Surface energy budget and closure of the eastern Tibetan Plateau during the GAME-Tibet IOP 1998

Surface energy budget and closure of the eastern Tibetan

Plateau during the GAME-Tibet IOP 1998

Kenji Tanakaa,*, Ichiro Tamagawab, Hirohiko Ishikawac, Yaoming Mad, Zeyong Hud

aDepartment of Civil and Environmental Engineering, Faculty of Engineering, Kumamoto University, Kurokami 2-39-1,

Kumamoto 860 8555, JapanbRiver Basin Research Center, Gifu University, Gifu, Japan

cDisaster Prevention Research Institute, Kyoto University, Kyoto, JapandCold and Arid Regions Environmental Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China

Received 15 August 2002; accepted 4 July 2003

Abstract

Turbulent flux measurements based on the eddy correlation technique were conducted on the Tibetan Plateau during the

Intensive Observation Period (IOP) of the GEWEX Asian Monsoon Experiment (GAME) in 1998. This paper presents on

analysis of the surface energy budget and its closure at the Amdo planetary boundary layer site in the eastern Tibetan Plateau

using GAME-Tibet IOP data. A seasonal variation in the surface energy closure ratio (CR) was seen. CR was higher than 0.8 in

the pre-monsoon period and after DOY 233, when the infrared hygrometer was performing satisfactorily. However, CR was

lower than 0.7 throughout most of the summer monsoon, due at least in part to degraded performance of the infrared hygrometer

under heavy precipitation. In addition, through detail analysis of the diurnal variations of surface energy flux for the best-CR

period of September 4–6, it was found that the melting and freezing of near-surface soil moisture plays a significant role in the

variation of surface energy fluxes, particularly in terms of latent heat flux. The calculated effective mass of melting and freezing

water in one day was 3.3–3.9 kg/m2, which is comparable to the daily total.

q 2003 Elsevier B.V. All rights reserved.

Keywords: Tibetan Plateau; Surface energy flux; Eddy correlation; Closure ratio; Melting/freezing of soil moisture

1. Introduction

The Global Energy and Water Cycle Experiment

(GEWEX) Asian Monsoon Experiment (GAME)

was conducted over a five-year period from April

1996 to March 2001. One of the objectives of this

experiment was to gain an understanding of the

mechanisms of the Asian monsoon by evaluating

energy and water cycles through ground-based

hydro-meteorological observations. The Tibetan

Plateau is one of the experimental regions for the

GAME (a subprogram called GAME-Tibet), and is

located at a mid-latitude (288N–358N) of the eastern

Eurasian continent (808E–1008E), covering an area

of about 1.2 million km2 with a mean altitude of

more than 4000 m above sea level.

The Tibetan Plateau has been thought to play an

important role in the progress of the Asian summer

monsoon through orographic and thermal effects on

0022-1694/$ - see front matter q 2003 Elsevier B.V. All rights reserved.

doi:10.1016/S0022-1694(03)00243-9

Journal of Hydrology 283 (2003) 169–183

www.elsevier.com/locate/jhydrol

* Corresponding author.

E-mail address: [email protected] (K. Tanaka).

http://www.elsevier.com/locate/jhydrol

the surrounding mid-troposphere, as discussed by

many authors. Two other experiments have been

conducted prior to GAME-Tibet; one as part of the

First Global Atmospheric Research Program Global

Experiment (Yeh et al., 1979) and the other the

Qinghai-Xizang Plateau Meteorology Experiment in

China (Johnson et al., 1987; Yeh, 1988; Zhang et al.,

1988; Ji et al., 1989). Using the data obtained in these

experiments, several indirect methods have been

applied to estimate surface energy fluxes, mainly by

Chinese scientists. He et al. (1987) estimated sensible

and latent heat fluxes from temperature and moisture

budgets in the troposphere over the Tibetan Plateau

and its surrounding region. Gao and Liu (1979)

estimated these fluxes using the Bowen ratio, while

Chen et al. (1985) employed bulk transfer theory for

this analysis, defining the transfer coefficient as a

function of the surface atmospheric pressure and the

wind 10 m above the ground. A review of these

studies by Yanai et al. (1992) leads to the recognition

of the presence of positive temperature anomalies

over the Tibetan Plateau and large-scale vertical

circulation induced by the plateau throughout the nine

months from winter to summer. Specifically, before

the onset of the summer monsoon, the heat source on

the plateau is surrounded by intense cooling in the

adjacent regions.

