SOLA, 2015, Vol. 11, 80−84, doi:10.2151/sola.2015-020

80Impact of Tropical Disturbance on the Indian Summer Monsoon Onset Simulated
by a Global Cloud-System-Resolving Model
Yoshiyuki Kajikawa1, Tsuyoshi Yamaura1, Hirofumi Tomita1, 2, and Masaki Satoh2, 3
1
RIKEN Advanced Institute for Computational Science, Kobe, Japan
2
Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
3
Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan

Abstract
The onset of the Indian summer monsoon (ISM) in 2012 wasinvestigated using the nonhydrostatic icosahedral atmosphericmodel (NICAM), a global cloud-system resolving model. We
focused on the effect of tropical disturbances on ISM onset andconsidered the potential extension of onset predictability. A seriesof NICAM experiments was performed under various initial conditions for the period 10 May to 10 June, 2012. NICAM showedpromising performance by realistically simulating ISM onset
based on the initial conditions two weeks before the onset. ISM
onset in both observations and simulations was accompanied bynorthward-migrating tropical disturbances over the Bay of Bengal
and the Arabian Sea. These disturbances were generated by theeastward propagating disturbance along the equatorial Indian
Ocean. As indicated by a comparison of NICAM experimental
results with those obtained by the Japan Meteorological Agency
Operational Ensemble Prediction System, we suggest that thebetter reproducing the tropical disturbance enhances the potential
to extend the predictability of the transition phase in the Asiansummer monsoon.
(Citation: Kajikawa, Y., T. Yamaura, H. Tomita, and M. Satoh,
2015: Impact of tropical disturbance on the Indian summer monsoon onset simulated by a global cloud-system-resolving model.
SOLA, 11, 80−84, doi:10.2151/sola.2015-020.)

1. Introduction
The onset of the Indian summer monsoon (ISM) signifies thecommencement of the rainy season in south-southeastern Asia,with an abrupt change in large-scale atmospheric circulations(Joseph et al. 1994; Joseph et al. 2006). The interannual variability
in the timing of ISM onset has marked effects on agricultural andeconomic practices in India and the broad Asian monsoon area
(Gadgil and Rupa Kumar 2006). This interannual variability of theonset is not always correlated with that of the seasonal meanmonsoon strength during boreal summer (Moron and Robertson2014). For instance, ISM onset was two weeks earlier in 1989
than in 2003, despite similar seasonal mean ISM strengths for thetwo years (Subrahmanyam et al. 2013).
The variability in seasonal mean monsoon strength has been
understood as a boundary value problem, e.g. the impact of sea
surface temperature (SST) anomalies associated with the El Niño−
Southern Oscillation (Kirtman and Shukla 2000). In contrast,
as part of the seasonal transition, monsoon onset is reported as
a complex event that involves a combination of several effects:
increased thermal contrast between land and ocean, increased
convective instability, and the arrival of tropical disturbances (e.g.,
Madden Julian oscillation (MJO), tropical cyclones, and tropicaldepressions) (Hung and Yanai 2004). Thus, the onset of monsoon
conditions can be markedly affected not only by the boundary
conditions but also by internal variability, such as tropical disturbances. In fact, ISM onset evolution is often associated with theCorresponding author: Yoshiyuki Kajikawa, RIKEN Advanced Institutefor Computational Science, Kobe, 650-0047, Japan. Email: ykaji@riken.
jp. ©2015, the Meteorological Society of Japan.

