole structure that explains 14% of the total variance. These two SLP patterns are generally consistent to the two leading WPSH patterns based on 850-hPa geopotential height(Huang et al., 2020). Both these SLP-PCs have certain responses to the M2 and M3 of wind anomalies in China. SLP-PC1 has negative correlation (R=-0.62) to the M3 of wind anomalies in China, while SLP-PC2 has negative correlation (R=-0.27) to the M2 of wind anomalies in China. These correlation coefficients are not satisfactorily large, but it is reasonable: M2 and M3 of wind anomalies are only the residual components above the M1 of wind anomalies and cannot completely reflect the influence of WPSH. In contrast, the west-east dipole structure is more meaningful than the north-south structure. In the west-east structure, the variability of the west side is smaller than that of the east side. However, the north-south dipole structure is actually a uniform pattern, considering that the southern part of the structure has a very small variability. This uniform pattern has the similar effect to the first pattern of WPSH(Huang et al., 2020), except that in the present study, the variability is more pronounced on the north side (East Asia) than on the south side (the southern part of the Maritime Continent).
The PC2 of SLP peaks in the summers of 1988, 1995, 1998, 2007, 2010 and 2020, corresponding to the decaying year of El Nino events. The M2 of wind anomalies has corresponding extreme lows in the summers of 1995, 2010 and 2020, but other extreme lows are in the summers of 1989,1992, 2000, 2004 and 2013, corresponding to the negative phase of ENSO.
4.1 Is there a shift of WPSH around late 1990s?
In the late 1990s, there appears to have been a decadal shift of WPSH due to changes of ENSO (Huang et al., 2020). This shift also can be broadly seen in the SLP’s PCs and the modes of wind anomalies in China. It seems that the dividing point is at 1995 other than at 1998 used in (Huang et al., 2020). Before 1995, the SLP PC1 (the uniform pattern) has a short periodicity (2–3 year) and relatively high peaks, combined with low amplitudes, while after 1995, SLP-PC1 has a longer periodicity of 5–6 years and lower peaks. This change implies a decrease in the variability of SLP-PC1. For SLP-PC2 (the dipole pattern), the amplitude is smaller before 1995, but becomes larger after 1995. This decreasing of the uniform pattern but increasing of the dipole pattern are well consistent to the shift of WPSH(Huang et al., 2020). These changes of SLP’s PCs also correspond to the trends of wind anomaly modes in China. The decrease of M3 strength after the late 1990s appears pronounced. Comparatively, the increase in M2 strength after the late 1990s is not as pronounced, but it does show a significant increase when compared to the period from late 1970s to late 1990s. The reason of such a shift is that the El Nino events of central eastern Pacific warming (CP El Nino) is more common than the El Nino events of eastern Pacific warming(EP El Nino)(Huang et al., 2020). During the developing CP El Nino, the positive SST anomalies in central eastern tropical Pacific triggers anomalous cyclonic circulation over the northwest Pacific through Rossby waves. The central and eastern equatorial Pacific warming leads to subsidence over the Maritime Continent and India Ocean via a weakened Walker circulation. This is why the dipole pattern develops. However, this explanation does not seem to fit the positive correlation between the M2 strength and SST in west India Ocean.
4.2 Can the modes reflect the south-flood-north-drought change?
The south-flood north-drought (SFND) pattern refers to the dipole pattern of precipitation in China since the late 1970s. That is, during the 1950s and 1960s, precipitation is abundant in northern China but is comparatively less in the Yangtze River and the Huai River, but after the late 1970s, northern China becomes drier, while more flooding events occurred in southern China(Ding et al., 2007; Gong and Ho, 2002). This change has been attributed to the weakening of EASM since the late 1970s(Ding et al., 2007; Zhou et al., 2009). However, there is actually no consensus on the definition of EASM. According to the monsoon index presented by (Li and Zeng, 2002), the EASM is weakening(Yang et al., 2017; LI and Zeng), however, this conclusion of EASM weakening is based on the NCEP/NCAR reanalysis, which, according to our analysis during the present study, has large inconsistencies to the ERA40 reanalysis for the period prior to 1979. If the ERA40 reanalysis is used, the weakening of EASM index is actually not so significant. (WANG et al., 2008) constructed a EASM index using multiple variables, which has a different meaning from the other definitions of monsoon indices. In summary, for northern China, a strong EASM index may imply abundant precipitation in some regions (e.g., North China, Northeast China) while less precipitation in other regions (e.g., Northwest China), or vice versa. Different definition of EASM has different meanings for different areas. Some views on the cause of the SFND pattern suggest that it is attributed to the changes in the Pacific Decadal Oscillation(PDO)(Yang et al., 2017; Pei et al., 2015). During the late 1970s, the PDO shifted from its cold phase to its warm phase, corresponding to the SFND change. According to this rule, the precipitation pattern should change to a south-drought-north-flooding pattern from 2000 to now, since the PDO has undergone a new shift from its warm phase to its cold phase(Yang et al., 2017). However, although precipitation in northern China appears to have increased in recent years, it cannot be regarded as has shifted to a pattern like that prior to the late 1970s. The SFND pattern has other explanations based on external forces, including changes in greenhouse gas concentration and aerosol emissions. However, SFND can be a role of an atmospheric internal variability, while the external forcings and PDO is not necessary causes(Wu et al., 2019). In conclusion, the causes of the SFND change remains unclear (Zhou et al., 2021).