During the GAME-Tibet, turbulent flux obser-

vations were conducted at four stations (Fig. 1) as part

of an intensive observation period (IOP) in the

summer of 1998. This experiment was apparently

the first in the Tibetan Plateau to involve direct

measurement of sensible and latent heat fluxes. The

stations were located along the Qinghai-Xizang

highway in the Tibetan Plateau, in predominantly

bare terrain with a sparse distribution of short grass

(1–3 cm) during the summer monsoon rainy season.

Site MS3478 was the sole exception, having a

moderate distribution of tall grass (10–20 cm) and

an earth hummock. Some preliminary results using

this data have been reported by scientists involved in

the observation (Tsukamoto et al., 2001; Gao et al.,

2000; Ma et al., 2000).

Tanaka et al. (2001) reported a drastic change in

the sensible and latent heat flux correlated with the

onset of the summer monsoon. The sensible heat flux

was dominant before the onset of the summer

monsoon (in May and early June), and the Bowen

ratio derived from turbulent fluxes ranged from 5 to

10. After the onset of the summer monsoon, the

sensible heat flux decreased and the latent heat flux

increased rapidly as precipitation became frequent

and the surface soil became wet. Those authors took

the residual using the net radiation flux (Rn), sensible

heat flux (H) and latent heat flux (LE), Rn 2 H 2 LE;

which is equivalent to the ground diffusive heat flux

assuming that the surface energy balance is satisfied.

The residual reached a maximum of more than

300 W m22 over a diurnal variation (more than 40%

of net radiation). This residual should be attributable

to the soil heat flux, but an independent estimation

based on measurements was not given because the

analysis of soil parameters such as thermal conduc-

tivity and porosity, had not yet been completed.

Instead, they independently estimated the averaged

soil heat flux needed to melt soil moisture in a 2.5 m-

thick frozen soil layer, and suggested that more than

half of the residual (about 25% of Rn) is used in this

process. However, about 15% of Rn has yet to be

accounted for.

The imbalance in the directly measured

surface energy fluxes has recently been discussed by

a number of authors. Using the closure ratio,

CR ¼ ðH þ LEÞ=ðRn 2 GÞ; where G is the ground

diffusive heat flux at the surface, Stannard et al.

(1994) reported that the typical value of CR for

agricultural land is 0.8–0.9. Kizer and Elliot (1991)

reported a lower value of 0.7. As all land surface

algorithms are constructed on the basis of the surface

energy balance, it is important to examine whether the

surface energy fluxes satisfy the surface energy

balance.

The purpose of this study is to present the seasonal

variation in land surface–atmosphere interaction and

to examine the surface energy balance observed at

Amdo in the eastern Tibetan Plateau. The surface

energy closure is assessed based on four-component

radiation, soil heat flux, and turbulent transport of

latent and sensible heat, and the quality of data for

each factor is checked carefully. A problem is

identified in the latent heat flux data, attributed to

the performance of the infrared hygrometer, and the

importance of the performance of the soil heat flux

meter is also recognized. After correction of the raw

output with respect to the observed soil water content,

a better closure ratio is achieved, and an updated

K. Tanaka et al. / Journal of Hydrology 283 (2003) 169–183170

diurnal variation of land surface–atmosphere inter-

action is presented. The effective mass of moisture

involved in freezing and thawing in the near-surface

soil layer is also computed to investigate the

importance of the freezing and thawing processes.

2. Instrumentation and general weather condition

The Amdo planetary boundary layer (PBL) site is

located in the middle of the Tibetan Plateau along the

Qinghai-Xizang highway (Fig. 1). The site

(32814.4680N, 91837.5070E, about 4700 m above sea

level) is about 6 km west of the town of Amdo and is

located in a wide valley that runs from northeast to

southwest. Wind along the valley is generally

observed to vary diurnally, except when a strong

system prevails. The observation system consisted of

a turbulent flux measurement system, a surface layer

profile measurement system on a 14 m tower, and a

four-component radiation measurement system.

The turbulent flux measurement system was

composed of a sonic anemo-thermometer (DAT-

300, Kaijo) and an infrared hygrometer (AH-300,

Kaijo). A clinometer was also used to measure sensor

inclination. A capacitive hygrometer (Humicap,

Vaisala) and thermometer (Pt-100) were also set

near the infrared hygrometer. The sensor assembly

was set on top of a short pole (sensor height 2.85 m)

beside the tower. Data was sampled at 10 Hz using an

analog/digital-converter (National Instruments) and

stored on a personal computer in data sets of 30 min.

