2030

JOURNAL OF CLIMATEVOLUME 23

Shallow and Deep Latent Heating Modes over Tropical Oceans Observedwith TRMM PR Spectral Latent Heating Data
YUKARI N. TAKAYABU
Center for Climate System Research, The University of Tokyo, Chiba, JapanSHOICHI SHIGE*
Osaka Prefecture University, Osaka, Japan

WEI-KUO TAO
NASA Goddard Space Flight Center, Greenbelt, Maryland

NAGIO HIROTA
Center for Climate System Research, The University of Tokyo, Chiba, Japan(Manuscript received 3 March 2009, in final form 19 September 2009)
ABSTRACT
Three-dimensional distributions of the apparent heat source (Q1) 2 radiative heating (QR) estimated from
Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) utilizing the spectral latent heating(SLH) algorithm are analyzed. Mass-weighted and vertically integrated Q1 2 QR averaged over the tropicaloceans is estimated as ;72.6 J s21 (;2.51 mm day21) and that over tropical land is ;73.7 J s21 (;2.55mm day21) for 308N–308S. It is shown that nondrizzle precipitation over tropical and subtropical oceansconsists of two dominant modes of rainfall systems: deep systems and congestus. A rough estimate of theshallow-heating contribution against the total heating is about 46.7% for the average tropical oceans, which issubstantially larger than the 23.7% over tropical land.
Although cumulus congestus heating linearly correlates with SST, deep-mode heating is dynamicallybounded by large-scale subsidence. It is notable that a substantial amount of rain, as large as 2.38 mm day21
on average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that,even in the region with SSTs warmer than 288C, large-scale subsidence effectively suppresses the deep
convection, with the remaining heating by congestus clouds.
The results support that the entrainment of mid–lower-tropospheric dry air, which accompanies the largescale subsidence, is the major factor suppressing the deep convection. Therefore, a representation of therealistic entrainment is very important for proper reproduction of precipitation distribution and the resultant
large-scale circulation.

1. Introduction
Over the tropical and subtropical oceans, destabilization of the atmosphere by warm sea surface temperatures* Current affiliation: Graduate School of Science, Kyoto University, Kyoto, Japan.

Corresponding author address: Yukari N. Takayabu, Centerfor Climate System Research, The University of Tokyo, 5-1-5
Kashiwanoha, Kashiwa, Chiba, 277-8568, Japan.
E-mail: yukari@ccsr.u-tokyo.ac.jp
DOI: 10.1175/2009JCLI3110.1
Ó 2010 American Meteorological Society(SSTs) and the stabilization by subsidence and horizontaltransport may be compared. As a result, although a large
precipitation amount is observed with very high SSTs,
it does not significantly correlate with SST over moderately warm sea surfaces. Various studies indicate that
SST works as a threshold for the precipitation activity(e.g., Gadgil et al. 1984). In the current climate, 288C
may be a generally good rule of thumb as a thresholdfor deep convection; however, the circulation is probably more important in determining the value of thethreshold.

15 APRIL 2010

TAKAYABU ET AL.

Under the influence of large-scale subsidence, a resulting temperature inversion and dry layer in the mid–low
troposphere are two factors suppressing deep convection. Historically, tropical convective clouds were considered to have a ‘‘bimodal structure,’’ consisting of deep
cumulus convection and shallow trade inversion cumuli.
In the 1990s, a melting level stable layer and associatedprominence of cumulus congestus clouds were reported
over the western Pacific warm pool region from theTropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE)(Johnson et al. 1999). Since then, our understanding of
the tropical convection has expanded from bimodal totrimodal structures—that is, deep convection, cumulus
congestus, and shallow cumuli.
Substantial contribution of cumulus congestus is also
reported by Petty (1999), utilizing surface synoptic reports together with infrared images of the Japanese fifth
geostationary meteorological satellite (GMS-5). He concluded that a substantial fraction (20%–40%) of precipitation comes from clouds warmer than 273 K in alarge area to the east of Australia. Mapes (2000) alsoemphasized the significant role of cumulus congestus in
helping to balance between the convective heating andatmospheric radiative cooling. Short and Nakamura (2000)
utilized the Tropical Rainfall Measuring Mission (TRMM)
Precipitation Radar (PR) data and estimated the precipitation associated with shallow rain accounts for ;20%of total tropical precipitation. More recently, Kubar andHartmann (2008) utilized CloudSat data to compare thevertical structure of cloud systems of the intertropicalconvergence zone (ITCZ) across the east and west Pacific. They found that, associated with moderate intensity
rainfall and also with mid-level thick systems, two peaks inthe cloud-top distribution at ;6 and ;2 km are significant. The trimodal structure is also observed in association
with a three-step-wise development of large-scale cloudsystems such as the Madden–Julian oscillation (MJO)
over the western Pacific (Kikuchi and Takayabu 2004).
The importance of a substantial amount of shallow
heating is emphasized by Zhang et al. (2004), who founda low-level meridional return flow associated with theshallow heating in the eastern Pacific ITCZ. Wu (2003)
investigated the circulation driven by deep heating andshallow congestus heating by linear equations and a dry
primitive equation model, and he showed that low-level
moisture convergence driven by shallow congestus heating is 5 times larger than the deep heating of the sameamount and exceeds the value to maintain the heatsource. On the other hand, moisture convergence associated with deep heating is not efficient enough to sustain the heating. He estimated about 24% of the total
precipitation must be associated with shallow heating.