In this study, neither of M1, M2 and M3 has obvious correlated responses to the PDO index. That is, the SFND cannot simply been reflected by any single mode of the EASM. Meanwhile, for the JJA precipitation in eastern China, the SFND change around the late 1970s is also not obvious, because the SFND changes also involves precipitation in other seasons, in addition to that in the JJA months.
From the daily wind anomalies at the 850-hPa pressure level in longitudinally central China, three main patterns are obtained. The first mode (M1) reflects the intensity of the most common WPSH pattern influencing China. Its positive phase favors precipitation in the central China and is unfavorable to precipitation in South China. The second mode (M2) reflects the circulation without WPSH directly covering the eastern part of China. Its positive phase favors precipitation in the areas south of the Yangtze River (including both Southwest China and South China) and the west part of Northeast China. Its negative phase favors precipitation in North China, including most of the Yellow River basin. The positive phase of the third mode (M3) reflects a northward-shifting WPSH, which favors precipitation in northern China and a small part of South China, but not to precipitation in the Yangtze River basin. Comparatively, PC3 has a more pronounced decreasing trend in the past decades, while M2 poses decadal changes and no significant trend.
The positive phase of M2 is positively correlated with the warm SST at both the central-eastern pacific and the western India Ocean, and negatively correlated with the SST in the south part of the Maritime Continent. The positive phase of M2 is also associated with a strong, large and spatially continuous southerly subtropical high that connects the WPSH and the subtropical high over the India Peninsular/Indian Ocean, leading to a strong eastward wind flow from the India Peninsular and the northern India Ocean to the South China Sea and then to the northwest Pacific. Accompanying with this large subtropical high system is a cyclonic circulation over the area of Southeastern China and the East China Sea. Therefore, M2 poses an India-East China (or west-east) dipole pattern, which basically corresponds to the dipole structure in the western North Pacific and India Ocean(Huang et al., 2020).
The main feature of M3 is a negative correlation with the SST across the whole Maritime Continent. M3 is associated with a strong south-north dipole structure of sea level pressure. The southern side of this structure is over the Maritime Continent, and the north side of this structure is over the Asia continent. The variation of SLP at the Maritime Continent is small compared to that in the Asian continent and the western North Pacific, so this dipole structure can also be regarded as a uniform structure, over the Asian-Australian region (Huang et al., 2020).
Most previous studies focus mainly on the strength of the common WPSH pattern which corresponds to the first mode of the East Asia summer monsoon. This study revealed that the other two different patterns of the summer WPSH are also significant for the monsoon circulation and precipitation in China. However, the second mode and the third mode are so subtle that perhaps few climate models can simulate them well. Meanwhile, the reason for these two modes actually are not very clear, except that given by (Huang et al., 2020). This study demonstrates two aspects: first, the climatic changes of the common WPSH strength does not directly mean the increasing/decreasing of precipitation in China, especially in northern China; second, the mechanisms of the EASM is very complex, using one well-defined index of EASM may be insufficient to represent the precipitation related circulations in different area of China.
Funding
No funding.
Author contribution statement
Yong-He Liu: writing and analyzing; Yong-Hong Hu: collecting reanalysis datasets; Jin-Ming Feng: data processing
Availability of data and material
The data and material that support the finds of this study from the corresponding author upon reasonable request.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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No competing interests reported.