INTERNATIONAL JOURNAL OF CLIMATOLOGY
Int. J. Climatol. (2010)
Published online in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/joc.2119

High-resolution modelling of the potential impact of land
surface conditions on regional climate over Indochina
associated with the diurnal precipitation cycle
Hiroshi G. Takahashi,a *†‡ Takao Yoshikane,a Masayuki Hara,a Kumiko Takataa
and Tetsuzo Yasunaria,ba Frontier Research Center for Global Change (FRCGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama,Japanb Hydrospheric Atmospheric Research Center (HyARC), Nagoya University, Nagoya, Japan

ABSTRACT: This study examined the impact of changes in land surface conditions on regional climate over Indochina
using a high-resolution regional climate model. Anthropogenically induced land surface changes are going on in this part oftropical Southeast Asia. Because a previous study suggested that deforestation in this area affected September precipitation,
we chose September as the study period. We performed a control simulation (CTL) driven by reanalysis data combinedwith current land use and predicted soil moisture data. The CTL reproduced the spatial distribution of total precipitation
well. In addition, it also simulated a distinct diurnal cycle of precipitation that was previously reported in observational
studies. Two sensitivity experiments, assuming wetter and drier land surface conditions over the Khorat Plateau (northeast
Thailand) compared with the current land surface condition, were conducted and examined the impact of land surfacechanges on precipitation. The results indicated that drier land surface conditions increased precipitation over the disturbed
region. A pronounced increase in precipitation was found only during nighttime, which coincided with the peak in the
climatological diurnal precipitation cycle. Climatologically, the diurnal peak in precipitation occurs from evening to earlymorning over the Khorat Plateau. Drier conditions intensified the diurnal variation of precipitable water associated with thethermally induced local circulation responsible for a horizontal gradient of near-surface temperature. The effects of land
use and land cover changes in the tropics are shown to be strongly related to the diurnal precipitation cycle. Copyright 2010 Royal Meteorological Society
KEY WORDS

land surface condition; Southeast Asian monsoon; diurnal cycle in precipitation; thermally induced local
circulation; precipitable water; regional climate change; regional climate modelling

Received 28 November 2008; Revised 11 December 2009; Accepted 5 January 2010

1.

Introduction

Land use and land cover changes (LUCCs) may impact
regional climates as well as the global climate. In thetropics, one of the largest LUCCs is deforestation. The
Asian monsoon region, including the Indochina Peninsula
and the maritime continent, has experienced intensive
anthropogenic deforestation since the latter half of the20th century (e.g. Ramankutty and Foley, 1999).
Over the past three decades, various global climate
modelling studies have examined the potential impactsof deforestation on regional and global climates (e.g.
Henderson-Sellers and Gornitz, 1984; Dickinson andHenderson-Sellers, 1988; Lean and Warrilow, 1989;
Shukla et al., 1990). Using coarse-resolution global and* Correspondence to: Hiroshi G. Takahashi, 3173-25 Showamachi,
Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan.
E-mail: hiroshi3@jamstec.go.jp† Current address: Research Institute for Global Change, Japan Agency
for Marine-Earth Science and Technology, Yokohama, Japan.
‡ Current address: Graduate School of Urban Environmental Science,
Tokyo Metropolitan University, Tokyo, Japan.
Copyright  2010 Royal Meteorological Society

regional climate models (GCM and RCM, respectively),some studies have conducted experiments with recorded
LUCC data to examine the effects of historical LUCCs
on global climate (e.g. Chase et al., 2000; Kanae et al.,
2001; Brovkin et al., 2006). Although these modellingstudies have provided somewhat different results, they
have generally agreed that deforestation leads to reduced
precipitation and evaporation and increased surface temperature in the disturbed regions.
Pielke (2001) argued that land surface changes affectboth regional and global climates. He noted that somestudies have shown a decrease in precipitation due todeforestation or conversion from original vegetation tocultivation, whereas others have found an increase inprecipitation. A decrease in precipitation would likely
relate to a decrease in water vapour from the surface orin convective available potential energy (Pielke, 2001).
Studies showing that LUCCs can enhance convection andincrease precipitation have implicated thermally induced
local circulation due to horizontally inhomogeneous sensible heating created by different surface properties (e.g.

H. G. TAKAHASHI et al.

Ookouchi et al., 1984; Segal and Arritt, 1992; Emori,1998).
D’Almeida et al. (2007) discussed observational andmesoscale modelling studies of the impacts of LUCCs
on precipitation and convective activity over the Amazon.
They noted that few observational and mesoscale modelling studies have shown reduced precipitation or suppressed convective activity under deforested conditions.
The results of observations and mesoscale modelling areinconsistent with the reduced precipitation predicted by
GCMs and coarse-resolution RCMs (D’Almeida et al.,2007). Consequently, D’Almeida et al. (2007) concluded
that, from local to regional scales, LUCC intensifies convective activity by creating horizontally inhomogeneous
near-surface temperature. Recently, a possible impact of
LUCCs on regional climate was examined over the South
Asian monsoon region using satellite-derived normalized difference vegetation index (NDVI) and precipitation datasets. The result suggested that a decrease in thethermal contrast between land and sea due to intensive
irrigation over land might induce a decrease in precipitation in that region (Lee et al., 2009). This observational
finding may be explained by the mechanism discussed by
D’Almeida et al. (2007).
Most studies on the impacts of deforestation haveused GCMs or coarse-resolution RCMs. However, models with horizontal resolutions coarser than approximately
50 km cannot resolve regional-scale terrain and land use.
For this reason, it is quite difficult to capture regional climate. More examinations of the climatological effects ofregional-scale LUCCs on regional climates using highresolution models are needed. In particular, no previous
high-resolution studies have examined the climatological effects of regional-scale LUCCs on the regional
climate over the Asian monsoon region although thisarea has experienced intensive LUCCs. In this study,
we focused on the Indochina Peninsula, where deforestation has occurred in northeast Thailand over the lastcentury. In addition, Kanae et al. (2001) found a decreasing trend of observed precipitation in September over the
Indochina Peninsula. They used a coarse-resolution RCM
and suggested that the decreasing trend may be associated with a decrease in evapotranspiration due to therecorded deforestation. However, as mentioned above,
their coarse-resolution RCM could not reproduce local
circulations due to regional-scale terrain and horizontally
inhomogeneous sensible heating created by different surface properties. Therefore, it is necessary to examine theimpact of LUCCs using a high-resolution model. To discuss the observed decrease in September precipitation,
we chose September as our study period.
Another major issue in the use of models with coarse
horizontal resolution is the need for cumulus convective
parameterization (CCP) to involve subgrid-scale convective activity. However, there are many uncertainties associated with CCP, and these parameterizations have different sensitivities to dynamic and thermodynamic fields,
as shown even when using an approximately 30-km
mesoscale model (Pan et al., 1996). Furthermore, CCP
Copyright  2010 Royal Meteorological Society

