Journal of Heat Island Institute International Vol. 12-2 (2017)

Academic Article

Impact of Land Breezes on Nocturnal Temperaturein the Osaka Plain
Takashi Ogawa*1, Ryusuke Yasuda*1, Atsumasa Yoshida*1*1 Department of Mechanical Engineering, Osaka Prefecture University
Corresponding author: Ryusuke YASUDA, yasuda@me.osakafu-u.ac.jp
ABSTRACT
To investigate whether land breeze can be effective for the mitigation of nocturnal urban heat island (UHI) in
the Osaka Plain, we evaluated land breeze cooling on summer nights. An analysis of observational data shows that
there is a mutual relationship between the nocturnal temperature and land breeze. The influence of changes in land
use and the sea surface temperature (SST) on long-term trends in nocturnal temperature and land breeze wasinvestigated using a numerical model. The results showed that the effect of land use change was larger than that of
SST change. The cooling effect of the nocturnal wind was also evaluated using the change rate of potential
temperature by advection. The result indicated that the cooling effect at night was about -0.2 K/h in the Osaka Plain
under the sea breeze condition. However, under the land breeze condition, the cooling effect was about -1.0 K/h ininland areas and about -0.6 K/h in the coastal areas. Although the cooling effect of land breezes reduces from inland
to the coast, the effect still exists around coastal areas. Therefore the study concluded that land breeze cooling iseffective in the mitigation of nocturnal UHI over the entire Osaka Plain.
Key Words : Urban heat island, Land breeze, Temperature, Cooling rate, Advection, Numerical model

１. Introduction
Kyoto

Nose

Osaka is the most populous metropolitan area in western Japan

Yodo River

Hyougoand is well known for its severe summertime thermal
environment(1). The Osaka Plain is the central area of the Osaka
Prefecture, and is surrounded by mountains to the north, east, andToyonaka

Hirakata

Osaka

Ikoma
Osaka

south. The western side faces the Osaka Bay (Fig.1). Since landsea breeze circulations often develop in this area, utilization of theKumatori

Osaka BayNara

sea breezes is expected to be effective for the mitigation of the

Yamato River
Sakai

daytime urban heat island (UHI) in summer(2)-(4). However, it is

20 km

well known that UHI is usually remarkable at night(5)(6). High

Wakayama

temperatures on summer nights not only deteriorate thermal
comfort and increase power consumption by air conditioning
units but also lead to increase of sleep disorder and heat stroke(7)(8).
To consider using land breezes as measures of nocturnal UHI, it

Fig.1 Analysis area. Red filled circles are AMeDAS
observation points. Prefecture names are underlined. The
photo was obtaned from Google Earth.

is necessary to investigate the influence of land breeze on the“land breeze” as a flow which generates inland and reaches to thenocturnal temperature and to evaluate its cooling effect.

coast. Driving force of it is basically a pressure gradient between

Cooling effects of sea breezes in the daytime in the Osaka Plain

land and sea, but drainage flow develops in the mountainous areas,

had been investigated by several researchers(9)-(11). On the otherwhich is a density flow, is also included as a source of it.

hand, research focused on a cooling effect of nocturnal land

Characteristic of the land breeze cooling will not be the same as

breezes in the plain are quite a few. In this study, we use the termthat of sea breeze. Since sea breezes in the daytime advance into

- 18 -

a mixing layer, a strong updraft usually accompanies at thewind and air temperature on summer nights by an analysis ofleading edge of it. On the other hand, land breezes penetrate into

observational data. In section 3, to investigate whether recent

stable layers; therefore, the head has a flattened shape(13) and thechanges in land use and SST affect the land breeze, the influence

updraft at the leading edge is not strong as in the sea breeze. Withof these changes were evaluated using a meteorological model. In

such a difference, the cooling effect of land breeze might besection 4, the cooling effect of nocturnal land breeze waslimited compared to that of sea breeze. Tamai etal.(12)have

estimated by numerical simulations. A summary and conclusion

investigated a cooling effect of nocturnal drainage flows coming

are provided in the final section.

from the eastern mountains of the plain. They concluded that thedrainage flows do not contribute to the cooling in the central area

