Tropospheric Biennial Oscillation of the Western Pacific Subtropical High and Its Relationships With the Tropical Sea Surface Temperature and Atmospheric Circulation Anomalies

CHAPTER

TROPOSPHERIC BIENNIAL OSCILLATION OF THE WESTERN PACIFIC SUBTROPICAL HIGH AND ITS RELATIONSHIPS WITH THE TROPICAL SEA SURFACE TEMPERATURE AND ATMOSPHERIC CIRCULATION ANOMALIES

6

6.1 INTRODUCTION Quasi-biennial oscillation presents opposite wind directions every two years in the tropical lowerstratospheric zonal wind, which was first discovered by Reed et al. (1961). A few years later Belmont and Dartt (1968) officially defined the quasi-period phenomenon as quasi-biennial oscillation (QBO). The QBO in the troposphere was also defined around the same time. Both the sea level pressure in the boreal northern hemisphere (James, 1971) and the average precipitation over the whole of India from June to September (Mooley and Parthasarathy, 1984) have a quasi-biennial period, and the phenomenon commonly exists in the atmospheric circulations, the tropical sea surface temperature (SST), and surface meteorological elements. Therefore it is called tropospheric biennial oscillation (TBO) to distinguish it from QBO in the lower-stratosphere (Meehl, 1994, 1997). Research on TBO over the East Asian monsoon region began to appear in the late-1980s, and found that East Asian monsoon precipitation has an interannual period of the QBO (Tian and Yasunari, 1992; Chang and Li, 2000; Chang et al., 2000; Ding, 2007). The observational precipitation data in most of China also have obvious TBO components (Huang, 1988; Wang et al., 1995; Liu et al., 2015), which will be discussed in Chapter 7, Tropospheric Biennial Oscillation of Monsoon Rainfall and Its Association With El Nin˜o-Southern Oscillation. Kuang et al. (2002) and Jia et al. (2009) further analyzed the spatial distribution and the long-term evolution of the precipitation TBO in China. As one of the dominant members of the East Asian monsoon system, the western Pacific subtropical high (WPSH) also exhibits significant periods at interannual and interdecadal timescales, and its variation in location and intensity has important impacts on the summer precipitation over China (Tao and Wei, 2006; Xu et al., 2001). The interannual variability of the WPSH directly The Asian Summer Monsoon. DOI: https://doi.org/10.1016/B978-0-12-815881-4.00006-8 © 2019 Elsevier Inc. All rights reserved.

97

98

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

decides the distribution of drought and floods over eastern China (Wu et al., 2002), while its interdecadal variability over the 1990s provides favorable climatic background of more rainfall in the middle and low reaches of the Yangtze River basin and less rainfall in northern China (Hu, 1997; Xiong, 2001). Based on a set of WPSH indices, the relationship between the WPSH and June July August (JJA) rainfall anomalies is analyzed in Chapter 5, Characteristics of the Western Pacific Subtropical High and June July August Rainfall Anomalies. It is further found that there are obvious TBO signals in the monthly time series from 1951 to 2011. Therefore this chapter focuses on the TBO component of the WPSH and investigates whether the TBO component experienced significant changes under the background of the climatological interdecadal transition. The corresponding relationships of TBO with the atmospheric circulation and tropical SST anomalies are further analyzed to attempt to provide some valuable signals for short-term climatic prediction in China. The primary datasets in this chapter include the monthly geopotential height and horizontal wind at 500 hPa derived from the NCEP/NCAR reanalysis from 1951 to 2011 (Kalnay et al., 1996) and the extended reconstructed SST data (ERSSTv3) published by the NOAA, with a horizontal resolution of 2 3 2 (Xue et al., 2003). Based on the NCEP/NCAR reanalysis, the monthly WPSH indices are calculated from 1951 to 2011, including the area index, intensity index, ridgeline index, and westernmost point. The main methods include the power spectrum analysis, Butterworth band pass filtering, low-pass filtering, time-lag correlation analysis, and composite analysis. This chapter is organized as follows. Section 6.2 shows the primary period of the WPSH on the interannual timescale. Section 6.3 discusses the interdecadal variation of the WPSH’s interannual component. Section 6.4 examines the relationship between the WPSH’s TBO component and the tropical SST and atmospheric circulation anomalies. Summary and discussions are given in Section 6.5.

