Flux variation in a Siberian taiga forest near Yakutsk from 1986 to 2000
estimated by a one-dimensional model with routine data
*YAMAZAKI Takeshi1, OHTA Takeshi2, SUZUKI Rikie3 and OHATA Tetsuo1(1: Institute of Observational Research for Global Change, JAMSTEC, 2: Nagoya Univ.,
3: Frontier Research Center for Global Change, JAMSTEC)* Institute of Observational Research for Global Change, JAMSTEC, Showa-machi, Kanazawa-ku,
Yokohama 236-0001, Japan. e-mail: yamaz@jamstec.go.jp
Abstract
Energy and water fluxes are estimated and their variations are investigated in a larch forest site near Yakutsk using a
one-dimensional model with daily basis routine data. Estimated period is 1986 to 2000 including the period before startof tower observation (1997) on the left bank of Lena River. The land surface model includes three submodels;vegetation, snow cover, and soil. It can calculate water and energy fluxes above and within forest, if meteorological dataover the forest are given as input. The data used in this study is Baseline Meteorological Data in Siberia (BMDS)
Version 3; it consists of daily data of main meteorological elements. Procedure is as follows: 1) preparing equations
between routine Yakutsk data and larch tower data, 2) estimating past meteorological data over taiga by the equations,and 3) estimating fluxes using the one-dimensional model. Date of leaf-out start is parameterized with soil temperatureand daily maximum air temperature; it corresponds to green-up time obtained from satellite NDVI data. Monthly
deviation of net radiation, Rn, is 10 Wm-2, maximum is 20 Wm-2. Monthly deviation of latent heat flux, lE, is less than
10 Wm-2, its warm season average is less than 5 Wm-2. Although magnitude of lE is almost zero in December andJanuary, it is several Wm-2 and sensible heat flux, H, sometimes becomes negative in cold season except these twomonth. The variation of evapotranspiration is significantly small compared with that of precipitation. The
evapotranspiration (E) normalized by potential evaporation (Ep), E/Ep is from 0.37 to 0.44 in warm season, it tends to belarge when the leaf-out starts early. The amount of evapotranspiration in warm season can be estimated from Ep in anerror of 5 mm using this relationship.
Keyword: flux variation, land surface model, leaf out, potential evaporation, Siberia

1. Introduction
Intensive meteorological and hydrological observationin GAME/Siberia was carried out from 1998 to 2000 at
Spasskaya Pad in a taiga larch forest near Yakutsk with atower (Ohta et al., 2001). What is the position of thesethree years compared with average? What is the variationof fluxes year to year? It is difficult to answer thesequestions only from observed data in intensive
observation period. Thus we estimated fluxes over thetaiga forest and investigated their variation before start of
the tower observation using a one-dimensional land
surface model with routine data. Furthermore, we will
discuss the characteristics of evapotranspiration
normalized by potential evaporation and possibility of
estimating total evapotranspiration in warm season
without land surface model.

2. Method
The estimation method is as follows:
1) The relationships of meteorological data between
Yakutsk and the tower are established from 1998 to2000.
2) Past meteorological conditions over the taiga forest
are estimated using the equations obtained step 1).
Diurnal variations are given with empirical equations.
3) The fluxes are estimated using a one-dimensional land
surface model.
The land surface model used in this study is that
described in Yamazaki et al. (2004) with addition ofsnow interception process (Yamazaki et al., 2005). It
includes three submodels; vegetation, snow cover, andsoil. It can calculate water and energy fluxes above andwithin forest, if meteorological data over the forest aregiven as input.
The data used in this study is Baseline Meteorological
Data in Siberia (BMDS) Version 3 completed as
GAME/Siberia project. It consists of daily mean,maximum and minimum air temperature, precipitation
amount, water vapor pressure, mean and maximum windspeed, duration of sunshine, snow depth, and otherelements from 1986 to 2000.
Linear relationships are recognized on daily eachmeteorological data between Yakutsk and the tower.
Therefore those linear regression equations are used.
Daily precipitation amount is assumed as 1.12 times ofthat in Yakutsk.
The leaf-out date is parameterized as the date of ‘soil
temperature at 10 cm becomes greater than 5 C’ and‘accumulated daily mean air temperature becomes
greater than 100 Cday after daily mean air temperature isbeyond 0 C’. The period until leaf-out finish is assumed
as 16 days. It is assumed that the fallen leaf starts at 1
Sep. and finishes 30 Sep. in every year.
Because the purpose of this study is to investigate
long-term variation of fluxes, hourly data measured at
the tower is used after 1998, when tower data are exist.
There is a long data missing in later half of 1997. Thus
just one year from 15 March 1997 is skipped in theestimation to connect the calculation smoothly before
and after the data missing.
It is important how to fall daily amount ofprecipitation in a day because interception evaporation issignificantly influenced by length of a rain event andprecipitation intensity. We investigated hourly
precipitation data but we did not recognize that rain falloccurs in certain time zone. For example, if precipitation

