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Reply to ‘‘Comments on ‘Interdecadal Change of the South China Sea Summer
Monsoon Onset’’’*BIN WANG
Department of Atmospheric Sciences and Atmosphere–Ocean Research Center, University of Hawai‘i at Manoa,Honolulu, Hawaii

YOSHIYUKI KAJIKAWA
RIKEN Advanced Institute for Computational Science, Kobe, Japan(Manuscript received 8 March 2015, in final form 27 August 2015)

Understanding the variability and change of monsoon
onset is of the utmost importance for agriculture planning and water management. The sudden onset of theSouth China Sea summer monsoon (SCSSM) is one ofthe most spectacular phenomena and has a profoundsocietal impact.
Kajikawa and Wang (2012, hereinafter KW12)
detected a significant change in the mean onset date of
the SCSSM around 1993/94: the epochal mean onset
date is 30 May for 1979–93 and 14 May for 1994–2008, so
the onset date in the post-1994 epoch has advanced by
16 days. Chen (2015, hereinafter C15) has carefully
checked the KW12 finding by using a different reanalysis dataset and extending the analysis period from
1979–2008 to 1979–2012. The result of C15 confirms that
the KW12 finding is robust even during the extended
period after 2008. We appreciate this contribution
from C15.
The fundamental science issue here is why the SCSSM
onset date advanced remarkably after 1993/94. The
comment of C15 states in its abstract that Kajikawa andWang (2012) ‘‘attributed this [onset] change to enhanced tropical cyclone (TC) activity and intraseasonalvariability (ISV) related to 30–80-day and 10–25-day
anomalies in the second epoch.’’ This misleading* Earth System Modelling Center Publication No. 063.

Corresponding author address: Yoshiyuki Kajikawa, RIKENAdvanced Institute for Computational Science, 7-1-26
Minatojima-minami-machi, Chuo-ku, Kobe, 650-0047, Japan.
E-mail: ykaji@riken.jp
DOI: 10.1175/JCLI-D-15-0173.1
Ó 2015 American Meteorological Society

statement motivated C15 to assess the individual impactof TCs and ISV on the change of the SCSSM onset. We
would like to start our reply by correcting C15’s misunderstanding of the work of KW12.
The fact is that KW12 attributed the root cause of theinterdecadal change of the SCSSM onset to decadalchanges in the lower boundary anomalies. They pointedout in their abstract that ‘‘the advanced SCSSM onset isrooted in the decadal change of the SST over theequatorial western Pacific.’’ KW12 further indicatedthat ‘‘the advanced onset during the second epoch is affected by the enhanced activity of northwestward-moving
tropical disturbances from the equatorial western Pacific’’ (italics added for emphasis). Here they highlighted
the processes by which the western Pacific SST anomalies may cause the interdecadal change in theSCSSM onset. C15 missed these points.
The major work of C15 is to assess the individualimpacts of the TCs and ISV on the SCSSM onset. For
that purpose, C15 applied bandpass filters to the SCSSM
circulation index in an attempt to remove anomalies
associated with TCs and ISV. The SCSSM circulationindex (hereafter SCS index for brevity) is measured by
the 850-hPa zonal wind averaged over the central South
China Sea (58–158N, 1108–1208E). This index is a key
variable that was used to determine the SCSSM onset
date. C15 showed that the SCSSM onset dates were notaffected by removing the TCs and the 10–25-day ISV
component, but were significantly affected by the removal of the 30–80-day ISV (Fig. 1 of C15). Thus, C15claimed, ‘‘TCs have no significant impact on the SCSSM
onset in all years, except 2006,’’ ‘‘the 10–25-day anomaly has an insignificant contribution to the interdecadal15 NOVEMBER 2015

