Spatial and diurnal variation of precipitation systems over Asia
Masafumi Hirose1 and Kenji Nakamura21). JAXA/EORC, Japan,2). HyARC, Nagoya University, JapanABSTRACT
The spatial and diurnal variation of rainfall over Asia was investigated using the spaceborne radar data for
four seasons during 1998–2003. The regional variation of the prevailing precipitation systems most closely
associated with the maximum hourly rainfall was shown by examining the fine-spatial distribution of rainfall
amount and scale-based precipitation systems.
Small precipitation systems (< 102 km2 ) occurred most frequently around early afternoon over most land.
The south-facing slopes of the Himalayas, especially south of Mount Evelest and the upper portion of theBrahmaputra valley, is the most obvious region of the daytime genesis of the cumulus-scale systems over
the Asian landmass. Over the Tibetan Plateau, the occurrence of the small systems was larger than overinland India and the foothills. Large systems (> 104 km2 ) developed mostly in the evening over near-flat
landmasses. Wide-spread systems with intense rain pixels developed over the foothills of the Himalayas inlate night-early morning period, that was distinct from the daytime-convection. Over ocean, in addition tothe morning signature, spatially inhomogeneous and systematic characteristics were evident over the offshore
region, for example, around the Maritime Continent.
Large systems, which are strongly associated with terrain, have a great influence on the total number ofrain pixels and the total amount of rainfall. For 86 % of the region where large system is dominant, the timeof maximum rainfall is within 3 hours of the time of maximum rainfall for large systems.

Introduction
The first spaceborne Precipitation Radar (PR) on the
Tropical Rainfall Measuring Mission (TRMM) satellite has provided a unique opportunity to observe thespatial variability of the seasonal and diurnal cyclesof precipitation systems. It has observed precipitation
structure evenly over land and ocean for various local
times from its non-sun synchronous orbit since the endof 1997. The representation of the universal and local
characteristics is a good step to obtain some insight
into the mechanisms of the different types of convective activity.
Several investigations of the diurnal cycle with theTRMM PR showed general characteristics in bulk overrelatively wide regions considering the temporal andspatial resolution. They mainly focused on continuously variable physical properties and implicitly included regional characteristics of many different kinds.
For observational studies by one non-sun synchronous
orbital satellite sampling remains the substantive problem. In order to take the sampling variabilites evenly
or to detect the first few harmonics accurately, the spatial and temporal resolution of TRMM data analyses
have been coarse (e.g., Nesbitt and Zipser 2003). However, high spatial frequency features should be examined to understand relationships between precipitationand the topography (Lang and Barros 2002). In thisstudy, understanding global and regional characteristics of rainfall by fine-scaled analyses is sought using

TRMM PR data. It will help to extract precipitation
regimes influenced by the topography or geography.
The target domain is Asia, which is known for significant seasonal and diurnal variation of rainfall and convective activity. The purpose of this study is to show
the spatiotemporal variation of the prevailing precipitation systems by examining the diurnal variation ofprecipitation properties.

Sampling biases on diurnal variation
Six years (1998–2003) of rainfall rate data were usedin this study. In order to cope with sampling biases,
we calculated monthly and hourly rainfall amount using the number of samples for each hour in each month,and then averaged the hourly data for multiple months.
The procedure was performed for all regional and gridded analyses in this study. The grid scales were 0.2
and 1 degree as shown in the following section. In thecase of August, monthly rainfall with disregard to thesampling biases was about 10 % overestimated overTibet in conjunction with the afternoon rainfall (notshown). The spatial frequency of rain is the numberof rain pixels divided by the total number of observed
fields of view (FOVs), that is, a normalized rain area
in each grid. Peaks of rainfall or spatial frequency ofrain used the hourly data averaged with plus and mi-nus one hour data to smooth the temporal variation.
Thus, hourly rainfall amount and spatial frequency ofrain are obtained. Such modification should be considered when one studies seasonal and diurnal variation of rainfall or the number of systems, especially incases with a weak diurnal signature, such as over ocean
at midlatitudes. It should, however, be kept in mind
that these methods possibly exaggerate hourly rainfall
amount over lightly sampled regions, especially overthe midlatitudes (around 35◦ latitude, e.g., over Japan)
and over the tropics showing checkerboard patterns inthe sampling (Negri et al. 2002). Although the total
number of samples in the midlatitudes is about fourtimes larger (twice a day) than that around the equator, the minimum number of hourly samples is muchsmaller if three years of data are used. A few clock
hours remain poorly covered for the monthly dataset
during three years (e.g., Kishtawal and Krishnamurti2001). Using TRMM data for more than six years has
greatly improved the temporal sampling.