2031

In the atmospheric general circulation models(AGCMs), tropical cumulus convection is dealt withby various cumulus parameterizations, which represent
effects of the subgrid-scale cumulus convection with gridscale variables; however, it has been noticed that many
AGCMs produce an incorrect distribution of tropicalprecipitation. One of the frequently reported problems
is the unrealistically parallel distribution of the intertropical convergence zones in both hemispheres along
the equator (double ITCZ). Also, Bony and Dufrence(2005) reported that the largest disagreements in sensitivity of cloud radiative forcing (CRF) among climate
models and between models and observations are foundin regions of large-scale subsidence. Their study indicates that at least some of the cumulus parameterizations utilized in AGCMs do not properly represent the
suppression of deep convection under the large-scale
subsidence. These results strongly suggest that understanding the mechanism of convection suppression bylarge-scale subsidence is essential for improvements ofcumulus parameterizations.
As for the effects of environmental factors, Jensen
and DelGenio (2006) utilized observations from an Atmospheric Radiation Measurement (ARM) surface-based
remote sensing site at Nauru Island and indicated thata drying of the midtroposphere is more effective to limit
congestus cloud-top heights compared to a freezing
level–induced stable layer. This result is consistent withresults of Brown and Zhang (1997), Redelsperger et al.
(2002), Takemi et al. (2004), and Takayabu et al. (2006).
In this study, we analyze the three-dimensional distributions of Q1 2 QR obtained from the spectral latentheating (SLH) data, where Q1 is the apparent heat source
invented by Yanai et al. (1973) and QR is the radiative
heating. Utilizing field campaign soundings, Schumacher
et al. (2007, 2008) presented total diabatic heating profiles that represent the dominant cloud types. The first
purpose of this study is to quantitatively examine Q1 2
QR distributions over the global tropical oceans. We findtwo predominant Q1 2 QR modes, a deep mode and ashallow mode, associated with nondrizzle precipitation.
Next, we aim to find the controlling environmental factors of these two vertical modes of precipitation systems.
Note that this bimodal structure is not the same as thewell-documented two primary modes; rather, it corresponds to the upper two modes of the trimodal structure
found by Johnson et al. (1999): deep convection andcumulus congestus. The TRMM PR rarely detects weak
precipitation associated with trade cumuli because of its
reflectivity sensitivity of 17 dBZ; therefore, we cannot
quantify the contribution of trade cumuli in this study.
It is assumed here that such a light rain contribution fromtrade cumuli does not largely increase the shallow rain

2032

JOURNAL OF CLIMATEVOLUME 23

FIG. 1. Eight-year unconditional mean Q1 2 QR profiles averaged for 308N–308S at all longitudes (a) over the ocean and (b) over land. Black solid lines indicate Q1 2 QR associated withconvective rain, black-dashed lines indicate Q1 2 QR with stratiform rain, and gray solid lines
are those associated with total rain.

contribution, which should be examined with recent
spaceborne cloud radar observation from CloudSat infuture studies.
In section 2, we describe the data utilized in this study.
In section 3, the relationship between the heating distribution and the sea surface temperature is examined.
In section 4, effects of large-scale subsidence on precipitation heating are examined. Finally, section 5 is devoted to summary and discussion.

2. Data and methodology
Since the launch of the TRMM satellite in December
1997, it has continuously provided a unique dataset ofspaceborne precipitation radar, which has a 13.8-GHz
Ku-band frequency. In this study, using the TRMM PR
data and conversion tables between precipitation andlatent heating, we utilized Q1 2 QR [Eq. (1)] as a largescale diabatic heating rate obtained from the SLH algorithm (Shige et al. 2004, 2007, 2008):
Q1 [

D
s ›
s
›
s
c
5
1 y  $s1v
5 QR 1 L(
Dt
›t
›p
›
$  s9y9
s9v9.
›p

e)
(1)

Here, Q1 is the apparent heat source invented by Yanai
et al. (1973); QR is the radiative heating; and s is the dry

static energy, s 5 CpT 1 gz. The SLH algorithm is atable method to estimate latent heating and Q1 2 QR,
utilizing the TRMM PR precipitation data. Conversion
tables are made from a simulation of TOGA COARE
convection with the Goddard Cumulus Ensemble Model,
in a spectral sense in terms of the precipitation-top height(PTH) for the convective rain and in terms of the melting
level precipitation rate for the stratiform rain.
For the atmospheric variables, we utilized the Japan
Meteorological Agency (JMA) Japanese 25-year Reanalysis Project (JRA25) data and the Japanese Climate
Data Assimilation System (JCDAS); and for SST weused the National Oceanic and Atmospheric Administration (NOAA) optimum interpolation (OI) SST data.
The analysis period is 8 yr from 1998 to 2005.