cannot reproduce the observed diurnal cycle of precipitation (e.g. Dai and Trenberth, 2004; Dai, 2006). Precipitation in the tropics, in particular, is characterized as convective precipitation. Recent studies using tropical rainfall measurement mission precipitation radar (TRMMPR) data have described distinct diurnal variations inprecipitation (e.g. Hirose and Nakamura, 2005). Even
when the horizontal resolution of several atmosphericgeneral circulation models (AGCMs) were improved to
0.5° , the diurnal cycle in precipitation still deviated fromobservations, probably due to the CCP (Lee et al., 2007).
Hara et al. (2009) demonstrated that for an AGCM witha 20-km grid, the CCP produced significant error in thediurnal cycle and spatial distribution of precipitation overthe maritime continent. Thus, the reproduced climatesand possible impacts of LUCCs over the tropics strongly
depend on the characteristics of CCP because the CCP
produces most of the precipitation. To examine impactsof regional-scale LUCCs over tropical regions, numerical models should be able to reproduce realistic regional
climate, including the diurnal variation of precipitation.
Therefore, in this study we investigated the potential
impact of intensive LUCCs over the Indochina Peninsula
using a high-resolution RCM without CCP. Because
tropical precipitation systems are generally nonlinear, we
reduced the uncertainty by using a long-term (one-month
period) simulation. Section 2 documents the experimental
design. Section 3 presents results of the numericalexperiments. Possible mechanisms behind the effects of
LUCCs are discussed in Section 4, and conclusions are
given in Section 5.

2.

Experimental design

We used a convective system resolving model to simulate a realistic distribution of precipitation and local
circulations related to terrain and land use. The advanced
weather research and forecasting (WRF) modelling system (Skamarock et al., 2005), which is a nonhydrostatic
RCM developed by the National Center for AtmosphericResearch (NCAR), was chosen for this purpose. The 40year reanalysis (ERA-40, Uppala et al., 2005) datasetof the European Centre for Medium-Range Weather
Forecasts (ECMWF) and the extended reconstructed sea
surface temperature (SST) V2 (Smith and Reynolds,
2004) datasets of the National Oceanic and Atmospheric
Administration (NOAA) were used as initial and boundary conditions. Soil moisture and temperature data from
ERA-40 were also used. The horizontal grid incrementof the coarse domain was 25 km and that of the twoway nested domain was 5 km. The domains and terrain
are shown in Figure 1(a). Both domains had 27 terrainfollowing vertical levels. Because preliminary experiments with CCP showed a very unrealistic precipitation
distribution and diurnal pattern, we did not apply CCP in
either domain. The WRF single-moment six-class microphysics scheme (Hong and Lim, 2006) and the Noah landInt. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA(a)

Model Domain & Terrain [m](b)Simplified Landuse category

Cultivation Grassland Rainforest

Figure 1. The upper panel (a) shows the terrain in the WRF model,
and the lower panel (b) presents the land use categories. D1 (D2) in(a) indicates the coarse (nested) domain. Grey-dashed line in (a) iscross-section of Figure 12. The thick line in (b) indicates the assumed
area of dense tropical rainforest (disturbed region).

surface model (Noah-LSM; Chen and Dudhia, 2001; Ek
et al., 2003) were also used.
The Noah-LSM had one canopy layer and four soil
layers down to 2 m, with the root zone in the upper
1 m. The surface skin temperature was determined bya surface energy balance equation for the combined
ground–vegetation surface. The total evapotranspiration
was the sum of the direct evaporation (Edir ) from the top
soil layer, evaporation of precipitation intercepted by the
canopy (Ec ), and transpiration (Et ) by the canopy. Edirand Ec were calculated by a Penman-based energy balance approach that included a stability-dependent aerodynamic resistance. The canopy resistance was calculatedwith empirical equations (Jacquemin and Noilhan, 1990).
Copyright  2010 Royal Meteorological Society

The simulation with current land use (CTL) was
performed three times from 30 August to 1 Octoberin each year from 1998 to 2000. The first two daysof the simulation (30 and 31 August) were assumed tobe the spin up. We analysed one-month results from 1
to 30 September. The current land use was taken from1992 data obtained from the United States Geological
Survey (USGS). In the past, northeast Thailand washighly forested; however, the 1992 data categorized the
majority of northeast Thailand as under cultivation. In
the WRF model, the prime cultivated land use wasgiven as ‘irrigated cropland and pasture’, and the tropicalrainforest was described as ‘evergreen broadleaf forest’.
Figure 1(b) shows the spatial distribution of land use.
We also conducted two sensitivity experiments assuming dense rainforest with wet soil moisture (WET) andsparse forest with dry soil moisture (DRY) to understandthe impact of changes in land surface conditions. The
design of WET was based on that of Kanae et al. (2001).
The CTL and WET experiments differed in regard to thesurface condition over northeast Thailand. The inner area
enclosed with the black thick line in Figure 1 was definedas the assumed area of dense tropical rainforest. For the
WET experiment, all land uses of the disturbed region
were given as evergreen broadleaf forest except for thewater body category. The parameter of the green fraction
was set to 90%, which is comparable with the fraction
found in undisturbed areas of the Indochina Peninsula.
Because the green fraction parameter indicates the green
vegetation coverage in a model grid, dense (little deforested) and sparse (intensively deforested) rainforests werecharacterized by the difference of green fraction. Overthe disturbed region, volumetric soil water content wasforced to remain at 0.45 m3 /m3 throughout the time integration. The value of volumetric soil water content wasalmost the same as that simulated just after a precipitation
event.
To understand the extreme impacts of intensive deforestation, DRY experiments were also conducted. The
surface condition was assumed to be dry, sparse forest.
The spatial distribution of this land use category was thesame as that for WET, but the green fraction was set
to 20%, and volumetric soil water content was forced
to remain at 0.20 m3 /m3 . This value for the green fraction can be found in intensively disturbed areas of the
Indochina Peninsula. The volumetric soil water content
was almost the same as that found in the dry season. The
WET and DRY experiments were also conducted during
September for three years from 1998 to 2000. These three
years had less precipitation than other years of the second half of the 20th century according to the time series
shown in Figure 5 from Takahashi and Yasunari (2008);
a similar result was also obtained from an examination ofarea mean precipitation using Climate Prediction Center(CPC) merged analysis of precipitation (CMAP; Xie andArkin, 1997) data for the Indochina Peninsula.
We used the TRMM-PR 2A25 precipitation product(Iguchi et al., 2000) included in the TRMM 3G68 version 6 product for evaluation of model reproducibility ofInt. J. Climatol. (2010)

H. G. TAKAHASHI et al.

precipitation amount and the diurnal cycle of precipitation. Hereafter, these precipitation data are referred tosimply as TRMM-PR. We analysed only precipitation
observed by the PR. Because the study area was limited
to the Indochina Peninsula, we used the unified local timealong 105 ° E. These data had a 0.5 × 0.5 grid resolution.
We used eight years of TRMM-PR observations from1998 to 2005. Hirose et al. (2008) investigated the issueof the sample number of TRMM-PR observations. Theysuggested that a minimum eight-year mean was likely
needed to describe 3-hourly diurnal variations of precipitation because of the sparse observations of TRMM.
To evaluate the simulated atmospheric structure, weused 6-hourly soundings measured at Ubon Ratchathani(104.87 ° E, 15.25 ° N), Thailand, under the frameworkof the Global Energy and Water Cycle Experiment(GEWEX)-Asian Monsoon Experiment-Tropics (GAMET).
The name of the Khorat Plateau, the key region ofthis study, sometimes causes misunderstanding. Although
the Khorat Plateau is higher than the low-altitude
plain around Bangkok, it is bordered by mountain
ranges on its eastern, northern and western sides. Thus,
the Khorat Plateau is basically a basin-shaped valley rather than a plateau. The region of the Khorat
Plateau is almost coincident with the disturbed region(Figure 1).