２. Relationship between observed nocturnal wind andof the plain; however, the cooling effect of land breezes in thetemperatureother areas in the Osaka Plain is not clear. In the daytime, thecooling effect of sea breezes become large as the wind speed

The relationship between nocturnal wind and air temperature on

increases. On the other hand, in the case of the land breeze, highsummer nights in the Osaka Plain was investigated using a cluster

wind speed may lead to an opposite result, in considering thatanalysis(18) based on hourly observational data obtained from theradiative cooling of the ground surface during the nighttime isAutomated Meteorological Data Acquisition System (AMeDAS)

large under clear and calm conditions. When wind speed ofoperated by JMA. The analysis period was in July and August

nocturnal land breezes is high, it may obstruct the cooling infrom 2006 to 2009. To avoid the influence of synoptic flow of thesurface layer by increasing heat transport from upper warm layer

wind and precipitation on the temperature, windy days (|𝑈𝑔 |≥15

through an enhancement of turbulence mixing.

m/s) and/or rainy days (R≥1 mm) were excluded from the analysis,

Another important factor concerned with the land breeze coolingwhere 𝑈𝑔 is the mean geostrophic wind and R is the total

is a trend of its occurrence. According to a report published inprecipitation, during 0100-0600 LST at the Osaka meteorological1987 by Osaka Regional Headquarter of Japan Meteorologicalobservatory. The geostrophic winds at the point were estimatedAgency (JMA)(14), the mean starting time of land breezes wasfrom the quadratic polynomial fitting of sea surface pressures(19)2300 LST around the center of the Osaka Plain, though thebased on observational data at 27 meteorological observation sites

statistical period and the method of the analysis were not shown.

around the Kansai area. The wind speed of 15 m/s is large;

Later, Kono et al.(1) also investigated the mean starting time of

however, the surface wind is much smaller than this. Under thisland breezes in the plain based on observation data obtained on

condition, the maximum value of mean nocturnal wind (0100-

clear days in July from 1994 to 1998. Their results indicated that

0600 LST) at AMeDAS Osaka site was 5.3 m/s, and 94% werethe mean starting time of the land breeze is late compared to theless than 3 m/s.

former study in most of the plain; e.g. the starting time around the

As a result, data used in this analysis covered 202 days. A degree

center of the Osaka Plain is 0500 LST. They also stated that theof distribution similarity (“distance”) between one day (a) andnocturnal wind around the coastal area of the Osaka city did not𝑊another day (b) for wind, 𝐷𝑎𝑏, was defined aschange to land breeze in more than half of the cases. These results

𝑊
𝐷𝑎𝑏
=

may suggest that the land breezes have been weakening in this

1
𝑁𝑀

𝑁
2
2 (1)
∑𝑀
𝑖=1 ∑𝑘=1 √(𝑈𝑎𝑖𝑘 − 𝑈𝑏𝑖𝑘 ) + (𝑉𝑎𝑖𝑘 − 𝑉𝑏𝑖𝑘 )𝑇and for temperature, 𝐷𝑎𝑏, asplain. The reason of such changes is not clear, but it is likely thaturbanization in the suburbs of the Osaka city has contributed to

𝑇
𝐷𝑎𝑏
=

the changes. In particular, changes in land use will have a

1
𝑁𝑀

𝑁
2
∑𝑀
𝑖=1 ∑𝑘=1 √(𝑇𝑎𝑖𝑘 − 𝑇𝑏𝑖𝑘 )(2)substantial influence on the land-sea breeze circulation of the area

where 𝑈𝑎𝑖𝑘 , 𝑉𝑎𝑖𝑘 , and 𝑇𝑎𝑖𝑘 are eastward and northward

gradient(15)-(17).

components of hourly wind speed, and air temperature,

Changes in the sea surface temperature (SST) around the Kansai

respectively. The subscript i is the hour, a is the date, and k is thearea may also affect on the land breezes. Tamai et al.(10) pointed

observation point index. N(=7) is the total number of observationout that SST of the Osaka Bay affects the nocturnal temperaturepoints (Fig.1), and M(=6) is average time (0100-0600 LST). The

in the Osaka Plain. Therefore, nocturnal wind system in the Osaka

Ward’s method was used as the linkage criterion. We grouped thePlain may be also influenced by the SST. In addition to the cooling

analysis days into three clusters for the wind (W1–W3) and threeeffect of the land breeze, the influence of these factors should beclusters for temperature (T1–T3).

investigated.