6.2 THE WESTERN PACIFIC SUBTROPICAL HIGH’S INTERANNUAL VARIATION: TROPOSPHERIC BIENNIAL OSCILLATION A power spectrum analysis can clearly demonstrate the main cycles of the subtropical high during the period of 1951 2011. Considering that the seasonal variability of the WPSH is more significant than other timescales, the low-pass filter is first used to remove the seasonal variability from the raw data to highlight the interannual signals. The power spectrum analysis for the filtered monthly WPSH’s intensity and westernmost point indices show that there are mainly two peak values at the interannual timescale during the 61-year period of 1951 2011 (Fig. 6.1), the quasi-four-year and quasi-biennial year (i.e., TBO), with the truncated maximum-length sequences of the power spectrum analysis is 150 months (the length of the time series is 732 months). While the TBO component of the WPSH corresponds to the dominant interannual cycle of the summer monsoon rainfall in East Asia and China (Chang and Li, 2000; Chang et al., 2000; Ding, 2007; Kuang et al., 2002), and their interaction with each other is closer than the quasi-four-year component, therefore the WPSH’s TBO component deserves further analysis.

6.2 WESTERN PACIFIC SUBTROPICAL INTERANNUAL VARIATION

99

FIGURE 6.1 Power spectrums (solid lines) of the western Pacific subtropical high (WPSH): (A) intensity index and (B) westernmost point during 1951 2011 after removing the seasonal variability (the dotted lines denote the 0.05 t-test significant level).

100

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

6.3 INTERDECADAL CHANGES OF THE TROPOSPHERIC BIENNIAL OSCILLATION It is known that many meteorological variables, including a variety of atmospheric circulation systems and precipitation in the Asian monsoon region, have had significant interdecadal variations during the past 60 years, with the turning period occurring in the late-1970s (Liu et al., 2012a,b; Huang et al., 2006a,b; Zhao et al., 2007). Fig. 6.2 shows the monthly anomalies and accumulative anomaly curves of the WPSH intensity index and westernmost point. It is seen that the intensity index is almost negative and the westernmost point is nearly positive before the late-1970s, which indicates that the subtropical high is weak and more eastward. However, the interdecadal condition turned to the opposite of this after the late-1970s. The positive intensity index and negative

FIGURE 6.2 Monthly anomalies and accumulative anomalies of (A) the WPSH intensity index and (B) westernmost point during 1951 2011 (the gray bars denote positive/negative anomalies, and the black curves denote accumulative anomalies). WPSH, Western Pacific subtropical high.

6.3 INTERDECADAL CHANGES

101

FIGURE 6.3 Response function of the Butterworth band pass filter with a sliding window of 24 36 months.

westernmost point demonstrate that the subtropical high became stronger and more westerly than normal over the past 30 years. The accumulative curves of these two indices also show an obvious interdecadal transition in the late-1970s. Do the WPSH’s TBO components also present any significant differences under the climatic background of the interdecadal transition? The Butterworth band pass filter can be used to isolate the TBO component from the raw data of the WPSH intensity and westernmost point indices. The time-sliding window is set to 24 36 months and the frequency response function is shown in Fig. 6.3. It can be seen from the filtered time series (Fig. 6.4) that the TBO components of the WPSH also appear in the obvious transition during the late-1970s. The amplitude of intensity index and westernmost point are relatively small before 1980, but they significantly increased in the following years. The variance contributions of their TBO components in the interannual and interdecadal timescales during the period 1951 80 are 9.8% and 14.1%, respectively, while they increased to 44.1% and 44.7% during the period of 1981 2011, respectively. The interdecadal variation of the WPSH’s TBO components seems to be consistent with the interdecadal ascending trend of the QBO in the stratosphere. Using the QBO timescale component of zonal wind anomalies at 100 10 hPa from ERA40 reanalysis to represent the QBO, Huang et al. (2012) found that both its intensity and vertical distribution exhibit significant interdecadal modulations, with the turning point being the end of the 1970s. Hu et al. (2012) further examined the connection of the long-term QBO variations to the tropical SST and atmospheric circulation, and found that their relationship has the same interdecadal modulation during the end of 1970s. In China the TBO signal of rainfall also exhibits the interdecadal variations (Yang, 2006). The coherent interdecadal variations in these meteorological variables are, to some extent, the results of the ocean atmospheric interaction.

