Spatial Distribution of Precipitation and Heat Fluxes over the
North Western Pacific During the Winter Monsoon Season∗

Munehisa Yamamoto1 and Kenji Nakamura2(1: Graduate School of Environmental Studies, Nagoya University,
2: Hydrospheric Atmospheric Research Center, Nagoya University)* Hydrospheric Atmospheric Research Center, Nagoya University, Japan, 464-8601, Furo-cho, Chikusa
Nagoya, Japan. e-mail: s040117d@mbox.nagoya-u.ac.jp

Abstract
Ocean around Japan is well known as the precipitation zone of the winter monsoon. In this region, synoptic
scale disturbances cause large changes of precipitation and cloud distributions. Especially, during the coldoutbreaks, heat fluxes are important role to form the precipitation. Then, we investigated the spatial characteristics of precipitation and the heat fluxes. In this study, Tropical Rainfall Measuring Mission (TRMM)(Precipitation Radar (PR), TRMM Microwave Imager (TMI), and Visible and Infrared Scanner (VIRS)), the
QuikScat SeaWinds, and the National Centers for Environmental Prediction-Department of Energy Atmospheric Model Intercomparison Project (NCEP-DOE AMIP-II) Reanalysis (NCEP2) dataset are used. The
analyzed area is 25◦ –40◦ N, 115◦ –180◦ E.
During the cold outbreak, the height of precipitation reaches around 2 km and precipitation dominates theshallow, isolated, and weak (20 dBZ). Around the extratropical cyclones and fronts, the height of precipitation
reaches around 3 km and precipitation is relatively broad and weak. The solid precipitation over the freezingheight is a few.
The heat fluxes are calculated using the simple bulk formulas. The cold outbreaks make the sum of sensible
and latent heat fluxes possible to reach to about 800 W m−2 . The sensible heat flux over the Japan Sea issimilar to that over the coastal region in the Pacific Ocean. The contribution of the latent heat flux over the
Pacific Ocean is larger than that over the Japan Sea. This is because the difference of the specific humidity
between the sea surface and atmosphere over the Pacific Ocean is larger than that over the Japan Sea due tothe Kuroshio Current. On the contrary, the region around the extratropical cyclones and fronts, the sensible
and the latent heat fluxes are very small. This is because the differences of temperature and specific humidity
between the sea surface and the atmosphere are small.
Keyword: winter precipitation, vertical structure, TRMM.

1. Introduction
Over the mid-latitude oceans, especially northwestern Pacific and north Atlantic area have large amount of precipitation second to the intertropical convergence zone
(ITCZ) (e.g. Fig. 4 in Huffman et al. 1997). These
areas are also well known as the “storm track”, which isthe area where many extratropical cyclones move. The
cyclone is a source of the heat and moisture supplies over
mid latitude area so that it is important to understand theprecipitation system around the area. Theoretical and observational studies have done over the Atlantic area, suchas the Experiment on Rapidly Intensifying Cyclones over
the Atlantic (ERICA) (Hadlock and Kreitzberg 1988) and
Fronts and Atlantic Storm Track Experiment (FASTEX)(Joly et al. 1997), and so on. Contrary, there are few
observational studies over the Pacific region especially in
winter.

amount along this area. However, more process studies
are needed to know further characteristics or mechanisms.
Therefore we focused on the dominant precipitation systems and compared these precipitation characteristics by
the TRMM-PR and TMI data.

2. DataIn this study, TRMM-PR, TMI, VIRS, the QuikScat SeaWinds (QSCAT), and NCEP-DOE AMIP-II Reanalysis(NCEP2) dataset (Kanamitsu et al. 2002) are used. The
period is during 5 winter seasons (1999/2000–2003/04
December–January–February). Analyzed area is over25◦ –40◦ N and 115◦ –180◦ E which covers the area of Japan,
the Japan Sea, the Yellow Sea, and the north western Pacific Ocean (Fig. 1).
120˚

130˚

40˚

140˚

150˚

160˚

170˚

180˚

[K]