Spatial variation of time of maximum rainfall
The diurnal cycle of precipitation does not simply exhibit sinusoidal behavior and may not be well represented in harmonic analysis (e.g., Ohsawa et al. 2001).
For the purpose of clarifying the prevailing precipitation systems, we focus on the spatial variation of
the time of maximum rainfall. Figure 1 shows thetime of maximum rainfall during June–August. Overocean where the diurnal signature is generally weak
and over regions with few samples in the checkerboard
patterns (Negri et al. 2002), hourly-rainfall amount exhibits sharp fluctuations due to the few rain samples.
We de-emphasized the pixels having negative anomaly
one-hour before or after the time of maximum rainfall (light-colored shadings). We mainly focused onthe significant diurnal features with the consecutive
positive anomalies for more than three hours (darkcolored shadings). Pixels with few rain samples (thespatial frequency of rain < 1 %) were excluded. A rain
frequency of 1 % corresponds to precipitation systems
covering a 0.2◦ ×0.2◦ grid box around the equator morethan 40 rain samples (more than two overpasses) for
consective three months during 1998–2003.
During June–August, the rainfall distribution
spreads farther into the foothills of the Himalayas,
and the Tibetan Plateau (Fig. 1). Early–afternoon(14–16 LT) rainfall is conspicuous over most of theTibetan Plateau and other regions higher than 2000
m. In detail, even over 4000 m, nighttime (18–4 LT)
rainfall prevails south of the peaks of the Himalayas(> 5500 m). The terrain-forced diurnal pattern may
be explained by the effects of the gravity wave andthe regional–scale circulations (e.g., Barros and Lang
2003). Eastern Tibet shows an evening peak. Major
mountains and valleys on the plateau are aligned along
an east-west direction. The valley region along with

the Yarlung-Zangbo river clearly shows maximum rainfall in the late evening. The spatial inhomogeneities ofmountains and valleys seem to modulate the afternoon
and morning rainfall maximum (e.g., Kurosaki andKimura 2002). Tibet clearly shows the topographic
dependence of the diurnal cycle since the environment
would be suitable for generating afternoon dominatedsystems. The lower southern side of the steep slopes
widely show maximum rainfall in the midnight to earlymorning period. In view of the spatial uniformity ofthe time of maximum rainfall, most of the regions
south of the Himalayas and the Sichuan Basin would
have the significant diurnal signal although they arede-emphasized due to the sharp fluctuation shown in
the following section. The northeastern part of Thailand, the mideastern part of India, and the eastern partof the south foothill of the Himalayas including theBrahmaputra valley (around 27◦ N, 93◦ E) show earlymorning rainfall maxima as reported by previous research (Barros and Lang 2003). The foothills on theAravalli range (∼ 250 m in altitude), show near-dawn
rainfall maxima. As well as the south-facing slope ofthe Himalayas, the Sulaiman Range (northwest of theThar desert) also has rainfall maximum in the afternoon. Over a large part of China, afternoon rainfallappears (Kato et al. 1995) in this season. Maximum
rainfall in the southern part of the Bay of Bengal andnearby coast appears in the early-afternoon and in themorning, respectively. This may be associated withsouthward advection of precipitation systems and land
effects studied by Zuidema (2003). Unlike other tropical islands, evening peak appears around ocean westof Luzon island, where the monsoonal flow converges.
The Maritime Continent is known as the region withthe most significant diurnal signal (e.g., Nesbitt andZipser 2003). Afternoon rainfall is dominant over thecoastal regions and relatively higher mountains such as
the Barisan Mountains on the island of Sumatra (thesouthwestern side), the Maoke and Bismarck Mountains on the island of New Guinea (the center line overnorthwest–southeast), and the Iran Mountains on theisland of Kalimantan (the northwestern part). On thelower part of these mountains, the peak time of rainfall shifts to evening–midnight (18–2 LT). This figureclearly shows that it is important to consider the island properties of not only the area of the island but
also the topography and the shape in order to understand the diurnal cycle over the islands. The time ofmaximum rainfall over the adjacent ocean seems to be
shifted from midnight to late morning from the coast
to offshore.

Impact of the scale–based systems
in rainfall
A “precipitation system” is defined as contiguous raincertain pixels observed by TRMM PR (Hirose andNakamura 2004). Here, the scale-based precipitation systems were grouped into the three classifica-Figure 1: Seasonal differences of time of maximum
rainfall at each 0.2◦ ×0.2◦ grid for June–August. Darkcolored shading indicates that rainfall within 1 hourof the time of maximum rainfall preserves positive
anomalies. Topographic contours are drawn with 200,2000 (thick), and 4000 m, respectively. Pixels with few
rain samples that the spatial frequency of rain was lessthan 1 % are blanked out.