102

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

FIGURE 6.4 Time series of the TBO components of (A) the WPSH intensity index and (B) westernmost point during 1951 2011. WPSH, Western Pacific subtropical high.

It is suggested through the above analysis that the TBO, as one of the dominant interannual components of the WPSH, existed during the entire period of 1951 2011, but due to its own interdecadal evolution it does not always significantly impact the atmospheric circulation and rainfall anomalies over the Asian monsoon region. The TBO signal of the WPSH has become increasingly significant over the past 30 years, which is worthy of more attention and analysis for short-term climatic prediction. Therefore the period of 1981 2011 was selected to further investigate the connection between the TBO and atmospheric circulation, as well as the tropical SST anomaly, and deepen the knowledge of the interannual signals for short-term climatic prediction.

6.4 TROPOSPHERIC BIENNIAL OSCILLATION RELATED TROPICAL SEA SURFACE TEMPERATURE AND ATMOSPHERIC CIRCULATION ANOMALIES In previous studies there is much disagreement concerning the physical mechanism of TBO in the Asian monsoon region. One of the arguments is that TBO seems to be the result of the

6.4 TROPOSPHERIC BIENNIAL OSCILLATION

103

ocean atmospheric interaction over the South China Sea western Pacific warm pool region (Shen and Lau, 1995; Lau and Yang, 1997; Huang et al., 2006a,b). Meehl and Arblaster (2002) emphasized that the contribution of the ocean atmospheric interaction (over the India Pacific region) is greater than the land atmospheric interaction (referring to South Asia). Raumusson et al. (1990) and Yasunari (1990) also proved the contribution of ENSO on TBO. However, Chang and Li (2000) and Li et al. (2001) took a different view by reporting that TBO is a local phenomenon. Without the role of the equatorial Pacific SST anomaly, there are still TBO signals over the Indian Ocean. Following this line of argument, Meehl et al. (2003) further pointed out that if there is no impact of ENSO, TBO in the Asian Australian monsoon region would be weakened. It can thus be summarized that TBO’s existence in the Asian monsoon region is mainly the result of the sea land air interaction, while the contributions of the tropical oceans and the atmospheric circulation anomalies on TBO are relatively significant. Therefore in the following, we mainly analyze the association of TBO with the tropical SST and atmospheric circulation to reveal the corresponding relationships among them.

6.4.1 TIME-LAG CORRELATION BETWEEN THE WESTERN PACIFIC SUBTROPICAL HIGH INDICES AND THE TROPICAL SEA SURFACE TEMPERATURE ANOMALY In order to understand the corresponding relationship between the WPSH’s TBO component and the tropical SST anomaly, we calculated the time-lag correlation of the raw (unfiltered) WPSH indices with SST anomalies in several key ocean regions: Nin˜o3.4, 5 S 5 N, 150 90 W (Meehl and Arblaster, 2002; Meehl et al., 2003); Pacific warm pool area (WP), 5 S 5 N, 120 160 E (Huang et al., 2006a,b); and the tropical western Indian Ocean (WIO), 5 S 5 N, 40 60 E (Chang and Li, 2000; Li et al., 2001). It is indicated that the WPSH indices are significantly influenced by ENSO and WIO SST anomalies except the ridgeline index, while the correlation with the SST anomaly in the WP is relatively weak (Fig. 6.5). The response in the westernmost point index to ENSO is earlier than other WPSH indices, with the most obvious correlation appearing with a lag of 2 5 months. There is a lag of 4 7 months when the time-lag correlation of the intensity and area indices with the SST anomalies is prominent. Time-lag correlations are also calculated between the WPSH TBO components and SST anomalies in the same key areas (Fig. 6.6). It is seen that correlations between them are more significant and of longer duration, which indicates significant influence of the tropical SST anomalies on the WPSH’s TBO components. The TBO of the WPSH intensity index lags the Nin˜o3.4 SST anomaly by about 2 months, and the obvious correlation of them can last 11 months. When the Nin˜o3.4 index lags by 5 6 months, the correlation is at its maximum. The response of the TBO on the westernmost point to ENSO is earlier than the intensity index, with the most significant negative correlation between them when lagging by 3 5 months. Compared to the Nin˜o3.4 SST anomaly, it takes a shorter time to achieve the maximum of the time-lag correlation between the TBO and SST anomalies in WIO. This is because the converting signals of the tropical SST anomalies always appear in the central eastern Pacific first, and then appear in the WIO.