3. Q1 2 QR versus SST
Eight-year unconditional mean Q1 2 QR profiles averaged for 308N–308S at all longitudes are depicted inFig. 1, separately for over the ocean and over land. Twopeaks in the convective heating at ;5 and ;2 km areapparent over the ocean, whereas only the former peakis significant over land. When we look back to the spectral table (Shige et al. 2007), it is known that the ;5-km
heating peak corresponds to deep convection, whereas
the ;2-km peak is associated with the precipitation

15 APRIL 2010

TAKAYABU ET AL.

from cumulus congestus with PTHs between 2 and 6 km.
The latter may well correspond to the ‘‘moderate rain’’class analyzed in Kubar and Hartmann (2008). Apparently, cumulus congestus is much more frequent over theocean than over land. When we examine the surface rain
contributions of each PTH bin for PR-based convective
rain (Fig. A1 in the appendix), we notice that abundantrain from PTHs between 2 and 6 km over the ocean is
missing over land; therefore, it is considered that thesecongestus rains contribute to the average oceanic ;2-km
heating peak. Here, let us note that, because cloud-top
heights associated with this type of rain may be higher
than the freezing level, such cumulus congestus clouds
may not purely represent warm rain processes but perhaps may include ice and/or mixed phase processes.
On the other hand, heating profiles associated withstratiform rain are characterized with positive heating in
the upper troposphere with a peak at ;8 km and coolingin the lower troposphere with a peak at ;4 km, bothover the ocean and over land. Deep stratiform rain comesfrom the nimbostratus clouds, which are associated primarily with the widespread continuous clouds of mesoscale convective systems, hurricanes, and extratropical
cyclones (Houze 1993). Because rainfall contribution fromthe tropical cyclones in the TRMM observation regionis as small as 3%–4% of the total rainfall (Yokoyama
and Takayabu 2008), we can consider that this tropicalstratiform heating profile mostly represents the heatingof the deep stratiform rain associated with mesoscaleorganized convective systems. The lower-troposphericevaporative cooling over land is larger than that over theocean. Total Q1 2 QR heating profiles have a broad peakaround 6–8 km over the ocean and over land and another peak at ;2 km over the ocean.
Mass-weighted and vertically integrated Q1 2 QR averaged over the ocean from 308N to 308S is estimated as;72.6 J s21 (;2.51 mm day21), and that averaged overland from 308N to 308S is ;73.7 J s21 (;2.55 mm day21).
Rough estimates of the shallow-heating contribution bymass-integrated Q1 2 QR below the freezing level of
4.5 km is about 46.7% for the average tropical oceansfrom 308N to 308S and about 23.8% for the averagetropical land from 308N to 308S, which is still larger thanvalues suggested by previous studies. It is interesting tonote that a 46.7% shallow-heating contribution to the total
heating is very similar to the contribution to total precipitation in the east Pacific ITCZ region from clouds lower
than 9.5 km in the Kubar and Hartmann (2008) study.
Based on the previously mentioned heating profiles,
we choose 7.5 km as a representative altitude for theupper-level heating and 2.0 km for the lower-level heating, to examine the seasonal mean horizontal distributions of upper and lower heatings (Figs. 2 and 3). The

2033

upper-level heating distributions are very similar to thetotal seasonal precipitation (not shown), and large values
are found over very warm SSTs (.288C) and overtropical land. However, for the moderate SST region(,288C), the deep-heating distribution does not obediently follow the SST distribution; for example, in thesouthern Pacific, we find warm SST contours extend
eastward nearly parallel to the equator, whereas thedeep heating bends southward beyond the date line.
Much more lower-level heating is found over theocean than over land, as shown in Fig. 3, which is consistent with what was found in Fig. 1. Second, over theocean the heating distribution follows the SST distribution (e.g., distribution along the line from the Philippine
Islands to Hawaii). It is apparent that ;2-km congestus
heating exhibits more double-ITCZ-like distribution
than ;7.5-km-deep heating, because the former moreclosely follows the SST distribution. It is interesting tonote that lower-level heating is larger over the ITCZ tothe east of the date line compared to the convective
region over the warm pool. This is consistent with findings by Zhang et al. (2004), who emphasized the importance of shallow circulation induced by congestus
heating in the eastern Pacific ITCZ region. It also agrees
with a prediction of a bimodal convection model developed by Back and Bretherton (2009). Their model consists of a shallow mode, which is related to all ‘‘boundary
layer convergence’’; a deep mode, which is proportional
to conditional instability in the surface convergence region; and realistically produced ‘‘bottom heavy’’ and‘‘top heavy’’ contrasts of the climatological precipitation heating distribution. It is also notable that particularly large low-level and upper-level amplitudes are
diagnosed along the western coasts of India and Indochina in June–August.
To further examine the SST heating relationship fordeep systems and for cumulus congestus, we scattereddeep heating and shallow heating against SST for eachseason (Figs. 4 and 5). It is clearly confirmed that SST
works as a threshold for deep convective systems ‘‘to beavailable’’ at the temperature of ;278C. On the other
hand, low-level congestus heating correlates with the
SST for almost the entire SST range from 188 to 308C for
every season. This confirms what we saw from the horizontal distributions in Fig. 3, suggesting that cumulus
congestus activity is very obedient to the boundary layer
destabilization and not especially sensitive to otherlarge-scale factors.