CORRESPONDENCE

shift of the SCSSM onset,’’ ‘‘the 30–80-day anomaly can, in part, play a role in the interdecadal shiftof the SCSSM onset.’’ These are the main results ofC15’s comment.
C15’s comments partially confirm the importance ofthe 30–80-day ISV; however, unfortunately, these results do not reveal new facts. Why? Let us look at how
the SCSSM onset date is defined. Defining the SCSSM
onset date in an individual year involves three criteria(Wang et al. 2004), which C15 followed: 1) on the onset
day and during the subsequent 5 days, the SCSSM index
must be positive (turning from easterly to westerly),2) the number of days with a positive index during thesubsequent 20 days reaches at least 15; and 3) the 20-day
mean index after the onset day must be larger than
1 m s21. Criteria 2 and 3 ensure that the onset daterepresents a ‘‘persistent’’ wind regime transition fromthe preonset easterly to the postonset westerly without
being affected by high-frequency weather fluctuations.
Therefore, the effects of the individual TCs and the 10–
25-day ISV are already ‘‘smoothed out’’ by the two
20-day averaged criteria in the determination of theonset dates. As such, it is fully expected that the linear
removal of high-frequency TCs and 10–25-day anomalies again will have minimal impact on the determinationof the onset data. Therefore, the results shown in Figs. 1aand 1b of C15 are trivial, as are the conclusions regarding the roles of the individual TCs and 10–25-day
anomaly in SCSSM onset change.
The results of Fig. 3 in C15 repeated that the TCs and
10–25-day components have little effects while the 30–
80-day ISV has significant effects on the composite onset
dates, which is again trivial. Note that these composite
diagrams were made with respect to two different epochmean onset dates; therefore, they are irrelevant to anexplanation of the interdecadal change of the mean onset. In fact, the composite amplitudes of the 30–80-day
ISV are nearly the same for the two epochs; as such, the30–80-day ISV could not account for the interdecadalchange of the onset date. KW12, on the other hand, tiedthe early onset in the second epoch to enhanced ISV
activity compared to the first epoch. They stated in theirabstract that ‘‘during 1994–2008, the intraseasonal variability (ISV) over the western Pacific was enhanced
during the period from mid-April to mid-May’’ (italics
added for emphasis). It is the enhancement of the ISV
active phase in a specific period prior to the seasonaltransition (from mid-April to mid-May) that contributed
to the advanced SCSSM onset in the second epoch.
We believe that the roles of ISV, TCs, and the biweekly anomaly should not be assessed separately
using linear decomposition because they are highlyinteractive. We consider that the 30–80-day ISV and9037

the associated high-frequency disturbances together
contribute to the change in the SCSSM onset (see also
Zhou and Chan 2005). Our results, shown in Fig. 1
herein, indicate that there would be no significant interdecadal change of SCSSM onset date provided alltransient anomalies with a period less than 80 days
were removed. As can be seen from Fig. 1, after the80-day low-pass filter is applied, the SCSSM mean onset date during 1979–93 becomes earlier whereas themean onset date during 1994–2008 becomes later. As aresult, the difference in the SCSSM onset date between
the two epochs is substantially shortened from 16 days
to 6 days. Therefore, without the synoptic to 30–80-day
variability the interdecadal change of SCSSM onset
date between the two epochs is no longer statisticallysignificant even at the 90% of confident level by aStudent’s t test. The result in Fig. 1 demonstrates that
the ISV and associated higher-frequency disturbances
together contribute to the interdecadal change of theSCSSM onset.
C15’s results deny the roles of individual TCs and 10–
25-day anomaly based on a linear decomposition analysis. We would like to point out that the intrinsic interplay between the 30–80-day ISV and the embedded
high-frequency disturbances are essentially nonlinear,and so analysis of individually filtered indices (i.e., remove 30–80-day ISV and TC separately) cannot adequately assess the nonlinear effects. This point is further
elaborated in the following two paragraphs.
The TCs and 10–25-day anomaly in the western Pacific do not occur independently; rather they are embedded in and regulated by the 30–80-day ISV. It is wellknown that the westward moving 2-day cloud clusters,
3–10-day northwestward propagating disturbances, andwestward propagating quasi-biweekly disturbances areall often embedded in and regulated by the 30–80-day
ISV (Nakazawa 1988; Murakami 1980; Lau and Lau
1990; Straub and Kiladis 2003; Kikuchi and Takayabu
2004; Moncrieff 2004; Wang et al. 2006; Biello et al.
2007; Kikuchi and Wang 2009; Wang et al. 2009). The
SCSSM onset is also often accompanied by the ISV withembedded synoptic disturbances. For instance, during
the second epoch, TCs were generated with the arrivalof active phases of ISV during the SCSSM onset periods
in 1996 (TC#199603 Bart), 2000 (TC#200001 Damrey),
2002 (TC#200203 Hagibis), 2004 (TC#200403 Omaiss),and 2008 (TC#200802 Rammasun).
It is stressed that the ISV and the embedded higherfrequency disturbances consist of an integrated two-way
interactive system. It has been shown that synoptic
eddies can extract (transfer) kinetic energy from the ISV
during the ISV active (suppressed) phase throughbarotropic energy conversion (Sobel and Maloney 2000;

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FIG. 1. Time series of the SCSSM onset date based on the original SCSSM index (closed circle with solid line) in KW12 and the low-passfiltered SCSSM index (open circle with dashed line). The blue (red) line denotes the mean onset date during the period of 1979–93 (1994–2008). The low-pass filtered SCSSM index is reconstructed by applying a 80-day low-pass Lanczos filter (Duchon 1979) with 121 weights.
The definition of SCSSM onset date with the low-pass filtered data is the same as that with the original index except that the ‘‘persistentseasonal transition’’ criterion (the cumulative 20-day mean SCSSM index must be greater than 1 m s21) is removed because the low-passfiltered data already assure the persistent seasonal transition.