104

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

FIGURE 6.5 Time-lag correlations between the raw time series of (A) the WPSH intensity, (B) area, (C) westernmost point, and (D) ridgeline indices and the tropic SST anomaly in some key regions. Where n (n) on the x-axis denotes the leading (lagging) months relative to the SST anomaly. The dashed lines are the 0.05 t-test significant level. WPSH, Western Pacific subtropical high; SST, sea surface temperature.

6.4 TROPOSPHERIC BIENNIAL OSCILLATION

FIGURE 6.5 (Continued.)

105

106

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

FIGURE 6.6 Time-lag correlations between the TBO components of (A) the WPSH intensity and (B) westernmost point indices and the tropic SST anomaly in some key regions. Where n (n) on the x-axis denotes the leading (lagging) months relative to the SST anomaly. The dashed lines are the 0.05 t-test significant level. WPSH, Western Pacific subtropical high; SST, sea surface temperature.

6.4 TROPOSPHERIC BIENNIAL OSCILLATION

107

FIGURE 6.7 Schematic diagram of the eight-phase cycle for the WPSH’s TBO. WPSH, Western Pacific subtropical high; TBO, tropospheric biennial oscillation.

6.4.2 SPATIAL DISTRIBUTIONS OF SEA SURFACE TEMPERATURE AND ATMOSPHERIC CIRCULATION ANOMALIES For a more detailed description of the relationship between the WPSH’s TBO components and the spatial distribution of the SST and atmospheric circulation anomalies, we divided the composited WPSH’s TBO cycle into eight phases. It is known from the TBO time series (Fig. 6.4) that it is often in the summer when the amplitude of the TBO time series is at its maximum. Therefore the summer of the previous year is defined as the first phase of TBO with the most-negative period. The TBO phase turns to positive in the following winter, corresponding with the largest variability and is defined as the third phase. The fifth phase is the largest positive phase of the TBO component, which corresponds with the summer of this year. Thereafter the TBO begins to weaken. In the seventh phase, the positive TBO turns to negative, and thereby completes the eight-phase cycle (Fig. 6.7). Fig. 6.8 shows the association of the eight-phase cycle for the WPSH’s TBO with the SST and 850 hPa wind anomalies. It is seen that in the summer of the previous year (Fig. 6.8A) when TBO is in the most-negative phase, the equatorial central eastern Pacific is in the El Nin˜o-like state, the WP SST anomaly begins to appear negative at the same time, and the Indian Ocean SST approaches the climate average. In the lower-level wind field, the cross-equatorial flow in the Bay of Bengal is stronger than normal, an anomalous cyclone is located over the South China Sea to the western Pacific areas, and an anomalous anticyclone is to the north of 30 N, which is the typical mode of a strong East Asian summer monsoon. The abnormal easterly flow on the south side of the cyclone, that is,

108

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

FIGURE 6.8 Distributions of the SST and 850 hPa wind anomalies corresponding to the eight different phases of the WPSH’s TBO (A H denote the first to eighth phase, respectively). WPSH, Western Pacific subtropical high; TBO, tropospheric biennial oscillation; SST, sea surface temperature.

