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Persistent Spring Shortwave Cloud Radiative Effect and the AssociatedCirculations over Southeastern China
JIANDONG LI,a,b WEI-CHYUNG WANG,c JIANGYU MAO,a ZIQIAN WANG,d GANG ZENG,b
AND GUOXING CHENc
a State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, ChinabCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of
Information Science and Technology, Nanjing, ChinacAtmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York
d School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
(Manuscript received 19 June 2018, in final form 26 February 2019)
ABSTRACT
Clouds strongly modulate regional radiation balance and their evolution is profoundly influenced by cir-
culations. This study uses 2001–16 satellite and reanalysis data together with regional model simulations to
investigate the spring shortwave cloud radiative effect (SWCRE) and the associated circulations over
southeastern China (SEC). Strong SWCRE, up to2110Wm22, persists throughout springtime in this region
and its spring mean is the largest among the same latitudes of the Northern Hemisphere. SWCRE exhibits
pronounced subseasonal variation and is closely associated with persistent regional ascending motion and
moisture convergence, which favor large amounts of cloud liquidwater and resultant strong SWCRE.Around
pentad 12 (late February), SWCRE abruptly increases and afterward remains stable between 228 and 328N.
The thermal and dynamic effects of Tibetan Plateau and westerly jet provide appropriate settings for the
maintenance of ascending motion, while water vapor, as cloud water supply, stably comes from the southern
flank of the Tibetan Plateau and South China Sea. During pentads 25–36 (early May to late June), SWCRE is
further enhanced by the increasedwater vapor transport caused by themarch of EastAsianmonsoon systems,
particularly after the onset of the South China Sea monsoon. After pentad 36, these circulations quickly
weaken and the SWCRE decreases accordingly. Individual years with spring strong and weak rainfall are
chosen to highlight the importance of the strength of the ascending motion. The simulation broadly repro-
duced the observed results, although biases exist. Finally, the model biases in SWCRE–circulation associa-
tions are discussed.
1. Introduction
Clouds play significant roles in climate systems by
modulating the radiative energy budget and hydrologi-
cal cycle. The importance and complexity of cloud
physics processes cause them to contribute the biggest
uncertainty in current climate simulations and predictions
(Stephens 2005; Boucher et al. 2013). Cloud formation,
type, and spatial distribution are deeply affected by general
circulations and then exhibit distinctive regional features
(Rogers and Yau 1989; Bony et al. 2015). Southeastern
China (SEC) is located in the East Asian monsoon re-
gion, which is characterized by prevailing monsoon cir-
culations and complicated topography. Meanwhile,
large amounts of continental stratus clouds and strong
cloud albedo effect are distributed in SEC (Klein and
Hartmann 1993; Yu et al. 2001, 2004). Due to monsoon
circulations, cloud radiative characteristics over SEC
also have remarkable seasonal variation, with strong
winter–summer contrast (Luo et al. 2009; Li et al.
2017a). At present, climate models show evident biases
of shortwave cloud radiative effect (CRE) at the top of
the atmosphere (TOA) and cloud cover over SEC,
Denotes content that is immediately available upon publica-
tion as open access.
Corresponding author: Dr. Jiandong Li, [email protected]
This article is licensed under a Creative Commons
Attribution 4.0 license (http://creativecommons.org/
licenses/by/4.0/).
VOLUME 32 J OURNAL OF CL IMATE 1 JUNE 2019
DOI: 10.1175/JCLI-D-18-0385.1
� 2019 American Meteorological Society 3069
where a large regional cloud albedo effect is particularly
underestimated (Flato et al. 2013; F. Wang et al. 2014).
These model biases significantly contribute to the un-
certainties of regional cloud feedbacks and climate
projections. Thus, accurate simulation of climate pro-
cesses over East Asia requires a more in-depth un-
derstanding of cloud radiation characteristics over SEC.
In addition to the winter–summer monsoon period,
spring is another distinctive period over SEC, where
persistent spring rainfall is a unique regional climatic
phenomenon (Tian and Yasunari 1998; Wan and Wu
2007). In this region, the spring rainfall contributes more
than 30% of the total annual precipitation (LinHo 2008;
Wu and Mao 2016) and also has obvious subseasonal
and interannual variation (Pan et al. 2013; Huang et al.
2015). The anomalies of spring rainfall and relevant
circulation exert great impacts on the weather, climate
processes, agriculture, and socioeconomics of this region.
It is noted that distinct spring shortwave CRE (SWCRE)
also appears over SEC. Work by Wang et al. (2004) and
Li et al. (2017a) withmonthly datasets showed that strong
SWCREover SEC occurs in winter and persists until full
spring. As shown in Fig. 1, spring mean SWCRE over
SEC (around 1048–1228E and 228–328N) is the strongest
at the same latitudes of the Northern Hemisphere with a
maximum value of up to 2120Wm22, the intensity of
which is much larger than over the eastern coasts of the
Pacific (Fig. 1a). Unlike the usual amount of spring
precipitation in SEC, sparse precipitation occurs over
the eastern coastal regions of the Pacific where de-
scending motion prevails (Fig. 1b). Meanwhile, the
spring SWCRE averaged over SEC is the largest of the
four seasons (Fig. 2). So robust spring SWCRE certainly
exerts a nonnegligible force on the regional climate
system. Moreover, spring is the winter–summer transi-
tion season, and cloud roles in radiation budget and at-
mospheric heating potentially affect the following
migration of East Asian summer monsoon circulation
(Guo et al. 2015; Li et al. 2015). Figure 1 also shows that
the spatial pattern of SWCRE is somewhat similar to
that of rainfall over the midlatitudes of the Northern
Hemisphere. Hence, it is very important to investigate
spring CRE over SEC for understanding the radiation
budget and hydrological cycle, and their seasonal tran-
sition in East Asia.
Some previous work noted that spring cloud radiative
characteristics over SEC are connected with regional
circulations to some extent. Yu et al. (2001) suggested
that the convergence below 700hPa in winter and spring
helps to the middle to low cloud formation over eastern
FIG. 1. Geographical distributions of spring mean [March–May (MAM)] (a) top-of-the-at-
mosphere shortwave cloud radiative effect (SWCRE; Wm22) derived from CERES-MODIS
(Clouds and the Earth’s Radiant Energy System–Moderate Resolution Imaging Spectroradi-
ometer) and (b) precipitation (mmday21) from the Global Precipitation Climatology Project
during the period of 2001–16. The black solid line is the Tibetan Plateau (over 3000m).
