SOLA, 2016, Vol. 12, 272−276, doi:10.2151/sola.2016-053

272

Resolution Dependence of the Diurnal Cycle of Precipitation Simulated
by a Global Cloud-System Resolving Model
Hisashi Yashiro1, Yoshiyuki Kajikawa1, 2, Yoshiaki Miyamoto1, 3, Tsuyoshi Yamaura1,
Ryuji Yoshida1, 2, and Hirofumi Tomita1
1
RIKEN Advanced Institute for Computational Science, Kobe, Japan
2
Research Center for Urban Safety and Security, Kobe University, Kobe, Japan
3
Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

Abstract
Resolution dependence was found in the simulated diurnal
precipitation cycle over land in the tropics. We conducted a seriesof grid refinement experiments of the atmosphere from 14 km
to 0.87 km using a global high-resolution model without any
convection parameterizations. In the high-resolution experiment,
the peak of the cycle was earlier and precipitation at the peak was
higher. The characteristics of the simulated diurnal precipitation
cycle changed at a grid spacing of around 2−3 km. The precipitation started to increase in the morning in the high-resolution
experiments, suggesting that small-scale moist convection became
active in the late morning. In the lower-resolution experiments,
convection and precipitation began in the late afternoon. As wellas the enhancement of moisture transport from the boundary layer
to the middle troposphere, the rapid formation of rain can also be
attributed to the difference in diurnal precipitation cycles between
lower and higher resolution experiments.
(Citation: Yashiro, H., Y. Kajikawa, Y. Miyamoto, T. Yamaura,
R. Yoshida, and H. Tomita, 2016: Resolution dependence of thediurnal cycle of precipitation simulated by a global cloud-system
resolving model. SOLA, 12, 272−276, doi:10.2151/sola.2016-053.)

1. Introduction
Precipitation is an essential variable of climate. Heavy precipitation, which is closely associated with deep convection, is
important not only for local weather stability but also for global
circulation (Neale and Slingo 2003). Tropical convective systems
indicate the diurnal precipitation cycle, and observations such as
those from the Tropical Rainfall Measuring Mission (TRMM)
have revealed the general features of the diurnal precipitation
cycle in the tropics. A small peak appears in the early morningover the ocean, and a large peak appears in the late afternoon overthe land (Sato et al. 2009). Many current conventional generalcirculation models (GCMs) do not capture this diurnal cycle oftropical precipitation, especially over land (Dai 2006). Several
studies have pointed out that the problem is related to the coarse
horizontal resolution and the (cumulus) convection parameterization (CP) (Neale and Slingo 2003; Dai 2006; Lee et al. 2007).
A similar discrepancy in the diurnal precipitation cycle is foundwhen comparing gridded rain gauge measurements and the
Coupled Model Intercomparison Project phase 5 (CMIP5) resultsover the southeastern United States (Rosa and Collins 2013). The
conventional GCM simulations with CP usually show the peak ofthe diurnal precipitation cycle around noon over land. Sensitivity
studies for the CP schemes have noted that the diurnal variation
can improve by changing the parameters of the scheme (Lee et al.
2007; Wang et al. 2010). A study using a 20-km mesh of highresolution GCM with CP showed an improvement in the peak
Corresponding author: Hisashi Yashiro, RIKEN Advanced Institute for
Computational Science, 7-1-26, Minatojima-minami-machi, Chuo-ku,
Kobe, Hyogo, 650-0047, Japan. E-mail: h.yashiro@riken.jp. ©2016, theMeteorological Society of Japan.

time of the diurnal precipitation cycle (Arakawa and Kitoh 2005).
However, simulations using CP still contain significant uncertainty. The explicit moisture convection simulation better represents
the diurnal precipitation cycle, compared to the GCM simulation
with CP at the same horizontal resolution of approximately 10 km(Dirmeyer et al. 2012).
In recent years, global cloud-permitting simulations havebeen used to study diurnal cycles of precipitation. Global simulations with 14 km and 7 km grid spacing without CP schemes
have effectively reproduced the diurnal precipitation cycle intropical regions (Sato et al. 2009; Noda et al. 2012; Kodama et al.
2015), especially over the ocean. Nevertheless, the precipitation
peak in the diurnal cycle over land occurs later than in TRMM
observations. Through sensitivity experiments for the horizontal
grid spacing, Sato et al. (2008, 2009) suggested that the peak precipitation time would approach that of TRMM observations withincreased horizontal resolution. Another approach, which differsfrom the global cloud resolving simulation, was also proposed
to replace the CP. The multiscale modeling framework (MMF,
also known as super-parameterization) employs a high-resolution
cloud-resolving model in each coarse grid (~100 km) GCM. Thisapproach has succeeded in improving the diurnal precipitation
cycle compared to conventional GCMs (e.g., Pritchard andSomerville 2009a, 2009b). However, the MMF does not explicitly
express the local weather phenomena. Therefore, it is expectedthat the global climate and local weather are fully expressed by
the global cloud-resolving simulation.
Recently, Miyamoto et al. (2013) conducted a global subkilometer resolution simulation. They found that a fundamental
change in convection properties occurred at a grid spacing of 2−3
km as a global mean. This implies a fundamental change in thediurnal precipitation cycle. The question is, how much resolution
is required for sufficient representation of the observed precipitation peak in a realistic global simulation. The purpose of this study
is to clarify the resolution dependence of the diurnal variation of
precipitation in the tropics, simulated by a global high-resolution
model. We conducted simulations with five different horizontal
resolutions. Several diagnostic variables were analyzed to show
the characteristics of the temporal development of convection andprecipitation.