During the IOP, more than 4900 of these 30-min files

were obtained (about 4.3 Gbytes total data size).

The radiation measurement system was composed

of two shortwave sensors (MS-801, EKO) and two

longwave sensors (PIR, Eppley) for both upward and

downward directions. Longwave radiation was cor-

rected for the dome temperature according to Shimura

(1996). A data logger (QLC50, Vaisala) was

employed to sample the data at 1 Hz, and data was

stored as 10-min averages.

A 14 m tower was set up to measure temperature,

humidity and wind profiles in the atmospheric surface

layer. In this system, atmospheric pressure, accumu-

lated precipitation, solar radiation, and soil par-

ameters were also measured. The sensors used are

listed in Table 1. The 10-min averages were stored by

Fig. 1. Location of four turbulent flux measurement stations (Amdo PBL, MS3478(N-PAM), Naqu-BJ, and MS3637(S-PAM) on the Tibetan

Plateau.

K. Tanaka et al. / Journal of Hydrology 283 (2003) 169–183 171

a data logger (Milos 500, Vaisala). The logger clock

was synchronized with that of the radiation system in

reference to the downward shortwave radiation data

from both systems.

A soil moisture and temperature measurement

system (SMTMS) was installed approximately 10 m

southwest of the 14 m tower. The system itself was

composed of Pt-100 thermometers at 10 levels (from 4

to 279 cm below ground surface) and time-domain

reflectrometer probes for monitoring soil moisture at

six levels (from 4 to 258 cm below the ground

surface).

Fig. 2 shows the meteorological variables

observed on the 14 m tower and the near-surface

soil moisture measured by the SMTMS. Tower

observation was interrupted during DOY 156–166,

and data for this period in the figure is the mean

temperature and specific humidity data from the

turbulent system at a height of 2.85 m. Significant

changes in the variables can bee seen over the

period DOY 160–190. In the pre-monsoon season

(before DOY 160), the surface layer atmosphere

was very dry: the specific humidity at 1.5 m was

only about 2–4 g/kg, and the soil moisture 4 cm

below the surface was 0.15–0.25 m3/m3. As the

summer monsoon progressed (DOY 160–190), the

surface became wet due to frequent precipitation,

and the specific humidity at 1.55 m increased to

8–10 g/kg. There was a short break in the monsoon

in the period DOY 190–200, during which the

specific humidity decreased rapidly and the atmos-

phere became temporarily dry. After DOY 200,

precipitation occurred almost every day and the

specific humidity remained high at 8–10 g/kg until

DOY 245.

Fig. 3 shows seasonal variations in the daily

maximum and minimum surface temperature ðTsfcÞ

and soil temperature 10 cm below the surface ðT10 cmÞ:

The surface temperature was derived from the

upward and downward longwave radiation according

to the relation

L# ¼ esT4sfc þ ð1 2 eÞL"

; ð1Þ

where L is the longwave radiation flux and the arrows

indicate the upward and downward directions, e

( ¼ 0.98) is the surface emissivity, and s is the Stefan-

Boltzmann constant (5.67 £ 1028 W m22 K24). In

the pre-monsoon season, a diurnal surface tempera-

ture change of over 60 8C (215 to 50 8C) was

recorded. The amplitude of this variation decreased

gradually over the period DOY 160–190 to less than

30 8C after DOY 200.

3. Evaluation of surface energy fluxes

3.1. Turbulent flux of sensible heat and latent heat

The sensible heat flux ðHÞ and the latent heat flux

(LE) are calculated as follows

H ¼ ðrdCpd þ rvCpvÞw0T 0; ð2Þ

LE ¼ rvlw 0q0v; ð3Þ

where Cpd and Cpv are the specific heat capacity of dry

air and water vapor, respectively, rd and rv are the

time averages (i.e. 30-min averages) of dry air density

and water vapor density, w is the vertical velocity, T is

air temperature, q is specific humidity, and l is the

latent heat of water (2.508 £ 106 J/kg). Primes

represent fluctuation values and over-bars represent

averaged values in the processing unit (30 min,

18,000 data in each run). Webb correction (Webb

et al., 1980) is naturally included in Eqs. (2) and (3).