3070 JOURNAL OF CL IMATE VOLUME 32
China, where total cloud fraction peaks in spring. Work
by Yu et al. (2004), Li and Gu (2006), and Zhang et al.
(2013) showed that Tibetan Plateau (TP) dynamic ef-
fects contribute to the low-level convergence, ascending
motion, and midlevel divergence over eastern China,
favoring regional stratus clouds and high SWCRE in the
cold season. Besides the TP, other regional circulations,
such as the low-level southerly wind from the South
China Sea, the northwest Pacific anticyclone, and the
East Asian subtropical jet, also have pronounced roles
in spring vertical motion and moisture supply over SEC
(Liang and Wang 1998; Zhao et al. 2007; Zhu et al.
2007), which are essential for regional clouds and rain-
fall. Moreover, distinct subseasonal features exist in the
East Asian monsoon region including SEC, where the
intensity, spatial distribution, and movement timing of
convection, moisture, and prevailing low-level air currents
experience remarkable subseasonal variations especially in
the winter–spring and spring–summer transition periods
(Lau and Yang 1997; Tian and Yasunari 1998; He et al.
2008). Consequently, spring cloud radiative characteristics
potentially show corresponding subseasonal variation and
interannual differences as influencing circulations. How-
ever, previous studies focused on seasonal or monthly
mean states of cloud radiative characteristics and
mostly did not reveal subseasonal features and associa-
tions with regional circulations. Particularly for spring
(March–May), the following issues remain unclear over
SEC: 1) How does subseasonal SWCRE vary? 2) What
types of relationships exist between SWCRE and re-
gional circulations in spring mean and subseasonal
scales? The purpose of this study is therefore to address
these questions. This study investigates spring SWCRE,
including the seasonal mean, subseasonal features and
some interannual differences, and identifiesmajor regional
circulation conditions contributing to the occurrence and
maintenance of spring SWCRE over SEC. Our analyses
are conducted using satellite and reanalysis data, as well
as a regional model. The regional simulation is used to
verify the climatological and case-year results and to
further enhance our confidence in the robustness of as-
sociated climatic features.
The remainder of this paper is organized as follows. In
section 2, the data and method used are introduced.
Section 3 presents the multiyear spring mean features of
SWCRE and circulations over SEC, and analyzes their
possible associations. Section 4 shows corresponding
subseasonal variations during late winter to early sum-
mer and investigates their connections in temporal
evolutions. Section 5 investigates the interannual dif-
ferences of SWCRE and regional circulations with the
analysis and simulation in two case years. Finally, the
conclusions and discussion are presented in section 6.
2. Data and method
a. Observational and reanalysis datasets
The cloud-radiation datasets used in this study consist
of two parts. The first part of the data is from satellite
retrievals. Daily and monthly mean TOA radiative
fluxes are fromNASA’s Clouds and the Earth’s Radiant
Energy System (CERES), which utilizes the most recent
CERES Energy Balanced and Filled at the TOA
(EBAF-TOA) Ed2.8 dataset (Doelling et al. 2013). The
CERES-EBAF includes incident shortwave (SW) flux
and outgoing SW and longwave (LW) radiative fluxes at
the TOA under clear-sky and all-sky conditions. This
dataset has been widely used to study the role of clouds
and the energy cycle in the Earth climate system (Loeb
et al. 2009; Wild et al. 2013). Thus, CERES-EBAF is the
observational radiation dataset used herein. The afore-
mentioned datasets have a spatial resolution of 1.08latitude by 1.08 longitude and are available from March
2000 to February 2017.
The second part of the data is from ERA-Interim
(Dee et al. 2011); these data include daily mean cloud
amount, liquid, and ice water. The aforementioned
cloud-radiation variables in ERA-Interim are calculated
in the host assimilation model and are physically con-
sistent with the reanalyzed meteorological variables to a
large degree. ERA-Interim provides reasonable de-
scription of spatiotemporal features of cloud-radiation
variables (e.g., total cloud amount, cloud vertical struc-
tures, and TOA CREs) over East Asia although some
intensity biases exist (Yin et al. 2015; Li and Mao 2015;
Li et al. 2017b). Another great advantage of ERA-
Interim reanalysis data is their continuous and long-term
states. The satellite data are limited by their operational
period, instrument performance and retrieval algorithm,
FIG. 2. Seasonal mean cloud radiative effects (CREs) averaged
over southeastern China (228–328N, 1048–1228E) during the periodof 2001–16. Here LWCRE, SWCRE, and NCRE are the abbrevi-
ations of longwave, shortwave, and net CREs, respectively. ANN,
DJF, MAM, JJA, and SON indicate the annual, winter, spring,
summer, and autumn mean, respectively.
1 JUNE 2019 L I E T AL . 3071
and cannot fully cover the spatiotemporal resolution in
this study. Thus, daily cloud cover and cloud water from
ERA-Interim are used to explain relevant cloud-radiation
issues, particularly in the subseasonal variation and
vertical distribution. The meteorological variables are
also taken from ERA-Interim and show good perfor-
mance in reproducing wind fields, atmospheric mois-
ture, and precipitation (Simmons et al. 2014; Huang
et al. 2016). The spatial resolution of ERA-Interim is
1.58 latitude by 1.58 longitude, with 37 vertical pressure
layers in this study.
The daily mean precipitation data are from theGlobal
Precipitation Climatology Project (GPCP) with a spatial
resolution of 1.08 latitude by 1.08 longitude, which rangesfromOctober 1996 to February 2017 (Adler et al. 2003).
The monthly GPCP has a spatial resolution of 2.58 lati-tude by 2.58 longitude. The GPCP dataset represents the
climatological state of precipitation well (Yin et al. 2004;
Huffman et al. 2009). In this study, CERES satellite re-
trievals, ERA-Interim meteorological fields, and GPCP
precipitation are used as observational references.
b. Analysis methods
CREs are widely used variables for effectively de-
scribing the bulk cloud effects on air-surface systems.