300
290
280
270
260
250
240
230
220
[dBZe]
45
40
35
30
25
20
15

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The Tropical Rainfall Measurement Mission (TRMM)
satellite carries the Precipitation Radar (PR), the Microwave Radiometer (TMI), and the Visible Infrared
Scanner (VIRS), which enable to directly measure thehorizontal and vertical distribution of precipitation. Kodama and Tamaoki (2002) investigated the climatology
of vertical characteristics of winter precipitation over thenorthwestern Pacific area (c.f. similar analysis in springand summer shown in by in Fu and Liu (2003)). Theysuggested from the vertical structure of precipitation observed by PR that shallow stratiform and convective precipitation largely contributed to the total precipitation

CO-Y

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30˚

1000

120˚

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160˚

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180˚

Fig. 1: Spatial distributions of (a) GMS-IR image,(b) SST, (c) divergence (contoured only negative values) with wind vector (arrow), (d) sensible heat fluxand (e) latent heat flux. On (d) and (e) positive value
indicates color contour and negative value indicatescontour line.



3. Results
3.1. Vertical structure of Winter Precipitation

Winter precipitation patterns are subjectively classified
with the cloud pattern into the two types; the extratropical cyclone and front (CF) pattern and the cold outbreak(CO) pattern. For the CO pattern, it is furthermore divided into three categories according to regions, that is,over the Japan Sea (CO-J), over the Yellow Sea (CO-Y),
and over the Pacific Ocean (CO-P). Figure 1 shows anexample in an orbit. The surface chart indicated thatan extratropical cyclone located about 34◦ N and 160◦ E,
and typical surface disturbances appeared over its western side. Over the Japan Sea, clear JPCZ appeared. The
classification was enforced by the same method for the allorbits in the analyzed period. The samples for the CO-J
and CO-Y pattern are relatively fewer than that of the
CO-P and CF pattern because the sampled area is small.
However, the samples are enough to analyze in this study.
Figure 2 shows the contoured frequency of altitude diagrams (CFAD) made from PR2A25 Z factor and histograms of the CloudH, the FreezH, the StormH, and theBBH for each pattern. The CFADs indicate the percentages of frequency in every altitudes.
For the CO pattern (Fig. 2a–c), precipitation echoes
are centered in 18–22 dBZ (about 0.2–1 mm h−1 ) below 2
km. The CFADs show the precipitation is relatively weak
and its vertical distributions are similar for the CO-J and
CO-Y pattern (Fig. 2a, b). These downward decreasecharacteristics correspond to the convective snow bands
with anvil over the Japan Sea, probably due to evaporation (Sakakibara, 1988). The vertical distribution for
the CO-P pattern (Fig. 2c) has downward increasing feature compared with the CO-J and CO-Y pattern. We  !

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Altitude [km]We used only the nadir ± 5 angle bins of the PR swath.
This corresponds to '500 m free cutter level. Because thefrequency of echo top height dominates '2 km ASL overthe north western Pacific region in winter (Kodama andTamaoki 2002), PR does not well observe precipitation
precisely on the edge of swath due to surface clutter by
about 2 km. The VIRS data are fitted into PR’s narrowswath. We made 0.05◦ × 0.05◦ datasets for PR and VIRS
to fit into the same resolution.
In the PR2A23 algorithm, the FreezH is estimatedfrom the monthly mean SST and a constant lapse rate (6K km−1 ) (hereafter FreezHPR2A23 ). This estimation is ingood agreement in the tropic because both intra-monthand inter-annual variability is low. However, the spatiotemporal variation of the FreezH over the mid-latitude
region is large (Harris et al. 2000). Thus, the FreezH derived from NCEP2 (hereafter “FreezHNCEP2 ”) is newly
defined. The FreezHNCEP2 is calculated that the 2.5◦
× 2.5◦ NCEP2 temperature and the geopotential heightdatasets are linear-interpolated spatiotemporally. The
cloud top height (CloudH) is also calculated using the IR
brightness temperature and the same method of PR2A23
vertical temperature estimation (CloudHSST ) and the interpolation using NCEP2 data (CloudHNCEP2 ). In addition, the BBH was re-calculated by the V-method to
remove the restriction that BBH should be within ±1.5
km from the FreezHPR2A23 .