4. Q1 2 QR versus large-scale vertical velocity
Because previous studies indicate that large-scale subsidence works to suppress deep convection effectively

2034

JOURNAL OF CLIMATEVOLUME 23

FIG. 2. The 8-yr unconditional mean Q1 2 QR at 7.5 km for each season in color shades, with SST distribution incontours. Contour interval (CI) is 1.08C and thick contours are for 288C.

15 APRIL 2010

TAKAYABU ET AL.

2035

FIG. 3. As in Fig. 2, but for Q1 2 QR at 2.0 km. Thick contours are for 258 and 308C.

(e.g., Yuan et al. 2008), we next examine the scatter ofQ1 2 QR for deep heating and for shallow heating, against
the pressure velocity (dp/dt 5 v) at 500 hPa (v500) for
the December–February season in Figs. 6 and 7, respec-tively. Heating from the deep systems correlates muchbetter (20.85 to 20.87) with v500 compared to that with
SST. On the other hand, shallow congestus heating is notdirectly related to the effects of large-scale subsidence,

2036

JOURNAL OF CLIMATEVOLUME 23

FIG. 4. Scatter diagrams of 8-yr unconditional mean Q1 2 QR at 7.5 km against SST at the same
18 3 18 grid for each season.

which is consistent with what was implied from theheating–SST relationship in Fig. 5. It is also interesting
to find there is no significant seasonal dependency inthese environment–heating relationships, either with
SST or with large-scale subsidence (Figs. 4–7).
A longitude–height section of the 8-yr unconditionalmean Q1 2 QR along 108S for the September–November
season and the saturated equivalent potential temperature is plotted in Fig. 8. Over the western and central
south Pacific from 1508E to 1708W, active deep heating
is observed together with shallow heating. The eastern
south Pacific from 1608 to 808W corresponds to thelarge-scale subsidence region under the influence of thesubtropical high, and there is a stable layer just below
700 hPa. The convective heating is significantly suppressed at the height of the stable layer, suggesting thepredominance of congestus heating. A similar structureis also found over the southeastern Atlantic and overthe southwestern Indian Ocean. Note that, although the
deep- and shallow-mode distinction corresponds to v500
over the ocean, it is not the same for those over land. In
the JRA data, deep heating is observed over land even
without average upward velocity at the midtroposphere
over the South America (;608W). We also examined thispoint with the 40-yr European Centre for Medium-Range
Weather Forecasts (ECMWF) Re-Analysis (ERA-40)

data (not shown), although midtropospheric vertical velocities with ERA-40 are not downward at deep-heating
longitudes over the South America; however, they show
very small upward velocities that are distinct from thoseover the ocean.
To examine the above west–east contrast in heatingand environment more closely, unconditional average
vertical profiles of the Q1 2 QR for the southwestern
Pacific (SWPac) region (138–38S, 1558–1658E) and forthe southeastern Pacific (SEPac) region (158–58S, 1558–
1458W) for the September–November season are compared in Fig. 9. Over the SWPac (Fig. 9a), deep convective
heating at ;5 km is as large as 3.4 K day21 and shallow
heating is found at a slightly higher than tropical average
altitude of ;2.2 km found in Fig. 1. The thermodynamic
profile in this region is slightly conditionally unstable in
the lower troposphere but almost neutral (Fig. 9c). On theother hand, deep systems are clearly suppressed in the
SEPac (Fig. 9b). Thermodynamic profiles evidently indicate the subsidence with a stable layer in the lower
troposphere between 700 and 850 hPa, which establishes
a very dry environment in the lower half of the troposphere (Fig. 9d). It is evident that deep convection iseffectively suppressed with this subsiding dry layer.
Mass-integrated Q1 2 QR values are 198.0 J s21(6.85 mm day21) in the SWPac and 68.8 J s21

15 APRIL 2010

TAKAYABU ET AL.

2037

FIG. 5. As in Fig. 4, but for Q1 2 QR at 2 km. Numbers at top left indicate correlation
coefficients between SST and Q1 2 QR at 2 km.