Therefore, in this study, CREs are used as key study var-
iables to analyze seasonal features of the regional cloud-
radiation process. Following previous work (Ramanathan
et al. 1989; Boucher et al. 2013), TOA CREs are defined
as differences in TOA radiative fluxes between clear-sky
and all-sky conditions:
LWCRE5OLRCS2OLR, (1)
SWCRE5RSUTCS2RSUT, (2)
NCRE5LWCRE1 SWCRE, (3)
where OLRCS and OLR are outgoing LW radiative
fluxes at the TOA under clear-sky and all-sky condi-
tions, respectively; RSUTCS and RSUT are the corre-
sponding outgoing SW radiative fluxes; and net CRE
(NCRE) is the arithmetic sum of LWCRE and SWCRE.
The radiative fluxes and CREs in this study are for TOA
without a special description.
The best CREs data are from CERES-EBAF, which
begins in March 2000. Thus, in this study, only rean-
alyzed and simulated datasets since the beginning of the
CERES satellite era are used. The spring climatological
state and interannual variabilities are examined in this
study. The 16-yr climatological means of the meteoro-
logical fields and cloud-radiation variables are obtained
for the period of 2001–16. The spring seasonal average is
calculated using the results for March, April, and May.
The climatological pentad (5 day) average is used to
analyze the subseasonal variation to identify the general
circulation influence on regional cloud radiative effects.
This procedure of pentad mean is effective for suppress-
ing synoptic disturbances and yet retains the prominent
feature of interest (Zhao et al. 2007; LinHo et al. 2008).
The subseasonal period of interest is pentads 1–36, which
ranges from late winter to early summer. Besides cli-
matological states, two real case years (2010 and 2011)
are selected to compare the differences in cloud-
radiation and circulation over SEC. The domain of
SEC is defined as 228–328N, 1048–1228E based on pre-
vious studies (Liang andWang 1998; Yu et al. 2001;Wan
andWu 2007; Li et al. 2017a; Li et al. 2018), which covers
the continental areas of the middle and lower Yangtze
River and South China.
c. Model and experimental design
In this study, the Weather Research and Forecasting
(WRF) Model (version 3.7.1) is used for the regional
simulation. The WRF Model shows considerable re-
producibility for the East Asian climate (e.g., Kim and
Hong 2010; Z. Wang et al. 2014). In our simulation,
physical packages include theWSM6 cloudmicrophysics
scheme (Hong and Lim 2006), Kain–Fritsch convective
scheme (Kain 2004), Noah land surface scheme (Chen
and Dudhia 2001), Yonsei University (YSU) planetary
boundary layer (PBL) scheme (Hong et al. 2006), and
RapidRadiativeTransferModel forGCMs (RRTMG) for
longwave and shortwave radiation (Iacono et al. 2008).
The simulation domain covers most parts of East Asia
and adjacent oceans with 260 grid points along the east–
west direction and 170 along the north–south direction
(the buffer zone has 10 grid points). A Lambert pro-
jection is adopted, and the domain is centered over
308N, 112.58E. The model has a 30-km horizontal reso-
lution and 30 vertical layers with a terrain-following
sigma coordinate and prescribed model top at 50 hPa.
The initial state of the atmosphere and lateral boundary
conditions (updated every 6 h) are from ERA-Interim,
which have a spatial resolution of 0.758 latitude by
0.758 longitude, and the daily updated sea surface tem-
perature (SST) forcing dataset is also fromERA-Interim.
For the climatological simulation of 2001–16, one run
is conducted and its initial run time is 0000 UTC
16December. The 16-yr simulation is averaged to obtain
multiyear mean spring and subseasonal results. As for
each case year (2010 and 2011), an ensemble experiment
with four runs is performed under different initial
conditions at 0000 UTC 16 December, 0600 UTC
17 December, 1200 UTC 18 December, and 1800 UTC
19December, and each run ends at 1800UTC 31August
of the following year. The simulation period before
3072 JOURNAL OF CL IMATE VOLUME 32
0000 UTC 1 January is considered to be the spinup time.
The simulation ranging from 1 January to 31 August is
used in this study. First, an arithmetic mean of four runs
is taken, and then the pentad mean is obtained to ana-
lyze subseasonal variations.
3. Results
a. Climatological states of spring mean
Figure 3 presents geographical distributions of spring
mean circulations and cloud water path. Here, the cir-
culations include 200-hPa westerly jet, 500-hPa vertical
velocity, 850-hPa wind, column-integrated water vapor
flux, and divergence. In spring, a strong westerly jet at
200hPa lies between the East China Sea and southern
Japan, and the southern side of the entrance region of
the jet is just located over SEC (Fig. 3a), which aids in
regional updraft motion (Liang and Wang 1998; Holton
and Hakim 2012). Low-level southwesterly wind to the
southern flank of the TP and southerly wind from the
west of South China Sea bring abundant water vapor
into SEC, where is an obvious moisture sink region
(Figs. 3a,b). Because of the above circulation distribu-
tions, considerable water vapor readily condenses as
cloud water with the ascending motion. As shown in
Fig. 3c, substantial cloud liquid water exists over SEC
(Fig. 3c). Large SWCRE, ascendingmotion, water vapor
sink, and cloud water are all distributed over SEC and
their high value centers are around 1108E (Figs. 1a and
3). This indicates that spring circulations over SEC favor
not only the occurrence of rain but also the formation of
cloud water and resultant SWCRE.
Figure 4 presents simulated SWCRE, circulations,
and cloud water path in spring. The simulation can re-
produces spring ascending motion at 500 hPa over SEC,
but the ascending motion over the Indochina Peninsula
is much larger than the observation. In the simulation,
the low-level southerly wind from South China Sea is
captured but the southwesterly wind from east to the TP
is weaker (Fig. 4b), inducing a weaker transfer of water
vapor over SEC. The spatial pattern of cloud water path
is well reproduced by themodel and its high value center
is very close to the observation (Fig. 4c). Note that
the simulated cloud water path is weaker than the
FIG. 3. Spring mean (a) circulations, (b) column water vapor flux (kgm21 s21) and divergence (1024 kgm22 s21),
and (c) cloud water path (CWP; gm22) from ERA-Interim during the period of 2001–16. In (a), the green line
indicates the 200-hPawesterly jet and the vector is 850-hPawind (m s21). In (c), the shading is the total CWP (liquid
and ice) and the blue contour line is liquid CWP with an interval of 20 (gm22). The black solid line is the TP (over
3000m). Here, column water vapor divergence is integrated from surface to 100 hPa. The vector data are masked
below 850 hPa.