Table 1

Sensors on the 14 m tower

Variable Level (m) Sensor

Wind 1.9, 6.0

and 14.1

Air borne

(OGASAWARA FF-11)

Temperature 1.55, 5.65

and 13.75

Pt-100

(VAISALA HMP35D)

Humidity 1.55, 5.65 and 13.75 Electric capacitance

(ibid)

Pressure – Semi-conductor

(VAISALA DPA-21)

Precipitation – Tipping bucket

(VAISALA RG-13)

Surface

temperature

– IR thermometer

(Optex HR1-FL)

Soil

temperature

0.05, 0.1 and 0.2 Pt-100

Soil heat

flux

0.1 and 0.2 Heat plate

(EKO MF-81)


Fig. 2. Meteorological variables observed at Amdo PBL site during the IOP. (a) Atmospheric temperature at 1.55 m, (b) specific humidity (solid

line) and daily precipitation (bar), and (c) soil moisture from soil moisture and temperature measurement system (SMTMS).


The correction for traverse wind is applied when

obtaining wind speed.

The AH-300 infrared hygrometer, rather than

measuring the absolute absorption by water vapor, is

an open-path humidity sensor that measures the

fluctuation in the intensity of infrared rays. I0 can

then be computed according to the relationship

proposed by Hyson and Hicks (1975) as follows

q0 / aðI0=�IÞ: ð4Þ

The coefficient a is calibrated at the factory.

However, for practical operation, a in fact varies

slightly depending on the ambient temperature and

other instrumental conditions. To resolve this issue,

dynamic calibration is employed, by which a is

calculated for each run in reference to a slower but

stable humidity sensor (Humicap, Vaisala). Fig. 4 is a

schematic of the dynamic calibration process. First,

the reference q fluctuation is computed from T (Pt-

100) and RH (Humicap). Then, the power spectrum of

water vapor density obtained from the infrared

hygrometer data is compared with this reference in

an appropriate frequency range (1/300–1/30 Hz). The

calibration coefficient can then be obtained as follows

(Wang and Mitsuta, 1992)

Qcoeff ¼

PFSqðSTÞPFSqðIRÞ

!1=2

; ð5Þ

whereP

is the summation of the power spectrum for

each vapor density, and Sq is the density of power

spectrum. Subscripts (ST) and (IR) represent data

obtained from the capacitive hygrometer (standard

sensor) and the infrared hygrometer. Turbulent

humidity data is obtained by combining the high-

frequency range of the infrared hygrometer with the

low-frequency range of the capacitive hygrometer

(Tamagawa, 1999). The cut-off frequency in this

study was 0.005 Hz (1/200 Hz).

The quality of turbulent humidity measurement

using the infrared hygrometer depends on the

power of the infrared radiation incident on the

detector, and in practice needs to be judged based

on the correlation between the infrared hygrometer

and the reference value from the capacitive

hygrometer in the relevant spectral range. The

latter is important in that the correlation directly

relates to the reliability of the absolute value.

When the correlation is sufficiently high (i.e. near

unity), the dynamic calibration works well.

Fig. 3. Variations of daily maximum and minimum surface temperatures (Tsfc) and soil temperatures 10 cm below the ground surface (T10 cm).


Fig. 5 shows the correlation between the infrared

hygrometer and the capacitive humidity sensor. The

correlation was poor at the beginning of the IOP (DOY

130–180), and became worse from late June (DOY

180). The infrared source weakened from the begin-

ning of August (DOY 215), and after the change of

infrared source on DOY 233, the correlation improved.

3.2. Net radiation flux

The net radiation flux density (Rn) was obtained

using data from the four-component radiation system

by the following relation

Rn ¼ S# 2 S" þ L# 2 L"; ð6Þ

Fig. 4. Schematic of processing for turbulent humidity fluctuation data.

Fig. 5. Classification of turbulent quality at Amdo PBL site in relation to the correlation between specific humidity from the infrared hygrometer

and the capacitive humidity sensor. Circles indicate a very good correlation (.0.9), triangles indicate a good correlation (0.8–0.9), crosses

indicate a fair correlation (0.7–0.8), and dots indicate a poor correlation (,0.7).


where S and L represent the shortwave and

longwave radiation fluxes, and arrows denote the

upward and downward directions. Considering the

secondary infrared emissions from the sensor’s

dome, the longwave radiation is corrected using

the dome temperature and body (internal) tempera-

ture as follows (Shimura, 1996)

L ¼ Lraw þ CLsðT4b 2 T4

d Þ; ð7Þ

where Lraw represents the longwave radiation before

correction, CL ( ¼ 2.5) is the correction coefficient,

and Td and Tb are the dome and body temperatures.

