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DAI Zhi-Xiu. New Metrics of the Tropospheric Biennial Oscillation in the East Asian Summer Monsoon and Its Interdecadal Shift. Atmospheric and Oceanic Science Letters, 2013, 6(6): 440-444  
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New Metrics of the Tropospheric Biennial Oscillation in the East Asian Summer Monsoon and Its Interdecadal Shift
DAI Zhi-Xiu
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institution of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Corresponding author: DAI Zhi-Xiu, jeccytye@gmail.com
Abstract

This study designed a simple index for measuring irregular tropospheric biennial oscillation (TBO) activities, which was used to determine that the TBO in the East Asian Summer Monsoon (EASM), the most important summer precipitation system for China, has strengthened rather than weakened since the late 1970s. The lead/lag correlations between the EASM and tropical Indian-Pacific sea surface temperature (SST) suggest a relationship between interbasin SST and EASM coupling processes and that this alternative correlation pattern is likely related to TBO. Significant correlation occurred only in recent decades, which implies a reinforcement of TBO in the EASM. From records of representative points in the Indian-Pacific, the interdecadal intrinsic SST modes of the areas can be obtained with ensemble empirical mode decomposition owing to its good temporal locality. Statistical results show Indian-Pacific SST interdecadal trends that include out-of-phase and in-phase warming before and after the late 1970s, respectively, which may be responsible for the TBO interdecadal augmentation present since the late 1970s.

Keyword: TBO; interdecadal shift; EASM; Indian-Pacific SST
1 Introduction

Tropospheric biennial oscillation (TBO) has been defined as the tendency for a relatively strong monsoon to be followed by a relatively weak one, and vice versa. In such a system, transitions occur in the season prior to the monsoon and involve coupled land-atmosphere-ocean processes over a large area of the Indo-Pacific region ( Meehl, 1994, 1997; Meehl and Arblaster, 2002). These transitions are affected by many factors such as precipitation, soil moisture, temperature, and snow cover over Asia (e.g., Meehl, 1994). A set of dynamically coupled ocean- atmosphere mechanisms has been previously proposed for the Asia-Pacific tropics to produce a dominant biennial component of interannual variability, i.e. TBO ( Li et al., 2011; Li et al., 2001b). For example, Chang and Li (2000) stated that warm SST anomalies (SSTAs) in July in the equatorial Indian Ocean cause an increase in surface moisture convergence into South Asia, leading to a stronger monsoon. The monsoon heating induces westerly wind anomalies in the Indian Ocean and leads to easterly anomalies over the western and central Pacific, which cool the Indian Ocean and warm the western Pacific through boreal fall primarily through variations in evaporation-wind feedback, the Walker cell, and thermocline depth. The warm western Pacific bringing the surface westerly anomalies over the Indian Ocean produce and persist cold SSTAs through the succeeding seasons, which leads to a weaker Asian monsoon in the following summer, and so on. In short, positive SSTAs that sustain in the Indian (Eastern Pacific) Ocean in the last seasons lead to a strong Asian-Australian summer monsoon that induces cold SSTAs in the following several seasons in approximately the same ocean areas; subsequently, a weaker monsoon occurs in the following summer, which warms the Indian (Eastern Pacific) Ocean. The TBO represents the intuitive result of the cycle ( Trenberth and Hurrell, 1994; Li et al., 2001a; Li et al., 2006).