6
4
2

2

0

0
0

5 10 15 20

0 10 20 30 40
Count [%]

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Count [%]

Fig.
2: CFAD (color image) of Ze factor
with in the TRMM-PR2A25 product (left panel),and the vertical histograms of the StormH (greenline), the CloudHSST (red dotted line), and the
CloudHNCEP2 (red solid line) (right panel with left
ordinate). Also plotted are the BBH (black solidline), the FreezHPR2A23 (blue dotted line), and theFreezHNCEP2 (blue solid line) (with right ordinate)in the case of (a) CO-J, (b) CO-Y, (c) CO-P, and (d)CF pattern.
further divided the CO-P pattern into 6 categories by theFreezHNCEP2 every 500 m (FreezHNCEP2 < 1 km) and
250 m (1 km < FreezHNCEP2 < 2.5 km) (not shown).
When the FreezHNCEP2 below 1 km, the CFADs are very
similar to the CO-J and CO-Y patterns. In the case of
1 km < FreezHNCEP2 < 2 km, the CFADs are similar
to whole CO-P pattern (Fig. 2c) because the class of thiscase is maximum. When the FreezHNCEP2 over 2 km, the
CFADs are also similar to those patterns. Compared with
FreezHNCEP2 , the peak dBZ is '1 km, so that it indicatesmaybe BB. As the FreezHNCEP2 is lower, the peak dBZ isalso lower. The downward increase pattern for the CO-P
pattern shows due to the BB near the surface.
These characteristics are also shown in the PR2A23
rain type classification (not shown). The percentages of
the rain flags of 12, 14, 15 (H-method = stratiform andV-method = others) in PR2A23 for the CO-J, CO-Y,
and CO-P pattern are 83.8%, 89.3%, and 76.3%, respectively. This suggests two reasons: 1) the weak precipitation without BB is dominant or 2) the BB detection is
failed because the FreezHPR2A23 overestimates comparedwith FreezHNCEP2 . The rain flag of 21 (H-method = convective and V-method = others) which means the convective precipitation cells are included. That of the CO-P and
the CO-J patterns are 15.7 % and 6.6 %. These pixels arein the strong precipitation with lightning and convergencezone (e.g. JPCZ). Compared with the CO-J and CO-Y
pattern, the CO-P pattern has large percentages of rainflags of 21.
Maximum numbers of the StormH is distributed at 2km and few echoes reach 4 km. Paying attention to eachpercentage of StormH / CloudHNCEP2 , it is higher in or-(a) CO-J pattern

In this section, we compare the each precipitation system among the patterns with the horizontal scale. Precipitation intensity (Z factor) increases as the system becomes larger common to all patterns by a certain size(not shown). It is reasonable because the cold air mass
supplied the sensible and latent heat from the relatively
warm ocean, and the convective clouds grow vertically andhorizontally due to the thermal stratification becomes unstable from the bottom as the fetch is longer for the CO
pattern. For the CF pattern, large systems contains theactive convective region, however, stratiform region withweak precipitation also includes.
Figure 3 shows the prevailing size of each precipitation
pattern. The radius of precipitation systems below 10 km
dominates for all patterns. However, the CO-P and theCF pattern contain a few percentages larger for medium(r = 10–100 km) and large (r > 100 km) scale of precipitation system than the other patterns. In other words,
during the CO, the precipitation systems over the Pacific
Ocean are apt to form the larger scale than that over theJapan Sea and the Yellow Sea. For the CF pattern, it
is reasonable to form the large scale precipitation aroundthe extratropical cyclone and front.
Most of systems have 2 km stormH, and its aspect ratio
is 1–3 common to the CO-J, CO-Y and CO-P pattern. Below 2–3 km, the systems broaden as the stormH is higher.
However, above the altitude, the systems narrow rapidly,
especially for the CO-J and CO-Y patterns. These characteristics show the precipitation system cannot develop
upward due to subsidence of the upper cold air mass. The
strength of subsidence appears as the rapid decrease of
the aspect ratio. What the larger systems are containedin the CO-P pattern corresponds to the strength of subsidence. We also further classified in some categories by theFreezHNCEP2 for the CO-P pattern as well as the previous
section, however, there are no significant different.
For the CF pattern, distributions of pixels are similar to
the CO patterns below 2km. However, the aspect ration
remains large. It shows that horizontally and verticallylarge precipitation systems are contained. Especially, thelarge scale of precipitation systems has more than 3 km
stormH.