TRMM-PR Sep 98-05

(a)
20°

200

2
20000

16°

200

0

500

12°

400
100°
(b)

104°

108°

Simulated Rain Sep 98-00

20°

300

200
16°
100

[mm/month]

12°

100°

3.

20

104°

108°

Results

3.1.

Performance of CTL

Before analysing the sensitivity experiments, we compared the precipitation simulated by CTL with theobserved precipitation (Figure 2). Abundant precipitation
was observed along the coasts of the eastern Bay of Bengal and eastern Gulf of Thailand, as well as the eastern
coast of northern Vietnam (Figure 2). The peaks of thesimulated precipitation were closely correlated with thepeaks indicated by TRMM-PR. To further examine these
spatial similarities, a spatial correlation coefficient rs wascalculated by the following equation:
rs =

N

i=1



 N
N



2
(xi − x)(yi − y)/(xi − x)  (yi − y)2
i=1

i=1

(1)
where N is the number of grids, xi is the eight-year
average of total rainfall measured by TRMM-PR for
September at the ith grid, yi is the three-year averageof simulated total precipitation for September at the ith
grid, x is the average of all xi , and y is the average of all
yi . The spatial resolution of simulated precipitation wasconverted to the spatial resolution of the observations. A
value of 0.55 was calculated for rs , which was statisticallysignificant at the 99.9% confidence level, indicating thatthe monthly mean precipitation was well simulated. In
addition, Takahashi et al. (2009) performed a long-term
simulation for September with the same model parameter
Copyright  2010 Royal Meteorological Society

Figure 2. Total amounts of September precipitation over the Indochina
Peninsula. (a) September precipitation averaged over eight years from1998 to 2005 for September, observed by TRMM-PR. (b) The
three-year averaged simulated precipitation.

settings; that study showed that long-term (30-year)
experiments can capture not only the spatial pattern of
precipitation but also the total amount of precipitation,compared with rain gauge observations. They suggested
that the precipitation amount indicated by TRMM-PR
was relatively less than rain gauge observations. At theleast, the spatial distribution of three-year precipitationof CTL was similar to the observed precipitation of the
Indochina Peninsula.
Table I. Temporal correlation coefficient of daily mean zonal
wind at 850 hPa (u850) and daily mean specific humidity at
925 hPa (sh925) between simulation (CTL) and observation(reanalysis).
Year

u850
(WRF JRA)u850(ERA JRA)sh925(WRF JRA)

sh925(ERA JRA)

1998
1999
2000

0.93
0.95
0.98

0.98
0.99
0.99

0.59
0.62
0.67

0.71
0.75
0.89

The second and fourth column showed the correlation between two
kinds of reanalysis datasets.
All values were statistically significant at the 99.9% confidence limit.
Int. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA

We also examined day-to-day variations of low-level
zonal wind and specific humidity averaged over the100° –104 ° E, 12° –15° N region. Table I shows the temporal correlation coefficient for zonal wind and specific humidity between the simulations and observations(given by reanalysis data). Low-level zonal wind, namely
the monsoon westerly, was well correlated with the observation data. Low-level humidity was also well simulated.
On the basis of correlations with two major reanalysis
datasets, the simulation fairly reproduced realistic dayto-day variations of atmospheric fields. Day-to-day variations of zonal wind showed strong and weak monsoon
westerly phases. Because monthly mean precipitation
is associated with various atmospheric conditions, suchas strong and weak monsoon westerly phases, a threeyear experiment can allow for discussion of the potential
impact of LUCCs.

The simulated atmospheric structure was examined,
compared with the 6-hourly soundings observed at Ubon
Ratchathani (104.87 ° E, 15.25 ° N), Thailand. The verticalstructure of virtual potential temperature was well simulated, compared with the observations (Figure 3). The
simulated heights of the boundary layer at 1200 local
time (LT) on 5 September and 8 September 1998 werealso consistent with the observed heights. The height ofthe planetary boundary layer was approximately 1000 m
at 1200 LT. Boundary layer heights on other days werealso well simulated (not shown). The vertical structuresof water vapour were simulated as well, although theabsolute values were sometimes overestimated in themodel (not shown). The consistency of the boundary
layer heights and the vertical structure of water vapour
imply that sensible and latent heat fluxes from the surface were realistically simulated. The simulated vertical

06LT 05 Sep 1998

06LT 08 Sep 1998

3000
[m]

3000
[m]

2000

2000

1000

1000

0

[K]
297 300 303 306 309 312 315 318

297 300 303 306 309 312 315 318

12LT 05 Sep 1998

12LT 08 Sep 1998

3000
[m]

3000
[m]

2000

2000

1000

1000

0

[K]
297 300 303 306 309 312 315 318

018LT 05 Sep 1998
3000
[m]

2000

2000

1000

1000
[K]
297 300 303 306 309 312 315 318

000LT 06 Sep 1998
3000
[m]

2000

2000

1000

1000
[K]
297 300 303 306 309 312 315 318[K]
297 300 303 306 309 312 315 318
00LT 09 Sep 1998

3000
[m]

0

[K]
297 300 303 306 309 312 315 318
18LT 08 Sep 1998

3000
[m]

0

[K]

0

0

[K]
297 300 303 306 309 312 315 318

Figure 3. The vertical structure of virtual potential temperature on 5 and 8 September 1998 at Ubon Ratchathani (104.87 ° E, 15.25 ° N), Thailand.
Black lines indicate the simulation. The open circles denote the vertical distribution of terrain-following levels in the model. Red lines represent
observations.
Copyright  2010 Royal Meteorological SocietyInt. J. Climatol. (2010)

H. G. TAKAHASHI et al.

Figure 4. The contribution rate to the total precipitation (a) of three-year (1998–2000) simulated precipitation for September and (b) of eight-year(1998–2005) climatological precipitation for September observed by TRMM-PR. This contribution rate is defined as the proportion of rainfall
during a 3-h period to the total rainfall amount for 24 h.