first arrival of northward-propagating intraseasonal variability(ISV). Therefore, the arrival of the tropical disturbance may be themore dominant effect in ISM initiation.
Recently, the global climate modeling has been advanced forthe better simulation of Asian summer monsoon in many aspects;
climatological seasonal mean, annual cycle, interannual variability
and intraseasonal variability (Sperber et al. 2013). However, using
the global model to predict the timing of ISM onset remains achallenging issue (Li and Zhang 2009). In general, ISM onset inglobal model simulations is much later than its actual occurrence(Sperber et al. 2013). Thus, the conditions for ISM initiation mustbe identified to improve the predictability and reproducibility oftropical disturbances in model simulations.
In this study, we investigated the conditions for ISM onset in2012 as a normal year, using the nonhydrostatic icosahedral atmospheric model (NICAM), a global cloud-system model without
convective parameterization, and considered potential extensionof ISM onset predictability. This model is able to simulate tropical disturbances better, in particular, the MJO (Miyakawa et al.
2014). NICAM simulations were compared with other operationalmodels to identify the precursor signals for ISM onset, which was
resolved in NICAM simulations.
This paper is organized as follows. In Section 2, datasets arepresented along with a description of the model and our experimental design. NICAM simulation results are examined and compared with observational data in Section 3. The proposed model isthen compared with conventional models in Section 4, followedby concluding remarks.

2. Models and datasets
This study used wind field data from the Japan 25-year Reanalysis (JRA-25)/Japan Meteorological Agency (JMA) Climate
Data Assimilation System (JCDAS) reanalysis (Onogi et al. 2007)
and daily mean-interpolated outgoing longwave radiation (OLR)
data from a National Oceanic and Atmospheric Association(NOAA) satellite (Liebmann and Smith 1996), as the observational dataset. A global cloud-system resolving model based on
NICAM (grid spacing: 14 km; vertical levels: 38) was used for
ISM onset simulations. NICAM was developed by (Satoh et al.
2008; Tomita and Satoh 2004); an overview of NICAM researchand the current status of development are described in (Satohet al. 2014). Previous studies have demonstrated the superior
performance of NICAM in its ability to predict tropical disturbances, such as tropical cyclones (Fudeyasu et al. 2008; Nakano
et al. 2015; Yamaura et al. 2013) and MJO (Miura et al. 2007;
Miyakawa et al. 2014), as opposed to conventional general circulation models (GCMs). Thus, the proposed model presented inthis study is expected to improve the predictability of ISM onset,
particularly with tropical disturbance origins. Note that cumulus
parameterization was not considered in this study (see (Holloway
et al. 2013) and cloud processes were explicitly calculated using
cloud microphysics.
To capture ISM onset and examine its sensitivity to the initialconditions, a series of experiments with different initial conditions
was performed. The simulation started at 00 UTC each day during
the period examined, from 10 May, 2012 to 10 June, 2012. The
earliest initial date was more than three weeks prior to the ISM

Kajikawa et al., ISM Onset Simulated by NICAM
onset in 2012. Time integration was performed for 30 days in eachsimulation. The initial atmospheric conditions were based on JMA
grid point value (GPV) analysis data from a global spectral model.
The initial oceanic conditions were based on a dataset finalized by
the National Centers for Environmental Prediction. We preparedlong-term spin-up data, using low-resolution NICAM (the equivalent of a 224-km mesh) and applied these data to initial land
conditions. The nudged SST and weekly NOAA SST (Reynolds
et al. 2002) were used for time-varying boundary conditions.
To evaluate the performance of the NICAM simulations, we
also used the one-month forecast of the JMA Ensemble Prediction
System (EPS). The initial conditions of the JMA EPS are shiftedby 7 days. The global model for predictions has a horizontal grid
spacing of 0.5625 deg (TL319; equivalent to 60 km) and 60 vertical levels. Each global analysis output consists of 25 ensemble
members with perturbations. We recall the cases of 17 May and 23
May as they relate to ISM onset in 2012 and compare these datawith NICAM simulations.

