GAME-Siberia findings on one-dimensional land-surface processes in forested areas
and follow-up research*Takeshi OHTA1, Tetsuo OHATA2, Yoshihiro FUKUSHIMA3, Trofim C. Maximov4,Roman V. Desyatkin4, and Varely S. Vuglinsky5
1( Graduate School of Bioagricultural Sciences, Nagoya University, 2Institute of Observational Research for Global
Change, 3Research Institute for Humanity and Nature, 4Institute for Biological Problems of Cryolithozone, SB, RAS,
5
State Hydrological Institute, RAS)
* Graduate School of Bioagricultural Sciences, Nagoya University, 464-8601, Furo-cho, Chikusa Nagoya, Japan.
E-mail: takeshi@agr.nagoya-u.ac.jp
Abstract
Global Energy and Water-cycle Experiment (GEWEX) Asian Monsoon Experiment-Siberia (GAME-Siberia) field researchextended from 1996 to 2002 and included two intensive observation periods in 1998 and 2000. This paper summarizes four
major findings on one-dimensional (1-D) land-surface processes related to water and energy cycles. First, plant phenology
strongly affects the energy balance above larch forest canopy in the middle reaches of the Lena River, and the Bowen ratio
dramatically decreases owing to leaf foliation. Second, no significant inter-annual variation of evapotranspiration was found,although precipitation varied widely by year. Steady evapotranspiration resulted from trees’ use of permafrost meltwater.
Third, energy budget differences above larch and pine forests were remarkable in early spring, but Bowen ratios were similarin summer. Finally, parameters indicating canopy-conductance response were similar in larch and pine forests in the middle
reaches of the Lena River, but differed in larch forests located between the Lena’s middle reaches and headwaters.
Keyword: Siberian forest, water balance, energy balance, one-dimensional scale, inter-annual andseasonalvariations

1. Introduction
Boreal forests stretch from 45 ﾟ N to 70 ﾟ N, occupying an
area of 13.7 million km2 and comprising one third of theworld’s forests. Forty percent of boreal forests are found in
Siberia. Siberian forests may play an important role in theclimate system, but water and energy balance characteristics
in this region are still unclear.
Intensive investigations of water and energy exchanges
began in the early 1900s in Scandinavia (NOPEX; Halldinet al., 1999) and North America (BOREAS; Sellers et al.,
1995, 1997). However, little is known of water and energy
cycles in Siberia, especially in eastern Siberia. Previous
research focused on short-term observations from central
and eastern Siberia (Kelliher et al., 1997, 1998). The
GAME-Siberia project examined three ecological regions(tundra, plain taiga, and mountain taiga) of the Lena River
watershed from 1998–2002 and included two intensive
observation periods.
GAME research revealed important aspects of water andenergy cycles in eastern Siberian forests. This paper
summarizes those findings and introduces follow-up
research. Additional results obtained from tundra andglassland sites have been reported by Kodama et al. (2004)
and Yabuki et al. (2004).

2. Outline of the forest sites
2.1.
Mature larch forest site on the left bank of
the middle reaches of the Lena River (LL)This site is located on the left bank of the Lena River, 62 ﾟ15’N, 129 ﾟ 37’E, about 20 km north of Yakutsk City. Larix
cajanderi dominates. Stand density is 840 trees ha-1 with anaverage height of 18 m; the leaf area index (LAI) is 3.71 in
the foliated season and 1.71 in the leaf-less season. Annual
mean temperature is -10 C, and the annual precipitation is
188 mm (IIASA). The maximum depth of the permafrost

thaw layer is 1.2–1.4 m.

2.2.

Mature pine forest site on the left bank ofthe middle reaches of the Lena River (LP)This site is also located on the left bank of the Lena River,
62 ﾟ 14’N, 129 ﾟ 39’E. The main tree species is Pinus
sylvestris. Stand density is 2660 trees ha-1 with an averageheight of 10 m. The LAI is 2.5. Climate conditions resemble
those at LL. The maximum thawing depth is 2.5 m.

2.3.

Young larch forest site on the right bank of
the middle reaches of the Lena River (RL)The young larch site is located on the right bank of theLena River. Larix cajanderi dominates at this site. The mean
stand height is 7.6 m, and the stand density is 4200 trees ha-1.
Annual mean temperature is -10 C, and annual precipitationis 210 mm (IIASA).

2.4.