1 JUNE 2019 L I E T AL . 3073
observational reference, but the simulated cloud liquid
radius is also small (not shown) and helps to intensify
cloud optical depth and SWCRE over SEC and its east-
ern sea. The weak CWP and small cloud radius in WRF
simulation show compensatory roles in determining
SWCRE, resulting in a comparable intensity of simulated
SWCRE relative to the observation (Figs. 1a and 4a). The
simulation basically reproduces strong spring SWCRE
and corresponding circulations, although biases exist.
Note that the high-value center of spring SWCRE is
mainly distributed inwestern and central SEC, but stronger
rainfall appears eastern SEC. This high-value distribution
difference between spring SWCREand rainfall is related to
orography and land–sea effects. Li and Yu (2014) showed
that compared with eastern SEC, weaker rainfall with
higher frequency is dominant over western SEC because of
terrain effects. Higher rainfall frequency means longer
cloud duration time and larger SWCRE. Relatively, east-
ern SEC is more adjacent to oceans, and the abundant
moisture and land–sea effects enable larger amounts of
rainfall (Yuan et al. 2012). Additionally, heavy aerosol
loading over western and central SEC also contributes to
small cloud radius and strong SWCRE (Li et al. 2017a).
SWCRE at subtropical andmidlatitudes highly depends
on low- to midlevel cloud water content (Cess et al. 1990;
Zhang et al. 2005). We further analyzed vertical distri-
butions of spring meridional mean cloud water and
winds to examine the relationship among vertical cir-
culations, cloudwater, and SWCRE.As clearly shown in
Fig. 5a, the westerly jet core is around 308N, and de-
scending motion and northerly wind occur north to
308N. The obvious ascending motion and southerly wind
appear over 208–308N (the SEC latitudinal zone) and
just correspond to large cloud water content between
850 and 500 hPa, the magnitude of which is much
larger than at same tropical longitudes (Fig. 5a). From
the pressure–longitude cross section averaged over
228–328N (Fig. 5b), the strongest ascending motion oc-
curs at low to midlevels immediately adjacent to the TP
(1048–1108E). The large cloud water appears between
the area east of the TP and the middle reaches of the
Yanzi River, and extends easterly to ocean regions
around 1228E. Moreover, cloud water is mainly distrib-
uted below 500hPa and the isotherm of 08C (Fig. 5b),
showing that cloud water over SEC mainly consists of
liquid water. At the same time, the westerly wind over
the TP and eastern China is conducive to the transfer of
cloud water downstream.
The simulation can capture major vertical distributions
of cloud water and wind as shown in Figs. 5c and 5d.
FIG. 4. Simulated spring mean (a) SWCRE, (b) circulations, and (c) cloud water path (gm22) during the period
2001–16. In (c), the shading is total CWP (liquid and ice) and the blue contour line is liquid CWPwith an interval of
20 (gm22). The black solid line is the TP (over 3000m). The vector data are masked below 850 hPa.
3074 JOURNAL OF CL IMATE VOLUME 32
Compared to the observation, the simulated central in-
tensity and location of westerly jet are stronger and more
southerly, and the ascending motion between 108 and
158N is also too large (Fig. 5c). Besides the low-level at-
mosphere, large cloud water content is also distributed
between 300 and 400hPa and extends eastward to the
East China Sea (Fig. 5d), where this considerable high-
level cloudwater complicates cloud overlap (Fig. 4a). The
TP is a heat source in spring relative to the same latitudes
over eastern China (Yeh et al. 1957; Wu et al. 2007). As
shown in Figs. 5b and 5d, a temperature gradient from
west to east exists in themiddle atmosphere around 1048–1108E, which can increase the stability at low to midlevels
over SEC (Wu and Zhang 1998; Zhang et al. 2013).
Previous work (Yu et al. 2001, 2004; Li and Gu 2006)
suggested that the TP can reduce the westerly wind and
then low-level convergence and midlevel divergence ap-
pear on the lee side of theTP. These thermal anddynamic
roles of the TP limit updraft motion in low to midlevels
but aid the accumulation of cloud water. Because of the
above-mentioned circulation distributions, spring cloud
water over SEC is mainly located in the low to midlevels.
The work by Luo et al. (2009) also shows that low to
middle clouds during March to May are the dominant
cloud types over eastern China with the almost same
domain as this study. As a result, large amounts of liquid
cloud reflect shortwave radiation and cause strong
SWCRE over SEC.
b. Subseasonal variation
Given that some subseasonal features cannot be re-
flected in spring mean (March to May) results, we used
the pentad mean variation to further investigate the
SWCRE and relevant circulations over SEC. This study
focuses on the spring and therefore pentads 1–48 (early
January to late September) are selected for analysis in
this study. The vertical velocity between 850 and 500 hPa
is averaged to represent the low-to-midlevel vertical
motion. Ascending motion and water vapor supply are
the major circulation conditions for the formation of
large-scale clouds and rainfall. Figure 6 presents the
observed subseasonal variation of rainfall, SWCRE, and
the two general circulations mentioned above. Some
researchers (He et al. 2007, 2008; Zhao et al. 2007; Zhu
et al. 2011) have pointed out that the subtropical spring
rain (around pentads 12–24), the establishment of the
South China Sea monsoon (around pentads 25–28), and
the following northwardmovement of summermonsoon
FIG. 5. Spring mean (a) pressure–latitude cross section of cloud water content (1026 kg kg21) and wind circu-
lations averaged over 1048–1228E and (b) corresponding pressure–longitude cross section averaged over 228–328N.
In (a), the red contour is westerly wind (m s21) and the vector is the meridional (20m s21)/vertical wind (5 31023 Pa s21) component. In (b), the red contour is air temperature (8C) with intervals of 38C and vector is zonal
(m s21)/vertical wind (2 3 1023 Pa s21) component. (c),(d) As in (a) and (b), but from the WRF simulation. The
gray shading is the TP altitude.