(2.38 mm day21) in the SEPac, respectively. It is notable that a substantial amount of rain, as large as
2.38 mm day21 on average, comes from congestus rainunder the large-scale subsiding circulation. The shallowheating (,4.5 km) ratio to the total heating is 37.2%
over the southwest Pacific region and 65.8% over thesoutheast Pacific region.
So far we have seen that shallow congestus heating
is yielded by warm SSTs and that deep-system heating
is well suppressed by the large-scale subsidence. To confirm if this discussion is applicable to the global tropics,
we overlay the v500 field onto the heating fields in
Figs. 10a,b. It is evident that, while low-level congestus
heating does not feel the effects of large-scale subsidence,
deep-heating distribution clearly follows the zero contourof v500, especially over the ocean. Figure 10c depicts
the ratio of 2.0-km heating against the 7.5-km heating. In
the subsidence region, the shallow heating is generally
more than factor of 6 larger than the deep heating. For
the large-scale vertical motion, we utilized the seasonalmean values of v500. Midlevel subsidence does not always consist of compensating subsidence induced by deep
convective activity but can be also dynamically induced
over the subtropical highs (e.g., Miyasaka and Nakamura
2005). In other words, deep heating is interpreted to be‘‘dynamically bounded’’ by the large-scale circulation.

To analyze the effect of vertical velocity on diabatic
heating, we next stratify the conditional mean Q1 2 QR
profiles against v500 for total, convective, and stratiform
rain (Fig. 11). From heating profiles associated with total
rain, we can find a clear bimodal structure, one with topheavy heating associated with mesoscale convective systems with maximum between 6–8 km and another withshallow heating with a peak at around 2 km and a slightcooling just above. As already noted in the introduction,

FIG. 6. Scatter diagram of 8-yr unconditional mean Q1 2 QR at
7.5 km against dp/dt at 500 hPa at the same 18 3 18 grid for the
December–February season.

2038

JOURNAL OF CLIMATE

FIG. 7. As in Fig. 6, but for Q1 2 QR at 2 km.

the bimodal structure focused on here consists of deep
modes and congestus modes, excluding the shallow trade
cumulus modes because of the sensitivity limit of
TRMM PR. These two modes switch their dominanceat around v ; 0. When the heating is separated into
convective and stratiform rain parts (Figs. 11b,c), it isnoticed that convective rain is largely affected by thelarge-scale subsidence in a manner that deep heating
at ;5 km is significantly suppressed, whereas the stratiform rain is not directly affected but slightly lowers its
height. This height shift is probably because of the lower

VOLUME 23

melting level height associated with lower SSTs in thesubsidence region.
Figure 12 depicts the environmental profiles against
v500 for relative humidity (RH) and for saturated equivalent potential temperature use, respectively, in the samemanner as in Fig. 11. In the large-scale subsidence region, a very dry atmosphere with relative humidity lessthan 40% is found from 400 to 700 hPa. When the average subsidence is larger than 20 hPa day21, the RH isless than 30% between 500 and 700 hPa, which canstrongly discourage the development of deep convection
beyond the freezing level. As for the temperature profiles,
lower-tropospheric conditional instability is concentrated
in the ascending region for v500 , 250 hPa day21. In
the intermediate range of 210 , v500 , 40 hPa day21,
there is a lower-level stable layer around 700 hPa. For
v500 . 40 hPa day21, the temperature profile is conditionally neutral.
Because large-scale vertical velocity and SST distributions are usually closely related to each other, it isdifficult to separate effects of the former from the latter;
therefore, we examine the effects of vertical velocity on
the total Q1 2 QR separately over limited SST grids of
22.08–23.08, 24.08–25.08, 26.08–27.08, and 28.08–29.08C,
respectively (Fig. 13). In all cases, very similar bimodal
structures of heating as we saw in Fig. 11a are found.

FIG. 8. Longitude–height section of 8-yr unconditional mean Q1 2 QR at 108S for September–
November season (color shades) and the use in contours (K). Contour levels are set at 320, 325,
330, 335, 340, 342, 344, 346, 348, 350, 355, 360, 365, and 370 K; values less than 344 K arecontoured in dashed lines. Vectors indicate zonal and vertical wind velocity. The unit vector at
the bottom indicates the scale of the zonal wind speed in m s21 and the vertical velocity is
stretched to appear clearly in the figure.

15 APRIL 2010

TAKAYABU ET AL.

2039

FIG. 9. Eight-year mean vertical profiles of the Q1 2 QR averaged for the (a) SWPac and (b)SEPac regions, for the September–November season. Black solid lines represent Q1 2 QR
associated with convective rain, black-dashed lines represent Q1 2 QR with stratiform rain, andgray lines are for total rain. (c),(d) As in (a),(b), respectively, but for potential temperature(K, gray solid lines), equivalent potential temperature (dashed lines), and use (K, black solid lines).