The Asia-Pacific climate system is characterized by intermittent decadal ?uctuations whereby the TBO during some periods is more pronounced than others ( Meehl and Arblaster, 2011). Many researchers have linked El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole ( Saji et al., 1999) with the biennial variability of monsoon systems ( Meehl et al., 2003, Pillai and Mohankumar, 2009a, b) and have speculated on the relationship between TBO intermittence and Interdecadal Pacific Oscillation ( Meehl et al., 2009; Li et al., 2010; Meehl and Arblaster, 2011; Chen et al., 2013). However, the mechanism causing interdecadal variations of the TBO in the monsoon systems remains vague. One difficulty in exploring TBO interdecadal variations is that measurement of the interannual signal itself is a lengthy process that often produces insufficient data to determine interdecadal trending of the TBO. Some researchers have reported that the stronger relationship between the Asian-Australian Monsoon and ENSO since the mid-1970s would disrupt or modify biennial variability associated with the TBO in the Indo-Pacific region to produce a weakened TBO ( Meehl, 2011). However, Li et al. (2010) reported that the East Asian Summer Monsoon (EASM) and SST in the equatorial central and eastern Pacific show an emerging interannual alternative correlation (Fig. 1), which indicates a biennial cycle related to TBO. No such correlation was detected before the late 1970s; therefore, it is apparent that biennial correlation between the EASM and equatorial Indian-Pacific SST has strengthened since that time. As a result, the TBO may also be strengthening rather than weakening.

Figure 1 Lead/lag correlation coefficients between the East Asian Summer Monsoon index known as EASMILZ, which includes area-averaged seasonally dynamical normalized seasonality (DNS) at 850 hPa within the East Asian monsoon domain (10-40°N, 110-140°E), and the equatorial sea surface temperature (SST) anomalies (5°S-5°N) from September (-1) to April (1) for (a) 1958-2010, (b) 1958-79, and (c) 1980-2010. The thick horizontal line represents July (0), which is the reference month of EASMI. Here, the -1, 0, and 1 in parenthesis indicate previous, current, and following years, respectively. The green (purple) areas represent significantly negative (positive) correlation areas, exceeding the 95% confidence level. This information was obtained from Fig. 6 of Li et al. (2010).

Section 2 describes the datasets and methods used in this study. To clarify the actual TBO trend in the EASM, we designed a TBO index (TBOI) and applied it into the EASM to determine the amount of interdecadal shifting of the TBO, which is discussed in section 3. Ense006Dble empirical mode decomposition based on the relationship between the EASM and Indian-Pacific SST was used to obtain the intrinsic modes of the Indian-Pacific SST that suggest interdecadal discrepancies in the interbasin coupling that occur simultaneously with the TBO activity shift. This process and potential SST modes related to TBO are discussed section 4, and a summary is given in section 5.

2 Data and methods

Two EASM indices were selected for calculating the TBO index ( Wang et al., 2008). The first is an area-averaged seasonally (June-July-August; JJA) dynamical normalized seasonality (DNS) at 850 hPa within the East Asian monsoon domain (10-40°N, 110-140°E) ( Li and Zeng, 2002, 2003, 2005), denoted by EASMILZ. The other represents the difference between the westerly anomalies averaged over (5-15°N, 90-130°E) and those averaged over (22.5-32.5°N, 110-140°E) ( Wang and Fan, 1999), which is denoted by EASMIWF.

The wind dataset of the National Centers for Atmospheric Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis I project was used to calculate the EASMIWF ( Kalnay et al., 1996). The SST dataset was obtained from the 1948-2011 segment of Extended Reconstructed Sea Surface Temperature (ERSST) v3b.

The study adopted EEMD ( Huang and Wu, 2008; Wu and Huang, 2009) rather than traditional decomposition to determine interdecadal signals of SST at particular ocean areas. EEMD is based on empirical mode decomposition (EMD) ( Huang et al., 1998; Huang and Wu, 2008), which is a method that emphasizes the adaptiveness and temporal locality of the data decomposition supporting the physical validity of the decomposed modes. Moreover, this study identified a moving correlation between the EASM index (EASMI) and tropical Indian-Pacific SST to link the interdecadal shift of SST modes to the interdecadal variation of TBO strength.

3 TBO index
3.1 Definition of TBOI

TBO is defined as the tendency for a system to reverse itself from year to year. An increase in these interannual reversals or transitions results in a more biennial system ( Meehl, 1997; Meehl and Arblaster, 2002; Shen and Lau, 1995). Thus, the TBO index (TBOI) is defined as the product of the forward and backward differences of the EASMI. Here, the forward difference is the EASMI of the prior year minus that of the current year, and the backward difference is the EASMI of the following year minus that of the current year.