1 JUNE 2019 L I E T AL . 3075
rain (after pentad 28) consecutively occur over Asian
regions, and the wind field and moisture then show
dramatic variations during late winter to early summer
over SEC. These features are also very clearly seen in
pentad mean variation of rainfall (Fig. 6a). Note that the
intensity of rainfall, SWCRE, ascending motion, and
water vapor convergence abruptly increases around
pentad 12 (late February) in Fig. 6, and the corre-
sponding low-level southerly wind and westerly jet
synchronously reduce (not shown). This abrupt change
almost simultaneously appears with the reversal of
temperature gradient between the Indochina Peninsula
and the western Pacific to the east of the Philippines in
late February (Tian and Yasunari 1998). After pentad
12, the low-to-midlevel ascending motion increases up
to250hPaday21 and persists until pentad 36 (late June)
in Fig. 6c. During the same period, SWCRE and water
vapor convergence gradually increase and then further
intensify starting at pentad 16 (mid-March), when
SWCRE intensity reaches up to 2110Wm22. After
pentad 24 (late April), SWCRE and water vapor con-
tinue to increase until pentad 36, and afterward reduce
quickly (Figs. 6b and 6d). The cloud water content shows
similar variations to those described above (not shown).
As listed in Table 1, the temporal correlations between
area-averaged SWCRE and updraft velocity (water va-
por convergence) during pentads 1–36 are over 0.84 in
the observation and simulation, showing that the two
circulation conditions are essential to maintain strong
SWCRE over SEC.
Figure 7 is simulated pentad mean variations. The
simulation can well reproduce subseasonal variation of
SWCRE to the north of 208N. The simulation accurately
captures the abrupt increase in SWCRE, ascending
motion, and water vapor convergence at pentad 12, and
their further intensification at pentads 16 and 24
(Figs. 7b–d). In contrast, simulated SWCRE around the
SEC latitudinal zone is weaker during pentads 1–20, and
rainfall, ascending motion, and water vapor conver-
gence to the south of 208N are stronger after pentad 24.
Moreover, large rainfall remains after pentad 36, which
is associated with strong convections from WRF cumu-
lus parameterization used in this study. In the simula-
tion, ascending motion and water vapor supply over
tropical regions to south of SEC (the South China Sea)
are also greatly enhanced since pentad 24, but the cor-
responding SWCRE is much weaker than that over
SEC. Note that large SWCRE stably exists at SEC lat-
itudinal bands (228–328N) during pentads 25–36, and
does not retreat southward and further intensify north-
ward as rainfall (Figs. 6b and 7b). This difference of
subseasonal variations between SWCRE and rainfall
is relevant to respective cloud-precipitation features
over subtropical (SEC) and tropical (South China Sea)
monsoon regions. Stratiform precipitation with large
area and long cloud duration time accounts for a
FIG. 6. Pentadmean variations of observed (a) precipitation (mmday21), (b) SWCRE (Wm22), (c) 850–500-hPa
mean ascending motion (hPa day21), and (d) column water vapor flux divergence (1024 kgm22 s21) averaged over
1048–1228E during the period of 2001–16. The x axis denotes the pentad number.
3076 JOURNAL OF CL IMATE VOLUME 32
considerable proportion over SEC and markedly in-
creases after the onset of South China Sea monsoon; by
comparison, although the convective precipitation
amount over South China Sea is dramatically enhanced
after pentad 24, its precipitation area quickly decreases,
indicative of short duration time (Hu et al. 2011). As
clearly shown in the simulation (Figs. 7a,b), the con-
vective rainfall ratio during pentads 25–36 is up to 0.9
over South China Sea, and then cloud lifetime and re-
sultant SWCRE are not as large as over SEC.
The above subseasonal variations of SWCRE are also
reflected in their regional mean time series. As shown in
Fig. 8, the observed and simulated SWCREdramatically
intensify around pentad 12 and then gradually increase.
The maximum of observed and simulated SWCRE oc-
curs in pentads 33 (mid-June) and 28 (late May), with
values of 2128 and 2120Wm22, respectively. The
earlier peak time of simulated SWCRE arises from the
high-value position bias of SWCRE, which is east in
comparison with the observation. During pentads 12–36,
LWCRE also increases and offsets with SWCRE, and
then NCRE intensity stably remains over 260Wm22.
As illustrated in Fig. 2, Fig. 8 further shows that SWCRE
over SEC is much larger than LWCRE and dominates
regional CREs. The intensity ratio of LWCRE to
SWCRE is only 0.2 before pentad 12 (Fig. 8). Afterward,
with the increase in ascending motion and high cloud,
the ratio of LWCRE gradually increases and exceeds 0.4
at around pentad 36. The simulated interannual vari-
abilities of SWCRE and NCRE are larger than the ob-
servations. Another interesting feature is that the
interannual variability of SWCRE is very close to
NCRE during pentads 1–30, indicating that SWCRE
dominates interannual variability of CREs over SEC.
Based on the pentad mean variations mentioned
above, Fig. 9 presents several important pentads to show
geographical distributions of water vapor and ascending
motion affecting SWCRE. In pentads 12, 18, and 24, the
westerly jet stays between eastern China and Japan, and
obvious moisture convergence and ascending motion
occur over SEC. Thewater vapormainly comes from the
westerly wind south to the TP and the southerly wind
TABLE 1. Temporal correlations between 850–500-hPa mean vertical
velocity (hPa day21)/column moisture divergence (1024 kgm22 s21)
and SWCRE (Wm22)/precipitation (mmday21) during pentads
1–36 for the observed and simulated data. The data are averaged
over SEC (228–328N, 1048–1228E) during the period of 2001–16.
‘‘Obs.’’ and ‘‘Sim.’’ are the abbreviations for observation and
simulation.
MAM
850–500-hPa mean
vertical velocity
Column moisture
divergence
SWCRE Obs. 0.85 0.90
Sim. 0.93 0.84
Precipitation Obs. 20.67 20.91
Sim. 20.94 20.97
FIG. 7. As in Fig. 6, but for theWRF simulation. In (a), the blue line is the ratio of convective rainfall amount to total
rainfall amount.
1 JUNE 2019 L I E T AL . 3077
from the South China Sea. At pentad 28 (mid-May)
when the South China Sea monsoon has been estab-
lished, the water vapor transport by the southwesterly
wind from the Bay of Bengal is greatly enhanced.
SWCRE over SEC then further increases since pentad
28. Afterward, the west Pacific subtropical high extends
westward and advances northward. In pentad 38, the
subtropical ridge is close to the middle and lower rea-
ches of the Yanzi River and suppresses strong updraft
motion; consequently, moisture convergence, updraft
motion, and SWCRE weaken. The simulation basically
reproduces the aforementioned circulation distributions,
but some evident biases of moisture transport exist.