Moreover, the transition region from the deep mode to
the shallow mode is found very similarly around zerovertical velocity, although there is a slight shift toward
the ascending regions as the SST increases. The suppression of the deep mode is significant even over very
warm SSTs of 28.08–29.08C in the subsidence regions.
The predominance of the deep mode with increasing
upward vertical velocity is also apparent in all SST ranges.
By examining the cloud radiative forcing as a function ofv500, Yuan et al. (2008) found that the thick high cloudamount strongly increases with increasing upward vertical velocity and that such a relationship hardly changes
even when cases are restricted to SST . 288C. It isconsistent with the increase of the deep mode in our
analysis.

Figure 14 depicts RH profiles stratified against v500
for separate SST conditions. In all cases, basic dependency on v500 is fairly similar to Fig. 12a. Boundary
layers are very humid over all velocity ranges, the upper
troposphere is also humid in the large-scale ascending
regions, and a significant mid–lower-tropospheric drylayer is found in the large-scale subsidence regions. The
levels of all these structures shift upward as SST increases. The middle altitudes of the lower-tropospheric
dry layer in the subsidence region are 600, 550, 500, and
400 hPa for SST 5 22.08–23.08, 24.08–25.08, 26.08–27.08,
and 28.08–29.08C, respectively. A very moist boundary
layer also thickens as the SST increases, and the level ofthe upper-tropospheric moist layer in the ascending region also significantly increases and deepens.

2040

JOURNAL OF CLIMATEVOLUME 23

FIG. 10. The-8 yr unconditional mean Q1 2 QR at (a) 7.5 and (b) 2.0 km and (c) their ratio (2.0 km/7.5 km) for the September–
November season in color shade with dp/dt at 500 hPa in contours. CI 10 hPa day21, and negative values are indicated with dashed lines.
Thick solid contours are for zero values.

In contrast, dependencies of thermodynamic profiles
against v500 in different SST ranges are different fromthe averaged feature seen in Fig. 12b (not shown); in
each 28C SST range, thermodynamic profiles do not varylargely with v500, which means that atmospheric thermodynamic condition is largely determined by SST. It isrealized that the average feature in Fig. 12b consists ofcombinations of these profiles.
In summary, a bimodal feature in the nondrizzle precipitation systems is found from the precipitation-associatedlatent heating over a wide range of SSTs. The transition

from deep systems to cumulus congestus is basically independent of SST and controlled by the large-scale subsidence represented with the seasonal average v500.
The lower-tropospheric dry layer associated with largescale subsidence is suggested to be the major environmental factor that suppresses deep convection.

5. Summary and discussion
In this study, we analyze three-dimensional distributions of Q1 2 QR estimated from TRMM PR utilizing15 APRIL 2010

TAKAYABU ET AL.

2041

FIG. 11. The 7-yr conditional mean Q1 2 QR profiles stratified with dp/dt at 500 hPa averaged
for September–November season and for 308N–308S at all lons over the ocean, associated with(a) all rain, (b) convective rain, and (c) stratiform rain. Factors 10, 2.5, and 10 are multiplied to
the values for color scale. White contours indicate the error bars for 3 and 6 in the same scale as
the color shade.

the SLH algorithm. Mass-integrated Q1 2 QR averaged
over the ocean from 308N to 308S is estimated as;72.6 J s21 (;2.51 mm day21), and that averaged overland from 308N to 308S is ;73.7 J s21 (;2.55 mm day21).
It is shown that nondrizzle precipitation over tropicaland subtropical oceans consists of two dominant modesof rainfall sytems: deep systems and congestus. A roughestimate of shallow-heating contribution against the total

heating is about 46.7% for the average tropical oceansfrom 308N to 308S, which is substantially larger thanthe 23.7% averaged over land for the same latitudes. A
large contribution from congestus rain, particularly inthe eastern Pacific ITCZ region, is consistent with recent studies that focus on the importance of the shallow
mode in that region (Zhang et al. 2004; Kubar andHartmann 2008).

2042

JOURNAL OF CLIMATEVOLUME 23

FIG. 12. As in Fig. 11, but for (a) RH and (b) use.

Next, relationships of shallow- and deep-mode amplitudes to the environmental condition are examined.
It is found that, although cumulus congestus linearly
increases with SST, deep mode is effectively boundedby large-scale subsidence. A typical mass-integrated
Q1 2 QR value in the deep convective region in SWPac
is 198.0 J s21 (6.85 mm day21), and that in the congestus region in SEPac is 68.8 J s21 (2.38 mm day21). It
is notable that a substantial amount of rain, as large as
2.38 mm day21 on average, is brought from congestus
clouds under the large-scale subsiding circulation. The
shallow-heating (,4.5 km) ratio to the total heating is
37.2% over SWPac, whereas it is 65.8% in SEPac.
Thermodynamical effects and dynamical effects of theenvironment are separated by comparing the verticalvelocity dependences in different SST ranges. It is foundthat, even in the region with SSTs warmer than 288C,
large-scale subsidence effectively suppresses deep convection, with congestus heating still remaining. This result
strongly supports the hypothesis that the mid–lowertropospheric dry layer, which accompanies the large-scale