Maloney and Hartmann 2001; Maloney and Dickinson
2003; Zhou and Li 2010; Hsu et al. 2011). On the otherhand, the high-frequency disturbances embedded in theISV can strongly feed back to the ISV (Krishnamurtiet al. 2003; Hsu and Li 2011; Hsu et al. 2011). In addition,
numerical experiments with AGCMs have shown thatthe existence of high-frequency weather perturbationsin the initial conditions can generally extend the ISV
prediction skill by about 5 days compared to those inwhich the high-frequency disturbances are filtered out(Fu et al. 2009).
In summary, during the post-1994 epoch the processthat contributed to the early onset of the SCSSM is theenhanced ISV and the embedded synoptic-biweekly
activity in a specific period prior to the seasonal transition (from mid-April to mid-May). However, thefundamental cause of the interdecadal changes in theISV and transient activity is rooted in the SST changes
in the western Pacific (KW12). While KW12 has tiedthe change of SCSSM onset to the SST changes, itremains a challenging issue to elucidate how the SST
anomalies-induced mean state change affected theISV and tropical disturbances in the late spring of thepost-1994 epoch. The numerical experiments with acoupled climate model made by Xiang and Wang (2013)
demonstrate that, indeed, the advanced SCSSM onset isprimarily determined by the abrupt SST warming near
the Philippine Sea after the mid-1990s. They also foundthat the SST anomalies affected the monsoon onset
through westward propagation of Rossby waves (themodel counterparts of TCs, 3–10-day and biweekly
anomalies) and their interaction with the spring asymmetric background states, which intensifies the Northern
Hemispheric perturbations and westerly winds in May.
Further numerical experiments and diagnostic studies
are requested to deepen our dynamical understandingof the causes of the Asian summer monsoon onsetvariability.
Acknowledgments. The authors are grateful to Dr. John
Chiang, the editor of the Journal of Climate, and the associate editor for their useful comments. This work is
supported by the Atmosphere–Ocean Research Center at
the University of Hawai’i at Manoa funded by Nanjing
University of Information Science and Technology andRIKEN Incentive Research Projects 2014.

15 NOVEMBER 2015

CORRESPONDENCEREFERENCES

Biello, J. A., A. J. Majda, and M. W. Moncrieff, 2007: Meridional
momentum flux and superrotation in the multiscale IPESD
MJO model. J. Atmos. Sci., 64, 1636–1651, doi:10.1175/
JAS3908.1.
Chen, G., 2015: Comments on ‘‘Interdecadal change of the South
China Sea summer monsoon onset.’’ J. Climate, 28, 9029–9035,
doi:10.1175/JCLI-D-14-00732.1.
Duchon, C. E., 1979: Lanczos filtering in one and two dimensions. J. Appl. Meteor., 18, 1016–1022, doi:10.1175/
1520-0450(1979)018,1016:LFIOAT.2.0.CO;2.
Fu, X., B. Wang, Q. Bao, P. Liu, and J.-Y. Lee, 2009: Impacts ofinitial conditions on monsoon intraseasonal forecasting. Geophys. Res. Lett., 36, L08801, doi:10.1029/2009GL037166.
Hsu, P.-C., and T. Li, 2011: Interactions between boreal summer
intraseasonal oscillations and synoptic-scale disturbances over
the western North Pacific. Part II: Apparent heat and moisturesources and eddy momentum transport. J. Climate, 24, 942–
961, doi:10.1175/2010JCLI3834.1.
——, ——, and C. H. Tsou, 2011: Interactions between boreal
summer intraseasonal oscillations and synoptic-scale disturbances over the western North Pacific. Part I: Energetics diagnosis. J. Climate, 24, 927–941, doi:10.1175/
2010JCLI3833.1.
Kajikawa, Y., and B. Wang, 2012: Interdecadal change of the South
China Sea summer monsoon onset. J. Climate, 25, 3207–3218,
doi:10.1175/JCLI-D-11-00207.1.
Kikuchi, K., and Y. N. Takayabu, 2004: The development of organized convection associated with the MJO during TOGACOARE IOP: Trimodal characteristics. Geophys. Res. Lett.,
31, L10101, doi:10.1029/2004GL019601.
——, and B. Wang, 2009: Global perspective of the quasi-biweekly
oscillation. J. Climate, 22, 1340–1359, doi:10.1175/
2008JCLI2368.1.
Krishnamurti, T. N., D. R. Chakraborty, N. Cubukcu, L. Stefanova,and T. S. V. Vijaya Kumar, 2003: A mechanism of theMadden–Julian oscillation based on interactions in the frequency domain. Quart. J. Roy. Meteor. Soc., 129, 2559–2590,
doi:10.1256/qj.02.151.
Lau, K.-H., and N.-C. Lau, 1990: Observed structure and propagation characteristics of tropical summertime synoptic scaledisturbances. Mon. Wea. Rev., 118, 1888–1913, doi:10.1175/1520-0493(1990)118,1888:OSAPCO.2.0.CO;2.
Maloney, E. D., and D. L. Hartmann, 2001: The Madden–
Julian oscillation, barotropic dynamics, and North Pacific9039