2. Simulation settings
The model we used in this study was the non-hydrostatic
icosahedral atmospheric model (NICAM, Satoh et al. 2014).
The experimental settings of this study were the same as thosein Miyamoto et al. (2013, 2015) and Kajikawa et al. (2016). We
conducted five simulations with different horizontal grid spacing:
14 km, 7 km, 3.5 km, 1.7 km, and 0.87 km, hereafter referred toas Δ14, Δ7, Δ3.5, Δ1.7, and Δ0.87, respectively. The same landsea distribution and terrain height were used in all experiments byinterpolating from the data of Δ14. After the 3-day spin-up usingcoarser resolution, we conducted a 48-hour simulation. We used
the output from the last 24 hours for analysis, which corresponds
to one day of results from 2012082600 UTC to 2012082700 UTC.
The data were sorted according to the local solar time (LST) andYashiro et al., Resolution Dependence of Precipitation Diurnal Cycle Simulated by GCSRM
were summarized according to land and ocean categories in thetropics (15°S−15°N). Details of the model and analytical method
are described in Supplement 1.

3. Results and discussions
Figure 1 shows the average diurnal variation of precipitation
over land and ocean in the tropics. The average diurnal precipitation cycle of August 2012, obtained from TRMM 3B42 dataset(Huffman et al. 2007), is also shown for reference. Regarding
the diurnal cycle of precipitation over the ocean in the tropics(Fig. 1a), the peak times are between 0300 LST and 0600 LST
in the four experiments, except for Δ14, where the peak time isdelayed to approximately 0900 LST. The amplitudes of the diurnal
cycle are between 1.6 and 2.1 mm day−1, similar to the value of
1.3 mm day−1 from TRMM observations. The resolution dependence of the amplitude and timing of the precipitation peak is notclear among the four higher resolution simulations.
On the other hand, the simulated diurnal precipitation cycles
over land in the tropics show a remarkable difference with horizontal resolution (Fig. 1b). The precipitation peaks appear around2400 LST in Δ14 and Δ7. Previous studies using NICAM (Satoet al. 2009; Noda et al. 2012) also reported a midnight peak ofprecipitation at these resolutions. The peak time changes to around2000 LST in Δ3.5. With increasing horizontal resolution, thepeak appears earlier, and the peak amplitude becomes larger. The
peak time appears at 1800 LST and 1700 LST in Δ1.7 and Δ0.87,
respectively, which is equivalent to a peak time of approximately
1800 LST in TRMM 3B42 data. The peak amplitudes in the twohigher resolution simulations are approximately 5 mm day−1,
which are slightly larger than from the TRMM observations(~3.2 mm day−1). The start times of the precipitation peaks also
show resolution dependence. The increase in precipitation begins
in the afternoon in Δ14, Δ7, and Δ3.5. On the other hand, precipitation begins to increase in the late morning in Δ1.7 and Δ0.87.
At 2400 LST and 0900 LST, the precipitation amount is relatively
small, and its resolution dependence is also weak.
Figure 2 depicts the diurnal variation of the maximum verticalvelocity (Wmax) and precipitable water (PW). The Wmax mainly
expresses the upward motion in the cloudy area (see Supplement1). With decreasing grid intervals, the maximum Wmax becomeslarger, and the diurnal cycle appears more clearly (Fig. 2a). The
minimum Wmax is also larger in the higher resolution experiments. In general, smaller grid spacing results in stronger verticalvelocity with smaller horizontal scale. The clear resolution
dependence of minimum Wmax suggests that relatively stronger
upward motions occur throughout the day in higher resolution
experiments. The peak times of Wmax become earlier, and thestart times of the increasing Wmax phase appear earlier in thehigher resolution experiment. The results of Δ1.7 and Δ0.87 showthat convection starts before noon and rapidly increases over the273