structures of virtual potential temperature at 1800 LT
sometimes differed from the observations, probably due
to the nonlinear behaviour of mesoscale convective systems.
Previous studies have noted that diurnal variations ofprecipitation dominate over and around the Indochina
Peninsula (Satomura, 2000; Ohsawa et al., 2001; Hirose
and Nakamura, 2005; Takahashi et al., 2010). Therefore,
we also examined the reproducibility of diurnal variationof precipitation by looking at 3-h mean diurnal precipitation variations. To facilitate the examination of thediurnal pattern of precipitation, the contribution rate isshown in Figure 4 because the total amount of precipitation of TRMM-PR was somewhat smaller than simulated
values. The contribution rate is defined as the proportionof rainfall during a 3-h period to the total rainfall amountfor 24 h at each grid point. The value at 1400 LT, forexample, indicates the mean precipitation from 1300 to1559 LT. The three-year diurnal variations of the simulated precipitation for September and the eight-year mean
diurnal variations of TRMM-PR precipitation are shownin Figure 4.
Copyright  2010 Royal Meteorological Society

Daytime precipitation was simulated over the mountain ranges and along the coasts [Figure 4(a)]. Evening
precipitation began at 1700 LT over low-altitude land
areas such as Bangkok, Thailand and a plain in Cambodia. Over the southern Khorat Plateau, precipitation
had a diurnal cycle with a peak at 2200 LT, lasting until
early morning. This simulated diurnal pattern of precipitation [Figure 4(a)] was similar to that of TRMM-PR[Figure 4(b)]. Thus, the diurnal pattern of precipitation
was fairly simulated, which indicated that CTL can beconsidered to have reproduced diurnal variations of precipitation over and around the Indochina Peninsula.
3.2. Differences among CTL, WET and DRY
The purpose of this study was to understand the impactsof surface condition changes on precipitation. With thisgoal in mind, this section discusses the differences inprecipitation among the three sensitivity experiments.
Because the effects of surface condition change may
depend on environmental circulation, we averaged thesimulated results for September over three years for eachexperiment.
Int. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA(b)

TOTAL WET

500
300

0

0

30

16°

400

0

16°

30

30

0

200

TOTAL DRY

20°

300

300

40

(a)
20°

400

50

350

0

400

300
250

0

0
670

0

104°

100°

108°
(d)

DIFF [CTL - WET]

(c)

30

0

70
0

100°

100

12°

12°

[mm/month]

104°

108°

DIFF [DRY - CTL]

20°

20°
0

200
160
120
80
40
0
-40
-80
-120
-160
-200

0

0

-80

80

0
0

16°

0

16°

80

0

0
-80

0

-80

12°

100°
(e)

104°

80

0

0

12°

100°

108°
(f)

# of increase (CTL - WET)

450

104°

108° [mm/month]# of increase (DRY - CTL)

20°

20°

16°

16°

12°

12°

100°

104°

108°

100°

104°

18
16
14
12
10
8
6
4
2
0
[pentad]108°

Figure 5. Total amount of monthly precipitation of (a) WET and (b) DRY. Differences in monthly precipitation (c) between DRY and CTL(CTL–WET) and (d) between CTL and DRY (DRY–CTL) are shown. The numbers of pentads out of 18 that calculate increase in pentad
precipitation (e) between DRY and CTL (CTL–WET) and (f) between CTL and DRY (DRY–CTL) are shown. The calculation period of eachexperiment is three months, which is 18 pentads (90 days). The numbers of pentads that show increase in precipitation were counted at eachhalf-degree grid. White and black lines indicate the disturbed region.

Figure 5(a) and (c) shows that the total precipitationin the CTL experiment was greater than that of WET
over the southern Khorat Plateau (around 104 ° E, 15° N,
within the disturbed region) and slightly less southof the Khorat Plateau (around 104 ° E, 13° N, outside
the disturbed region). Although the area mean total
precipitation of CTL was almost the same as that of
WET over the disturbed region, the change in surface
conditions altered the spatial distribution of precipitation
around the southern boundary between the disturbed andundisturbed regions [Figure 5(a)].
To investigate the impact of severe deforestation,
we conducted the DRY experiment. Compared with
CTL, DRY showed an increase in precipitation overthe disturbed region, particularly over the southern
Khorat Plateau [104 ° E, 15° N, Figure 5(d)]. However,precipitation decreased in the area surrounding the
Copyright  2010 Royal Meteorological Society

disturbed region, particularly to the south of the Khorat
Plateau (104 ° E, 13° N, outside the disturbed region). The
spatial distribution of precipitation also differed between
CTL and DRY [Figure 5(b) and (d)]. Among the threeexperiments, signals of precipitation differences were
found over and around the disturbed regions.
To investigate the robustness of the increases in precipitation over the disturbed region between the sensitivity experiments and CTL, we show the spatial distribution of the number of pentads out of 18 in which
increased precipitation was calculated. Each experiment
was conducted for three months, and each experimenthad 18 pentads (90 days). Large numbers indicate thatprecipitation increased in various atmospheric conditions,such as in the strong and weak monsoon westerly phases.
If a few unusual precipitation events contributed to theincrease in precipitation, the number should be small.
Int. J. Climatol. (2010)

H. G. TAKAHASHI et al.

(b)

20°

DIFF (DRY - CTL)
2000 LT
20°

20°

DIFF (CTL - WET)
2000 LT
20°

16°

16°

16°

16°

12°

12°

12°

12°

(a)
0800 LT

96°

100°

104°

108°

96°

100°

0800 LT

104°

108°

96°

2300 LT1100 LT
20°

20°

16°

16°

100°

104°

108°

96°

100°

104°

108°

2300 LT1100 LT
20°

20°

16°

16°

12°

12°

0.3
12°

12°
96°

100°

104°

108°

96°

100°

104°

108°

0.2

96°

0200 LT

1400 LT

100°

104°

108°

96°

20°

0.1

20°

20°

16°

16°

-0.1

16°

16°

-0.2

12°

12°

12°
96°

100°

104°

108°

96°

100°

104°

108°

100°

104°

108°

20°

20°

16°

16°

16°

16°

12°

12°

104°

108°

100°

104°

108°
-0.3

[mm/hour][mm/hour]

12°
100°

0.2

-0.1

0500 LT

1700 LT

20°

96°

108°

0.1

96°

20°

12°

104°

-0.2
96°

-0.3

0500 LT

1700 LT

100°

0200 LT

1400 LT

20°

12°

0.3

96°

100°

104°

108°

96°

100°

104°

108°

96°

100°

104°

108°

Figure 6. Difference in the September mean diurnal cycle in precipitation over three years (a) between DRY and CTL (DRY–CTL) and(b) between CTL and WET (CTL–WET).