located to the south of 30 N, contributes to the eastward extension of the warm SST in the WP, which is favorable to increase the positive SSTA in the tropical central-eastern Pacific. In the fall of the previous year (Fig. 6.8B), the distribution of the cold anomaly in the west and warm anomaly in the east of the Pacific is further strengthened under the driving of the equatorial easterly flow, and the SST anomaly in the Indian Ocean will be more significant than in the preceding summer. Meanwhile, a divergent circulation appears over the WP, and the equatorial westerly flow continues to strengthen at the lower-level wind anomaly field. Then in the winter (Fig. 6.8C), the El Nin˜o-like state reaches a peak with the further warming of the SST in Indian Ocean. An anomalous anticyclone is stimulated on the east of Philippines and the East Asian winter monsoon is weaker than normal. Then in the spring of this year (Fig. 6.8D), the El Nin˜o-like state begins to decay, while the Indian Ocean basin wide (IOBW) mode reaches its peak. The IOBW lags by about a season for the evolution of the maximum SST anomaly in the equatorial central eastern Pacific, which is consistent with the lagging time of the WPSH’s correlation with SST anomalies in Nin˜o3.4 and the WIO region, respectively (Fig. 6.6). The abnormal anticyclone over the east of the Philippines in prewinter moved northward to the South China Sea, and the Somali crossequatorial flow is weaker than normal.

6.4 TROPOSPHERIC BIENNIAL OSCILLATION

109

In the summer of this year (Fig. 6.8E), the evolution of the SST anomaly in the equatorial Pacific begins to take on a La Nin˜a-like state as it is the strongest positive period of the WPSH’s TBO. An anomalous anticyclone is located to the south of 30 N over the western Pacific, corresponding with a weak East Asian monsoon. The southerly flow on the western side of the anticyclone and the northerly flow from the high latitude converges over the Yangtze River basin, which is conducive to excessive rainfall. The abnormal easterly flow seems to appear over the WP area, accelerating SST warming. With the appearance of the negative SST anomaly in the central eastern Pacific, the SST in the Indian Ocean region becomes lower than that in the previous spring, and the Somali cross-equatorial flow is weaker than normal. Such distribution of the atmospheric circulation and tropical SST anomalies is almost opposite to that of the summer of the previous year (Fig. 6.8A). In the fall of this year (Fig. 6.8F), the equatorial easterly flow anomaly further strengthens and the La Nin˜a-like state in the central-eastern Pacific continues to develop an exhibits the antiphase distribution in the same period of the previous year, but the degree of abnormality was much weaker than that in the El Nin˜o-like period. When the La Nin˜a-like state in the equatorial central eastern Pacific arrives at peak level (Fig. 6.8G), the East Asian winter monsoon is stronger than normal and the lower-level flows converge over the WP area. In the spring of the next year, the La Nin˜a-like state starts to decay, the anomalous anticyclone appears again over the east of the Philippines, the intensity of WPSH is weaker than normal, and double the number of cyclones appear over the equatorial Indian Ocean region, which indicates the relatively earlier outbreak and stronger ASM than normal, once again demonstrated the anomalous distribution as in Fig. 6.8A, thereby completing the process of the TBO cycle. It is confirmed by this analysis that in a complete WPSH’s TBO cycle, the most significant variability of SST anomalies is in the equatorial central eastern Pacific. The process entails the SST anomalies there beginning to display an El Nin˜o-like state in the previous summer, then strengthen in the previous fall and arriving at the peak in the previous winter and turns to descending in the following spring and summer, and then developing into a La Nin˜a-like state, coming to its strongest period in the winter of that year, and advancing again in the next spring and summer to exhibit the conversion from La Nin˜a-like to El Nin˜o-like state. In the corresponding lower-level wind anomaly fields, it experiences the changes of strong summer monsoon weak winter monsoon weak summer monsoon strong winter monsoon strong summer monsoon from the previous summer to the next summer. This TBO cycling variation of the East Asian monsoon coincides with the viewpoint of Li et al. (2011) based on their East Asian monsoon index research. During the WPSH’s TBO cycle, the El Nin˜o-like state in winter is always coupled with a weak winter monsoon, when is just the third phase of the WPSH’s TBO with the most developing variability. On the contrary, the La Nin˜a-like state always couples with the strong winter monsoon, corresponding to the seventh TBO phase with the most decaying variability. In summary, the entire TBO cycle performance is the result of the typical ocean atmosphere interaction. Chapter 1, Basic Features of the Asian Summer Monsoon System, introduced the TBO phenomenon in the typical SST anomalies based on the raw data, while this chapter gives the entire TBO cycles for both atmospheric circulation and SST anomalies based on filtered data, which is more clearly representative of the remarkable characteristics of TBO in the Asian monsoon region. It is seen from the contrast between the previous and the next year in the TBO cycle that during the eight-phase TBO cycle, the abnormality degree of the El Nin˜o-like mode in the central and