following six hours. The peak time of Wmax is approximately
two or three hours earlier than that of maximum precipitation (Fig.
1b). However, Δ14 shows relatively small diurnal variations, withthe maximum at 2400 LST, which is almost the same as the timeof peak precipitation.
The diurnal variation of PW is similar in all five experiments(Fig. 2b). The PW begins to increase around 0900 LST, in conjunction with heat and water vapor fluxes from the surface, before
decreasing at around 1700 LST. The diurnal average PW increases
with increasing resolution from Δ14 to Δ3.5, and Δ1.7 and Δ0.87
show similar values to Δ3.5. The change of PW from Δ14 to Δ3.5
is mainly caused by the increase of water vapor in the middle
troposphere. Figure 3 shows the diurnal variation of the verticalprofile of relative humidity (RH) and total hydrometeors in Δ14,
Δ3.5, and Δ1.7. Drier conditions are found in Δ14 between 2 km
and 6 km altitude (Fig, 3a), owing to the lower specific humidity.
This difference can be related to the resolution dependence ofWmax. We speculate that the strong and small-scale upward
motion contributes moisture transport from the boundary layer
to the middle troposphere. The profile of RH shows a small difference between Δ3.5 and Δ1.7 (Figs. 3b and c), suggesting thatvertical moisture transport and condensation become balanced at
resolutions higher than Δ3.5. On the other hand, the diurnal variation of the cloud condensate profile differs significantly between
Δ3.5 and Δ1.7 (Figs. 3e and f ). Whereas the daily total of condensate increases from Δ14 to Δ3.5, it decreases from Δ3.5 to Δ1.7. In
Δ1.7 and Δ0.87, less condensate remains in the atmosphere. At thetime of total condensate increase, the hydrometeors are distributedin the lower to upper troposphere, indicating the existence of deep
moist convection. The peak time appears around midnight in Δ14(Fig. 3d) and becomes earlier in higher resolution experiments.
The increase of condensate in Δ14 can be linked to the decrease of
PW, which is equivalent to the decrease of RH in the middle troposphere. The results of Δ3.5 show similar characteristics to Δ14
but larger PW can result in more condensates and precipitation.
For Δ1.7, the increase of precipitation starts before the time when
PW begins to decrease.
Figure 4 shows the diurnal cycles of boundary layer height(BLH) and cloud base height (CBH). The maximum BLH clearly
differs among the experiments (Fig. 4a). In the lower resolution
simulations, the peak BLH is larger, and occurs later. The height
difference reaches several hundred meters between the lowest andhighest resolution experiments. For the CBH, the three experiments from Δ14 to Δ3.5 show an increase in cloud height at 1100
LST and 1500 LST, and then a decrease until 2300 LST (Fig. 4b).
On the other hand, the CBHs gradually increase in experiments
Δ1.7 and Δ0.87 until 0100 LST and then decrease over the following nine hours. One of the possible reasons for the difference
between the two groups may be the process of precipitating
convection. In the lower resolution experiments, non-precipitating
clouds can be dominant, and are pushed upwards with development of the boundary layer. In the higher resolution simulations,Fig. 1. Simulated diurnal cycle of precipitation in the tropics (15°S−15°N) for five horizontal resolutions:
Δ14, Δ7, Δ3.5, Δ1.7, and Δ0.87. Left panel (a) is over the ocean, and right panel (b) is over land.

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SOLA, 2016, Vol. 12, 272−276, doi:10.2151/sola.2016-053

Fig. 2. Diurnal cycles of a) column maximum vertical velocity (Wmax) and b) precipitable water (PW) over land in thetropics (15°S−15°N) for five horizontal resolutions.

Fig. 3. Diurnal cycles of the vertical profile of relative humidity (a–c) and totalhydrometeors (d–f ) over land in the tropics (15°S−15°N) for Δ14, Δ3.5, and Δ1.7.

the CBH can be kept relatively lower in the morning because of
the presence of convective clouds and precipitation (Fig. 1b andFig. 2a).
The diurnal cycles of convective available potential energy(CAPE) and convection inhibition (CIN) from five experiments
are shown in Fig. 5. CAPE shows a clear resolution dependence(Fig. 5a). It decreases in all experiments during the period from1700 LST to 0600 LST, with relatively larger values in Δ14 andΔ7. Generally, simulations with larger grid spacing need moreenergy for grid-scale convection near the surface under the sameenvironmental conditions. Although the PW is less apparent in thelower resolution experiments (Fig. 2b), the daily averaged CAPE
is larger than in higher resolution simulations. All experiments
show the increase of CAPE during the daytime. It is notablethat CAPE in Δ1.7 and Δ0.87 increases more rapidly from 0600
LST to 1200 LST. Especially in Δ0.87, CAPE values close to the
maximum are maintained from 1200 LST to 1700 LST, whereas
single, narrow peaks appear at 1700 LST in the lower resolution
experiments.
There are several potential factors that affect/change CAPE.
Enhancement of the surface sensible heat flux and water vapor
flux can increase CAPE, whereas increased moisture in the middle
troposphere due to shallow cumulus clouds acts to decrease CAPE
(Waite and Khoudier 2010). Evaporation of precipitation cools
and increases moisture in the lowermost atmosphere, which tends
to both increase and decrease CAPE. We speculate that local
moisture convergence is a possible cause of the more rapid increase in CAPE in Δ1.7 and Δ0.87. The high-resolution simulation
enables us to resolve smaller-scale convergence and divergencein connection with convection. The diurnal cycle of CIN indicatessimilar behavior to that of CAPE (Fig. 5b). While the maximum
values of CIN are almost equal in all experiments, in the higher
resolution experiments the increase in CIN is more rapid, and thepeaks appear earlier. The lower resolution simulations show lessnegative values at nighttime.