Thus, the pentad number can be used to investigate
the robustness of the mean difference in precipitation.
Larger numbers of pentads appear over the regions where
increases in precipitation were found [Figure 5(e) and(f)]. This result indicated that the increases in precipitation over the disturbed region were calculated undervarious atmospheric conditions. Therefore, the signals
are robust and indicate that changes in the surface
conditions can locally alter the spatial distribution of
precipitation.
Note that the three experiments not only showed
an association between a drier surface condition andlikely increases in precipitation over the disturbed region
but also showed decreases in precipitation in areas
around that disturbed region. Interestingly, there wasno large difference between WET and CTL. However, CTL and DRY showed large precipitation differences over the disturbed region, as will be discussed in
Section 4.
As noted previously, the CTL experiment reproduced
the diurnal pattern of precipitation. Because changes
in precipitation may be closely associated with basic
precipitation processes in the region, this subsection also
discusses changes in the diurnal pattern of precipitation
due to changes in the surface condition.
Figure 6(a) presents changes in precipitation from CTL
to DRY during each time period. Increased precipitation
Copyright  2010 Royal Meteorological Society

was calculated from evening to morning over the disturbed region, whereas small changes in daytime precipitation were also found in the disturbed region. The
timing of increased precipitation over the Khorat Plateau
coincided with the climatological peak in the diurnal precipitation cycle of the region. The differences seemed to
be associated with the climatological diurnal cycle of precipitation. Thus, the sensitivity experiment indicated thatthe diurnal cycle of precipitation was more marked in
DRY compared with CTL.
A similar tendency was found for the difference
between CTL and WET [Figure 6(b)], although the signal
was weaker than that between CTL and DRY. Nocturnal
precipitation was also increased over the disturbed area.
These sensitivity experiments suggest that diurnal variation in precipitation is likely the key process for understanding the mechanism of precipitation changes responsible for the surface condition changes over northeast
Thailand. Therefore, the following subsection investigates characteristics of precipitation from evening tomorning over northeast Thailand.
3.3. Climatological diurnal cycle of precipitation overnortheast Thailand
To investigate the atmospheric circulation fields associated with the diurnal cycle of precipitation, we examined the diurnal component of water vapour flux andInt. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA
Diurnal Component of QV & PW
0700 LT20°100 [kg/m/s]

Diurnal Component of QV & PW

16°

16°

12°

12°

100°

104° [mm]-3.0 -2.4 -1.8 -1.2 -0.6 0.0 0.6 1.2 1.8 2.4 3.0

100°

100 [kg/m/s]

Diurnal Component of QV & PW
0100 LT
20°

16°

16°

12°

12°

100°

104° [mm]-3.0 -2.4 -1.8 -1.2 -0.6 0.0 0.6 1.2 1.8 2.4 3.0

104° [mm]-3.0 -2.4 -1.8 -1.2 -0.6 0.0 0.6 1.2 1.8 2.4 3.0

Diurnal Component of QV & PW
1900 LT20°100 [kg/m/s]

1300 LT20°100 [kg/m/s]

100°

104° [mm]-3.0 -2.4 -1.8 -1.2 -0.6 0.0 0.6 1.2 1.8 2.4 3.0

Figure 7. The monthly mean diurnal cycle of vertically integrated water vapour flux (vector) and precipitable water (colours) of CTL over three
years for 0700, 1300, 1900 and 0100 LT. The diurnal component is shown.

precipitable water. The diurnal component was calculated
as the monthly daily mean subtracted from the monthly
mean diurnal cycle.
The diurnal variation in precipitable water (Figure 7)
was consistent with that of precipitation (Figure 4).
Water vapour was transported to the mountain ranges at
1300 LT, probably in association with thermally induced
local circulation. The increase in water vapour over themountain ranges was consistent with daytime convective
activity there. Along the coasts, the sea breeze probablytransported water vapour from the sea to the coast
during daytime. At 1900 LT, water vapour fluxes fromthe Annam Mountain range and the Gulf of Thailand
met at the southern Khorat Plateau. The increase inprecipitable water from evening to midnight (0100 LT)
was consistent with the heavy nocturnal precipitation over
the Khorat Plateau. The water vapour over land was
gradually transported to the adjacent sea by 0700 LT.
Copyright  2010 Royal Meteorological Society

Because the Indochina Peninsula is located in thetropics, it receives enough energy for the developmentof convective activity. Much water vapour is probably also supplied from adjacent seas. These conditions
favour the development of convective activity in daytime.
However, the convective activity of the Khorat Plateau
is suppressed during daytime, implying the possible
existence of a suppression mechanism. To understandthe suppression of convective activity during daytime, avertical–longitudinal cross-section of vertical wind along
17° N is shown in Figure 8. Ascending motion developed
along the mountain ranges from 1000 to 1600 LT (1300
LT is shown in Figure 8), whereas descending motion
was simulated over the Khorat Plateau (102° –104 ° E).
The descending motion was likely induced by the thermally induced local circulations and a compensating
downward motion, coupled with the convective activities
over the mountain ranges. Daytime convective activity
Int. J. Climatol. (2010)

H. G. TAKAHASHI et al.
(a)1300 LT

Vertical Wind [m/s x 0.01](b)

Vertical Wind [m/s x 0.01]

2000 m2000 m

1500 m

1500 m1000 m1000 m

500 m

500 m

0m
98 E

0m
98 E

99 E 100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 E
-4

-2

-1

0

1

2

4

1900 LT99 E 100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 E
-4

-2

-1

0

1

2

4

Figure 8. Vertical–longitudinal cross-section of monthly mean vertical wind of CTL over three years along 17° N for 1300 LT (a) and 1900 LT(b). The red colour indicates ascending motion, whereas the blue colour denotes descending motion. The grey mask indicates terrain.
(a)Virtual Potential Temperature [K] 1300 LT

2000 m(b)

Virtual Potential Temperature [K] 1900 LT

2000 m
310

1500 m

1500 m308

3081000 m

4

306

30

500 m

0m
98 E

99 E 100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 E

6

500 m

306
30

6

1000 m

30

0m
98 E

99 E 100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 E

Figure 9. Vertical–longitudinal cross-section of monthly mean virtual potential temperature of CTL over three years along 17° N for 1300 LT(a) and 1900 LT (b). The grey mask indicates terrain.

over the Khorat Plateau was probably suppressed by thisdescending motion. In addition, some water vapour wastransported to the surrounding mountain regions, a process that may also have supported suppression throughthe decrease of potential convective instability. By 1900
LT, the downward motion weakened because of theabsence of convective activity over the mountain ranges
and the alternation of local winds from anabatic winds tokatabatic ones. The absence of descending motion can
produce an atmospheric structure in which convective
activity can develop.
Figure 9 shows a vertical–longitudinal cross-section ofvirtual potential temperature. The convective boundary
layer was developed over the Khorat Plateau during
daytime [Figure 9(a)]. The structure of virtual potential
temperature favoured the development of anabatic winds,
which probably formed convective activity along themountain ranges. During nighttime, the isothermal lines
followed the terrain, favouring the formation of katabatic
winds [Figure 9(b)].
Figure 10 shows the diurnal components of wind at
10 m above the surface. Winds converged over the mountain ranges at 1300 LT [Figure 10(a)]. Thermally induced
circulations were strong near the coast, a phenomenon
Copyright  2010 Royal Meteorological Societythat can be explained by the superposition of mountain–valley and land–sea breezes. After sunset, strong
downslope winds were simulated along the western sideof the Annam Mountain ranges [1900 LT, Figure 10(b)].
Westward winds also developed over the central Khorat
Plateau. The climatological characteristics of the diurnal variations of low-level wind fields were consistent
with those of virtual potential temperature. The katabatic winds from the Annam Mountains flowing into the
Khorat Plateau at 1900 LT possibly triggered convective activity. However, the intensification of downslope
winds from the Annam Mountains may not be explained
solely by radiative cooling of the slope after sunset.
Rather, part of the intensification may be related to themoist processes of convective activity. Because the moist
processes of mesoscale convective systems are, in general, highly nonlinear, it is not possible to identify themechanisms of the triggers and developments of convective activities from climatological mean fields. Thus, weinvestigated typical cases of the development of nocturnal precipitation over the Khorat Plateau. Analysis of two
typical cases is presented in the following subsection.
Int. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA(a)
1300 LT

Simulated horizontal wind at 10m
1 [m/s](b)1900 LT

20°

20°

16°

16°

12°

12°

100°

104°

Simulated horizontal wind at 10m
1 [m/s]

100°

104°

Figure 10. September mean diurnal component of the horizontal wind pattern at 10 m above the surface of CTL over three years for 1300 LT(a) and 1900 LT (b).