In practice, predictability should be considered. On the basis of the hypothesis that the interannual TBO activity is quite stable, we can use data from the past three years to model current TBO activity to predict the EASM amplitude for the following summer. The TBOI of the ith year can be modified in the form of the EASM in the ( i-2) th to the ith year as

where the I represents the EASMI time series, and the subscripts are the serial number;

Therefore, the presence of the TBO has a stronger relationship with the difference of EASM and thus relative intensity rather than absolute intensity. If the relative intensities of the EASM are oscillating, such that they show alternating signs during three or more continuous years, the TBO of the EASM is pronounced during the period. If the relative intensities of the EASM maintain specific trends, such that they exhibit the same signs for more than two years, the TBO of the EASM is inexplicit during the period.

As a result, if the signs of relative intensities are arranged in the order of “- + -” or “+ - +”, the TBOI is positive and the TBO is strong; if the signs of relative intensities are arranged in the order of “- - +”, “+ - -”, “- + +”, or “+ + -”, the TBOI is negative and the TBO is weak. A greater TBOI relates to a stronger TBO.

3.2 Application of TBOI

Figure 2 shows the time series of the TBOI and its linear trend in the period. The correlation between the TBOI and the EASMIs are rather insignificant, as indicates that the TBO is independent of the intensity of the EASM. A distinct increase trend of the TBOI is evident from the 1950s to the present despite the definition of EASMI. Specifically, after the 1970s, the TBOI strengthened and remained positive in most years. Moreover, the values of the TBOI are rather independent of those of EASMI.

4 Interdecadal shift potential related to the TBO

Because Indian-Pacific SST is an important component in the TBO-related atmosphere-ocean coupling process, it should be possible for interdecadal shifting of the TBO to be tracked to those of Indian-Pacific SST patterns ( Zheng et al., 2008; Li et al., 2001b). Therefore, interdecadal intrinsic modes of the Indian-Pacific SST may suggest interdecadal shifting.

4.1 Intrinsic interdecadal modes of Indian-Pacific SST

Owing to its good performance on temporal locality, EEMD can be used to determine fairly valid intrinsic modes of a specific area from data of a representative point. The present study uses the data of point of (4°N, 60°E) to show SST variation in the center of the tropical Indian Ocean, which exhibits a basin-scale uniform warming pattern. Similarly, the data of point of (4°N, 100°W) in Niño Region 3 could indicate SST variation in eastern tropical Pacific Ocean. Filtered the high frequency noises, observations of each point here are decomposed into ten modes that represent successively the remainder after one more EEMD oscillatory mode is removed. The higher frequency components, the first to seventh intrinsic modes (IM1-7) (figures not shown) indicate signals of shorter periods, and the eighth ones (IM8) of these points represent local interdecadal signals to some extent (Fig. 3), although the freedom dimension is quite low due to insufficient data of the short time length. The most interesting indication of Fig. 3 is that the IM8 of the Indian Ocean SST and that of the central Pacific Ocean SST were out-of-phase before 1980 and were in-phase after that time. The interdecadal change of the relationship synchronizes the interdecadal augmentation of the TBOI shown in Fig. 2.

Figure 2 1949-2009 time series of the tropospheric biennial oscillation index (TBOI) (real curve) and its linear trend with reference to zero line (dash line) and the correlation coefficient between the TBOI and the corresponding EASMI as for (a) EASMILZ, which includes area-averaged seasonally DNS at 850 hPa within the East Asian monsoon domain (10-40°N, 110-140°E), and (b) EASMIWF, which includes represents the difference between the westerly anomalies averaged over (5-15°N, 90-130°E) and those averaged over (22.5-32.5°N, 110-140°E), respectively. The correlations are both insignificant. The positive slope of the linear trend indicates the increase of the TBOI in the period.