Particularly, moisture transfer by the southwest air
current is weak over SEC in pentad 18 but too strong in
pentads 28, 33, and 38 over the Indochina Peninsula, the
South China Sea, and south of Japan (Fig. A1). The
overestimated moisture leads to large rainfall over
tropical regions south of SEC.
According to the results shown in Figs. 6, 7, and 9,
large SWCRE over SEC is closely associated with re-
gional water vapor supply and low-to-midlevel ascend-
ing motion, which exhibit pronounced stage features.
Around pentad 12, ascending motion, moisture supply,
and SWCRE over SEC abruptly increases, which is
caused by the reversal of thermal contrast between the
Indochina Peninsula and the western Pacific to east of
the Philippines in late February. The subsequent pentad
mean variations of SWCRE over SEC are roughly di-
vided into two stages during late winter to early summer.
In stage 1 (pentads 12–24), regional ascending motion is
mainly caused by the TP thermal and dynamic roles and
westerly jet while water vapor as cloud water supply
stably comes from the southern flank of the TP and
South China Sea. In stage 2 (pentads 25–36), SWCRE
intensity is strongly affected by the march of East Asian
monsoon systems (the tropical South China Sea mon-
soon and subtropical East Asian monsoon). Particularly,
FIG. 8. Pentad mean variations of CREs (Wm22) in the (a) observation and (b) simulation
averaged over SEC (228–328N, 1048–1228E) during the period of 2001–16. Here, the orange line
denotes the ratio of the LWCRE magnitude to that of negative SWCRE. The vertical bars
denote the standard deviation at each pentad, reflecting the interannual variability. The x axis
denotes the pentad number.
3078 JOURNAL OF CL IMATE VOLUME 32
after the onset of the South China Sea monsoon (around
pentads 24–28), the greatly intensified moisture transport
from the Bay of Bengal increases cloud water supply and
then enhances SWCRE over SEC.
c. Case studies in 2010 and 2011
Spring circulation conditions have remarkable in-
terannual variation over SEC, and regional cloud radi-
ative characteristics including SWCRE readily exhibit
interannual differences. Here, spring SWCRE and rel-
evant circulations are further examined in two real case
years using satellite and reanalyzed datasets as well as
WRF regional simulation. The most severe drought in
the last 30 years occurred persistently over SEC from
January to May 2011, but the precipitation amount was
relatively larger in 2010; the corresponding general cir-
culations showed a sharp contrast between the two years
(Sun and Yang 2012). Furthermore, these two years are
the only pair of continuous years with the occurrence of
contrasting precipitation in spring since the CERES-
MODIS satellite era. Thus, 2010 and 2011 are selected
as the strong and weak case years. During the period of
2001–16, the normalized standard deviations of spring
mean precipitation averaged over SEC are 0.92
and 22.46 in 2010 and 2011, respectively, and the cor-
responding values of SWCRE are 1.6 and 20.46, re-
spectively, showing large interannual differences in the
two case years. In this section, pentad 1–36 is selected for
the analysis of subseasonal variations.
Figure 10 presents pentad mean precipitation and
SWCRE averaged over SEC in 2010 and 2011. Com-
pared to the observation, the simulation well reproduces
subseasonal variations of rainfall and SWCREover SEC
in 2010, with temporal correlation of 0.78 and 0.86, re-
spectively (Figs. 10a and 10b). In contrast, the temporal
correlation of SWCRE in 2011 is only 0.55 because the
simulated SWCRE is much weaker before pentad 22.
During the strong year (2010), strong ascending motion
appears early, with the development height reaching up
to 400 hPa in pentads 9 and 13, and corresponds well to
large moisture convergence and cloud liquid water path
(Figs. 10b and 11a–d). SWCRE (less than2110Wm22)
and moisture convergence are relatively stable until
pentad 18; afterward, SWCRE markedly increases up
to 2130Wm22 while the moisture convergence also
gradually increases and the ascending motion becomes
continuous and deep (Figs. 10b and 11a–d). The simu-
lation also performs well in subseasonal variations of
ascending motion and moisture convergence in 2010.
During the weak year (2011), deep ascending motion
before pentad 24 is much weaker than that of 2010,
corresponding to weaker moisture convergence and
cloud liquid water path during the same period
(Figs. 11e–h). Before pentad 18 of 2011, considerable
ascending motion still appears in low to midlevels
(Fig. 11e) and helps to maintain SWCRE (Fig. 10d).
Compared to the observation in 2011, the simulated
moisture convergence before pentad 18 is close to the
FIG. 9. Geographical distributions of 200-hPa westerly jet (red dashed line; m s21), column water vapor flux (vector; kgm21 s21), and
divergence (shading; 1024 kgm22 s21) at selected pentads averaged during 2001–16. The data are from ERA-Interim. The black solid line
is the TP (over 3000m). The vector data are masked below 850 hPa.
1 JUNE 2019 L I E T AL . 3079
observation (Fig. 11g), but the simulated low-to-midlevel
ascending motion is obviously weaker (Figs. 11e,f), which
can partly explain the weaker SWCRE in the simulation.
As shown in Fig. 11, although the simulated intensity has
some deviation, the simulation basically captures the
timing of strong ascending motion in 2011. Note that the
contrast of cloud liquid water path between 2010 and
2011 is larger than cloud ice water path (Figs. 11d and
11h), indicating that cloud liquid water is more sensitive
to the ascending motion.
To examine the geographical distribution of the in-
terannual differences, the observed and simulated mean
of pentads 18–30 is selected as the spring mean period
when the simulation performs relatively better and the
interannual contrast is also large. Figure 12 presents the
SWCRE, circulations, and relevant differences aver-
aged during pentads 18–30 in 2010 and 2011. In 2010
(strong year), there is strong ascending motion and
SWCRE over SEC as well as a strong low-level south-
westerly from the Bay of Bengal and a southerly from
the South China Sea (Figs. 12a,c). In contrast, the
SWCRE and southwesterly over SEC are much weaker
in 2011 (weak year) (Figs. 12b,e). In the strong spring
rainfall case year (2010), the larger SWCRE (up
to 260Wm22) corresponds to a larger updraft velocity
(less than 230Paday21) at 500hPa over SEC, the
southwesterly (southerly) brings abundant water vapor
into SEC, and the northwesterly from Siberia and
northern China enters this region and causes a strong
low-level convergence (Figs. 12c,f). The distributions of
the regional circulation and SWCRE over SEC are
closely related to the pattern of large-scale circulation in
both case years. Relative to the pattern that occurs in
2010, the westerly jet (.40ms21) at 200 hPa and the
northwestern Pacific subtropical high are weak, and
their center positions shift eastward in 2011. This cir-
culation pattern in 2011 produces a weaker southwest-
erly, ascending motion and precipitation over SEC
(Fig. 12; see also Fig. A2 in the appendix). The strong
circulation differences between these two case years
were mainly caused by La Niña and the North Atlantic
Oscillation in 2010–11 (Sun and Yang 2012). The strong
differences between the two case years are also very
clear in the domain mean values, as listed in Table 2.