3.4. Mechanism of nocturnal precipitation over
the Khorat Plateau
Previous subsections have described the climatological
diurnal pattern in precipitation and the associated atmospheric circulations. The climatological analysis suggested that nocturnal precipitation was likely associatedwith downslope wind from the mountains surrounding
the Khorat Plateau (Figure 10). However, the essential
mechanism of nocturnal precipitation systems over the
Khorat Plateau requires further clarification. This subsection investigates that mechanism.
Two cases were chosen that are typical in terms ofsimilarity of the diurnal pattern of precipitation to theclimatological diurnal pattern of precipitation. In thefirst case, a strong monsoon westerly prevailed over the
Indochina Peninsula on 1 September 1999. In the second
case, on 23 September 1999, the monsoon westerly
was weak. Figure 11 shows the diurnal sequences ofprecipitation for these two cases, which were similar
to the climatological diurnal pattern of precipitation(Figure 4).
Figure 12 presents the vertical section of moist static
energy (contours), winds (vectors), precipitation (openblack bar in each lower panel) and virtual potential
temperature (shading) along the grey-dashed line in
Figure 1(a). The vectors show the horizontal wind velocities along the section and vertical wind velocities. Moist
static energy is given in Kelvin. The accumulated precipitation, shown as an open black bar in the lower panels,
was totalled from the current time (shown at the upper
left of the upper panel) to 30 min later.
The convective boundary layer gradually developed
over land, particularly over the Khorat Plateau after
sunrise (not shown). Anabatic winds met over the crestsof the western and eastern mountain ranges of the Khorat
Copyright  2010 Royal Meteorological Society

Plateau, inducing convective activities at 1500 LT. A
cold air mass was formed on top of the mountain ranges,
possibly as a result of convective activities. Descending
motions were shown over the Khorat Plateau. The cold
air mass drifted into the basin-shaped Khorat Plateau
from 1600 to 1900 LT. Gravity-current-like flow probably
triggered convection at the eastern slope of the mountain
ranges at 102.5 ° E at 1800 LT. The induced convective
activity could further form the cold air mass (2100 LT)
and likely result from the evaporation of raindrops andfrom raindrops carrying down low moist static energy air
from above the planetary boundary layer. A cold air massseemed to induce convection in sequence (not shown).
As a result of these processes, the simulated precipitation system over the Khorat Plateau moved eastward.
Similar systems repeated during the night. In addition,
similar gravity-current-like flow formed on the western
slope of the Annam Mountain range although the induced
precipitation was relatively weaker.
On 23 September 1999 (Figure 13), a precipitation system was developed on the western slope of the mountain
ranges of 106 ° E at 1400 LT (not shown). A cold air mass
was formed on the western slope of the mountain range
and drifted westward into the Khorat Plateau (1800 and1900 LT). The cold air mass, associated with a westwardtravelling precipitation system, extended to 104 ° E in the
Khorat Plateau at 2100 LT. This westward flow was also
likely to be a gravity current, and the cold air mass probably triggered the convective systems around 104 ° E. The
system moved westward. The formation mechanism of
this cold air mass seems to have been similar to that ofthe precipitation system on 1 September 1999. In thismanner, moist convective processes intensified the katabatic winds from the mountain ranges. The cold air massthat resulted from convective activity probably enhanced
the katabatic winds.
Int. J. Climatol. (2010)

H. G. TAKAHASHI et al.
(a)Precipitation on 1 Sep. 1999
2000 LT
20°

(b)
20°

Precipitation on 23 Sep. 1999
2000 LT
20°

16°

16°

16°

16°

12°

12°

12°

12°

20°

0800 LT96° 100°
1100 LT

104°

108°

96° 100°
2300 LT

0800 LT

104°

108°

96°

100°

104°

108°

96°

20°

20°

20°

20°

16°

16°

16°

16°

12°

12°

12°

12°

96°
20°

100°

104°

108°

1400 LT

16°

16°

12°

12°

96°
20°

100°

104°

108°

1700 LT

104°

108°
1.0

100°

104°

108°

100°

104°

108°

96°

100°

104°

108°

0200 LT

1400 LT
20°

20°

16°

16°

12°

12°

1.0

0.2

0.2
100°

104°

108°

0500 LT

96°
0.0

96°

100°

104°

108°

96°

100°

104°

108°

0500 LT

1700 LT
20°

20°

16°

16°

12°

12°

0.0

[mm/hour]

12°

12°

108°

5.0

96°

16°

16°

96°

100°

0200 LT

96°
20°

104°

5.0

96°
20°

100°

2300 LT1100 LT

100°

104°

108°

96°

100°

104°

108°

96°

[mm/hour]
100°

104°

108°

Figure 11. Diurnal sequence of 3-h precipitation of CTL for each time period (a) on 1 September 1999 and (b) on 2 September 1999.

Both eastward and westward migrations of precipitation systems were identified. The examination of relationship of these systems to the low-level monsoon westerly indicated that eastward-migrating systems prevailed
during the westerly phases. However, some westward
migrations were also found when the westerly prevailed.
During weak monsoon westerly phases, more westward
migrations were indentified. Other days showed similar convective systems during nighttime. Basically, theprecipitation system in this area was associated withthe low-level monsoon westerlies. During the monsoon
season, more eastward-migrating precipitation systems
were simulated. These simulated convective systems
were likely consistent with the two-dimensional cloudresolving modelling results of Satomura (2000). This
result was also consistent with recent findings by Oouchi
et al. (2009), who used a global cloud-resolving model.