4. Concluding remarks
Global atmospheric simulations with five different horizontal
resolutions and without CP schemes showed a clear resolution
dependence of the diurnal cycle of precipitation over land in thetropics. In this study, we examined the diurnal cycle of precipitation and parameters related to convective activity using thesimulation results. The lower resolution simulations indicateda precipitation peak at midnight, whereas the TRMM observed
precipitation peak appeared in the late afternoon. In the lowest
resolution experiment, precipitating convection is initiated after
the BLH decreases at approximately 1500 LST, and the precipitation peak is later than the peak of CAPE/CIN. These results
suggest that moisture convection during the night is affected byorographic lift of water vapor in the two lowest resolution experiments. Kodama et al. (2015) showed the spatial distribution of
precipitation peak times simulated by NICAM with a grid spacingof 14 km. In their results, midnight precipitation occurred near
the mountainous areas. With increasing horizontal resolution, thepeak time became earlier and the amplitude became larger. The
two highest resolution experiments better reproduced the observed

Yashiro et al., Resolution Dependence of Precipitation Diurnal Cycle Simulated by GCSRM

275

Fig. 4. Same as Fig. 2, but for a) boundary layer height (BLH) and b)
cloud base height (CBH).

Fig. 5. Same as Fig. 2, but for a) convective available potential energy(CAPE) and b) convection inhibition (CIN).

time of peak precipitation. After sunrise, vertical velocity andprecipitation in those experiments began to increase at an earlier
time. Previous studies using large eddy simulation (LES) show
the generation of convection in the morning, transitioning to deep
convection in the afternoon (Khairoutdinov and Randall 2006; Wu
et al. 2009). This process is important for effective representationof the diurnal precipitation cycle. Our results suggest that thehigh-resolution simulations with grid spacing of less than 2−3 km
have the ability to reproduce weak convection with precipitationin the late morning. The Δ3.5 experiment showed the same RH
level as Δ1.7 in the middle troposphere in the morning (Fig. 3b
and c), but precipitation was not significant until the afternoon.
This leads to the time difference in the precipitation peak between
Δ3.5 and Δ1.7. The high-resolution simulation can effectively
reproduce both small convective areas and small condensation
areas. Thus, grid spacing affects not only moisture transport fromthe boundary layer to the middle troposphere, but also the rapid
formation of rain. This fundamental change is related to the different representation of convection at resolutions less than 2−3 km,
shown by Miyamoto et al. (2013) and Kajikawa et al. (2016). It
is notable that the change in the diurnal precipitation cycle overland in the tropics occurs without the effect of steep and complex
terrain in the high-resolution experiments.
Our study shows that improved representation of the diurnal
cycle of precipitation and related variables can be achieved byincreasing the horizontal resolution. However, the resolution
dependence of variables can be seen even in higher resolution
experiments. The resolutions used in this study are not yet sufficient to resolve all moisture convective phenomena, which require
much higher resolution for the convergence of all variables. The
resolution dependence of each model component also remains an
issue for future study. For example, overestimation of the precipitation maximum in the higher resolution experiments is possibly
caused by the lack of lateral mixing in deep convective clouds inour model (discussed in Supplement 2). Therefore, an appropriate
set of schemes is required to enable better representation of thediurnal precipitation cycle.

Acknowledgements
The authors are grateful to the editor of Scientific Online
Letters on the Atmosphere, and two anonymous reviewers. The
authors would like to thank Akira T. Noda at the Japan Agency for
Marine–Earth Science and Technology (JAMSTEC) for providing
us with the compiled data of TRIMM. We would like to express
our thanks to Drs. S. Nishizawa, S.A. Adachi, and Y. Sato at
RIKEN Advanced Institute for Computational Science (AICS).
The simulations were performed using the K computer at the
RIKEN AICS. This study was supported by Strategic Programsfor Innovative Research (SPIRE) Field 3 (Projection of Planet
Earth Variations for Mitigating Natural Disasters), which is promoted by the Ministry of Education, Culture, Sports, Science andTechnology (MEXT), Japan.
Edited by: T. Takemi

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