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GEOPHYSICAL RESEARCH LETTERS, VOL. 33, L16805, doi:10.1029/2006GL026547, 2006

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ArticleObservations of tropical precipitating clouds ranging from shallow to
deep convective systems
Hirohiko Masunaga1 and Christian D. Kummerow1
Received 10 April 2006; revised 12 June 2006; accepted 13 July 2006; published 22 August 2006.

[1] Regional and temporal variability in a broad spectrumof tropical precipitation systems is investigated inconjunction with the large-scale environment. The
analysis utilizes four storm categories (Shallow, Cumulus
Congestus, Deep Stratiform, and Deep Convective)
determined from Tropical Rainfall Measuring Mission(TRMM) measurements. Deep Stratiform and Deep
Convective systems are found to be clearly correlatedwith large-scale circulation deduced from a reanalysis dataset, and are modulated by a distinct seasonal cycle overland. The Shallow category is practically the only
component of tropical oceanic rainfall for cold sea
surfaces, while it gives way to deeper systems as SST
exceeds 28– 29C. The cloud horizontal scale of organized
rainfall systems tends to be increasingly extensive relative
to the raining portion as the system becomes larger. The
present results are discussed in light of existing relevant
studies. Citation: Masunaga, H., and C. D. Kummerow (2006),
Observations of tropical precipitating clouds ranging fromshallow to deep convective systems, Geophys. Res. Lett., 33,
L16805, doi:10.1029/2006GL026547.

1. Introduction[2] Precipitating cloud systems are a critical geophysicalelement involved in tropical large-scale circulation. A
popular observational tool to investigate tropical convection
on a planetary scale is satellite-measured outgoing longwave radiation (OLR). Satellite OLR serves as a usefulproxy of deep convection, while shallow cumulus clouds
are not detectable by OLR. Less attention has been paid toshallow rainfall than to deep convection because precipitation and diabatic heating ascribed to shallow cumulus are
so limited that shallow clouds per se have a smallerhydrological and dynamical impact to the climate systemthan deep convection. Shallow cumulus, however, is adominant member of tropical convection in number[Johnson et al., 1999; Short and Nakamura, 2000; Lau
and Wu, 2003] and provides a significant fraction of rainfall
under the trade inversion [Schumacher, 2006].
[3] Masunaga et al. [2005, hereinafter referred to as
MLK] analyzed Tropical Rainfall Measuring Mission(TRMM) data to investigate a wide spectrum of tropicalprecipitation systems ranging from shallow cumulus to deep
convection. MLK used TRMM Precipitation Radar (PR)echo-top height and Visible/Infrared Scanner 10.8-mm
brightness temperature (VIRS IR Tb) to classify detected1

Department of Atmospheric Science, Colorado State University, Fort
Collins, Colorado, USA.
Copyright 2006 by the American Geophysical Union.
0094-8276/06/2006GL026547$05.00

rainfall events into the four storm categories of Shallow,
Cumulus Congestus, Deep Stratiform, and Deep Convective. The analysis of MLK focused on testing the proposed
methodology and was thus limited to two months (Februaries of 1998 and 2000) and to three Pacific domains as wellas two tropical continents. In the present paper, the MLK’s
approach is extended to a longer time period with additional
oceanic regions in order to explore more robust climatological signals recorded in the data. The data sets and analysis
methods are described in section 2. The results are presented
in section 3 and summarized in section 4, where implications of the present findings are discussed as well.

2. Data and Methodology[4] The PR 2A23 and VIRS 1B01 products are employedfor PR echo-top height (or ‘‘storm height’’ in the official
terminology) and VIRS IR Tb, respectively, from the
TRMM operational data archives. The TRMM satellite
was boosted from the original altitude of 350 km up to
402.5 km in August 2001. The present analysis is applied tothe pre-boost period so as to avoid the bias that might arise
from a change in the PR sensitivity due to the orbital boost.
Consequently, the time period to be investigated consists of
43 months from January 1998 to July 2001. The same
period from the monthly mean data set of the National
Centers for Environmental Prediction (NCEP)/National
Center for Atmospheric Research (NCAR) Reanalysis dataarchives [Kalnay et al., 1996] is used for pressure verticalvelocity or w at 500 hPa as an indicator of large-scale ascentand subsidence. The daily data set of sea surface temperature (SST) derived from TRMM Microwave Imager (TMI)
measurements is provided by the Remote Sensing Systems(RSS). SSTs at four adjacent quarter-degree grid points fromboth the ascending and descending orbits each day are
combined to mitigate the deficiency of SST data in raining
scenes.
[5] Following MLK, storm categories are defined by PR
echo-top height and VIRS IR Tb as illustrated in Figure 1.
The Shallow category consists of cumulus clouds trapped in
the boundary layer that produce moderate, warm rainfall.
Cumulus Congestus events develop deeper than Shallow
events but not sufficiently to reach the tropopause. Both the
Deep Stratiform and Deep Convective categories havecloud tops as high as the tropopause and are differentiatedfrom each other by PR echo-top height. Deep Stratiform
events do not have an appreciable amount of frozen hydrometeors large enough to be detectable by the PR, whilelarge ice particles are present much higher than the freezing
level for Deep Convective events. Such large frozen particles are presumably generated in deep convective updraft,
and then precipitate across the surrounding stratiform sec-