-50200

2001

2000

1999

1998

1997

1996

1995

1994

from Sin/Sout

1993

1992

1991

1990

1989

1988

1987

0Year-100

2000 Left Larch (Pr: all day)Fig. 2: Estimated date of leaf-out start with theparameterization. +: Date from measured solar
radiation ratio in forest to outside.

150
100

35

50

is distributed evenly in all day, latent (sensible) heatbecomes too much (less) in rainy days (Fig.1 lower).
After many examinations, we choose that half of daily
amount falls midnight (0-1 h) and the other half falls
noon (12-13 h) (Fig.1 upper).

20
15

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

101988Fig. 1: Reproducibility of hourly fluxes. Upper:
rainfall in 0-1h and 12-13h, lower: even rainfall in allday. Lines are using tower data, marks are fromroutine data.

senescence

25

1987

-50
-100

mature30

1986

0green up

1985

H, lE (W/m2)

parameterization

1985

50

3530
25
20
1510501986

100

Date of leaf-out start(May)150

H LLdatalE LLdata
H from Yks
lE from Yks

10-day of year

H, lE (W/m2)

200

2000 Left Larch (Pr: 0&12h)

Fig. 3: Green-up, mature and senescence time from10-daily NDVI (threshold is 0.25).

green-up
35

3. Results

3025
from NDVI (0.25)

Figure 2 shows date of leaf-out start estimated by theparameterization, also the date determined from ratio ofsolar radiation in the forest to outside is indicated. Tovalidate the parameterization of leaf-out, NDVI data wasanalyzed. The 10-daily composite NDVI provided byCEReS Chiba University was averaged over 128.5E 131.5E and 61.0E - 63.0E. Figure 3 shows estimatedgreen-up time in 10-day of year (e.g. 15 means 21-31,May) as well as mature and senescence season. The
green-up (senescence) is defined as the date when NDVI
becomes greater (smaller) than the threshold of 0.25.
Figure 4 shows the comparison between leaf-out start by
the parameterization and green-up from NDVI. Note thatNDVI includes the signal of not only larch forest butother species of tree and grassland.
Estimated monthly mean fluxes and anomaly fromevery month’s mean during 15 years are shown in Figs 5and 6. Monthly deviation of net radiation Rn and sensible
heat flux H are about 10 Wm-2, 20 Wm-2 in maximum.
Latent heat flux lE deviation is less than 12 Wm-2. Thevalue of lE in winter is several Wm-2 except for
December and January and sometimes H becomes
negative. Anomalies of H and lE are not always
synchronous.
Monthly normalized evapotranspiration E/Ep is shownin Fig.7. The value of E/Ep is stable in 0.4 through 0.55
in warm season (Jun-Aug). In May, it varies from 0.15 to0.37 according to leaf-out time. On the other hand, it isscattering in cold season because the absolute values of E

20151050051015

20253035

parameterization

Fig. 4: Comparison between leaf-out start by theparameterization and green-up from NDVI. Bothaxes are indicated in the date of May.

and Ep are small (sometimes Ep is negative). Large valueof E/Ep is often found in March and October because oflarge interception evaporation of snow.
Figure 8 shows warm season (May – Aug) averaged
fluxes and anomaly including potential evaporation Ep.
Deviations of H and lE are 7 Wm-2 or less except for H
in 1998. It is found that 1998 is extraordinary because
deviations of each flux are abnormally large in this year.
Variation of Ep is similar to Rn variation but slightly

Left Larch (1986-2000 Warm Season) 0&12 Ppara

Left Larch (1986-2000) 0&12 Ppara
Average flux(W/m2)

150

500Year-50

Rn mean

H meanlE mean
Left Larch (1986-2000 Warm Season) 0&12 Ppara
Anomaly (W/m2)

Fig. 5: Estimated monthly mean fluxes.