Mean wind vectors and air temperatures in each wind cluster

In this study, we evaluated the land breeze cooling on summer

during the averaging time at AMeDAS monitoring points arenights in the Osaka Plain to investigate whether utilization of land

shown in Fig. 2 (W1)-(W3). In W1, the wind direction in thebreezes can be effective for the mitigation of nocturnal UHI. In

central area of the Osaka Plain is westerly, i.e. this cluster

section 2, we investigated the relationship between nocturnal

corresponds to a sea breeze pattern. Conversely, in W3 an easterly

through changes in temperature and pressure- 19 -

W2

27

W3
Temperature (℃)

W1

26
25
24
(5 years moving average)

23
1990
100
Osaka
80

T3

T2

Freqency of land breezes
occurrence (%)

T1

Fig.2 Mean wind vectors and air temperatures in each cluster at
AMeDAS monitoring points. W1-W3 (upper) are the wind
pattern groups, and T1-T3 (lower) are the temperature pattern

Toyonaka

W2

36days12days34daysHirakata

20(5 years moving average)

1995

2000
Toyonaka

2005
Hirakata

Fig.4 Long-term trends of (a) mean nocturnal temperature and17days 97days(48%)

44days

2005

40

Osaka
W1

2000

60

0
1990

groups. All values were averaged from 0100 to 0600 LST.

1995(b) frequency of land breeze occurrence.

67days(33%)

21daysThe number of days in each cross-category between wind andW3 5days

10days0%50%
T138days(19%)

23daystemperature is shown in Fig.3. In W1, the ratio of T1 is higher
than T3, while in W3, the opposite is true. Therefore, nocturnal

100%
T2

temperatures in the Osaka Plain are often high under the sea

T3

breeze pattern and often low under the land breeze pattern.

Fig.3 The number of days and percentages in each cross-category

Although these results do not indicate a cause-effect relationshipbetween wind and temperature groups.

between the land-sea breeze condition and temperature
distribution in the plain during summer nights, they clearly show

wind dominates in the area, which indicates this cluster

a mutual relationship between them.

corresponds to a land breeze pattern. The wind direction in W2 is

To examine long-term trends in nocturnal land breezes andsimilar to the land breeze pattern; however, the wind speed istemperature in the plain, AMeDAS observation data at three

relatively weak. Therefore, W2 is regarded as an intermediate

points (Osaka, Toyonaka, and Hirakata) were investigated. The

pattern between W1 and W2. The frequency of land breeze patternanalysis period was in July and August from 1988 to 2010. As(W3, 19%) seems to be somewhat too much if the average startingwith the cluster analysis, hourly data during 0100-0600 LST weretime of the land breezes around the center of the Osaka Plain isused and windy/rainy days were excluded. Fig. 4(a) shows long-

0500 LST as reported by Kono et al.(1); however it is difficult toterm changes of mean nocturnal temperature. Nocturnal

make further discussions on it quantitatively because detailed

temperature has been rising at every point. The rates ofconditions of their analyses are not presented. The figures clearlytemperature rise are greater in the early 1990s than later in theshow that mean nocturnal temperature at the monitoring points
under the land breeze condition is lower than that under the sea

study period. Fig. 4(b) shows the trends in land breeze occurrence.

breeze condition. At the AMeDAS Osaka monitoring point, theThe land breeze occurrence was determined from the vector meanof wind directions during 0100–0600 LST at each AMeDAS point.

mean nocturnal temperatures in W1, W2, and W3 are 26.9 °C,

The land breeze directions of the nocturnal wind were identified

26.0 °C, and 24.8 °C, respectively. In W3, temperatures at otheras the following (clockwise):observation points were also 1.2–2.3 °C lower than those in W1.
Fig. 2 (T1)-(T3) show mean nocturnal wind vectors and Osakatemperatures averaged in each air temperature cluster. The mean

- N, NNE-ENE

 Toyonaka - NNE-E, NW-N

temperature is high in cluster T1 and low in cluster T3. The Hirakata

distribution pattern of mean wind direction in T1 is similar to W1(sea breeze pattern), and that of T3 is similar to W3 (land breeze- NE-SE

with reference to the wind rose at each point. The land breeze ratio

pattern).