3.3. Ground diffusive heat flux at surface

The ground diffusive heat flux at the surface ðGsfcÞ

is expressed as a vertical integration of the heat

storage, i.e.

Gsfc ¼ð1

sfc

›CsoilT

›tdz; ð8Þ

where Csoil is the volumetric heat capacity of the

soil. Here, the following approximation is assumed

for Gsfc

Gsfc < �Cðdsfc›Tsfc þ d5 cm›T5 cm þ d10 cm›T10 cmÞ=

›t þ G10 cm; ð9Þ

where the d terms are the effective thicknesses of each

measured temperature, Tsfc; T5 cm; and T10 cm

(dsfc ¼ 0:01 m, d5 cm ¼ 0:06 m, d10 cm ¼ 0:03 m).

The values of d were determined empirically. After

testing several models (linear, polynomials and hybrid

exponential), Eq. (9) gave the most stable estimation

for a variety of situations. In Eq. (9), G10 cm is the

observed soil heat flux at a depth of 10 cm after

correction for soil moisture, and �C is the averaged

volumetric heat capacity defined as

�C ¼ Cdry þ rliqcliqu4 cm; ð10Þ

where rliq ¼ 1:00 £ 103 kg m23 K21, cliq ¼ 4:18

£103 J kg21, u4 cm is the soil moisture content from

the SMTMS, and Cdry ( ¼ 0.90 £ 106 J m23 K21) is

the volumetric heat capacity of dry soil.

The soil heat flux sensor installed in the tower

system is basically applicable under dry conditions,

having a thermal conductivity of 0.21 W m21 K21,

which is about the same value as for dry soil and sand.

When the thermal conductivity of the soil is different

from that of the sensor, Philip (1961) suggested the

use of the following correction function

f ¼F0

F¼

v

1 þ ðv2 1ÞHðhÞ; ð11Þ

where HðhÞ ¼ 1 2 1:70h:

Here, v (¼ lplate=lsoil) is the ratio of the thermal

conductivity of the heat plate to that of the soil, and

h ¼ ðd=A1=2Þ is the deformation factor of the plate

defined by the ratio of the thickness d ( ¼ 4 mm) to

the square root of the area of the measuring surface A

(20 mm £ 110 mm). F0 and F are heat flux through

the heat plate and the corrected value, respectively.

The relationship between thermal conductivity and

soil moisture content is based on McIness’ (1981)

experimental formula (Campbell, 1985), given by

lsoil ¼ A þ Bu2 ðA 2 DÞexp½2ðCuÞE; ð12Þ

in which coefficients A ¼ 0:786; B ¼ 1:484;

C ¼ 12:63; D ¼ 0:227; E ¼ 4:0 are obtained exper-

imentally using local soil samples (private communi-

cation by Dr Nagai).

Fig. 6 compares the soil heat flux through the heat

plate at a depth of 10 cm before and after correction.

The diurnal amplitude of soil heat flux after correction

was 60–80% larger than before correction: ground

diffusive heat flux before correction, 30–50 W m22;

after correction, 40–80 W m22.

4. Seasonal scale variation of surface energy fluxes

and closure ratio

Fig. 7 shows the daily averaged surface radiation

fluxes. The daily averaged downward shortwave

radiation at the top of the atmosphere is plotted in

the same figure, computed as a function of solar zenith

angle and the distance between the sun and the earth.

A solar constant of 1353 W m22 was employed, taken

from Xue et al. (1995). More than 80% of the

downward shortwave radiation reached the plateau

surface under fine weather conditions. During the first

phase of the summer monsoon (DOY 160–190), the

downward shortwave radiation decreased gradually

with increasing cloud cover, implying that the upper

air was gaining moisture. Two fine cloudless days


Fig. 6. Ground diffusive heat flux at a depth of 10 cm, before (upper panel) and after (lower panel) correction of soil moisture.

Fig. 7. Daily averaged surface radiation flux during the IOP. Four-component radiation flux, i.e. downward shortwave (DSW), upward

shortwave (USW), downward longwave (DLW), and upward longwave (ULW) fluxes are shown. Incoming shortwave radiation flux from the

top of the atmosphere (DSW_TOA) is plotted as a dotted line.


occurred in mid-July during a break in the summer

monsoon, on July 12 (DOY 193) and July 16 (DOY

197). The downward shortwave radiation fluctuated

more during the second phase of summer monsoon

(DOY 200–240) than during the first phase.