For example, the SWCRE differences are 231.6
and 235.2Wm22 for the observation and simulation,
respectively, and the vertical velocity differences at
500 hPa are 237.8 and 233.4 hPaday21, respectively
(Table 2). The observed and simulated differences of
cloud liquid water path are 45.4 and 38.0 gm22, re-
spectively and much larger than their counterparts of
cloud ice water path, with the values of 8.3 and 6.9 gm22,
respectively, showing that cloud water differences be-
tween 2010 and 2011 are mainly contributed by liquid
phase cloud.
The above results show that the ascending motion is
one of key general conditions relating the regional cir-
culation to the SWCRE. Water vapor is condensed to
cloud water through the lifting role of the ascending
motion, the maintenance of which provides stable con-
ditions for cloud formation. Thus, the domain 228–328N,
1108–1208E where large SWCRE contrast exists is
FIG. 10. Pentad mean variations of observed (black line) and simulated (blue line) (a) precipitation (mmday21)
and (b) SWCRE (Wm22) averaged over SEC (228–328N, 1048–1228E) in 2010. (c),(d) As in (a) and (b), but for the
corresponding results in 2011. The temporal correlation coefficients are marked at the top-right corner in each
subfigure. The x axis is the pentad number.
3080 JOURNAL OF CL IMATE VOLUME 32
selected to examine the scatter relationship between the
SWCRE and ascending motion at 500 hPa in pentads
18–30 of 2010 and 2011. In the observations, the larger
SWCRE (points with negative value) nearly corre-
sponds to the ascending motion (points with negative
value), and the linear correlation is up to 0.70 (Fig. 13a).
In the simulation, the value of most points is less than
zero, the linear correlation is 0.64, and the regressive
slope is also very close to the observation (Fig. 13b). In
addition to the updraft motion, water vapor convergence
FIG. 11. Pentad mean variations of (a) ERA-Interim reanalyzed vertical velocity (hPa day21), (b) simulated vertical velocity
(hPa day21), (c) column water vapor flux divergence (1024 kgm22 s21), and (d) simulated cloud water path (gm22) averaged over SEC
(228–328N, 1048–1228E) in 2010. (e)–(h) As in (a)–(d), but showing the corresponding results in 2011. Here, IWP denotes cloud ice water
path. The x axis is the pentad number.
1 JUNE 2019 L I E T AL . 3081
supplies the source of cloud water, and then the intensity
of the moisture convergence over SEC affects the re-
gional SWCRE to some extent. As for the scatter re-
lationship between the SWCRE and column moisture
convergence in the above region, the linear correlation
coefficients are 0.51 and 0.55 for the observation and
simulation, respectively (not shown). Water vapor con-
vergence still corresponds well to larger SWCRE in
the observation; however, the simulation poorly cap-
tures the good observed scatter distribution and un-
derestimates the difference of water vapor convergence
between the two case years. The above analysis shows
that the contribution of the updraft motion to cloud
water and SWCRE is likely larger than the air moisture
in the simulation. In Asian monsoon regions, water va-
por transportation is mainly driven by the regional cir-
culation (Wang et al. 2017) and the vertical motion is the
prominent influencing factor for the spring moisture
budget over SEC (Li et al. 2018). In this sense, theWRF
model has broadly reproducibility in interannual dif-
ferences of above cloud radiative characteristics over
SEC. According to the results in Figs. 10–13, favorable
spring general circulations cause stronger ascending
motion over SEC in the strong case year, and then
produce more cloud liquid water and larger SWCRE
relative to the weak case year. Consequently, the
FIG. 12. Geographical distributions of (a) CERES SWCRE (shading; Wm22), vertical velocity (Pa day21) at 500 hPa, and wind field at
850 hPa averaged during the period of pentads 18–30 in 2010, (b) the corresponding results for 2011, and (c) the differences between 2010
and 2011. (d)–(f) As in (a)–(c), but for the corresponding results from the WRF simulation. The black solid line is the TP (over 3000m).
The vector data are masked below 850 hPa.
TABLE 2. Observed and simulated cloud radiation and meteorological variables averaged over SEC (228–328N, 1048–1228E) during the
18th–30th pentad in 2010 and 2011. Here, the differences are between the corresponding values in 2010 and 2011.
18th–30th pentad mean 2010 2011 2010 2 2011
SWCRE (Wm22) Obs. 2127.9 296.3 231.6
Sim. 2126.2 291.0 235.2
Cloud liquid water path (gm22) Obs. 139.9 94.5 45.4
Sim. 73.1 35.1 38.0
Cloud ice water path (gm22) Obs. 37.6 29.3 8.3
Sim. 41.4 34.5 6.9
Total cloud water path (gm22) Obs. 177.5 123.8 53.7
Sim. 114.5 69.5 45.0
W500 (hPa day21) Obs. 231.6 6.2 237.8
Sim. 228.2 5.2 233.4
Water vapor divergence (1024 kgm22 s21) Obs. 20.641 20.185 20.456
Sim. 20.746 20.522 20.224
3082 JOURNAL OF CL IMATE VOLUME 32
interannual differences of SWCRE in other cases very
likely contribute to the anomalous ascending motion
over SEC.
4. Conclusions and discussion
This study shows that SWCRE over SEC (228–328N,
1048–1228E) exhibits strong and persistent features in
spring. As for the spring (March–May) mean, the in-
tensity of SWCRE over SEC is up to2110Wm22, being
the largest at the same latitude bands of the Northern
Hemisphere. In this region, strong spring SWCRE
is mainly caused by large and stable cloud liquid
water, which is closely associated with persistent water
vapor transport and low-to-midlevel ascending motion.