- 20 -

Table 1 Correlation between nocturnal temperature andTable 2 Calculation parameters of the numerical model.

frequency of land breeze occurrence.

Items

Domain 1

Domain 2

AMeDAS points

Correlation coefficients

Horizontal grid interval

3 km

1 km

Osaka

-0.73 (p<0.01)

Number of horizontal grids

120×120103×103

Toyonaka-0.68 (p<0.01)

Central coordinate (Lat.,Long.)(34.672° ,135.480°)

Hirakata-0.63 (p<0.01)

Number of vertical layers

30

Microphysics

WSM-3 Class

decreased over time at every point. Table 1 shows that there arenegative correlations between the frequencies of land breeze
occurrence and temperatures.
３ . Influence of changes in land use and SST on
nocturnal land breeze and temperature
3.1 Numerical model

Planetary boundary layer

MYNN Level 2.5

Surface layer

M-O Similarity Theory

Longwave radiation

RRTM scheme

Shortwave radiation

Dudhia scheme

Land surface model

Noah LSM

Urban surface model

Single Layer UCM

used for analysis.

We investigated the influences of land use change in the Osaka
area and SST change around the Kansai area on long-term

3.2changes in the nocturnal land breeze and temperature using a

Analysis cases

The urban ratio in 1976 in Domain 2 is shown in Fig. 6(a). The

numerical model; the Weather Research and Forecasting (WRF)

urban ratio of each calculation grid (1 km square) was defined asmodeling system ver.3.7.1(20). The model parameters are shown ina ratio of land use meshes categorized as artificial surfaces (i.e.

Table 2. Initial and boundary conditions for the meteorologicalbuildings, major roads, and railways) to the total meshes, based on

variables were obtained from the Final Operational Global

100 m land use data. The central area of the Osaka Plain had al-

Analysis database of the National Centers for Environmental

ready urbanized in the mid-1970s and the urban area has been ex-

Prediction, with 1° resolution and 6-hour interval. Grid data of thepanding to its suburbs since then. Fig. 6(b) shows the increment ofaltitude (50 m resolution) and land use (100 m resolution) werethe urban ratio from 1976 to 2009. During this period, the urban

from the National Land Numerical Information database of theratio clearly increased in the northern and southern edges of the

National and Regional Planning Bureau. A single-layer urban

plain, along with the Yodo River, Nara Basin, and coastal areas in

canopy model(21) was activated on the urban grids specified by the

Hyogo and Wakayama.

land use data. Anthropogenic sensible heat estimated by Shimoda

Fig. 7 shows the long-term trend of the SST in summer (July-Sep-

et al.(22) was given in Domain 2.

tember) around the whole calculation domain (Domain 1), based

The calculation domain is shown in Fig. 5. Two domains were set

on data provided by JMA. SSTN is the SST on the north side of thewith a two-way nesting configuration. The depth of the lowest

domain (southwest zone of Sea of Japan) and SSTS is on the southlayer was approximately 57 m. A target date of August 26, 2006,

side (off coast zone of Shikoku-Tokai). In the last three decades,

was chosen from W3 (land breeze pattern) described in section 2.

they both increase (p<0.01) and the rates are approximately

Calculation started at 0900 LST on August 24, 2006. After the 39+0.02 °C/year.

hours spin-up, hourly data of 0100–0600 LST in Domain 2 wereWe simulated three cases as shown below:

Domain1
 Case1: Baseline. Land use data in 2009 was used.
 Case2: Same as Case 1 but land use was changed to as of 1976.
 Case3: Same as Case 1 but SST was 0.5 °C lower.
Domain2
3.3 Results and discussions
Fig. 8(a) shows the horizontal distribution of mean nocturnal temperature at 2 m and wind vectors at 10 m (averaged from 0100 to
0600 LST). Two major courses of land breezes can be seen in the
Osaka Plain. In the northern portion of the plain, the land breeze
flows from the northeast to the southwest along the Yodo River. In
the mid-south portion of the plain, the land breeze is generated in

Fig.5 Calculation domains of the numerical model.