Young larch forest site in a mountainous
area (ML)This site is located in the headwaters of the Amur River in
the Stanovoi Mountains (55 ﾟ N, 124 ﾟ E) about 50 km northof Tynda City. Larix cajanderi dominates. The stand density
is 4100 trees ha-1 with an average height of 4.3 m, althoughsome trees exceed 15 m. The annual mean temperature is -6
C, and the site receives 425 mm of precipitation annually(IIASA).

3. Seasonal energy balance variations
Seasonal energy balance variations above the canopy
were successfully measured at LL from the snowmelt
season to the leaf-fall season in 1998 (Ohta et al., 2001).
Figure 1 indicates the time series of each energy-balancecomponent and land-surface conditions. As shown in thefigure, the latent heat flux suddenly increased as trees
started to foliate in early June. Although snow melt occurredin mid-May, latent heat flux kept values low in this period.

environmental conditions occur, whereas larch trees require
two to three weeks to acquire leaves before the onset oftranspiration. A large part of the effective radiation is shared
as sensible heat flux during this period. These energybalance differences between deciduous and evergreen
forests are most apparent in spring.

4. Water balances in eastern Siberian forests in
the 1-D scale
One-dimensional water balances based on flux
measurements were calculated at LL, LP, and RL. Table 1summarizes the water balances obtained at each site.
Inter-annual variation in precipitation was wide, as shown in
the results obtained at LL. Consequently, soil moisture
contents also displayed wide annual variation (not shown inthis paper), but the amount of evapotranspiration remained
steady. Almost all precipitation was transpired or
evaporated during the warm seasons (except at LL in 1999),
regardless of tree species.
Table 1 Annual water balance at ML, MP, and YL from spring tosummer
Input
rain
snowmelt
Outputtranspiration
evaporation
sublimation

LL
1998
211(100)
106
105
151(72)
124
1611

1999
360(100)
257
103
143(40)108 *335*-

2000
222(100)13290145(65)112 *3
303

LP *1
2000
228(100)
14385
208(91)
162
46-

RL *2
2000
309(100)
191
118
274(87)-Figure 1 Time series of the energy balance components (a) and (b),Bowen ratio (c), and land-surface conditions (bottom bar) at LL in1998. (Ohta et al., 1998)*1: Hamada et al., (2004), *2: Tanaka et al., (2001), *3: These values
were calculated by a big-leaf model with parameters determined bydata collected in 1998 (Tanaka et al., 2000)

In contrast, sensible heat flux dropped at the end of May,
though net all-wave radiation increased until mid-June.
Consequently, the Bowen ratio time series shows a clear“U” shape and has a value of 1.0 even in the vegetation
growing season. At site RL, the Bowen ratio was 0.5 – 3.5 inearly spring and 0.1 – 1.5 in summer of 2000; the seasonal
trend indicated a U shape, similar to that at LL (Tanaka et al.,2001). Plant phenology strongly affects the energy balance
above larch canopies, and the energy budget wasdramatically changed by tree activity.
Seasonal variation of the Bowen ratio at LP differed fromthat at RL and LL (Hamada et al., 2004), especially in spring.
Site LP showed high latent heat flux values even in spring
2000, in contrast to values at RL. All sites showedmagnitudes of latent heat flux almost equal to those ofsensible heat flux at MP. Consequently, MP showed aBowen ratio of about 1.0 from spring to summer and did notdisplay a U shape.
There are two possible reasons for the differences inseasonal variations between LP and LL/RL. First,
permafrost thawing conditions differ between the two forest
types: the larch forests (LL and RL) have a lower thaw rate
than the pine forest. Thus, pine trees can use water in the soil
layer earlier in spring. Additionally, pine trees are evergreen
and do not spend time unfolding leaves. Pine trees,
consequently, can transpire as soon as suitable

It is important to understand how evapotranspiration
remains steady despite wide inter-annual variation inprecipitation and/or soil moisture contents. Permafrost plays
an important role in keeping evapotranspiration steady inthis region (Sugimoto et al., 2002). Figure 2 shows thevalues of δ O18 in summer precipitation, tree water, and soil
water. Annual δ O18 ranges in trees were obtained inAugust. The frozen zone showed a δ O18 value of -24 ‰. In
1998, a drought year, only surface soil above 15-cm deep
had a value higher than δ O18; water in the melting soilbelow 15-cm deep also showed low δ O18 values, about-24 ‰ . This tendency implies that meltwater from thepermafrost percolated from a deeper layer to a surface layer
according to the hydraulic gradient (not shown in this paper).
Trees could uptake this permafrost meltwater in 1998 owing
to their δ O18 values, which were lower than those ofsummer precipitation and equal to those of the surface soil.
However, during the rainy years of 1997 and 1999, δ O18values for the surface soil and trees were similar to those ofsummer precipitation. These results suggest that trees use
precipitated water for photosynthesis in usual and/or rainy
years. Trees will use the permafrost meltwater in droughtyears and precipitated water in rainy years. Consequently,
evapotranspiration remains steady.