110

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

eastern Pacific in the previous year is significantly stronger than that the La Nin˜a-like mode in the next year. The abnormal cyclones and anticyclones at the lower-level wind fields in the previous year exhibit more clearly than those in the next year. Such asymmetrical, abnormal distribution in the tropical SST and atmospheric circulation over two years indicates that the WPSH’s TBO is more significant in the period of the development of the El Nin˜o-like state and the transition from the strong summer monsoon to weak winter monsoon than that during the period of the development of the La Nin˜a-like state and the transition from the weak summer monsoon to the strong winter monsoon. In other words, as one of the dominant interannual components, the TBO signal needs to be given more attention for short-term climatic forecasts when it is in the developing period of an El Nin˜o-like state.

6.5 SUMMARY AND DISCUSSION The WPSH system has two dominant interannual cycles, namely the quasi-four-year oscillation and the TBO. This chapter focuses on the TBO component, which has a close relationship with the East Asian monsoon rainfall anomalies. Based on a set of WPSH indices, the TBO component is isolated from the raw monthly WPSH indices from 1951 to 2011 through the Butterworth band pass filter, and its interdecadal differences are compared under the climatic background of the interdecadal transition. Its association with the tropical SST and lower-level atmospheric circulation anomalies are further analyzed to reveal its relationship with the WPSH’s TBO. The conclusions are as follows: 1. As an important interannual component, the WPSH’s TBO exists within the entire period of 1951 2011. With the interdecadal evolution of the WPSH raw data, the TBO component also shows an obvious transition by the end of 1970s, and the amplitude of the WPSH TBO increased significantly after 1980. 2. Time-lag correlations between the WPSH’s TBO and the tropical SST anomalies in some key areas are more significant than that between the WPSH’s raw data, with longer correlation duration, which indicates the important influence of the SST anomalies on the TBO components. The TBO of the WPSH intensity index lags the Nin˜o3.4 SST anomaly by about 2 months, and when lagging 5 6 months, the correlation coefficient achieves its maximum. The response of the westernmost point’s TBO component to ENSO is earlier than the intensity index, with the most significant negative correlation between them when lagging by 3 5 months. It takes a shorter time to achieve the maximum of the time-lag correlation between TBO and the SST anomaly in the WIO. That is because the changing signals of the tropical SST anomaly always appear in the central eastern Pacific first, and then propagate to the WIO. 3. The behavior of the WPSH TBO cycle is the result of the typical ocean atmosphere interaction. In the course of a WPSH’s TBO cycle, the occurrence of the El Nin˜o-like anomaly in the tropical central eastern Pacific in winter is always coupled with a weak East Asian winter monsoon, when the WPSH’s TBO is in the third phase with the strongest enhancing trend. In contrast, the La Nin˜a-like anomaly in the central eastern Pacific in winter is coupled with a strong East Asian winter monsoon, when TBO is in the seventh phase and in the most decaying period.

REFERENCES

111

4. The tropical SST anomaly and atmospheric circulations present the asymmetric distribution in the TBO cycle. The WPSH’s TBO is more significant in the period of the developing El Nin˜olike state in the central eastern Pacific than in the period of the developing La Nin˜a-like state. Therefore in the period of developing an El Nin˜o-like state, the interannual component of the TBO signal needs more attention for short-term climatic prediction. It is seen from the above statistics that the most significant variability of the SST anomaly is in the equatorial central eastern Pacific in a complete WPSH’s TBO cycle. The SST anomalies evolution in the tropical Indian Ocean and warm pool area always lag by about one season to the El Nin˜o-like or La Nin˜a-like state, and their degree of abnormality are also much weaker than the SST anomalies in the tropical central eastern Pacific. Therefore the modulation of the SST in the tropical central-eastern Pacific on the WPSH’s TBO seems to be earlier and more important than others. The SST anomalies evolution in the Indian Ocean plays an enhancing role in the TBO cycle, which is consistent with the findings by Meehl et al. (2003).