Interdecadal changes in TBOI, which are directly affected by the relationship between forward and backward differences, likely experienced several multidecadal stable phases of various relationships between the interdecadal modes of tropical Indian SST and Pacific SST. The moving correlation between forward and backward differences indicates the correlation of the EASM relative intensities in successive years in a relatively long period within a decade. Significant correlation is apparent between the backward and forward differences in the phases of the 1960s and 1970s and those since the 1990s to the present (figures not shown). Compared with the IM8 time series, the two phases likely correspond to the two stable states in which the IM8 of tropical Indian-Pacific SST is out-of- phase and in-phase, respectively. The 1980s may have been the transition period for the two tropical Indian- Pacific SST coupling regimes. It appears that out-of-phase Indian-Pacific SST relates to a weak EASM TBO, while in-phase warming corresponds to a strong EASM TBO.

4.2 Interdecadal climate shift in the Indo-Pacific region

A moving correlation between the EASMI and global SST (Fig. 4) revealed a significant area of concentration in the tropical area. Figure 4b indicates that no significant correlation between SST and the EASMI was apparent during 1958-79. However, Fig. 4c shows that in the leading half an year for monsoon periods of 1980-2010, par- ticularly in leading winters, a significant El Niño-like negative correlation area persisted in the Pacific and also occurred to a lesser extent in the west Indian Ocean. However, a significant El Niño-Modoki-like positive correlation area persisted in the Pacific Ocean during the lagging winters of these years, and also a lesser degree of significant positive correlation occurred in the east Indian Ocean in the lagging spring seasons. The annual lead/lag correlation emphasizes the significance of the tropical Indian-Pacific SST for the EASM TBO. In the last boreal winter, a sustained negative SST anomaly in the eastern Pacific and western Indian Ocean may have led to a strong EASM. In the following boreal winter, a positive SST anomaly is expected to persist in the center Pacific, which may result in warming of the eastern Indian Ocean in the following season. This positive SST anomaly in May would be able to reactivate the sustained local warming SST pattern to result in an additional half cycle, which is consistent with the ideal TBO model and results reported by Li et al. (2010). Furthermore, the statistical result suggests that the TBO interdecadal augmentation may be associated with the more frequent El Niño-Modoki occurrence ( Karumuri, 2007) and the more important role of Indian Ocean SST. Despite the stronger relationship among ENSO, the Asian-Australian monsoon, and the elongated ENSO life cycle (e.g., Wang et al., 2008), the biennial signal in the Indian-Pacific SST could strengthen due to the stronger association of interbasin SSTs under general warming conditions. As a result, the TBO in the EASM directly affected by the Indian-Pacific SST would naturally strengthen.

Figure 3 Time series of interdecadal seventh intrinsic modes (IM8) of (a) (4°N, 60°E) and (b) (4°N, 100°W) decomposed by the ensemble empirical mode decomposition (EEMD).

5 Summary

The TBO index created in the present study can readily show TBO activities among which a clear TBO augmentation is present after the late 1970s. Before that time, the intrinsic interdecadal modes of the tropical Indian-Pacific SST were out-of-phase, and no significant correlation was detected between the EASM system and tropical SST. After the late 1970s, the interdecadal modes of the tropical Indian-Pacific SST indicated in-phase warming. Moreover, significant alternative correlation was detected between the EASM and tropical central and eastern Pacific Ocean SSTs and between the EASM and tropical Indian Ocean SST. Therefore, the interdecadal shift of the interbasin SST coupling pattern is likely responsible for TBO augmentation occurring since the late 1970s.

Figure 4 Lead/lag correlation coefficients between EASMILZ, an East Asian Summer Monsoon index that includes area-averaged seasonally dynamical normalized seasonality (DNS) at 850 hPa within the East Asian monsoon domain (10-40°N, 110-140°E), and global SST from September (-1) to May (1) for (a) 1958-2010, (b) 1958-79, and (c) 1980-2010. The thick horizontal line indicates the equator, and the dotted-dashes lines bound the tropics. The middle line of July (0) indicates the reference month of EASMILZ. Here, -1, 0, and 1 in parenthesis indicate previous, current, and following years, respectively. The green (purple) areas are significantly negative (positive) correlation areas, exceeding the 95% confidence level.

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