tions; small “cumulus-scale” systems less than 100
km2 , medium systems with rain area between 100–
10000 km2 , and large systems greater than 10000 km2 .
Over a large part of the landmasses, there is a clear tendency for a change of prevailing systems from small tolarge through the afternoon and evening (not shown).
In order to generalize the local characteristics, the impact of each scale systems was focused upon. Figure 2shows the time of maximum rainfall for each scale ofsystems. Where the time of maximum rainfall is notwithin 3 hours of the time of maximum rain frequency(normalized bulk rain coverage), the grid box is givena white edge. The rainfall is temporally averaged asFig. 1. For 75 % of the grids over land and 67 % overwater the time of maximum rainfall is within 3 hours of
the time of maximum rain frequency (the top panel).
Over the regions with strong correlation, the prevailingsystems which provide large amounts of rainfall could
be understood in terms of the largest spatial frequencyof rain providing maximum rainfall amount for eachsystem classification by horizontal scale. On the otherhand, the places for which the time of maximum rainfall does not correspond to that of maximum rain frequency need to be considered in terms of the strengthof rain. In the case of the mature monsoon season
over India, the number of heavy rainfall rates decreased
while the number of large systems increased, so thatthe averaged rain intensity changed even for similar
scale systems between different precipitation regimes(Hirose and Nakamura 2004). Such contribution of relatively small (large) but intense (weak) precipitation
systems and significant rainfall with minor frequency
appeared on the white-edged grid boxes in Fig. 2. Over
land, a large number of the grids showed an afternoon

rain maximum implying that the rain coverage had less
impact than heavy afternoon rain.
The second panel shows a clear contrast between afternoon rain over land and morning rain over ocean.
Small systems generally dominate in the early afternoon over land even over mountains. In detail,higher regions such as over the Tibetan Plateau andthe northern part of the Indochina Peninsula include
late morning rainfall. Over ocean, there are regionaltrends. Near-dawn peaks are shown over the southernpart of the East China Sea, early morning peaks overthe northern part of the East China Sea and the Indian Sea, midnight to early morning peaks around theopen ocean under the Pacific High. The third panel
shows the case of medium systems. The peaks overland shift later. Nighttime maxima are seen over theHimalayas and the eastern mountains of the Indochina
Peninsula. Japan has an evening rain peak surroundedby early morning rain over the nearby ocean. Largesystems (the bottom panel) show the geographical pattern more clearly. The early morning peaks are clear
around the lower side of high terrain such as south ofthe Himalayas, the lower region in the Maritime Continent such as east of the Barisan Mountains, and themideastern part of the Decan Plateau. The evening
peaks over the Tibetan Plateau, inland India, lowlandof the Indochina Peninsula are localized. The contrast
between the eastern and the western part of the southern facing Himalayas is clearly shown as early morning and near dawn peaks, respectively. Over ocean,morning rainfall dominates. Rainfall over the adjacent ocean west Luzon Island where large systems frequently occur has a late-evening peak. That is different
from the morning peak west of the Indochina Peninsula. Over the southern Bay of Bengal, the afternoon
signature is shown. By comparison with the time ofmaximum rainfall in the top panel, few but large systems affect the total rainfall significantly. For example,
the pattern of large system occurrences is similar tothat of maximum rainfall over the southern part of theHimalayas, the eastern part of the Tibetan Plateau,
the Sichuan Basin, the Maritime Continent, the oceanwest of the Indochina Peninsula, and inland India. Numerous large systems prevail in the Bay of Bengal inthe morning.
We investigated the rain area fraction of large precipitation systems from June to August (not shown).
The fraction indicates % of total spatial frequency ofrain due to large systems. For 56 % of the region, thetime of maximum rainfall coincides with the time ofmaximum rainfall for large system. The region wherethe phase lag is within 3 hours accounts for 81 % of thedomain. For 60 % of the region, the rain area fractionof large systems is greater than 50 %. And 86 % of theregion where large system is dominant has the phaselag within 3 hours. The significant proportion indicates that the variation of large systems is the prime
factor in regional characteristics of rainfall. The timeof maximum rainfall is a few hours prior to the peak oflarge systems over the Tibetan Plateau. The impact oflarge systems is not significant over the region wherethe rain area fraction of large systems is less than 30%.

precipitation climatology and the mechanisms therein
more specifically. Again, understanding the dynamic
state of large systems is of prime importance. Fuller
studies on the genesis of the precipitation systems needmore comprehensive analyses with atmoshperic properties.
Acknowledgements. This paper is currently underreview by JGR. The authors would like to express theirgratitude to the members of the TRMM project, especially in JAXA/EORC. The authors would like toexpress their gratitude to Prof. T. T. Wilheit, T.N.
Rao, Mr. B. C. Bhatt and Ms. P. Singh for theirconstructive comments.

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Figure 2: Time of maximum rainfall for scale-based
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Concluding remarks
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