REFERENCES Belmont, A.D., Dartt, D.G., 1968. Variation with longitude of the quasi-biennial oscillation. Monthly Weather Rev. 96, 767 777. Chang, C.P., Li, T., 2000. A theory of the tropical tropospheric biennial oscillation. J. Atmos. Sci. 57, 2209 2224. Chang, C.P., Zhang, Y.S., Li, T., 2000. Interannual and interdecadal variations of the East Asian summer monsoon and tropical Pacific SSTs. Part I. Roles of the subtropical ridge. J. Clim. 13, 4310 4340. Ding, Y.H., 2007. The variability of the Asian summer monsoon. J. Meteorol. Soc. Jpn 85, 21 54. Hu, Z.-Z., 1997. Interdecadal variability of summer climate over East Asia and its association with 500hPa height and global sea surface temperature. J. Geophys. Res. 102 (D16), 19403 19412. Hu, Z.-Z., Huang, B.H., Kinter III, J.L., et al., 2012. Connection of the stratospheric QBO with global atmospheric general circulation and tropical SST. Part II. Interdecadal variations. Clim. Dyn. 38, 25 43. Huang, J.Y., 1988. The representations of the tropospheric biennial oscillation in precipitation over China. Chin. J. Atmos. Sci. 12, 267 273 (in Chinese). Huang, R.H., Cai, R.S., Chen, J.L., et al., 2006a. Interdecadal variations of Drought and flooding disasters in China and their association with the East Asian climate system. Chin. J. Atmos. Sci. 30, 730 743 (in Chinese). Huang, R.H., Chen, J.L., Huang, G., et al., 2006b. The quasi-biennial oscillation of summer monsoon rainfall in East China and its cause. Chin. J. Atmos. Sci. 30, 545 560 (in Chinese). Huang, B.H., Hu, Z. Z., Kinter III, J.L., et al., 2012. Connection of the stratospheric QBO with global atmospheric general circulation and tropical SST. Part I. Methodology and composite life cycle. Clim. Dyn. 38, 1 23. James, W.A., 1971. Long-period variations in seasonal sea-level pressure over the northern hemisphere. Monthly Weather Rev. 99, 49 66. Jia, J.Y., Sun, Z.B., Liu, X.W., et al., 2009. Evolution of summer precipitation quasi-biennial oscillation in eastern China. Chin. J. Atmos. Sci. 33, 397 407 (in Chinese). Kalnay, E., Kanamitsu, M., Kistler, R., et al., 1996. The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteorol. Soc. 77, 437 472.

