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GEOPHYSICAL RESEARCH LETTERS, VOL. 35, L22808, doi:10.1029/2008GL036003, 2008

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ArticleGlobal cloud-system-resolving model NICAM successfully simulated
the lifecycles of two real tropical cyclones
Hironori Fudeyasu,1 Yuqing Wang,1 Masaki Satoh,2,3 Tomoe Nasuno,3 Hiroaki Miura,3and Wataru Yanase2
Received 12 September 2008; revised 8 October 2008; accepted 17 October 2008; published 25 November 2008.

[1] The increasing capability of high-end computersallows numerical simulations with horizontal resolutions
high enough to resolve cloud systems in a global model. In
this paper, initial results from the global Nonhydrostatic
ICosahedral Atmospheric Model (NICAM) are highlighted
to demonstrate the beginning of a potentially new era forweather and climate predictions with global cloud-systemresolving models. The NICAM simulation with a horizontal
resolution of about 7 km successfully reproduced thelifecycles of two real tropical cyclones that formed in Indian
Ocean in the austral summer 2006. Initialized with theatmospheric conditions 1-2 weeks before the cyclones
genesis, the model captured reasonably not only the timingof the observed cyclone geneses but also their motions
and mesoscale structures. The model provides a hightemporal/spatial resolution dataset for detailed studies ofmesoscale aspects of tropical cyclone genesis. These
promising results suggest the predictability of tropical
cyclones by high-resolution global cloud-system-resolving
models. Citation: Fudeyasu, H., Y. Wang, M. Satoh, T. Nasuno,
H. Miura, and W. Yanase (2008), Global cloud-system-resolving
model NICAM successfully simulated the lifecycles of two real
tropical cyclones, Geophys. Res. Lett., 35, L22808, doi:10.1029/
2008GL036003.

1. Introduction[2] For several decades, cloud-resolving models havegreatly contributed to our understanding of cloud andmesoscale atmospheric processes. These models have been
run so far in limited areas because of their excessive
computational needs. In realistic simulations, the large-scale
control of the cloud and mesoscale processes is either
through lateral boundary conditions or spectral nudging of
the large-scale component in the limited-area model domain[Wang et al., 2004]. One caveat of problem with thisapproach is the implicit assumption that the processes in
the limited-area cloud-resolving model domain do notsignificantly affect the large-scale circulation that drives
the cloud-resolving model. Although two-way nesting canreduce this discrepancy, the best way to avoid the problem
completely is to run cloud-resolving models globally. This
1
International Pacific Research Center, School of Ocean and Earth
Science and Technology, University of Hawai’i at Manoa, Honolulu,
Hawaii, USA.
2
Center for Climate System Research, University of Tokyo, Kashiwa,
Japan.
3
Frontier Research Center for Global Change, Japan Agency for
Marine-Earth Science and Technology, Yokohama, Japan.

Copyright 2008 by the American Geophysical Union.
0094-8276/08/2008GL036003$05.00

is now being made possible by the ever-increasing capability of powerful computers.
[3] The first global cloud-system-resolving model, namely, the Nonhydrostatic ICosahedral Atmospheric Model, orin brief NICAM, has been developed at the Frontier
Research Center for Global Change (FRCGC) on theJapan’s powerful supercomputer, the Earth Simulator[Tomita and Satoh, 2004; Satoh et al., 2008a]. With ahorizontal grid-size of only a few kilometers, the global
NICAM simultaneously models cloud clusters, organizedmesoscale convective systems, and the associated largescale circulations, such as the Madden-Julian Oscillation(MJO). Integrating NICAM once at a horizontal resolutionof about 3.5 km and once at 7 km, Miura et al. [2007]
reported the realistic simulation of an MJO event in the
austral summer 2006. The model reproduced not only thelarge-scale organized cloud systems in the MJO, but also
the lifecycles of multiscale cloud clusters in the convective
phase in the MJO.
[4] The study we present here reports on additional
analyses of the 7-km NICAM run used by Miura et al.
[2007]. Our analyses reveal the first successful simulationof the lifecycles of two real tropical cyclones (TCs) over the
Indian Ocean. We will show that, initialized with theatmospheric conditions 1 – 2 weeks before the cyclones
genesis, NICAM reproduced not only the timing of theobserved TC geneses and their subsequent intensification
but also their motions and mesoscale structures