3. Observation and simulation of ISM onset
The announcement of ISM onset in 2012 over Kerala by the
Indian Institute of Tropical Meteorology occurred on 5 June. Because this date is close to the climatological mean ISM onset dateof 1 June, we considered the ISM onset of 2012 to be a normal
event in terms of annual occurrence. In this study, we used the
ISM index defined by (Wang et al. 2001), the meridional shear of
the zonal wind at 850 hPa over the Indian continent (40°E−80°E,
5°N−15°N minus 70°E−90°E, 20°N−30°N). Figure 1 shows thetime series of ISM index observations and NICAM simulations.
The observational ISM index (thick red line) turned positive, indicating westerly wind shear, from 24 May to 1 June. This signified
ISM onset of large-scale circulation in 2012. This change in thewind circulation brought about an increase in precipitation overthe Indian sub-continent and the commencement of the rainyseason. It is noteworthy that the NICAM simulations initialized
in mid-May show an abrupt onset of the monsoon, quite similar
to observations. Because the simulations initialized before 14
May had a less abrupt change in wind circulation during lateMay, we assumed that the initial conditions after 15 May would

Fig. 1. (Top) Time‒integrated time (day) diagram of the Indian summer
monsoon (ISM) indices. Top and bottom shading denote the observational
ISM index. Each simulated ISM index goes upper right. (Bottom) Time
series of the ISM indices for each run (black), averaging five members withinitial conditions covering 15−19 May (blue) and actual observations (red).

81

be sufficient for more realistic ISM onset simulations. The initialconditions of five ensemble members corresponding to 15−19
May 2012 were used for analyses in this study. The lead time for
abrupt ISM onset prediction was approximately two weeks.
The ISM index of the NICAM simulations reached nearlyzero in the middle of June, exhibiting tendencies that drifted fromobservational features. Although this behavior was the result ofnorthward-shifted of the monsoon westerly axis, we confirmedthat the simulated ISM became established after monsoon theonset in early June, with increasing rainfall over the Indian
sub-continent. In addition, NICAM simulations have had difficulty
in providing an accurate representation of the western North Pacific monsoon (WNPM). In fact, the WNPM index defined by (Wanget al. 2001) strays from that observed after 4−5 days integration
during late May and early June (Figure not shown). The lead time
for the prediction is also much less than that of ISM onset; this isdue to relatively weak convection over the western North Pacificarea compared with observations, similar to previous NICAM
simulations (Oouchi et al. 2009).
Figures 2 and 3 show the evolution of ISM onset in observations and NICAM simulations, averaging five runs with different
initial conditions over the period from 15−19 May, 2012. In theobservations, the enhanced convection located over the southeastern Indian Ocean on 21 May is thought to be eastward propagating convection system from the western Indian Ocean. The
Boreal Summer Intraseasonal Oscillation (BSISO) index (Kikuchi
et al. 2012) indicates that the convection was associated with theintraseasonal variability over the India and Maritime continent.
From 23 May through 27 May, twin cyclonic circulations formed
along the 90°E gridline in the northern and southern hemispheres,and the westerly wind along the equator strengthened. From 23
May to 31 May, convection with a positive vortex over the Bay of
Bengal increased in strength and moved northward. This induced

Fig. 2. Outgoing longwave radiation (OLR) [W m−2] and 850-hPa windcirculation field [m s−1] from (a) 21 May, 2012 to (f) 31 May, 2012 during
ISM onset process in observations.

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SOLA, 2015, Vol. 11, 80−84, doi:10.2151/sola.2015-020

Fig. 3. Same as Fig. 2 except for the NICAM simulations averaging fiveruns with different initial conditions from 15−19 May.

Fig. 5. (Top) OLR [W m−2] and 850-hPa wind [m s−1] averaging 85°E−
95°E in observations. (Middle) OLR of NICAM simulations averaging
five runs with different initial conditions from 15−19 May (shading), withobservational OLR (contour) superimposed. (Bottom) Same as the Middle,
but averaging five runs with different initial conditions from 10−14 May.