The downward longwave radiation increased

gradually from about 250 W m22 on DOY 140 to

320 W m22 on DOY 190. Two depressions in down-

ward longwave radiation appeared in the middle of

July, corresponding to the cloudless days (July 12 and

16). After that, the downward longwave radiation

fluctuated slightly around 300 W m22. The upward

shortwave radiation decreased in parallel with the

downward shortwave radiation. The upward long-

wave radiation was rather high and fluctuating prior to

DOY 176, after which it decreased and became

steady. This feature is consistent with the soil

moisture shown in Fig. 2. The ground surface first

became wet following the first massive rainfall around

DOY 178, with some drying after that time until

another very wet period from DOY 188. In mid-July

(DOY 190–200), the downward shortwave radiation

(i.e. incoming solar radiation) jumped to 350 W m22

and the downward longwave radiation decreased to

250 W m22, corresponding to the break in the

summer monsoon. The upward longwave radiation

remained nearly constant after the break at about

370 W m22.

Fig. 8 shows the average daily surface energy

fluxes. During the pre-monsoon period, the sensible

heat flux was dominant, and the latent heat flux was

less than 20 W m22 (daily average). In the first phase

of the summer monsoon, the latent heat flux increased

gradually, whereas the sensible heat flux decreased.

The latent heat flux became comparable to the

sensible heat flux during the break of the summer

monsoon. After that, the latent heat flux continuously

increased and the sensible heat flux decreased. At the

end of the summer monsoon (DOY 250) the latent

heat flux was dominant. The ground diffusive flux at

the surface Gsfc varied between 210 and 20 W m22,

with an average of 10 W m22 (about 5–10% of net

radiation), which is about 60–80% higher than before

correction in the previous section. A negative-Gsfc

was sometimes seen (e.g. DOY 186 and 191),

corresponding to heavy precipitation (rainfall or hail

attack) events. The daily averaged net radiation was

no more than 100 W m22 for most negative-Gsfc days.

Fig. 9 shows the closure ratio, which is defined by

the equation of Stannard et al. (1994)

CR ¼�H þ LE

Rn 2 Gsfc

; ð13Þ

where the over-bar denotes the daily averaged value.

In the computation of the CR, days with daily

averaged net radiation less than 100 W m22 were

eliminated. The daily averaged intensity measured by

the infrared hygrometer is also plotted in the same

figure. CR was computed using a complete data set.

After varying around 0.9 during the pre-monsoon

Fig. 8. Daily averaged surface energy fluxes during the IOP.


period, CR decreased gradually in parallel with the

decrease in infrared intensity as the summer monsoon

progressed, to values of 0.5 up to DOY 200. CR

increased gradually after DOY 210, although the

infrared intensity continued to decrease. After chan-

ging the infrared source of the hygrometer on DOY

233, the infrared intensity recovered to 0.7 (70%), and

CR recovered to 0.8 and sometime more than 0.9.

The closure ratio was highest on September 5.

Correction of the soil heat flux increased CR slightly

by about 2–3%. According to Kustas et al. (1999), the

typical value of CR is about 0.9 bare ground, or about

0.7 over forest (Kizer and Elliot, 1991). Therefore, the

CR obtained here during the summer monsoon season

was very low.

Comparing the variation of CR with Fig. 5, there

was some inconsistency between the variations in CR

and turbulent humidity. As the summer monsoon

progressed, precipitation became frequent and the

performance of the infrared hygrometer degraded due

to weakening of the incident infrared radiation. This

can be expected to result in an underestimation of the

latent heat flux, and this error may have contributed to

the surface energy imbalance. However, as seen in

Fig. 9, CR increased again after DOY 210 despite the

continual decrease in infrared intensity. Therefore,

some effects beyond the accuracy of the measurement,

such as lateral heat transportation or non-zero vertical

mean wind speed (Lee, 1998), may also contribute to

the large surface energy imbalance. It still remains

unclear quantitatively the degree of contributed of

these effects and the degree of underestimation of LE

measured by the infrared hygrometer.

5. Diurnal variation of surface energy

fluxes on September 5

Fig. 10 shows the diurnal variation of surface

energy fluxes for the period September 4–6 (DOY

247–249), corresponding to the period of highest CR.