112

CHAPTER 6 TROPOSPHERIC BIENNIAL OSCILLATION

Kuang, X.Y., Ding, Y.G., Shi, N., 2002. The distribution patterns and long term variability features for precipitation QBO over China. J. Trop. Meteorol. 18, 359 367 (in Chinese). Lau, K.M., Yang, S., 1997. Climatology and interannual variability of the Southeast Asian summer monsoon. Adv. Atmos. Sci. 14, 141 162. Li, T., Tham, C.W., Chang, C.P., 2001. A coupled air sea monsoon oscillator for the tropospheric biennial oscillation. J. Clim. 14, 752 764. Li, C.Y., Pan, J., Que, Z.P., 2011. Variation of the East Asian monsoon and the tropospheric biennial oscillation. Chin. Sci. Bull. 56, 70 75. Liu, Y.Y., Ding, Y.H., 2012a. Analysis of the leading modes of the Asian-Pacific summer monsoon system. Chin. J. Atmos. Sci. 36, 673 685 (in Chinese). Liu, Y.Y., Li, W.J., Ai, W.X., et al., 2012b. Reconstruction and application of the monthly western Pacific subtropical high indices. J. Appl. Meteorol. Sci. 23, 414 423 (in Chinese). Liu, Y.Y., Hu, Z.-Z., Kumar, A., et al., 2015. Tropospheric biennial oscillation of summer monsoon rainfall over East Asia and its association with ENSO. Clim. Dyn. 45, 1147 1159. Meehl, G.A., 1994. Influence of the land surface in the Asian summer monsoon: external conditions versus internal feedback. J. Clim. 7, 1033 1049. Meehl, G.A., 1997. The South Asian monsoon and the tropospheric biennial oscillation. J. Clim. 10, 1921 1943. Meehl, G.A., Arblaster, J.M., 2002. The tropospheric biennial oscillation and Asian Australian monsoon rainfall. J. Clim. 15, 722 744. Meehl, G.A., Arblaster, J.M., Loschnigg, J., 2003. Coupled ocean atmosphere dynamical processes in the tropical Indian and Pacific Ocean regions and the TBO. J. Clim. 16, 2138 2158. Mooley, D.A., Parthasarathy, B., 1984. Fluctuations in All-India summer monsoon rainfall during 1871 1978. Clim. Change 6, 287 301. Rasmusson, E.M., Wang, X.L., Ropelewski, C.F., 1990. The biennial component of ENSO variability. J. Mar. Syst. 1, 71 96. Reed, R., Cambell, W.J., Rasmusson, L.A., et al., 1961. Evidence of a downward propagating annual wind reversal in the equatorial stratosphere. J. Geophys. Res. 66, 813 818. Shen, S., Lau, K.M., 1995. Biennial oscillation associated with the East Asian monsoon and tropical sea surface temperatures. J. Meteorol. Soc. Jpn 73, 105 124. Tao, S.Y., Wei, J., 2006. The westward and northward advance of the subtropical high over the western Pacific in summer. J. Appl. Meteorol. Sci. 17, 513 525 (in Chinese). Tian, S.F., Yasunari, T., 1992. Time and space structure of interannual variations in summer rainfall over China. J. Meteorol. Soc. Jpn 70, 585 596. Wang, J.X., Lv, J.N., Shi, Y.G., 1995. Quasi-biennial oscillation of wet season precipitation in the upper and middle reaches of the Yangtze River. J. Nanjing Inst. Meteorol. 18, 229 233 (in Chinese). Wu, G.X., Chou, J.F., Liu, Y.M., et al., 2002. Dynamics of the formation and variation of subtropical anticyclones. Science Press, Beijing, pp. 1 20 (in Chinese). Xiong, A.Y., 2001. Analysis on background of climatic variation for extremely rainfall over the middle reach of the Yangtze River in 1990s. J. Appl. Meteorol. Sci. 12, 113 117 (in Chinese). Xu, H.M., He, J.H., Zhou, B., 2001. The features of atmospheric circulation during Meiyu onset and possible mechanism for westward extension and northward shift of the Pacific subtropical high. J. Appl. Meteorol. Sci. 12, 150 158 (in Chinese). Xue, Y., Smith, T.M., Reynolds, R.W., 2003. Interdecadal changes of 30-yr SST normals during 1871-2000. J. Clim. 16, 1601 1612. Yang, Q.M., 2006. Interdecadal variations of connection between the principal quasi-biennial oscillation pattern of rainfall in China and 500-hPa atmospheric circulation. Chin. J. Atmos. Sci. 30, 131 145 (in Chinese).

FURTHER READING

113

Yasunari, T., 1990. Impact of Indian monsoon on the coupled atmosphere- ocean system in the tropical Pacific. Meteorol. Atmos. Phys. 44, 29 41. Zhao, P., Zhu, Y.N., Zhang, R.H., 2007. An Asian-Pacific teleconnection in summer tropospheric temperature and associated Asian climate variability. Clim. Dyn. 29, 293 303.

FURTHER READING Zheng, B., Gu, D.J., Li, C.H., 2006. Differences of South China sea summer monsoon derived from NCEP and ECMWF reanalysis data. J. Trop. Meteorol. 22, 217 222 (in Chinese).