subsidence, plays an essential role to suppress deep convection through entrainment as suggested by Raymondand Blyth (1992) and Blyth (1993).
Wu (2003) suggested that shallow heating induces surface circulation much more effectively than deep heating,thus resulting in larger low-level moisture convergence.
Existence of a substantial amount of congestus heating
may be essential to maintain deep systems. Khouider
and Majda (2007) emphasized the importance of theexistence of congestus cloud heating, in addition to deep
convective heating and deep stratiform heating, in reproducing realistic convectively coupled equatorial wave
modes. Because our results show that congestus heating
substantially contributes to global tropical rain, it is essential to reproduce this amount of shallow rain to understand the global circulation correctly.
With various AGCMs, an unrealistic double-ITCZ
problem is reported. Our results suggest that cumulus
congestus certainly follows the lower-level destabilization with warm SST, but it is not the sufficient condition
for deep systems to be generated. Deep systems are15 APRIL 2010

TAKAYABU ET AL.

FIG. 13. As in Fig. 11, but for all rain averaged over the grids with SST of (a) 22.08–23.08, (b)24.08–25.08, (c) 26.08–27.08, and (d) 28.08–29.08C. White contours depict where 99% significancelevel with the Student’s t test attains 3.0 and 6.0 in the same scale as color shades.

2043

2044

JOURNAL OF CLIMATE

FIG. 14. As in Fig. 13, but for vertical profiles of RH.

VOLUME 23

15 APRIL 2010

2045

TAKAYABU ET AL.

FIG. A1. Contribution to the surface rain from every 250-m RTH
bin for (top) convective rain and (bottom) stratiform rain. Abscissa
is RTH (m) and ordinate is rain contribution (mm day21), in thesame manner as in Takayabu (2006). Black curves are for seasonal
averages over the oceans from 308N to 308S at all lons and gray ones
are those over land averaged for 1998–2000.

strictly bounded by large-scale subsidence. It is strongly
suggested that a realistic parameterization that represents the suppression of deep systems by large-scale
subsidence independent of SST is essential to overcome
the double-ITCZ problem, as well as to generate realistic large-scale circulation. Because our results support that the entrainment of dry lower-tropospheric air
is a major factor suppressing deep convection, representation of the realistic entrainment is very important.
Acknowledgments. The authors would like to express
their hearty thanks to two anonymous reviewers fortheir very helpful comments and suggestions to improvethe manuscript. They also would like to acknowledge
Dr. Anthony Del Genio for his kind help as an editor.
This work is partially supported by the Global Environment Research Fund (S-5) of the Ministry of theEnvironment, Japan, and by the TRMM Fifth Japanese
Research Announcement (TRMM JRA5) by the Japan
Aerospace Exploration Agency. The Grid Analysis andDisplay System (GrADS) is utilized for plotting thefigures.

APPENDIX
Rain-Top Height Statistics
With Fig. 1, we have discussed that cumulus congestus
heating is significant over ocean but not over land. Here,we want to see this point again by examining contributions to the surface rain from each 250-m bin of rain-top
height (RTH) in the same manner as in Takayabu (2006;

Fig. A1), based on TRMM PR data. We can find thata significant convective rain over the ocean starts fromaltitudes of 2–6 km, which is absent over land. On theother hand, contributions to the convective rain from 8
to 16-km RTH are much higher over land than over theocean. We identify the former relatively shallower RTH
contributions with the ;2-km-height heating peak andcall it congestus heating. Note that, as for RTHs of deep
stratiform rain, large contributions are found at altitudes
from 6–8 km and there is not much difference foundbetween over the ocean and over land. There is a difference in relatively shallow stratiform rain with RTHsof 2–3 km, which is significant only over the ocean. However, note that, because shallow rain does not accompany
the bright band, it is difficult to distinctly separate theshallow stratiform rain from the shallow convective rain.