- 21 -

the Nara basin, flows through a valley, and proceeds to the west

(a)along the Yamato River. The air temperatures along these land
breeze pathways are lower than the other areas on the plain. In thecentral area of the plain (sandwiched between these paths), theland breeze is weak and the temperature is high. Fig. 8(b) shows
the differences in mean nocturnal temperatures and wind vectors(0100-0600 LST) between Case 1 and Case 2. Note that thedifference between Case 2 and Case1 is brought by achange in the land use only. The calculation result of Case2 does not represent a meteorological state in 1976 because
the calculation conditions other than the land use are thesame as 2006. In most of the parts of the plain, from 1976 to(b)

2009, the temperature increased when land use changed. In areas
where there is a substantial rise in temperature, there is also a significant increase of urban ratio. The distribution of rising temperatures appears to affect the wind pattern through a change in thepressure gradient. The direction of the difference vectors along the
Yodo River is northeast, which indicates that land breeze weakens.
Such a change in direction is also true of the area along the YamatoRiver; the direction of the difference vectors in this area is eastward. Fig. 8(c) shows the differences of nocturnal average temperatures and wind vectors between Case 1 and Case 3. Since the SST
in Case 1 is 0.5 °C higher than Case 3, the temperature rise is(c)greater in sea areas but the temperature changes on the land arevery small compared to sea areas. The change in the land breezes

Fig. 6 Distribution of urban ratio (a) in 1976, and (b) its incrementfrom 1976 to 2009.

Fig. 8 Horizontal distribution of mean nocturnal
temperature at 2 m and wind vectors at 10 m. (a)Distribution on August 26, 2006. (b) Case 1-Case 2, (c)Case 1-Case 3. All of the values were averaged from 0100
to 0600 LST.
in the plain is also small though the land breeze is slightly weakened around the Yodo River and is slightly strengthened aroundthe Yamato River.
Table 3 and Table 4 show the increase of mean nocturnal temperature and the decrease of mean nocturnal wind speed, respectively.
These values were obtained by averaging the grid values lower
than 100 m in each region shown in Fig. 9. The influence of theFig. 7 Changes of mean SST in summer (July-September) fromchanges in SST on the nocturnal temperature and land breezes are

1976 to 2009. SSTN is “southwest zone of Sea of Japan”, andvery small compared to those of the land use change. As will be

SSTS is “off coast zone of Shikoku-Tokai”, according to JMA

shown in section 4.2, the temperature difference between observedlabeling. Solid line: moving average for 5 years. Dashed line:

and model values at night may reach around 1 °C; however, suchlinear regression.

- 22 -

value is a measure of the agreement between observation andmodel values, and it does not directly relate to the sensitivity on

Table 3 Difference of mean nocturnal temperature averaged ineach region (°C).

the physical mechanisms. These results indicate that the land use
Factorchange of urbanization has a larger impact on the temperature rise
and the land breeze weakening than the SST change.

Land use(Case1-Case2)
SST(Case1-Case3)

４. Evaluation of land breeze cooling
4.1

Central Northern Southern Kyoto
Osaka Osaka Osaka
Basin

Nara
Basin

+0.41

+0.33

+0.60

+0.30

+0.85

+0.02

+0.03

+0.07

+0.02

+0.02

Target cases and evaluation method

To evaluate the land breeze cooling, numerical simulations on the

Table 4 Difference of mean nocturnal wind speed averaged ineach region (m/s).

sea breeze case (August 11, 12, and 22, 2006) and land breeze case(August 23, 24, and 26, 2006) were executed using WRF. Thesedays were selected from W1 (sea breeze) and W3 (land breeze)

Factordescribed in section 2, as they are typical conditions of each noc-

Land use(Case1-Case2)
SST(Case1-Case3)

turnal wind pattern. A local cooling effect was evaluated by thechange rate of potential temperature. The change rate by each termin the conservation equation for potential temperature is given by𝜕𝜃

Advection: ( )𝜕𝑡 𝑎𝑑𝑣

Diffusion:

𝜕𝜃

( )

𝜕𝑡 𝑑𝑖𝑓𝑓𝜕𝜃

Radiation: ( )𝜕𝑡 𝑟𝑎𝑑𝜕𝜃Total: ( )𝜕𝑡 𝑡𝑜𝑡

=−
=

𝜕
𝜕𝑥𝑗

=

𝜕𝜃

=( )