2. Model, Experimental Design, andObservational Data
[5] NICAM is a global cloud-system-resolving model,
which was documented in detail by Tomita and Satoh[2004] and Satoh et al. [2008a]. The model was run twice,once with a horizontal grid spacing of about 3.5 km andonce with 7 km; there are 40 unevenly distributed verticallevels with the model top at about 38 km in a terrainfollowing height coordinate [Miura et al., 2007]. The
explicit cloud-microphysics scheme of Grabowski [1998]
was used for moist processes without subgrid-scale convective parameterization. The model run at 7-km resolution was
integrated for 32 days, starting at 0000UTC 15 December
2006 and with initial conditions of atmospheric variables
and soil moisture given by the National Centers forEnvironmental Prediction (NCEP) analysis, which has ahorizontal resolution of 1.0° latitude by 1.0° longitude. The
sea surface temperature (SST) was spatially and temporallyinterpolated from the weekly Reynolds SST. Miura et al.
[2007] indicated that the structure and propagation of the
MJO event were well represented in both 3.5-km and 7-km

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L22808Figure 1. Tracks and locations at 0000UTC (green lines and closed circle) from simulated tropical cyclones, comparedwith these (red lines and closed circle) from JTWC best track data. Numbers mean the dates of the month.
mesh experiments, though the integration time of the 3.5-km
mesh experiment was only for a week. We thus focus on the
7-km mesh experiment, in which TCs were generated along
the passage of the MJO propagation as described below.
[6] Satellite observations were used to verify the spatial
structure of the simulated TCs. The mesoscale precipitation
pattern and the convective activity associated with the TCs
were derived from the 2A12 product of the Tropical Rainfall
Measuring Mission Microwave Imager (TRMM-TMI). The
TRMM-TMI data consist of instantaneous precipitation
retrievals and profiles of hydrometeors with a horizontal
resolution of approximately 5.1 km. To evaluate the largescale organized cloud pattern, the global (60°N – 60°S)
black body temperature (TBB) merged from 11 infrared (IR)channels aboard 5 geostationary satellites of the Climate
Prediction Center (CPC-IR) were also used. These satellite
data have a horizontal resolution of approximately 4 km.
[7] The tracks of the observed TCs were obtained fromthe Joint Typhoon Warning Center (JTWC). The JTWC best
track dataset includes locations and maximum wind speedsof TCs, generally recorded at 6-h intervals. Estimates of thehourly positions of the storm centers were obtained bylinear interpolation in this study.

3. Results[8] During the NICAM simulation period from15 December 2006 to 16 January 2007, three TCs that had
maximum 10-m wind speeds greater than 34 knots wereobserved in the JTWC best track data. TCs Bondo andClovis occurred in the western Indian Ocean and Tropical
Storm Isobel in the eastern Indian Ocean (Figure 1). The
NICAM simulation reproduced Bondo and Isobel (Figure 1).
3.1. TC Bondo[9] TC Bondo was first observed as a tropical storm at
1200 UTC 18 December 2006 in the central Indian Ocean(Figure 1). It moved westward and intensified to a category4 storm. In the NICAM simulation, a low pressure systembecame identifiable at 0000 UTC 18 December, i.e., after
3 days of the model integration. The storm system, resembling the observed Bondo, had closed isobars and a minimum
sea level pressure (SLP) less than 1000 hPa near its center(not shown). The simulated track, determined on the basisof the central position of minimum SLP, is in good agreement with the observed track taken by TC Bondo (Figure 1).

[10] Figure 2 compares the cloud features of the simulated
storm and of the observed TC Bondo. The simulated clouds
first organized in the Intertropical Convergence Zone (ITCZ)
in the central and eastern Indian Ocean (Figure 2b). The
storm’s cyclonic vorticity originated also in the ITCZ in thecentral Indian Ocean (not shown). The distribution of
the simulated cloud pattern is roughly similar to that
depicted in the TBB image of the CPC-IR (Figure 2a).
Although the comparison of TBB with the model outgoing
longwave radiation (OLR) is not straightforward, they bothreflect the cloud-top features of cloud systems in tropics.
The simulated storm reached a minimum SLP of 960 hPa
and a maximum azimuthal mean 10-m wind speed of about
100 knots, which is comparable to the observed maximum
10-m wind speeds of 90—120 knots during TC Bondo’s
mature phase given in the JTWC best track data. [Note thata direct comparison of winds is not straightforward since thesustained 10-m wind in the best track data was not fromdirect measurements but was estimated based on the
Dovorak technique, while the model winds are the instantaneous values at a given time step and represent an area
mean in a given individual grid boxes].
[11] As can be seen from the surface rain rate from
TRMM-TMI products (Figure 2c), Bondo developed aneyewall with a ring of heavy precipitation, a clear eye withlittle rain near the storm center, and several spiral rainbands
with embedded deep convective cells outside the eyewall.
The simulated Bondo also developed a typical eyewall
structure and spiral rainbands (Figure 2d) that are comparable to the observed. The storm, however, developed thesefeatures (shown in Figure 2d) about 24 h later and its center
was about 350 km to the west of the real storm center. The
vertical structure of the simulated cloud systems was also
comparable to the observed except that the simulatedhydrometers were higher (Figures 2e and 2f). This is partly
due to the use of the relatively coarse model resolution of
7 km and the peculiar features of the cloud microphysics
scheme of Grabowski [1998], as reported by Satoh et al.
[2008b]. Nevertheless, despite some discrepancies, theseresults strongly suggest that NICAM, given the atmosphericand SST conditions existing 4 – 7 days before TC Bondo
occurred could successfully reproduce not only the development but also the mesoscale structure of Bondo.
[12] In addition, it is interesting to note that a cloud clusterwith cyclonic circulation appeared in the northwestern Indian