3.3. Spatial variation in heat fluxes andwind field

10(b) CO-Y pattern25

100

r [km] = 2.5

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Altitude [km]3.2. Horizontal scale of Winter Precipitationr [km] = 2.5

Altitude [km]der of the CO-P, CO-Y, and CO-J pattern. It is the samewith the distributions of the FreezHNCEP2 and the percentages of warm rain flag. The reason may be because
the PR is sensitive for solid precipitation.
For the CF pattern (Fig. 2d), vertical distribution of
precipitation echo is downward increasing and its variation is large (20–32 dBZ (0.3–4 mm h−1 ) near thesurface. It means that relatively strong precipitations
with fluctuations are included for the CF pattern. The
maximum frequency of the StormH appears around 3km, and some echoes reach to above 6 km and the
CloudHNCEP2 distributed around 6 km. The percentage of the stratiform certain flag from PR2A23 is 53.5%.
FreezHPR2A23 distributed around 3 km which corresponds
to FreezHNCEP2 .

0.03
0

0.01
0
1
Aspect Ratio [10x]2Fig. 3: CFAD (color image) of aspect ratio and radius of precipitation system (solid lines) in the case of(a) CO-J, (b) CO-Y, (c) CO-P, and (d) CF pattern.
We investigated the spatial variations of heat fluxes fromthe ocean by the simple bulk method using the fine gridobservational data. The sensible and latent heat flux are
calculated as follows:H
lE=

Cp · ρ · CH · |U1000 hPa | · (TSST − T1000 hPa )(1)∗= λ · ρ · CE · |U1000 hPa | · (qSST− q1000 hPa )(2)
CH = CE = 1.2 × 10−3(3)where H is the sensible heat flux, Cp , λ and ρ are the specific heat capacity at constant pressure, the latent heat ofvaporization that is the function of temperature, and thedensity of air, respectively. U , T , q are the wind speed,
temperature, specific humidity, subscripts SST and 1000hPa denote the sea surface and 1000 hPa. CH and CE
are the bulk transfer coefficients for sensible heat and latent heat fluxes. This study simply used the constantvalue of 1.2 × 10−3 . For SST and wind speed data, SST
derived from TMI and QSCAT wind data with 0.25◦ ×
0.25◦ data are also used. For the temperature and relative
humidity, there are no observational data over the ocean
besides the remote sensing. Thus, 0.25◦ × 0.25◦ dataset
is generated by interpolation from NCEP2 with 2.5◦ ×
2.5◦ data to match other data. QSCAT passes over the
analyzed region at 18-21 UTC for morning pass. In order to synchronize the observational time, GMS-IR image,
NCEP2 data and surface weather charts at 18 UTC areused. The divergence and vorticity near the surface arealso calculated from the QSCAT dataset using a methodby Sharp (2002). Although this method is for the early
detection of tropical cyclone, it is useful for his purpose.
First, divergence and vorticity are calculated by the centered difference operation. These values of divergence areused to see the small scale convergence and divergence
field. Vorticity was averaged to detect the extratropical
cyclone and front. The spatial scale for averaged vortic-