The residual of surface energy fluxes d; given by

d ¼ Rn 2 Gsfc 2 H 2 LE; ð14Þ

is also plotted. Note that Beijing Standard Time

(BST), þ8 h from UTC, is employed in the figure. On

September 4, a short rainfall event occurred between

0900 and 0930 BST, and the net radiation flux varied

over the day due to cloud cover. September 5 was

cloudless and fine throughout the day, and the net

radiation varied smoothly. September 6 was very clear

in the morning, yet became cloudy in the afternoon

with a corresponding change in the net radiation flux.

However, no precipitation was observed.

The sensible heat flux was about 120 W m22 in the

afternoon of September 5. The latent heat flux exceeded

300 W m22 in the afternoon of September 5 and 6, and

the Bowen ratio was between 0.3 and 0.4 during the day.

The ground diffusive flux at the surface Gsfc was about

270 W m22, which is about 2 or 3 times higher than

Fig. 9. The surface energy closure ratio (CR) and the daily averaged infrared intensity measured by the infrared hygrometer (I).


the typical value observed in other fields (Garatt, 1993).

Interestingly, on September 5, the latent heat flux was

close to 0 W m22 for about 3 h immediately after

sunrise, and then increased suddenly at 1030 BST. The

residual, d; increased rapidly to an extreme peak of

about 200 W m22, subsequently fluctuating between

220 andþ100 W m22 throughout the afternoon under

fine conditions.

Fig. 11 shows the diurnal variation of surface and

near-surface soil temperatures. There is a relationship

between surface temperature and d in Figs. 10 and 11.

When the surface cooled down to 0 8C during the

night, d became negative. The extreme positive d just

after sunrise is consistent with the subsequent

warming of the surface to 0 8C. In addition, the

near-surface soil was very wet, about 0.45 m3/m3

(Fig. 2c), which is 2.5–3 times that of the dry season.

Eq. (9) does not include the heat generated by the

melting or freezing of soil moisture. Hence, d seems

to represent the heat generated by the freezing or

melting of near-surface soil moisture.

Fig. 12 is a schematic of the diurnal variation of

surface temperature and residual flux, d: The diurnal

variation of residual surface energy flux and surface

temperature can be divided into the following periods:

(1) midnight (September 4, 2230 BST–September 5,

0830 BST), when the surface temperature was less

than 0 8C and the residual flux was negative, (2) just

Fig. 10. Diurnal variation of surface energy fluxes between September 4 (DOY 247) and September 6 (DOY 249), 1998.

Fig. 11. Diurnal variation of surface and soil temperature between September 4 and September 6, 1998.


after sunrise (September 5, 0830–1100 BST), when

the surface temperature increased to 0 8C and the

residual flux was over 200 W m22, and (3) day to

early night (September 5, 1100–2300 BST), when the

surface temperature was higher than 0 8C and melting

and freezing processes had ceased. The total residual

energy per unit area for each period d1; d2 and d3; is

given as follows

d1 ¼ 21:295 £ 106 ðJ m22Þ;

d2 ¼ 1:135 £ 106ðJ m22Þ;

d3 ¼ 0:840 £ 106ðJ m22Þ:

The equivalent mass of frozen/melted water was

estimated by dividing the residual energy by the latent

heat for fusion Lf ( ¼ 3.34 £ 105 J kg21). The

equivalent mass per unit area, m1 and m2; is then

given by

m1 ¼ 23:929 ðkg m22Þ and m2 ¼ 3:398 ðkg m22Þ:

The absolute values of m1 and m2 are nearly

identical. The thickness of the active layer dh;

corresponding to the soil layer that freezes during

the night and thaws up in the morning, is estimated

from the equivalent mass of the soil water content as

dh ¼ lml=rwu: ð15Þ

Substituting typical values m ¼ lm1l ¼ 3:93

(kg m22), rw ¼ 1:00 £ 103 (kg m22) and u ¼ 0:45

(m3/m3), into Eq. (15) gives Dh ¼ 8:73 (mm). In

comparison, according to the turbulent flux obser-

vations, the daily evaporation of this 24-h period was

3.199 kg m22.

Thus, the residual energy flux during the night and

morning is adequately explained by the freezing and

melting of near-surface soil moisture. The masses as

determined were equivalent to the diurnal evaporation

value. Therefore, the freezing and melting of soil

water play a significant role in the surface energy

budget on a diurnal scale. Although, these two

equivalent masses of water are cancelled out over a

daily average, the time scale of thawing and freezing

of near-surface soil moisture, several hours, is

significantly longer than the time step of the

numerical models, for example, about 5 min in

computing 18 £ 18 horizontal resolution. Hence, the

diurnal variation in surface energy fluxes and

equivalent masses of frozen and melt water shown

in this section represent significant information that

may improve the land-surface process algorithm of

the high-resolution general circulation model pre-

sently under development.