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L22808Figure 2. (a) Equivalent black body temperature (TBB, K) from CPC-IR and 850-hPa winds from NCEP analysis and(b) outgoing longwave radiation flux (OLR, W m 2) and 850-hPa winds from NICAM simulation at 1200 UTC
21 December 2006. Surface rain rate (mm hour 1) derived from (c) TRMM-TMI at 0537 UTC 19 and (d) NICAM
simulation at 0600 UTC 20. Cross-section of the mixing ratio of total hydrometeors (cloud water, precipitation water,
cloud ice, and precipitation ice; g kg 1) derived from (e) TRMM-TMI at 0537 UTC 19 and (f) NICAM simulation at
0600 UTC 20. Locations of cross-sections are marked as the lines AB and CD in Figures 2c and 2d, respectively.
Ocean in both observation and simulation (Figures 2aand 2b). The cyclonic gyre north of the equator and TC
Bondo displayed the typical twin cyclone structure with two
cyclones straddling the equator, indicating the importantrole of equatorial Rossby waves in the genesis of Bondo,
consistent with previous findings [e.g., Frank and Roundy,2006].
3.2. Tropical Storm Isobel[13] Tropical Storm Isobel was first observed over theeastern Indian Ocean at 0600 UTC 2 January 2007 (Figure 1).
It moved southward and finally made landfall on thenorthwest coast of Australia at 0300 UTC 3 January. In
the NICAM simulation, a storm was detected after 14-day
model integration in the SLP field over the sea south of Java
at 0000 UTC 29 December 2006. The model storm intensified as it moved southeastward over the eastern Indian
Ocean and reached its peak intensity with a minimum SLPof 965 hPa and a maximum 10-m wind speed of around60 knots. The JTWC data for Tropical Storm Isobel showeda maximum 10-m wind speed of 40 knots, indicating thatthe simulated storm was stronger than the real one.
Although the simulated Isobel made landfall on the north-west coast of Australia about 1 day later than the real storm,
it is promising that NICAM, given the atmospheric conditions more than 2 weeks beforehand and the observed
SST, simulated the overall lifecycle of Tropical Storm
Isobel.
[14] NICAM reproduced well the large-scale environmental conditions around the Maritime Continent region
characterized by the onset of the MJO [Miura et al., 2007]
and the penetration of the northeast monsoonal surge into
the Southern Hemisphere in a longitudinal band between
100° E and 120°E (Figures 3a and 3b). Accompanying the
MJO onset on 28 –29 December 2006 in the eastern Indian
Ocean and its eastward propagation were loosely organized
convective activities over the Maritime Continent region
and an equatorial westerly wind burst (WWB) (Figures 3aand 3b). As indicated by observational study of Wu et al.
[2007], the northerly cross-equatorial flow originated fromthe cold surge over the South China Sea intensified in late
December 2006. It seems that the cross-equatorial flow and
the MJO provided the favorable large-scale conditions forthe genesis of Isobel in both observations and the NICAM
simulation.

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L22808Figure 3. Same as Figure 2 except for cross sections. The time is (a) and (b) 0000 UTC, (c) 0920 UTC, and (d) 2230 UTC
2 January 2007. Crosses represent the position of the storm center.
[15] Tropical Storm Isobel did not develop a typicaleyewall as Bondo did, but a large, broken one with little
convection in its southeastern section on 2 January 2007
(Figure 3c). The NICAM simulation reproduced the broken
eyewell structure, especially the stronger convection in western than in the eastern section of the eyewall (Figure 3d).
Remarkable is that this took place after about 18 days ofmodel integration, indicating the possible use of highresolution cloud-system-resolving global models in predicting not only the large-scale flow patterns, such as the MJO,
but also the organized convective systems, such as TCs.
[16] Furthermore, the NICAM simulation provides a hightemporal and spatial resolution dataset for detailed studiesof the mesoscale processes responsible for TC genesis andthe associated interactions with the large-scale environmental flow. An example of such a multi-scale interaction
associated with the genesis of Isobel is given in Figure 4.
It is clear that the large-scale cyclonic shear closely related
to the WWB in the MJO provided a favorable condition fordeep convection, as evidenced by the organized convective
precipitation over the sea north of Java (Figure 4a). The
deep convection was accompanied by small-scale high lowlevel cyclonic potential vorticity with diameters less than
40 km (Figure 4b), very similar to the so-called vortical hot
towers discussed by Simpson et al. [1998], Hendricks et al.
[2004], and Montgomery et al. [2006]. Isobel thus formed asa result of the following events: increased cyclonic shear
due to the WWB, collective heating from the vortical hot
towers, the merging and strengthening of low-level potential
vorticity of the hot towers (Figures 4c, 4d, and 4e), andeventually the axisymmetrization of mesoscale features by
the storm-scale low-level cyclonic circulation (Figures 4eand 4f) over the sea south of Java. A detailed process study