20

25
20
15
1050-5-10-15

10RnH
lElEp

0Year-10

Fig. 8: Warm season (May-Aug) averaged fluxes(upper) and anomaly (lower) including potential
evaporation Ep.

-20
20
100-10

Yakutsk 1986-2000 warm

-20

0.5

20
100.4

0-10-20

Fig. 6: Estimated monthly anomaly from every
month’s mean during 15 years: Net radiation,sensible heat flux and latent heat flux from the top.

Left Larch (1986-2000)

10.8

Jun-Aug
Mar & OctMayothers

0.6
0.4

E/Ep

lE anomaly (W/m2)

H anomaly (W/m2)

Rn anomaly (W/m2)

Left Larch (1986-2000) 0&12 Ppara

E/Ep

RnH
lElEp
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001

100

200
150
100
5001985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001

Monthly mean flux (W/m2)

200

0.3
0.2
0.1
00

0.1

0.20.30.4

0.5Pr/Ep

Fig. 9: The relationship between precipitation andevapotranspiration in warm season.

0.20Fig. 7: Monthly evapotranspiration normalized bepotential evaporation.

emphasized. The influence of water and energy balanceon the deviation of leaf-out period is small compared
with
fixed
leaf-outsimulation.
The
total
evapotranspiration increases as the leaf-out is early(maximum +5.1 mm in 2000); it decreases as the leaf-outis late (maximum -8.9 mm in 1987).
Figure 9 indicates relationship between precipitation
Pr and evapotranspiration E in warm season where bothvariables are normalized by Ep. It is found that variationof E is small compared with variation of Pr. It suggeststhat forest and soil (including permafrost) make E
variation even. The reason why evapotranspiration islarger than precipitation is that snow is not included inthe precipitation.
Figure 10 shows normalized evapotranspiration E/Ep
in warm season against lEp anomaly and date of leaf-out
start. The value of E/Ep is 0.37 through 0.44; it decreases
as lEp anomaly increases or leaf-out is late. It is possiblethat the amount of evapotranspiration in warm season isestimated using these relationships in the accuracy of 10mm from lEp anomaly, and 5 mm accuracy from the dateof leaf-out start without land surface model.

0.46

E/Ep

0.44
0.42
0.4
0.38
0.36

E/Ep

-20

-10

010lEp anomaly (W/m2)

2030

0.46
0.44
0.42
0.4
0.38
0.36

20 Wm-2) and that of lE is less than 12 Wm-2. The year
1986, when main observation was started inGAME/Siberia, is abnormal having positive anomalieson all fluxes. The normalized evapotranspiration E/Ep is
0.37 through 0.44 in warm season average; it tends to besmall when Ep is large or leaf-out is late. The amount ofevapotranspiration can be estimated from Ep and leaf-out
date in the error of 5 mm.
The problems of this study are as follows:
1) The effect of soil dryness on plant physiology is notconsidered.
2) Also the length of the period until finishing leaf-out
and the date of senescence should be parameterized.

References
1015202530
Date of leaf-out start (May)35

Fig. 10: Evapotranspiration normalized by potential
evaporation against potential evaporation anomaly(upper) and date of leaf-out start (lower).

4. Conclusions
Flux variations are estimated using routine data inconsideration of leaf-out variance. The estimatedmonthly variation of Rn is less than 10 Wm-2 (maximumOhta, T., T. Hiyama, H. Tanaka, T. Kuwada, T.C. Maximov, T.
Ohata and Y. Fukushima, Seasonal variation in theenergy and water exchanges above and below a larch
forest in eastern Siberia. Hydrological Processes 15:1459–1476. DOI: 10.1002/hyp.219, 2001.
Yamazaki, T., H. Yabuki, Y. Ishii, T. Ohta and T. Ohata, Waterand energy exchanges at forests and a grassland ineastern Siberia evaluated using a one-dimensional land
surface model. J. Hydrometeorology 5: 504–515, 2004.
Yamazaki, T., H. Yabuki and T. Ohata, Hydrometeorologicaleffects of intercepted snow at an eastern Siberian taiga
forest using a land surface model. Hydrological
Processes, (submitted), 2005.