low-level convergence along the Western Ghats with westerly
flow over the Indian sub-continent. This convection, accompaniedby the tropical disturbances over the Bay of Bengal, most likely
triggered ISM onset in 2012.
Figure 3 shows NICAM simulation data similar to thoseshown in Fig. 2. Although strong convection was prominent over
the South China Sea by 27 May in the simulations, which differedfrom observational findings, the five-member ensemble simulation
results show symmetric convection of two cyclonic circulations
over the northern and southern hemispheres along the 90°E gridline on 21 May. The convection with cyclonic circulation overthe southern hemisphere in the simulations became weaker thanthat observed; however, the tropical disturbance over the Bay of
Bengal moved northward and ISM onset occurred in early June.
The NICAM simulations of the tropical disturbances were in good

agreement with observations, including ISM onset prediction,with a lead time of approximately two weeks.
On the other hand, it should be noted that the developmentof convection in northern and southern hemisphere is different
between NICAM simulations and observations. More developed
convection over the northern convection and less developed overthe southern convection in the simulations modified the monsoon
westerly over the Bay of Bengal. As a result, the meridional shearof zonal wind (ISM index) became weak. This corresponds tosmall value of ISM index in the middle of June after the onset(Fig. 1).
To highlight the effect of being able to reproduce the tropicaldisturbances accurately in ISM onset simulations, Figs. 4 and 5
show a Hovmoller diagram of the OLR along the equator and
80°E in observation and two different ensemble composites: one

Fig. 4. (Left) OLR [W m−2] and 850-hPa wind[m s−1] averaging 5°S−5°N in observations.
(Middle) OLR of NICAM simulations averaging five runs with different initial conditions
from 15−19 May (shading), with observational
OLR (contour) superimposed. (Right) Sameas the Middle, but averaging five runs withdifferent initial conditions from 10−14 May.

Kajikawa et al., ISM Onset Simulated by NICAM
that corresponds to the average of the simulations initialized from
15 May to 19 May as the most realistic ISM onset simulation, andthe other as the average from 10 May to 14 May. Note that thelatter ensemble composite fails to capture the actual ISM onset
process (Fig. 1). In the observations, over the period from 18−26
May the active convection moved significantly eastward, from
70°E to 120°E. The former ensemble composite captured theeastward-propagating convection, although the convection over
the western Pacific was much weaker, whereas the latter did notshow a clear signal over the Indian Ocean corresponding to the
21 May data, and eastward-moving convection was not detected.
After the eastward-propagating convection reached the eastern
Indian Ocean, the northward moving convection was formed in
the observations and former ensemble composite. That convection
was not reproduced in the latter ensemble due to the failure of theeastward propagating convection. Hence, the ability to reproduce
the tropical disturbance over the equatorial Indian Ocean and the
Bay of Bengal was strongly correlated with ISM onset behavior insimulations.

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4. Comparison with the JMA ensemble prediction
systemHere, we compared the NICAM simulations with the JMA
EPS forecast to evaluate the performance. Figure 6 shows timeseries of the ensemble mean ISM indices of the JMA EPS initialized at 17 May and 23 May. The ensemble mean starting on
17 May fails to capture the abrupt ISM onset, showing instead a
gradual increase in the ISM index. This signifies that the axis of
the westerly monsoon gradually moved northward. The simulations starting on 23 May capture the abrupt ISM onset well, in
addition to the northward moving tropical disturbances over the
Bay of Bengal (figure not shown). The difference between the two
results should be evident in the signal corresponding to the initialconditions, deemed to be the seed of the eastward-propagating
tropical disturbance.
Figure 7 shows the observational conditions on 17 May and
23 May and the ensemble simulation results starting on 17 May
from the JMA EPS. A vertical velocity at 500 hPa was assumed
as an alternative for OLR in the JMA EPS results (Figs. 7c, d, e).
The difference in the observational evidence between 17 May and
23 May shows the robustness of the convection over the Indian
Ocean. The convection associated with the eastward-propagating
tropical disturbance over the western Indian Ocean was still
weaker on 17 May. The JMA EPS results from 17 May show
relatively weak convection (upward motion) over the equatorial
Indian Ocean during late May, followed by gradual movement
northward, which contributed to westerly flow over the Indian
sub-continent later than that observed. In contrast, based on the 17
May data, NICAM simulated the eastward-propagating convection along the equatorial Indian Ocean and reproduced the tropicaldisturbance that induced ISM onset in early June (Fig. 3).