𝜕𝑡 𝑎𝑑𝑣𝜕(𝑈𝑗 𝜃)

(3)

𝜕𝑥𝑗

(𝐷𝑗𝜃

𝜕𝜃
𝜕𝑥𝑗

Central Northern Southern Kyoto
Osaka Osaka Osaka
Basin

Nara
Basin

-0.24

-0.25

-0.28

-0.18

-0.43

-0.15

-0.13

-0.22

-0.07

-0.16

was not included. The spin-up time was 39 hours before the target
days and hourly data of 0100–0600 LST in Domain 2 were used)

𝜃 1 𝜕𝐹𝑇 𝜌𝐶𝑝 𝜕𝑧
𝜕𝜃

𝜕𝜃

+( )

𝜕𝑡 𝑑𝑖𝑓𝑓+( )𝜕𝑡 𝑟𝑎𝑑(4)

for analysis (same as Section 3).

(5)

4.2 Results and discussions(6)

4.2.1 Comparison of the model results with observations
Statistical evaluations were made using the measurements of thewhere 𝑈𝑗 is a component of wind speed, θ is the potential temper-

surface monitoring stations in the Osaka Prefecture (9 AMeDAS

ature, T is the air temperature, 𝜌 is the density, 𝐶𝑝 is the specificsites and 59 meteorological monitoring stations operated by local

heat at constant pressure, 𝐷𝑗𝜃 is the turbulent diffusion coefficient

governments). The statistics are defined as follows:for heat, and F is the long/short radiation flux. Sensible heat flux
from the land and sea surfaces are evaluated in the diffusion term.
The values in Eqs. (3) - (5) are evaluated at the lowest grid of theatmospheric layer. The representative height is the midpoint of the
1st layer (ca. 30 m). These terms are calculated by reconstructing(7)

Mean Gross Error (MGE)̅̅̅̅̅̅̅̅̅̅
𝑀𝐺𝐸 = |𝑀
− 𝑂|

(8)

Root Mean Square Error (RMSE)

the discrete equations of WRF model (including higher order up-

1

wind scheme) using grid values extracted from the output file of̅̅̅̅̅̅̅̅̅̅̅̅
𝑅𝑀𝑆𝐸 = {|𝑀− 𝑂|2 }2

WRF model. The heat exchange by condensation or evaporation(9)

Index of Agreement (IA)̅̅̅̅̅̅̅̅̅̅̅̅(𝑀− 𝑂)2
𝐼𝐴 = 1 −(10)̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅
(|𝑀 − 𝑂̅ | + |𝑂 − 𝑂̅ |)2
where O represents the surface measurements and M represents

KB
NO
CO
SO

Mean Bias Error (MBE)̅ − 𝑂̅
𝑀𝐵𝐸 = 𝑀

model values (wind speed at 10 m or air temperature at 2 m) at the
NB

monitoring points. Both are hourly values. The overline indicatesthe arithmetic mean of all hours for all points. Table 5 shows theresults and the benchmarks recommended by Emery et al.(23) The
boundary of a day is 0900 LST and the label is the date of the lasthour. All of the MGE and IA values of temperature and the RMSE

Fig. 9 Averaging regions used in Section 3.3. Altitude is less thanof wind speed are within the recommended values, though the

100 m. NO: Northern Osaka, CO: Central Osaka, SO: Southern

MBEs indicate that the model tends to over predict the wind speed

Osaka, KB: Kyoto Basin, NB: Nara Basin. In NO, a part of
Hyogo Prefecture is included.