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Pacific (180– 150W), east Pacific (120W – 90W), Indian
Ocean (60E–90E), Atlantic Ocean (45W – 15W), SouthAmerica, and Africa. All the regions are latitudinally boundby 15S and 15N. This meridional band has been expandedfrom that chosen by MLK (10S – 10N) so that the intertropical convergence zone (ITCZ) remains included in theanalysis during solstice seasons in which the ITCZ migrates
off the equator. Landmasses and islands encompassed in theselected oceanic regions, including the Maritime Continent,
are all masked out.

3. Results
Figure 1. The storm categories, defined based on the joint
probability density function (shaded) of PR echo-top heightand VIRS IR Tb.
tion. The current terminology is parallel to the conventional
convective/stratiform classification to the extent that ahorizontal gradient in PR echo-top height, under the constraint of cold (<245 K in Tb) cloud tops, reflects thecontrast between deep convective cores and stratiform
precipitation areas.
[6] Cloud correlation scale length (CSL) and rain CSL
are defined as a statistical measure of the horizontal organization of precipitating cloud systems. The cloud (rain)
CSL represents how quickly cloud-top height (raining area
coverage) decays with distance as deduced from a large
number of observations. In contrast to the direct estimate ofcloudy/raining areas by counting contiguous satellite pixels[e.g., Nesbitt et al., 2000], the CSL is inapplicable toinstantaneous snapshots of individual storm systems but
has the advantage that the CSL is not very susceptible to thetruncation by satellite swaths. The reader is referred to MLK
for further details.
[7] Geographical regions investigated in this study consist of five oceanic domains and two continents: west
Pacific and Australasian seas (105E – 150E, hereafter
denoted simply as the ‘‘west Pacific’’ for brevity), central[8] The time series of each storm category is shown in
Figure 2 in terms of the monthly frequency of occurrence.
The Deep Stratiform and Deep Convective categories
dominate the Shallow category in the west Pacific except
for the first 5 months in 1998, during which the 1997 – 98 El
Niño episode was still active. The overall trend is inverted
in the central Pacific, where the Shallow category isdominant over others once the El Niño ceases. The Cumulus
Congestus category closely resembles the Shallow category
in the west Pacific, but stays constantly less frequent thanthe Shallow category in the central Pacific. The east Pacificis similar to the central Pacific in terms of the average
population of each storm category, whereas a noticeable
annual cycle, which is absent in the west and central Pacific,
manifests itself in the east Pacific: deep systems overwhelm
Shallow events from April through October. This seasonal
cycle might be related to the enhanced activity of theintraseasonal oscillation in the east Pacific during boreal
summer [Knutson and Weickmann, 1987; Maloney andHartmann, 2000]. Deep Stratiform and Deep Convective
systems are more frequent in the Indian Ocean than in thecentral and east Pacific, although not as much as in the west
Pacific. None of the members of the storm categories areactive in the Atlantic Ocean, where only Shallow events
exhibit a modest seasonal cycle that peaks in July. Atlantic
Shallow events are found suppressed near the African coastin their least frequent phase of the annual cycle (not shown).