REFERENCES
Back, L. E., and C. S. Bretherton, 2009: A simple model of climatological rainfall and vertical motion patterns over thetropical oceans. J. Climate, 22, 6477–6497.
Blyth, A. M., 1993: Entrainment in cumulus clouds. J. Appl. Meteor., 32, 626–641.
Bony, S., and J.-L. Dufrence, 2005: Marine boundary layer clouds
at the heart of tropical cloud feedback uncertainties in climate models. Geophys. Res. Lett., 32, L20806, doi:10.1029/
2005GL023851.
Brown, R. G., and C. Zhang, 1997: Variability of midtroposphericmoisture and its effect on cloud-top height distribution during
TOGA COARE. J. Atmos. Sci., 54, 2760–2774.
Gadgil, S., P. V. Joseph, and N. V. Joshi, 1984: Ocean–atmosphere
coupling over monsoon regions. Nature, 312, 141–143.
Houze, R. A., 1993: Cloud Dynamics. Academic Press, 573 pp.
Jensen, M. P., and A. D. Del Genio, 2006: Factors limiting convective cloud-top height at the ARM Nauru Island climate
research facility. J. Climate, 19, 2105–2117.
Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski,
and W. H. Schubert, 1999: Trimodal characteristics of tropicalconvection. J. Climate, 12, 2397–2418.
Khouider, B., and A. J. Majda, 2007: A simple multicloud parameterization for convectively coupled tropical waves. Part II:
Nonlinear simulations. J. Atmos. Sci., 64, 381–400.
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.
Kubar, T. L., and D. L. Hartmann, 2008: Vertical structure of tropicaloceanic convective clouds and its relation to precipitation. Geophys. Res. Lett., 35, L03804, doi:10.1029/2007GL032811.
Mapes, B. E., 2000: Convective inhibition, subgrid-scale triggering
energy, and stratiform instability in a toy tropical wave model.
J. Atmos. Sci., 57, 1515–1535.
Miyasaka, T., and H. Nakamura, 2005: Structure and formation
mechanisms of northern summertime subtropical highs. J. Climate, 18, 5046–5065.
Petty, G. W., 1999: Prevalence of precipitation from warm-topped
clouds over eastern Asia and the western Pacific. J. Climate,12, 220–229.

2046

JOURNAL OF CLIMATE

Raymond, D. J., and A. M. Blyth, 1992: Extension of the stochastic
mixing model to cumulonimbus clouds. J. Atmos. Sci., 49, 1968–
1983.
Redelsperger, J.-L., D. B. Parsons, and F. Guichard, 2002: Recovery processes and factors limiting cloud-top height following
the arrival of a dry intrusion observed during TOGA COARE.
J. Atmos. Sci., 59, 2438–2457.
Schumacher, C., M. H. Zhang, and P. E. Ciesielski, 2007: Heating
structures of the TRMM field campaigns. J. Atmos. Sci., 64,
2593–2610.
——, P. E. Ciesielski, and M. H. Zhang, 2008: Tropical cloudheating profiles: Analysis from KWAJEX. Mon. Wea. Rev.,
136, 4289–4300.
Shige, S., Y. N. Takayabu, W.-K. Tao, and D. E. Johnson, 2004:
Spectral retrieval of latent-heating profiles from TRMM PR
data. Part 1: Development of a model-based algorithm. J. Appl.
Meteor., 43, 1095–1113.
——, ——, ——, and C.-L. Shie, 2007: Spectral retrieval of latentheating profiles from TRMM PR data. Part II: Algorithm
improvement and heating estimates over tropical ocean regions. J. Appl. Meteor. Climatol., 46, 1098–1124.
——, ——, and ——, 2008: Spectral retrieval of latent heating
profiles from TRMM PR data. Part III: Estimating apparent
moisture sink profiles over tropical oceans. J. Appl. Meteor.
Climatol., 47, 620–640.
Short, D. A., and K. Nakamura, 2000: TRMM radar observationsof shallow precipitation over tropical oceans. J. Climate, 13,
4107–4124.

VOLUME 23

Takayabu, Y. N., 2006: Rain-yield per flash calculated from
TRMM PR and LIS data and its relationship to the contribution of tall convective rain. Geophys. Res. Lett., 33, L18705,
doi:10.1029/2006GL027531.
——, J. Yokomori, and K. Yoneyama, 2006: A diagnostic study oninteractions between atmospheric thermodynamic structure
and cumulus convection over the tropical western Pacific
Ocean and over the Indochina Peninsula. J. Meteor. Soc.
Japan, 84A, 151–169.
Takemi, T., O. Hirayama, and C. Liu, 2004: Factors responsible
for the vertical development of tropical oceanic cumulus
convection. Geophys. Res. Lett., 31, L11109, doi:10.1029/
2004GL020225.
Wu, Z., 2003: A shallow CISK, deep equilibrium mechanism for theinteraction between large-scale convection and large-scale
circulation in the tropics. J. Atmos. Sci., 60, 377–392.
Yanai, M., S. Esbensen, and J.-H. Chu, 1973: Determination of
bulk properties of tropical cloud clusters from large-scale heatand moisture budgets. J. Atmos. Sci., 30, 611–627.
Yokoyama, C., and Y. N. Takayabu, 2008: A statistical study onrain characteristics of tropical cyclones using TRMM satellite
data. Mon. Wea. Rev., 136, 3848–3862.
Yuan, J., D. L. Hartmann, and R. Wood, 2008: Dynamic effects
on the tropical cloud radiative forcing and radiation budget.
J. Climate, 21, 2337–2351.
Zhang, C., M. McGauley, and N. A. Bond, 2004: Shallow meridional circulation in the tropical eastern Pacific. J. Climate, 17,
133–139.