- 23 -

The nocturnal flows would be shallow under the stableconditions, and the locality of the flows might be prominentcompared with those in the daytime. To investigate whether WRF
performance degrades at night, the evaluation indices shown
above were estimated for each time zone (01-06, 07-12, 13-18,
19-24 LST) during the analysis period.
Fig.11 shows the result of temperature indices. In general, IA
value in each time zone is smaller than the daily value because thevariation during an averaging time is included in the denominatorof the fraction in IA. Note that the difference from theobservations was particularly large in the daytime on 22 August(22D) because of an occurrence of the shower which was notpredicted by the model. The MBEs of temperature sometimes(a) August 11,12, 2006

show large positive or negative values and exceed the range
recommended by Emery et al.(23) especially in the morning(yellow bars) and daytime (red bars). Time series comparison
between the observation and model results suggests that hightemperatures in the daytime tend to be predicted somewhat lower.
The nighttime values of MBE (black bars) except 12 August(12N) are generally smaller than those in the morning and daytime.
All of MGEs except 22D are within the recommended range.
Since variations of temperature in the nighttime are smaller thanthose in the daytime, MGEs in the nighttime often show smallvalues in comparison with the daytime values. IAs in thenighttime except 12 August satisfy the benchmark value.
Fig.12 shows the variation of the evaluation indices on wind(b) August 22-24, 2006

speed. The MBEs show that the wind speeds are overpredicted inmost of the time zones, especially in the evening and nighttime.
As of 2006, wind speeds at AMeDAS points were recorded in 1
m/s unit, therefore the MBE’s benchmark of 0.5 m/s might be too
restrictive. All of the RMSEs are within the recommended range,
but it must be taken into account that the wind speed is generally
small at night, which leads to a small value of RMSE. IAs of windspeed for each time zone in the daytime seems to show relatively
large values in comparison with the nighttime though only a few
of them satisfy the benchmark.
Table 5 Evaluation indices of agreement between
calculation and observation. Boldfaces indicate within the(c) August 24, 26, 2006
Fig. 10 Comparison between observed value and calculation

benchmarks.
Air temperature

result at Osaka AMeDAS point. Observed wind speeds were
adjusted to a value at 10 m above ground level using a Log law.

Date

Period of (a)-(c) was calculated individually. First 39 hours in

MBE MGE
(°C)

(°C)

IA

≦±0.5 ≦2.0 ≧0.8

each run is spin-up period.
and under predict the air temperature. As shown in Fig. 10, theagreement between the model result and the observations is fairly
good. The model results successfully reproduced the changes inAugust 22.

- 24 -

(m/s)

(m/s)

IA

≦±0.5 ≦2.0 ≧0.6

2006/8/11 -0.20

1.00

0.94

0.98

1.34

0.66

2006/8/12 -1.05

1.35

0.93

1.03

1.69

0.49

2006/8/22 -0.70

1.00

0.94

0.64

1.29

0.59

0.35

1.25

0.87

0.80

1.56

0.51

2006/8/24 -0.41

0.90

0.97

0.88

1.46

0.62

2006/8/26 -0.76

1.43

0.92

0.30

1.11

0.54

2006/8/23

temperature and wind except for a shower in the late afternoon on

Wind speed
MBE RMSE

Fig.11 Evaluation indices about temperature in every time

Fig.12 Evaluation indices about wind speed in every timezone during the analysis period. Upper: MBE, Middle: MGE,

zone during the analysis period. Upper: MBE, Middle:

Lower: IA. The horizontal axis indicates a date (in August,

RMSE, Lower: IA. The horizontal axis is the same in2006) with time zone suffix. The suffixes are N:nighttime

Fig.11.

(01-06 LST, Black bars), M:morning (07-12 LST, yellow

is also a land breeze case). Compared to the sea breeze case, thebars), D: daytime (13-18 LST, Red bars) and E:evening(19-temperature along the Yodo River and the Yamato River, the main

24 LST, Blue bars). Gray areas show the ranges

routes of the land breeze, are relatively low and a high-temperature

recommended by Emery et al.(23)region appears in the eastern part of the plain.
4.2.3 Cooling effect of nocturnal flow

These results suggest that the WRF accuracy in the nighttime isFig. 14(a)(b) shows the time series of the change rates of each term

not so inferior to that in the daytime, at least from the point ofin the conservation equation of potential temperature in the lowest

view of the evaluation indices we have used.

layer of a grid where an Osaka AMeDAS site is present. As pointed
out by Yoshida et al.(4), in both cases, the variation in the change