5. Concluding remarks and discussion

Fig. 6. Time series of the ISM index in the operational ensemble prediction system extended-range forecasting of JMA with initial data from 17
May (Top) and 23 May (Bottom).

The onset of ISM signifies the commencement of the rainyseason in south-southeastern Asia, with an abrupt change in largescale atmospheric circulations. Although the interannual variability in the timing of ISM onset strongly affects the broad Asianmonsoon area, the ability to predict monsoon onset accurately
remains a challenge owing to the short lead time. In this study, weinvestigated the onset processes of ISM in 2012 and discussed theFig. 7. OLR [W m−2] and 850-hPa wind field[m s−1] in observations for (a) 17 May and (b)23 May. Vertical wind speed at 500-hPa and
850-hPa wind fields of the ensemble simulation of JMA EPS on (c) 20 May, (d) 23 May,and (e) 26 May, initialized on 17 May.

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potential of extended forecasting by using a global cloud-system
resolving model, which has the advantage of more accurate simulation of tropical disturbances.
In 2012, ISM onset was announced on 5 June. A series of
NICAM experiments with 14-km horizontal resolution was
performed with various initial conditions. NICAM demonstrated
excellent performance in providing a realistic simulation of abrupt
ISM onset, with northward-migrating tropical disturbances overthe Bay of Bengal and the Arabian Sea during late May. The
earliest initial date for accurate ISM onset simulations using
NICAM was 15 May, whereas the JMA operational EPS (1-month
duration) did not capture the abrupt ISM onset given the initialconditions of 17 May. In a comparison with JMA EPS, the better
reproducibility of the tropical disturbances seen with the NICAMbased model extended the predictability of the transition phase for
the Asian summer monsoon. When the model failed to reproduce
the eastward-propagating tropical disturbance along the equatorial
Indian Ocean, the simulated ISM did not have an abrupt onset but
instead developed gradually in both the NICAM and JMA EPS
simulations.
The development of tropical disturbances over the central
Indian Ocean and Bay of Bengal was a key phenomenon for better
simulation of ISM onset in 2012. This tropical disturbance overthe Bay of Bengal was accompanied by the eastward-propagating
convections. Thus, better reproduction of the tropical disturbanceover the Indian Ocean in models should enhance their potential
to extend the predictability of the transition phase for the Asiansummer monsoon. Less accurate reproducibility of the tropicaldisturbances in simulations may result in gradual northward
movement of the monsoon westerly winds, and hence a delay in
ISM onset compared with observations. Thus, these results provide insight into improving the predictability of monsoon onset
using the global model (Sperber et al. 2013). We suggest that
global cloud-system resolving models without convective parameterization have potential to better simulation of ISM, as similar
result to the MJO simulations (Holloway et al. 2013)
The underlying triggering mechanism and the interaction
between tropical disturbances and large-scale monsoon onset are
still under discussion. NICAM was used as an atmosphere-only
GCM in this study; however, air‒sea interactions may provide additional information on ISM onset with the tropical disturbances.
Questions remain regarding the physical mechanisms of this inter­action. Additionally, WNPM onset is difficult to simulate morethan 1 week in advance. Climatologically, WNPM onset is two
weeks earlier than that of ISM. Failure to simulate WNPM onset
realistically may limit extension of ISM onset predictability. Thus,
the relationship between ISM and WNPM is an interesting topic
for future work.

Acknowledgements
The authors are grateful to Dr. Masato Sugi, the editor of the
SOLA, and anonymous reviewers for their useful comments.
Special thanks are due to Prof. Bin Wang in IPRC, University of
Hawaii for lots of useful comments. This work is supported by
RIKEN Incentive Research Projects 2014 and MEXT Strategic
Programs for Innovative Research (SPIRE). This work also has
been done by using the K computer at the RIKEN AICS (Proposal
number hp120313).

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Manuscript received 28 February 2015, accepted 10 May 2015
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