SWCRE over SEC also has distinctive subseasonal
variation and its high value stays over SEC during
pentads 12–36 (late February to late June). Around
pentad 12, ascent motion, moisture supply, and SWCRE
over SEC abruptly increases, which is accompanied by
the reversal of thermal contrast between the Indochina
Peninsula and western Pacific to east of the Philippines
on late February. During pentads 12–24 (late February
to late April), the TP thermal and dynamic roles and
high-level westerly jet provide appropriate settings for
the stable occurrence of continuous ascending motion
over SEC, while water vapor is transferred from south of
the TP and the South China Sea. During pentads 25–36
(earlyMay to late June), SWCRE is strongly affected by
the march of East Asian monsoon systems (the tropical
South China Sea monsoon and subtropical East Asian
monsoon) and its intensity further increases. Particu-
larly, after the onset of South China Sea monsoon
(around pentads 24–28), the greatly intensified moisture
transport from the Bay of Bengal increases cloud water
supply and then enhances SWCRE over SEC. After
pentad 36, the above circulations favoring the mainte-
nance of cloud water and SWCRE quickly weaken and
then large SWCRE cannot remain over SEC. These
subseasonal results indicate that the spring SWCRE
over SEC is not just affected by specific circulations
(e.g., the dynamical and thermal roles of the TP, west-
erly jet) but is also deeply influenced by the seasonal
march of the East Asian monsoon system. In the observed
case analysis, stronger ascending motion, larger amounts
of cloud liquid water, and SWCRE occur during a strong
spring rainfall year, and the differences in SWCRE be-
tween strong and weak spring rainfall years are well
related to the strengths of the anomalous ascending
motion over SEC.
The regional model (WRF) can basically reproduce
large spring SWCRE over SEC and its persistence
during late winter to early summer. In contrast, the
simulated association of SWCRE with ascending mo-
tion is closer than water vapor convergence. As shown
in Figs. 9 and A1, considerable simulation biases exist
over the East Asian monsoon regions regarding the
geographical distribution and intensity of moisture
transport and convergence. Similar deficiencies of
moisture simulation are also common in current state-
of-the-art climate models (Sperber et al. 2013; Yang
et al. 2015) and closely relevant to the uncertainties of
FIG. 13. Scatterplot of SWCRE (Wm22) and vertical velocity (Pa day21) at 500 hPa over SEC (228–328N, 1108–1208E). Here, the SWCRE (vertical velocity) is the difference between the 18th–30th pentad mean results in 2010
and 2011 (as shown in Figs. 11c and 11f). The grid over SEC is selected to plot the scatter figure. The regression
equation and linear correlation coefficient are shown in the lower right of each panel.
1 JUNE 2019 L I E T AL . 3083
physics parameterizations (e.g., convection, cloud
precipitation, and planet boundary layer) and numer-
ical algorithms. The complicated topography in the TP
and surrounding areas further increases above simu-
lation difficulties. To well capture the roles of water
vapor in spring SWCRE over SEC, more model work is
needed to carefully select and tune model parameter-
ization schemes regarding moisture and cloud water.
Both observation and simulation show that sub-
seasonal evolution of SWCRE is not exactly same with
rainfall over SEC and South China Sea, reflecting that
ambient conditions influencing SWCRE and rainfall are
different over these regions. Besides cloud water and
associated regional circulations, SWCRE is also sensitive
to the microcloud radius, which is highly modulated by
aerosols as cloud condensation nuclei (Gettelman and
Sherwood 2016). A large number of aerosols are dis-
tributed over SEC and readily produce remarkable con-
trasts of cloud microphysical characteristics (e.g., cloud
number concentration and radius) and radiative proper-
ties relative to the adjacent oceans (Li et al. 2016). Thus,
more cloud microphysics analysis and well-designed
simulations should be conducted to explore climatic
mechanisms resulting in the maintenance of spring
SWCRE over SEC.
The case studies clearly show that circulations (e.g., the
East Asian westerly jet, the northwestern Pacific sub-
tropical high, and the low-latitude tropical circulation)
FIG. A1. As in Fig. 9, but from the WRF simulation.
FIG. A2. Observational distribution of the 850-hPa wind (vector), zonal wind speed (red dashed line; m s21) at
200 hPa, and precipitation (shading; mmday21) averaged during the 18th–30th pentads of (a) 2010 and (b) 2011.
The pentad number is marked at the top-right corner in each subfigure. The black solid line is the TP (over 3000m).
The vector data are masked below 850 hPa.
3084 JOURNAL OF CL IMATE VOLUME 32
around East Asia have obvious interannual variations,
which affect the distribution, strength, and variability of
CREs over SEC. To identify individual roles of these
circulations in regional SWCRE, it is very necessary to
quantitatively examine the associations between these
circulations and SWCRE in the interannual scale. Addi-
tionally, CERES satellite and ERA-Interim reanalysis
data used in this study still have some uncertainties in
describing regional cloud–radiation variables, especially
in their quantitative aspects. As for further work, more
comparative analysis with model and observational data
should be conducted to obtain reasonable physical con-
sistency results for East Asian cloud–radiation processes.
Acknowledgments. This research was jointly sup-
ported by the National Key R&D Program of China
(2017YFA0603503), the National Science Foundation
of China (91737306, 41730963, and 41876020), the Pri-
ority Research Program of the Chinese Academy of
Sciences (QYZDY-SSW-DQC018), the Strategic Pri-
ority Research Program of Chinese Academy of Sci-
ences (Grant XDA17010105), and a grant (toUniversity
at Albany) from the Office of Science (BER), U.S.
Department of Energy. CERES-MODIS cloud prop-
erties and CERESEBAF products used in this study are
produced by the NASA CERES Team, available at
http://ceres.larc.nasa.gov.
APPENDIX
Geographical Distribution of Circulations in theSimulation and Case Years
FigureA1 shows 200-hPa zonalwind speed, columnwater
vapor flux, and divergence simulated from WRF Model
at selected pentads averaged during 2001–16. Figure A1
clearly shows the simulated biases of air moisture regarding
its spatial location and intensity. The possible reasons are
discussed in the main text. To show the differences of large-
scale circulations in two case years, Fig.A2presents 850-hPa
wind, 200-hPa zonal wind speed, and precipitation aver-
aged from the 18th–36th pentads of 2010 and 2011.
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