tropical cyclone formation. Part I: Observations. J. Atmos.
Sci., 58, 2545–2558, doi:10.1175/1520-0469(2001)058,2545:
TMJOBD.2.0.CO;2.
——, and M. J. Dickinson, 2003: The intraseasonal oscillation andthe energetics of summertime tropical western North Pacificsynoptic-scale disturbances. J. Atmos. Sci., 60, 2153–2168,
doi:10.1175/1520-0469(2003)060,2153:TIOATE.2.0.CO;2.
Moncrieff, M. W., 2004: Analytic representation of the large-scaleorganization of tropical convection. J. Atmos. Sci., 61, 1521–1538,
doi:10.1175/1520-0469(2004)061,1521:AROTLO.2.0.CO;2.
Murakami, T., 1980: Empirical orthogonal function-analysis of satelliteobserved outgoing longwave radiation during summer. Mon. Wea.
Rev., 108, 205–222, doi:10.1175/1520-0493(1980)108,0205:
EOFAOS.2.0.CO;2.
Nakazawa, T., 1988: Tropical super clusters within intraseasonalvariations over the western Pacific. J. Meteor. Soc. Japan, 66,823–839.
Sobel, A. H., and E. D. Maloney, 2000: Effect of ENSO and theMJO on western North Pacific tropical cyclones. Geophys.
Res. Lett., 27, 1739–1742, doi:10.1029/1999GL011043.
Straub, K. H., and G. N. Kiladis, 2003: Interactions between theboreal summer intraseasonal oscillation and higher-frequency
tropical wave activity. Mon. Wea. Rev., 131, 945–960,
doi:10.1175/1520-0493(2003)131,0945:IBTBSI.2.0.CO;2.
Wang, B., LinHo, Y. S. Zhang, and M. M. Lu, 2004: Definition ofSouth China Sea monsoon onset and commencement ofthe East Asia summer monsoon. J. Climate, 17, 699–710,doi:10.1175/2932.1.
——, P. Webster, K. Kikuchi, T. Yasunari, and Y. J. Qi, 2006:
Boreal summer quasi-monthly oscillation in the global tropics.
Climate Dyn., 27, 661–675, doi:10.1007/s00382-006-0163-3.
——, F. Huang, Z. W. Wu, J. Yang, X. H. Fu, and K. Kikuchi, 2009:
Multi-scale climate variability of the South China Sea monsoon: A review. Dyn. Atmos. Oceans, 47, 15–37, doi:10.1016/j.dynatmoce.2008.09.004.
Xiang, B., and B. Wang, 2013: Mechanisms for the advanced Asiansummer monsoon onset since the mid-to-late 1990s. J. Climate,26, 1993–2009, doi:10.1175/JCLI-D-12-00445.1.
Zhou, C., and T. Li, 2010: Upscale feedback of tropical synoptic
variability to intraseasonal oscillations through the nonlinear
rectification of the surface latent heat flux. J. Climate, 23,5738–5754, doi:10.1175/2010JCLI3468.1.
Zhou, W., and J. C. L. Chan, 2005: Intraseasonal oscillations andthe South China Sea summer monsoon onset. Int. J. Climatol.,
25, 1585–1609, doi:10.1002/joc.1209.