a) Diurnal variation of energy flux componentsb) Seasonal variation of Bowen ratio

Figure 2 The δ O18 values for summer precipitation, trees, and the soil

layer. The δ O18 values in trees were observed annually in August.
(Sugimoto et al., 2002)

5. Evaluation of water and energy cycle
characteristics in eastern Siberian forests using
one-dimensional models
Characteristics of water and energy exchanges above
forests were evaluated using a one-dimensional land-surface
model (2LM) at LL, LP, and RL (Yamazaki et al., 2004).
Figure 3 shows the simulated and observed diurnal variationof the energy balance components at LP (a) and thesimulated and observed seasonal Bowen ratio time series atRL and LP (b). Both results simulated by the 2LM agreed
well with observed values. Forest physiological response isrepresented by the three parameters: minimum stomatal
resistance (rm), stomatal parameter of solar radiation (Sabm),
and air dryness (B). There were no significant differencesamong the three parameters, and the values of rm and Sabm
showed particular similarity at the three forest sites. The B
value was slightly larger at LP than at the other sites. These
results suggest that physiological responses to transpiration
were similar at the three forest sites in the middle reaches of
the Lena River despite differences in tree species and ages.
In contrast, the conductance model parameters showeddifferences between LL and ML. The Jarvis-typeconductance model was applied to the results at these twosites (Tanaka et al., 2000; Kimoto et al., 2001). The optimal
temperature for transpiration was estimated as
approximately 9 C and 7–20 C at LL and RL, respectively.
In addition, the atmospheric-saturation-deficit parameter

Figure 3 Time series of (a) the observed and simulated
components of energy balance at LL in the 2000
summer, and b) the Bowen ratio at the RL and LP in the2000 snowmelt-summer-autumn seasons.
was 1.5 times larger at LL than at ML. These results imply
that trees become more active under cooler conditions andrespond little to air dryness at LL, although both LL and RL
feature the same dominant tree species.

6. Concluding remarks and follow-up projects
The GAME-Siberia project clarified basic characteristics
of water and energy exchanges in Siberian forests. Plant
phenology is an important factor in water and energy cycles
in Siberian forests, especially deciduous forests. The
partition of effective energy into sensible heat flux is larger
in Siberian forests than in temperate and tropical forests,
and latent heat is strongly limited by air dryness. Moreover,the Bowen ratio is higher in Siberia, especially in spring andautumn, even compared to that in North American borealforests.
A large part of precipitation is transpired and evaporated
from the entire eastern Siberian ecosystem. Thus, major
runoff may be limited to the snow-melt season. Inter-annual
evaptranspiration is steady despite the wide variation in
annual precipitation, and trees will use permafrost
meltwater in times of drought.
Land-surface model parameters show similar
characteristics for the water and energy exchanges at eachsite in the middle reaches of the Lena River. However,model parameters show variances in optimal temperatures
and atmospheric saturation deficits at sites with the same

tree species. These results imply a spatial distribution oftranspiration responses in Siberia, despite the region’s
relatively simple vegetative composition and structure.
GAME-Siberia research intensively examined seasonaland inter-annual variation of water and energy cycles, but
the temporal and spatial distribution of plant activities
related to these cycles is still not well known. To develop
land-surface process models, it is critical to understand thedistribution of forest eco-physiological parameters. One
follow-up project supported by the Japan Science andTechnology Agency (JST) is setting parameters for forest
eco-physiological effects on water/energy/carbon cycles intemperate to boreal forests. Preliminary results suggest thatthe parameters in the Jarvis-type conductance model areaffected by not only forest functional types but also climate
conditions, temperature, radiation, and air dryness.
Another major research avenue will be to examine howsnow and ice affect water/energy/carbon cycles in Siberianforests. Snowmelt is particularly important for the water
cycle in the boreal zone, but interactions among forests,
snowmelt, and permafrost thawing have not yet been
analyzed well in Siberia. The Institute of Observational
Research for Global Change is monitoring climate
conditions from the tundra to Mongolia, an area that
includes the eastern Siberian taiga. Snow and ice influences
will be investigated in this long-term monitoring.

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