4. Discussion
4.1. Diurnal variations in water vapour modulated
by surface condition change
A pronounced increase in precipitation during nighttime
was shown due to changes in the surface condition from
CTL to DRY. Because of this large sensitivity experimentsignal, we investigated the differences between CTL and
DRY. The area-averaged precipitation over the disturbed
Copyright  2010 Royal Meteorological Society

area was 323.9 mm/month in CTL and 366.0 mm/monthin DRY. Precipitation may have increased due to alarger number of precipitation events, or it may haveincreased with an increase in precipitation intensity rather
than in precipitation frequency. How do we explain
the increase? In this study, we did not consider thelife cycle of precipitation events. Thus, precipitation
frequency coincided with the duration of precipitation.
We examined changes in the frequency by counting
precipitation events, defined by certain criteria. The
mean precipitation intensity of CTL, P , was 0.45 mm/h.
The changes in the frequency of precipitation eventsof more than 0.1, 0.22 and 0.45 mm/h were 2.3%,
2.7% and 3.9%, respectively (Table II). Although thefrequency of precipitation may have increased somewhat,these changes would not explain the 13% increase intotal September precipitation. Therefore, increased mean
precipitation intensity was probably the main reason for
the increase in total precipitation. In general, the change
shown in each individual precipitation event cannot
reflect the climatological change in precipitation becauseof the nonlinearity of precipitation events. To understandthe increase, we examined changes in the climatological
diurnal cycles of winds and water vapour fields.
The differences in temperature at 2 m and winds at
10 m between CTL and DRY showed that the temperature of DRY was much higher than that of CTL
Int. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA
1800 LT0.05 [m/s]Wind: Horizontal wind along the section;w

3481000 m
8

34
34

0m

100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 0.0
E

98 E

99 E

4

[K]

0

100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 0.0
E

0.5

0.5

1.0

1.0

1.5

1.5

0.05 [m/s]2100 LT
Wind: Horizontal wind along the section;w

5 [m/s]
315
314
313
312
311
310
309
308
307
306
305
304
303
302
301
300
299
298
297
296
295

34

8

344

1500 m1000 m

34

500 m

[K]
99 E

315
314
313
312
311
310
309
308
307
306
305
304
303
302
301
300
299
298
297
296
295

344

344

0m
98 E

344

500 m

5 [m/s]

340

0
34
344

348

1500 m

344

36

315
314
313
312
311
310
309
308
307
306
305
304
303
302
301
300
299
298
297
296
295

1500 m1000 m0.05 [m/s]Wind: Horizontal wind along the section;w

5 [m/s]344

1500 LT

340

344

344

500 m

34

0

340

0m
98 E

99 E

[K]

100 E 101 E 102 E 103 E 104 E 105 E 106 E 107 0.0
E
0.5
1.0
1.5

Figure 12. Vertical section moist static energy (dashed lines) and virtual potential temperature (shading) and winds in each upper panel andprecipitation in each lower panel of CTL along the grey-dashed line in Figure 1(a) for 1500, 1800 and 2100 LT of 1 September 1999. The
vectors show horizontal wind along the section and vertical velocity. The bars in each lower panel denote accumulated precipitation was totalledfrom the current time (shown at the upper left of the upper panel) to 30 min later. The accumulated precipitation is shown in the right verticalaxis. The unit of the accumulated precipitation is millimetre. The grey mask indicates terrain. The vectors at upper right-hand corner indicate
the lengths of horizontal and vertical velocities, 0.05 and 5 m/s, respectively.

(Figure 14). The difference in near-surface temperature along the boundary between the disturbed andundisturbed regions in DRY induced local circulations.
Wind convergence was identified over the disturbed
region. The convergence in wind possibly enhanced theconvective activity and precipitation. However, the precipitation increase due to the assumed surface condition change of extreme deforestation was distinct during
nighttime. The difference in 10-m wind also indicatedwind convergence at 1300 LT (not shown). Nevertheless, no increase in daytime precipitation was found(Figure 6). The wind convergence did not directly explain
the increase in precipitation.
We also examined the modulated diurnal variationsof water vapour fields (Figure 15). The difference inprecipitable water during each time period showed adecrease from late morning to evening and an increase
from late evening to early morning. The decrease inprecipitable water in daytime was likely responsible
Copyright  2010 Royal Meteorological Society

Table II. The simulated precipitation of CTL and DRY,
area-averaged within the disturbed region (Figure 1).
Category

CTL
DRY
Increase (%)

Precip(mm/month)

Freq
>0.1

Freq
>0.22 P /2

Freq
>0.45 P

323.9
366.0
13.0

32.75
33.51
2.3

25.79
26.48
2.7

19.38
20.13
3.9

The unit of precipitation is mm/month.
The frequency of precipitation was defined as the frequency at whichaccumulated precipitation for 3 h in each grid exceeded thresholdvalues, set at 0.1, 0.22 and 0.45 mm/h.
The value of 0.45 mm/h was the averaged intensity of precipitation P
for CTL.
The bottom line denotes the increase rate of each parameter from CTL
to DRY.

for the decrease of evapotranspiration from the surface
because the difference in evapotranspiration from theInt. J. Climatol. (2010)

H. G. TAKAHASHI et al.
1800 LT0.05 [m/s]Wind: Horizontal wind along the section;w

1900 LT5 [m/s]
315
314
313
312
311
310
309
308
307
306
305
304
303
302
301
300
299
298
297
296
295

1000 m

344

340

34

4

34

0

1000 m

340

500 m
34
8

0m

348

348

500 m

315
314
313
312
311
310
309
308
307
306
305
304
303
302
301
300
299
298
297
296
295

344

340

344

5 [m/s]1500 m

340

340

1500 m0.05 [m/s]Wind: Horizontal wind along the section;w

34

[K]

8

[K]

0m
98 E

99 E

100 E

101 E

102 E

103 E

104 E

105 E

106 E

107 E
0.0

98 E

99 E

100 E

101 E

102 E

107 E
0.0

1.0

1.5

1.5

0.05 [m/s]
5 [m/s]
40

315
314
313
312
311
310
309
308
307
306
305
304
303
302
301
300
299
298
297
296
295

340

340

344

348

98 E

106 E

0.5

1500 m

0m

105 E

1.0

2100 LT

500 m

104 E

0.5

Wind: Horizontal wind along the section;w1000 m

103 E

348

44

3

[K]
99 E

100 E

101 E

102 E

103 E

104 E

105 E

106 E

107 E
0.0
0.5
1.0
1.5

Figure 13. As in Figure 12 except for 1800, 1900 and 2100 LT of 23 September 1999.

surface between DRY and CTL was comparable withthe decrease in precipitable water. The timing of thedrastic increase in precipitable water during the night
corresponded to the increase in precipitation due tothe surface condition change from CTL to DRY. The
modulated pattern of water vapour flux was correlatedwith that of 10-m winds, indicating that the thermallyinduced winds altered the diurnal cycle of precipitablewater. Note also that the phase of diurnal variationsof the modulated precipitable water was synchronizedwith the climatological phase of the diurnal cycle ofwater vapour. Once a precipitation system occurs over
the Khorat Plateau during nighttime, larger amounts ofprecipitation can fall due to the increased precipitablewater. The thermally induced local circulation modulates
the diurnal cycle of precipitable water over and aroundthe disturbed region. However, the enhancement of water
vapour convergence may not be solely explained bythermally induced circulation. Enhanced convection overthe disturbed region may lead to more water vapour
around the convection. The two mechanisms may interact
and enhance each other. The modulated diurnal variationsof water vapour can explain the increase in precipitation.
The daytime decrease of precipitable water was not
Copyright  2010 Royal Meteorological Society

1900 LT
20°

DIFF 10-Wind [DRY-CTL]
1 [m/s]