6. Concluding remarks

In this paper, two major conclusions were

obtained. First, a seasonal-scale variation in the

surface energy closure ratio (CR) was identified. CR

Fig. 12. Schematic of diurnal variation of surface temperature and the residual energy flux on September 5.


was higher than 0.8 in the pre-monsoon dry period and

after late August, at which time the performance of

the infrared hygrometer had degraded. However, CR

was less than 0.7 during most of the summer monsoon

period. The large surface energy imbalance is at least

in part attributed to an underestimation of the latent

heat flux because of the weak infrared radiation

detected during periods of precipitation. However, CR

increase gradually after DOY 210, even though the

infrared intensity measured by the infrared

hygrometer continued to decrease. Hence, the energy

imbalance during the summer monsoon includes

contributions from both the underestimation of latent

heat flux due to the limitations of the infrared

hygrometer and other effects beyond instrumental

error, such as a lateral heat transport or non-zero mean

vertical wind speed. However, these effects could not

be isolated. Computation of Gsfc and correction of the

soil heat flux through the sensor using local soil

parameter also affects the evaluation of CR to some

degree.

The authors investigated the detailed diurnal

variation of the surface energy flux for the three

days (September 4–6), corresponding to the period of

best closure ratio obtained in the IOP, and found that

the freezing and melting of near-surface soil moisture

play a significant role in the surface energy budget on

a diurnal scale, especially in terms of latent heat flux.

According to the estimation for September 4–5, the

mass of frozen and melt water during the night and

morning was about 3.3–3.9 kg m22, which is equiv-

alent to the total daily evaporation.

The authors also attempted to determine how

well the surface energy budget was closed using

raw observation data. During most of the IOP, the

surface energy budget was not closed well. The

possible sources of such surface energy imbalance

have been discussed by many authors. Tamagawa

(2000) generated a continuous turbulent humidity

fluctuation dataset from the data used in this study

to evaluate latent heat flux as a part of an analysis

of the change in flux with averaging time. The

calculated latent heat flux was a little higher

(several percent) than that presented here. Lee

(1998) pointed out that non-zero vertical mean

wind speed at the sensor level will cause the

energy flux to be underestimated by 100 W m22.

Although the present authors attempted to estimate

the vertical wind speed to evaluated this possibility,

no concrete result could be obtained because the

effect is very sensitive to the vertical mean wind

speed and the difference between the temperatures

given by sonic anemo-thermometer and the tower.

However, a well-closed data set was successfully

identified in this study.

In order to understand the role of the Tibetan

Plateau as an elevated heat source in this region, it is

necessary to evaluate inter-annual variations in sur-

face energy fluxes. The authors are using continuous

in situ observations by automated weather stations

following the IOP in 1998, including logging by the

surface radiation system at the Amdo PBL site, to

evaluate the long-term variations in sensible and

latent heat fluxes based on bulk transfer theory. The

coefficients for this evaluation are generated as a

function of atmospheric stability by combining the

14 m tower profile and turbulent flux. The results of

that study are expected to provide good long-term data

on the variation of surface energy fluxes, provided

that the turbulent flux data is of sufficient quality.

Acknowledgements

The data used in this work was obtained during the

intensive observation period of the GAME-Tibet in

1998. Observations were conducted under rigorous

conditions on the Tibetan Plateau. The authors would

like to express their thanks to Prof. Jieming Wang of

the Cold and Arid Regions Environmental and

Engineering Research Institute (CAREERI), Chinese

Academy of Sciences, for understanding coordination

throughout the project. Dr Hongchun Gao and other

staff of CAREERI are also acknowledged for their

assistance during the observations. Thanks are

extended to Prof. Osamu Tsukamoto of Okayama

University, Dr Jun Asanuma of Tsukuba Univsersity,

Mr Yongqiang Qi at Ehime University, and other

staff members involved in the boundary layer

observations during the IOP. Soil layer data was

provided by Prof. Toshio Koike of Tokyo University,

and the parameters of soil properties were provided by

Dr Hideyuki Nagai of Naogoya University.


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Surface energy budget and closure of the eastern Tibetan Plateau during the GAME-Tibet IOP 1998