Figure 2. The frequency of occurrence of Shallow (red), Cumulus Congestus (green), Deep Stratiform (blue), and Deep
Convective (purple) events as well as w at 500 hPa (histogram) in [Pa/s] labeled on the right-hand axis. Negative w,
indicating large-scale ascent, is defined upward. Each variable is a regionally averaged, monthly mean value shown in atime series from January 1998 to July 2001. Different panels are for different regions as indicated.
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Figure 3. (a) Deep Stratiform and Deep Convective and(b) Shallow and Cumulus Congestus plotted in thefrequency of occurrence versus w plane. A single plot
represents a regionally averaged, monthly mean value.
Negative w, indicating large-scale ascent, is definedrightward.
Matsui et al. [2004] showed the observational evidence that
low clouds are typically not raining in this region, whereaerosol concentration and lower-tropospheric stability are
relatively high. The annual cycle is prominent over theSouth American and African continents especially for deep
systems, as expected from the monsoonal changes ofclimate regime in these regions. The Deep Convective
category prevails over others in Africa.
[9] The temporal variation of the Deep Stratiform andDeep Convective categories is generally well synchronizedwith the 500-hPa w velocity (histogram in Figure 2),
suggesting a close connection between the development of
deep precipitation systems and large-scale circulation in all
study areas. Figure 3a confirms that a higher (lower)
population of Deep Stratiform and Deep Convective systems is well correlated with the large-scale ascent (subsidence). A similar result was obtained by Del Genio andKovari [2002]. This correlation is still clear for Cumulus
Congestus events although the sensitivity to w is weaker
than deep systems. No appreciable relationship with w isfound for the Shallow category (Figure 3b).
[10] The frequency of rainfall occurrence is further broken down by SST for the oceanic domains. Figures 4a – 4dshows the percent occurrence computed individually for
different SSTs. When SST is lower than 27C, Shallow
events are practically the only component of tropical precipitation. Deep Convective systems, however, sharply
increase with SST for warmer sea surfaces, leading the
Deep Convective category to overwhelm other storm categories once SST exceeds 28 –29C. The Deep Stratiform
category also increases with SST although not as markedly
as the Deep Convective. The diverse oceanic regions
delineate a tightly bundled group of curves, topped by the
Atlantic Ocean and east Pacific and bottomed by the west
Pacific and Indian Ocean for Deep Stratiform and Deep
Convective systems. Interestingly, this regional gradient isseemingly contrary to what was shown in Figure 2. A clue
to reconcile the apparent discrepancy lies in the SST
histogram (Figure 4e). SSTs higher than 29C occur much
more often in the Indian Ocean and west Pacific than in the
Atlantic Ocean and east Pacific. The high population ofdeep systems in the west Pacific and Indian Ocean istherefore largely owed to the frequent occurrence of warm

L16805Figure 4. The frequency of occurrence partitioned by SST
for (a) Shallow, (b) Cumulus Congestus, (c) Deep Stratiform, and (d) Deep Convective, separated by different
oceanic regions as indicated Figure 4a. (e) The SST
histogram.
sea surface, and the opposite argument applies to the
Atlantic Ocean and east Pacific.
[11] The CSL estimated for Deep Stratiform and Deep
Convective events is investigated next to examine thehorizontal organization of precipitating clouds. The Shallow
and Cumulus Congestus categories are not considered here
because they are usually not accompanied with substantiallyorganized systems [see MLK]. A slight increase in the cloudCSL is barely recognizable as the frequency of occurrence
increases (Figure 5a), where the correlation coefficient is0.236 for the Deep Stratiform category and 0.416 for the
Deep Convective. Although these correlations are statistically significant compared to the correlation coefficient of±0.148 at the 99% significance level, the tendency is so
subtle that it is not necessarily concluded that a large-scale
environment favorable to the development of deep systems
promotes their horizontal organization, and vice versa. On
the other hand, the cloud CSL and rain CSL are closely
linked with each other (Figure 5b). The cloud CSL is about

Figure 5. Scatter plots for (a) the cloud CSL versus thefrequency of occurrence and (b) the cloud CSL versus therain CSL. A single plot represents a regionally averaged,
monthly mean value. The cloud CSL exceeds the rain CSL
above the solid line given in Figure 5b.

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the same in magnitude as the rain CSL at their bottom endof 100 km, while the cloud CSL tends to be 1.5 times ornearly twice as large where the rain CSL exceeds 200 km.
This result suggests that cirrus anvil clouds detrained fromdeep convection could gain increasingly large spatial extent
compared to the size of the raining portion itself as thesystem is organized on a greater horizontal scale.