4.2.2 Mean distribution of nocturnal wind and temperature

rate of the advection term is almost the same in magnitude but op-

Model results were averaged in each case to reduce the fluctuation

posite in sign to that of diffusion term. In the sea breeze case, cool-brought by the day-to-day disturbance. The distribution of mean

ing by advection in the daytime is significant, but it becomes muchtemperature and wind vectors averaged in 0100-0600 LST isless at night. The daytime cooling by advection in the land breeze

shown in Fig. 13(a)(b). During the night in the sea breeze case, thecase is less than the sea breeze case, but it does not reach the low

air temperature is high in the central and northern areas of thecooling levels at night shown in the sea breeze case. Note that the

Osaka Plain because the sea breezes with high temperature keep

wind during the day is sometimes sea breeze in the land breeze

proceeding over the plain along the Yodo River. A remarkablycase because both cases are categorized by wind direction only at

high-temperature region is located inland along the Yodo River be-night. The cooling rate by advection at night is -0.3 K/hcause the cooling effect of the sea breeze is weakening at the loca-

approximately in the sea breeze case and approximately -1.0 K/htion. Mean temperature and wind vectors in the land breeze casein the land breeze case. The diffusion heating during the nighttime

show almost the same distributions as Fig. 8(b) in Section 3 (which- 25 -

4
Change rate of θ [K/h](a)(a) Sea breeze case

3
2
1
0
-1
-2
-3
-4

8

12

16

20
LST [h]

0

4

8

0

4

8

Change rate of θ [K/h]4(b)(b)Land breeze case

3
2
1
0
-1
-2
-3
-4

8

12

16

Advection
Radiation

20
LST [h]Diffusion
Total

Fig.14 Change rates of each term in the conservation
equation of potential temperature at Osaka AMeDAS point

Fig. 13 Distribution of mean nocturnal temperature at 2 m and(the lowest layer). (a) the sea breeze case. (b) the land breezewind vectors at 10 m (a) in the sea breeze case, (b) in the landcase. Averaged values of all days in each case .

breeze case. Averaged values from 0100 to 0600 LST on alldays in each case are shown.

breezes reduces from inland to coastal areas, the effect remains

in the land breeze case is greater than in the sea breeze case. Thiseven around the coasts. In the temperature distributions under theis because the air temperature in the land breeze is lower than thatland breeze condition (Fig.8 (a) and Fig.13 (b)), a relatively high-of the temperature in the sea breeze and there is a large temperaturetemperature area exists on the eastern side of Osaka Prefecture. In

difference between the ground surface and the air. In the sea breeze

there, cooling rate by advection is also small. These distributions

case, sea breeze at high temperatures continue to flow at night, andsuggest that the drainage flow from Mt. Ikoma seems not to havethe temperature remains high. On the other hand, in the land breezea direct influence of cooling in this area, as described in Tamai etcase, colder wind flows from surrounding mountainous and/or ru-al.(12). The cooling of the area and the central area of the Osaka

ral areas remove heat from the urban surface. In an urban area, heat

Plain is brought by the land breeze along the main route of the land

flux at the ground surface is often positive even at night(24). Heatbreeze. Therefore, it is concluded that land breeze cooling is effec-

transport to the upper layer at the top of the lowest layer by turbu-

tive in the mitigation of nocturnal UHI over the entire area of thelent diffusion is smaller than the surface heat flux because net

Osaka Plain.

change rate of diffusion term is positive. Radiation term shows
5. Conclusion

negative value at night but small in magnitude. Therefore, thecooling effect of the advection is important, especially in urban
area.

In the Osaka Plain, the nocturnal temperature and the land-sea

Fig. 15(a)(b) shows the horizontal distribution of the cooling rate

breezes have a mutual relationship. The nocturnal temperature isby advection in the lowest layer of the model over the plain area

relatively low under the land breeze cases and relatively high un-(altitude is less than 100 m). In the sea breeze case the cooling rate

der the sea breeze cases. From 1976 to 2009, the nocturnal tem-is about -0.2 K/h on the plain. In the land breeze case, the coolingperature has increased and the frequency of the land breeze has

rate is -1.0 K/h approximately in inland areas, and -0.6 K/h ap-

decreased through the plain. The influence of changes in land use

proximately in coastal areas. Although the cooling effect of land

and SST on the trends in the nocturnal temperature and the land

- 26 -

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(Received Apr. 30, 2017, Accepted Jul. 7, 2017)- 28 -