16°

12°

100°

104° [K]0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 3.6 4.0

Figure 14. Difference in monthly mean diurnal pattern of winds at 10 m
above the surface over three years between DRY and CTL (DRY–CTL)
for 1900 LT.
Int. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA
DIFF (PW & QV) [DRY-CTL]

DIFF (PW & QV) [DRY-CTL]

0700 LT20°1300 LT20°100 [kg/m/s]

16°

16°

12°

12°

100°

104° [mm]100 [kg/m/s]

100°

104° [mm]-1.6 -1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 1.6-1.6 -1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 1.6

DIFF (PW & QV) [DRY-CTL]

DIFF (PW & QV) [DRY-CTL]

1900 LT
20°0100 LT20°100 [kg/m/s]

16°

16°

12°

12°

100°

104° [mm]-1.6 -1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 1.6

100 [kg/m/s]

100°

104° [mm]-1.6 -1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 1.6

Figure 15. Difference in the monthly mean diurnal cycle of vertically integrated water vapour flux (vector) and precipitable water (colours) overthree years between DRY and CTL (DRY–CTL) for 0700, 1300, 1900 and 0100 LT.

strongly associated with daytime convective activities
because daytime convection over the Khorat Plateau
was not climatologically active (Figure 16). Although
the daily mean precipitable water of DRY was lower
than that of CTL (Figure 16), the modulated amplitudeof precipitable water may nonlinearly affect precipitation
systems.
The signal of WET was much weaker than that of
DRY, compared with CTL. Table III shows the area
mean sensible heat flux, latent heat flux from the surface,
Bowen ratio and temperature at 2 m above the surface.
The difference in Bowen ratios was large between DRY
and CTL but small between WET and CTL. Changes
in surface flux from WET to CTL were smaller thanthose from CTL to DRY, which likely resulted in weakerthermally induced local circulations and smaller changes
in precipitation in WET.
Copyright  2010 Royal Meteorological Society

4.2. Observed long-term decrease in precipitation
This study investigated the potential impact of LUCCs
over northeast Thailand on the Indochina Peninsula. One
motivation of this study was Kanae et al.’s (2001) findingthat the observed decrease in precipitation in this region
may be explained by regional-scale LUCCs. On thebasis of observational and numerical modelling studies,
Takahashi and Yasunari (2006, 2008) and Takahashi
et al. (2009) reported that concurrent changes in tropical
cyclone activity can explain the observed decrease inprecipitation. Furthermore, our study suggested that anincrease in precipitation was responsible for the changes
from the wet to dry surface conditions. Our results
disagree with those of Kanae et al. (2001). Kanae et al.
(2001) used a 60-km mesh, which would not have been
fine enough to resolve local circulations and may have
led to the discrepancy between their study and ours.
Another large difference involves whether CCP was used;
Int. J. Climatol. (2010)

H. G. TAKAHASHI et al.

Precipitable Water (102.5-105E, 14.5-17N)
62.0
61.6
61.2
60.8

[mm]

60.4
60.0
59.6
59.2
58.8
58.4
58.0
10LT

16LT

22LT

04LT

10LT

16LT

22LT

04LT

Figure 16. The monthly mean diurnal cycle of precipitable water of DRY (dashed) and CTL (solid) over three years. The precipitable water was
domain averaged within an area at 102.5° –105 ° E, 14.5° –17° N where increase of precipitation was due to the changes in land surface condition
from CTL to DRY. Their daily mean values were also shown. The unit is millimetre.

Table III. The simulated sensible heat flux H , latent heat flux
LE from the surface, Bowen ratio Bo and temperature at 2 m
T2m at 1300 LT of WET, CTL and DRY, area-averaged within
the disturbed region (Figure 1).
CategoryH(W/m2 )

LE
(W/m2 )

Bo

T2m
(K)

WET
CTL
DRY

81.3
113.8
257.1

302.7
274.9
131.1

0.27
0.41
1.96

301.6
302.2
304.5

CCP strongly affects the reproduction of the diurnal
cycle of precipitation, even if local circulation is almost
simulated (Hara et al., 2009). Hence, the observed longterm decrease in precipitation during the latter half of thelast century cannot be explained by the effects of LUCCs.

5.

Conclusions

This study investigated the potential impact on regional
climate of LUCCs in northeast Thailand (Khorat Plateau),in terms of diurnal variations of precipitation, using ahigh-resolution regional climate model. Northeast Thailand, which was once widely covered by tropical rainforest, has been intensively deforested over the past century.
Currently, most land in northeast Thailand is used for
cultivation.
Comparison of CTL with observations showed that thesimulation captured the spatial distribution of the total
amount of precipitation over and around the Indochina
Peninsula. The simulated height of the planetary boundary layer and vertical structure of water vapour also
corresponded to the observations, indicating that CTL
reproduced realistic sensible and latent heat fluxes from
Copyright  2010 Royal Meteorological Society

the surface. CTL also reproduced realistic diurnal variations of precipitation, showing a peak over the Khorat
Plateau from evening to midnight.
Two sensitivity experiments were conducted with different soil moistures and vegetation densities. Comparedwith the CTL experiment, WET (DRY) showed less(more) precipitation, less (more) sensible heating, more(less) latent heating and lower (higher) surface temperature over the converted region. Thus, a drier surface condition increased precipitation in the study area.
Note that distinct changes in precipitation due to LUCCs
were found during nighttime over the Khorat Plateau.
Because nocturnal precipitation is dominant in this area,
the changes are closely tied with climatological diurnal
variations of precipitation over the Indochina Peninsula
region.
Over northeast Thailand during daytime, a weak downward flow was formed, which was probably caused by
the thermally induced local circulation and a compensating downward motion associated with the convective
activity over the surrounding mountain ranges. During
the evening, the structure of virtual potential temperature changed, and katabatic winds were developed fromthe surrounding mountain ranges to the Khorat Plateau.
Case studies showed that daytime convection formed a
cold-air-mass-like cold pool over the mountain ranges;
this pool drifted into the basin-shaped Khorat Plateau
and induced convective activity in evening. The flow
seemed to be a gravity current. The induced convection
further formed the cold air mass, which in turn developed convection. Consequently, the precipitation systems
moved into the Khorat Plateau. The climatological nocturnal precipitation over the Khorat Plateau consisted of
the repeatable formation of convective systems.
The increase of total precipitation due to the LUCC
over the converted region was associated with diurnal
Int. J. Climatol. (2010)

IMPACT OF LAND SURFACE CONDITIONS ON PRECIPITATION OVER INDOCHINA

variation of water vapour flux. Climatologically, the diurnal peak in precipitation was from evening to early morning over the Khorat Plateau. The drier condition intensified diurnal variation of precipitable water associatedwith the thermally induced local circulation responsible
for the horizontal gradient of surface conditions. That is,more water vapour was supplied to the Khorat Plateau
during nighttime. The modulated diurnal variation of precipitable water due to the LUCC synchronized with theclimatological diurnal cycle of precipitation, which can
explain the increase in total precipitation.
Acknowledgements
This work was partly supported by the Global Environment Research Fund (B-061) and (B-092) of the Ministryof the Environment, Japan.
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