ity is a 7-pixels (175 km) by 7-pixels box centered on theswath points.
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Fig. 4: Spatial distributions of (a, f) GMS-IR image,(b, g) SST, (c, h) divergence (contoured only negative values) with wind vector (arrow), (d, i) sensible
heat flux and (e, j) latent heat flux (positive value
indicates color contour and negative value indicatescontour line) in the case of CO pattern at 18UTC
14th January 2001 (left panel) and the case of CF
pattern at 18 UTC 26th January 2001 (right panel).
In this section, we show the two cases for the typical patterns (Fig. 4). One case is on 14 January 2001,
when the strong CO appeared (Fig. 4a). The JPCZ wasclearly shown in the image of GMS-IR, and the Benald
form clouds spread over the Pacific Ocean along the south
coast of Japan. These clouds correspond to the convergence area (Fig. 4c). Keep this phenomenon in mind,
spatial variations in sensible and latent heat fluxes aredescribed (Fig. 4d, e). From the Japan Sea to the Pacific Ocean, sensible heat flux was high (about 800 W
m−2 ) distributed and weakened southerly. Over the eastern part (160◦ –), the sensible heat flux is in almost zeroor minus. The latent heat flux was strengthened from thebase of continent to the southern coast of Japan, and was
weakened to the offing from the south coast of Japan, as
fetch is longer. It can be explained reasonably. According
to meteorological parameters to calculate the heat fluxes,
the SST pattern clearly shows the warm Kuroshio Current over the near south coastal zone of Japan (Fig. 4b).
Corresponding to location of Kuroshio, ∆T and ∆q arealso large (about +20 ◦ C, +12 g kg−1 , respectively) (notshown). On the contrary, it was dry condition in the atmosphere over the east coast of Japan (35◦ − 40◦ N and150◦ E) (not shown). Specific humidity was small due to
low temperature in condition. As the results of this, thesensible and latent heat fluxes are strengthened.
In 26 January 2001, extratropical cyclones were locatedat the 32◦ N and 136◦ E, and 36◦ N and 158◦ E (Fig. 4f).
Here, in this case study, the extratropical cyclone at 36◦ N
and 158◦ E and the warm core over the southern part arefocused. From the GMS-IR image in Fig. 4f, high cumulus cloud was observed, corresponding to the cold front
along 30◦ N and 150◦ E to 33◦ N and 157◦ E. There is broad
convergence area over this region and relatively strong
convergence zone are indicated at the north of extratropical cyclone (Fig. 4h). Over the northern part, thewind was counterclockwise with strong speed. Over thenorthwestern region of the extratropical cyclone, positive
vorticity is strengthened (not shown). The sensible andthe latent heat flux was indicated almost zero and minus
value (Fig. 4i, j). According to the each meteorologicalparameter (not shown), under cloud-covered area, ∆T was
negative. The relative humidity is near 100 %, and thespecific humidity was more than 10 g kg−1 . Besides, ∆q
was near zero at the south of the extratropical cyclone. A
series of results shows that the warm and moisture advection was brought from the southwest. While both sensible
and latent heat fluxes indicated quite high values around34◦ N and 148◦ E. On the SST distribution (Fig. 4g), relatively warm SST (20◦ C) is distributed around the 35◦ N
and 150◦ E, although Kuroshio Current cannot be clearlyseen around the south of Tokyo due to the continuous precipitation. In the result, ∆T indicated 10◦ C over there.
Similarly, ∆q was also high associated with high SST.
In addition, the wind speed was quite strong around thesouthwest of extratropical cyclone. Such combinative factors leads high sensible and latent heat flux around 34◦ N
and 148◦ E.

4. Conclusion
Figure 5 shows the schematic diagrams on each patternof vertical structure with thermodynamic environment on
the sea surface. The characteristics which are shallow isolated precipitation are similar among the CO patterns.
The heat fluxes have important role to form the pattern.
Energy contribution from the surface among the CO patterns is similar, but their partitioning ratio is different.
On the contrary, the broad but shallow precipitiation isdominated in the CF pattern. The contribution to the formation and development of precipitation system for theheat fluxes is small.
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the CO pattern. But added the effect of lower environments. Cloud area is inside the bold line, gray contoured area and dots are precipitation and its phase(∗; solid precipitation, 0:liquid precipitation )References
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