4. Discussion and Conclusions[12] The present work seeks to understand the variability
in a broad spectrum of tropical precipitation systems asa function of the large-scale environment. The analysis
method follows that proposed by MLK, introducing
four storm categories (Shallow, Cumulus Congestus, Deep
Stratiform, and Deep Convective) determined by the combination of TRMM PR echo-top height and VIRS IR Tb.
Deep systems are clearly correlated with large-scale circulation, and are modulated by a distinct seasonal cycle
over land. Shallow cumulus is virtually disconnected fromlarge-scale dynamics. Shallow systems are therefore a main
provider of tropical oceanic rainfall in the presence of largescale subsidence, which suppresses deep convection, outside the deep Tropics as observed by Schumacher andHouze [2003].
[13] The dependence of raining cloud populations on SST
are qualitatively consistent across diverse oceanic regions in
the Tropics. Shallow events are ubiquitous over the entire
SST range of tropical oceans, growing slightly in population
as SST increases. Deeper systems do not develop at all forcold SSTs (<27C) but increase rapidly over warmer sea
surfaces. As a result, the dominant mode of tropical rainfall
switches from shallow cumulus to deep convective systems
around an SST threshold of 28– 29C, as also implied bypreceding observational work [Waliser and Graham, 1993;
Del Genio and Kovari, 2002; MLK]. The high sensitivity to
SST for deep systems over warm ocean could be attributed
to local thermodynamic conditions nonlinearly changing
with underlying SST [Sobel and Bretherton, 2000].
[14] Shallow systems are more likely dependent on local
thermodynamic conditions rather than large-scale dynamics.
The thermodynamic role of shallow precipitation in tropicalatmospheres has been discussed in the literature. Increasing
SST would gradually expedite the precipitation efficiency ofshallow cumulus clouds [Lau and Wu, 2003; Rapp et al.,2005], resulting in free-tropospheric moistening that preconditions the development of deep convection [KemballCook and Weare, 2001]. The eventual deep convection isfollowed by stratiform rain that peaks at a later time as
observed at various spatial and temporal scales such as
mesoscale squall lines [Houze, 1977], cloud clusters [Learyand Houze, 1979], the quasi-2-day oscillation [Takayabu etal., 1996], and the Madden-Julian Oscillation [Lin et al.,
2004; Kiladis et al., 2005]. The Deep Stratiform category
appears weaker in its sensitivity to SST than the Deep
Convective (Figure 4). This result could arise in part from a
temporal lag of stratiform rain occurrence behind deep
convection which may have already begun to modify theunderlying SST. One might argue that it could be also
related to the SST-dependent precipitation efficiency of
deep convective clouds as discussed by Lindzen et al.
[2001] in their adaptive iris hypothesis. An extensive

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examination of the iris hypothesis based on TRMM measurements is given by Rapp et al. [2005].
[15] Variation in the population of Deep Stratiform andDeep Convective systems shows only a subtle systematictendency with the horizontal organization of the storms as
measured by the CSL. The organization of precipitation
systems inferably involve dynamic processes that are notdescribable by large-scale environment alone, such as
mesoscale momentum transport [Houze et al., 2000]. The
cloud and rain CSLs are highly correlated with each other,with the cloud CSL growing more rapidly than the rain CSL
above a common lower end of 100 km. This finding has
two intriguing implications. First, so-called super cloudclusters identified from OLR measurements are indeed apractical measure of organized precipitation systems, exceptthat the horizontal scale of high clouds is increasingly‘‘excessive’’ relative to the underlying raining area as thesystem becomes larger. The second implication arises inlight of the Earth’s energy budget. Tropical convective
systems are not only the source of latent heating but also
contribute to the radiative energy budget through theassociated high clouds [L’Ecuyer et al., 2006]. The relative
importance of the cloud radiative heating/cooling is then
expected to be enhanced as the rainfall system develops ona greater horizontal scale.
[ 16 ] Acknowledgments. Stimulating discussions with Tristan
L’Ecuyer and Toshi Matsui and the helpful comments of the reviewers
are greatly appreciated. The TRMM data sets (1B01 and 2A23) were
provided by the National Aeronautics and Space Administration (NASA)
Goddard Space Flight Center (GSFC). NCEP/NCAR Reanalysis data were
provided by the NOAA Cooperative Institute for Research in Environmental Sciences (CIRES) Climate Diagnostics Center (CDC), Boulder, Colorado, USA, from their Web site at www.cdc.noaa.gov. TMI SST data,
available at www.remss.com, are produced by the RSS and sponsored by
the NASA Earth Science REASoN DISCOVER Project. This research is
supported by NOAA’s office of Global Program Grant NA17RJ1228#15
and NASA’s Precipitation Program Grant NAG5-13694.

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C. D. Kummerow and H. Masunaga, Department of Atmospheric
Science, Colorado State University, Fort Collins, CO 80523-1371, USA.
(kummerow@atmos.colostate.edu; masunaga@atmos.colostate.edu)

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