on the genesis of Isobel is under way, and the results will bereported elsewhere.

4. Concluding Remarks[17] This paper highlights a successful simulation of thelifecycles of two real TCs over the Indian Ocean by the
global, nonhydrostatic, cloud-system-resolving model
NICAM at about 7- km horizontal resolution. The model
had been initialized with the observed synoptic scaleatmospheric conditions on 15 December 2006 and then let
run freely until 16 January 2007 with the observed SST. The
successful simulations are due to the realistic simulations of
not only the large-scale circulation, such as the MJO and thecross-equatorial flow, but also the embedded mesoscaleconvective systems, such as vortical hot towers and theirsubsequent organization and axisymmetrization.
[18] NICAM also reproduced the twin cyclones straddling the equator in the Indian Ocean. However, it failed toreproduce the development of the third storm seen inobservations, TC Clovis. We noted that NICAM did capture
the cloud features near Madagascar (Figures 3a and 3b),indicating that the failure could be due to a mismatch
between the convective cloud systems in the simulationand in the observations either with regard to time or location
or both.
[19] The present NICAM simulation also provides adataset of high temporal and spatial resolution for detailed
studies of TC genesis. The formation mechanism and thesize of the two simulated TCs were quite different. Thismight be due to the different large-scale environmental
conditions and the internal dynamics associated with theorganization of the convective and mesoscale cloud features. These will be the topic for a future study. Therefore,

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L22808Figure 4. (a) Precipitation rate (shading, mm h 1) and horizontal winds at 310-K level at 0000 UTC 28 December 2006
showing the WWB associated with the MJO. The evolution of cyclonic potential vorticity (shading and contour, PVU)
and horizontal winds at 310-K level in a 2.5°  2.0° box are shown at (b) 0000 UTC, (c) 0600 UTC, (d) 1200 UTC,(e) 1800 UTC 28, and (f) 0000 UTC 29 December 2006. Rectangle in Figure 4a represents the domain in Figure 4b.
this paper not only demonstrates that global cloud-systemresolving models may be able to predict tropical cyclone
formation and evolution but the data set created also marks
an unprecedented opportunity for advancing our understanding of multiscale interactions related to TC genesis,
intensification, and evolution in a global context.
[20] Two long-term simulations at both 7-km and 14-km
resolutions have recently been completed. One is a onemonth perpetual July-equilibrium run and the other is a five-month run of the boreal summer 2004. Our preliminary
analyses are encouraging. These runs also allow us to study
the statistics of the model TCs in different ocean basins,
which is a key test of a model to be used for the study of TC
climate. Again, in these runs, the model reproduced many
important scenarios of TC genesis, including the large-scale
circulation features (such as equatorial waves, easterly
waves, the MJO, and the monsoon circulation) and the

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mesoscale cloud system organizations. The results fromthese new simulations will be reported separately.
[21] Promisingly, the model captured some mesoscale
structures of the real TCs about 1– 2 weeks after initialization. As the capability of supercomputers increases, NICAM
will be run at 3.5-km resolution for monthly-to-seasonal
simulations. With such a fine resolution, cloud systems
can be resolved much better. We thus look forward to a
new era for weather and climate predictions with global
cloud-system-resolving models.
[22] Acknowledgments. The authors are grateful to Gisela Speidel
for her careful reading and editing of the manuscript. This study has been
supported in part by NSF grants ATM-0427128 and ATM-0754039 andONR grant 00014-06-10303 and in part by the JAMSTEC, NASA, andNOAA through their sponsorships of the International Pacific ResearchCenter (IPRC) in the School of Ocean and Earth Science and Technology(SOEST) at the University of Hawaii. The Earth Simulator is used for the
NICAM simulations. This is the SOEST publication 7578 and IPRC
publication 557.

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