Characteristics of roughness parameters in boreal, cool-temperate
and warm-temperate forests∗Taro NAKAI1,2 , Takashi KUWADA1,3 , Yuji KODAMA2 , Takeshi OHTA3and Trofim C. Maximov4(1: CREST, JST, 2: ILTS, Hokkaido University, 3: Graduate School of Bioagricultural Sciences,Nagoya University and 4: IBPC, SD-RAS, Russia)∗ILTS, Hokkaido University, Sapporo 060-0819, Japan. e-mail: taro@pop.lowtem.hokudai.ac.jp

Abstract
Zero-plane displacement d and roughness length z0 were compared among boreal, cool-temperate, and warmtemperate forests. z0 was large in the forest include coniferous trees, whereas small in the forest consist ofbroad-leaved trees. The normalized zero-plane displacement d/h (where h is the tree height) increased withstand density, whereas z0 decreased. On the other hand, d/h showed a negative correlation with plant areaindex (PAI), which was inconsistent with parameterization of the models. The effect of the vertical structureof the forest might be included in PAI. Seasonal variation in d/h appeared in the forest including deciduous
broadleaved trees. The change of d/h corresponded to the change of PAI. However, d/h was underestimatedby the models, and the decrease in d/h for cool-temperate forest appeared to be small compared with thatpredicted using the models.
Keywords: Zero-plane displacement, Roughness length, Stand density, PAI, vertical structure.

1. Introduction
Roughness parameters, such as zero-plane displacement d (m) and roughness length z0 (m), are necessary factors to estimate transportation of heat, water,and scalar gasses (CO2 , etc.) through aerodynamic resistance in Penman-Monteith equation or atmosphericstability function. These parameters are related to forest structure factors (LAI, stand density, etc.), andtheir relationships are needed for estimation of plantphysiological factors in wide-scale area of boreal forest by using satellite data. In this study, as a partof CREST project which follows GAME-Siberia study,
roughness parameters are compared among boreal forest, cool-temperate forest, and warm-temperate forest,
and the characteristics of them are discussed.

2. Material and method
2.1. Study site
We have 5 meteorological towers in 3 research areas. The boreal forest site is located in Spasskaya Pad
near Yakutsk, Russia (62◦ 15’ N, 129◦ 37’ N), the cooltemperate forest site is located in Moshiri, Hokkaido,Japan (44◦ 20’ N, 142◦ 15’ N), and the warm-temperateforest site is located in Seto, Aichi, Japan (35◦ 15’ N,137◦ 04’ N). Figure 1 shows the location of the study
sites.
In the boreal forest site, we have two observationsites. The Yakutsk-Larch site (YL) is in the larch forest(deciduous conifers), and the Yakutsk-Pine site (YP)
is in the red pine forest (evergreen conifers). We also
have two study sites in the cool-temperate forest site.
The Moshiri-Birch site (MB) is in the birch forest (deciduous broadleaved trees), and the Moshiri-Mixed site(MM) is in a mixed forest of evergreen conifer and deciduous broadleaved trees. The warm-temperate forest
site, the Seto-Mixed site (SM), is in a mixed forest consisting of deciduous and evergreen broad-leaved trees.
The forest structure factors: stand density (trees
ha−1 ), tree height h (m) and plant area index (PAI)of each site are shown in table 1. PAI of the YL andYP site was estimated by fish-eye photos (Toba andOhta, 2002), whereas a plant canopy analyzer LAI2000 (Li-COR) was used for the other sites. In theMM site, the forest consists of broadleaved trees (maximum tree height hmax = 22.9 m) and coniferous trees(hmax = 35.5 m), and the tall coniferous trees appeared
to affect the aerodynamic roughness; hence, h = 25 m
was assumed as the apparent mean tree height of tallconiferous trees.
100˚ 110˚ 120˚ 130˚ 140˚ 150˚ 160˚ 170˚60˚Yakutsk

50˚60˚50˚Moshiri
40˚40˚Seto30˚30˚100˚ 110˚ 120˚ 130˚ 140˚ 150˚ 160˚ 170˚

Fig. 1: Location of study sites

2.2. Observation
The data from the Sonic AnemometerThermometer (SAT) and the anemometers are usedin this study. From the SAT mounted at the heightof zSAT (m), the friction velocity u∗ (m s−1 ) andthe Monin-Obukhov length L (m) were obtained.
The wind speed U (z) (m s−1 ) was measured by theanemometers at two heights, za and zb (m) (za > zb ).
In the YP site, however, wind profile data was notavailable, and hence only data from the SAT was used.
The height of instruments, zSAT , za and zb of each site
are also shown in table 1. The SAT data was sampled
in 10 Hz, and was calculated above parameters every
30 minutes with the coordinate correcrion by double
rotation method. U (z) was sampled every 10 seconds,and was averaged every 30 minutes.

Table 1: Forest structure factors and observation height at each siteStand density Tree height h Plant area index (PAI) zSATzazb(trees ha−1 )
(m)
(m)
(m)
(m)
YL840∗18∗
3.71 (Jul. 1997)∗
32.0
3024
∗∗
∗
YP
2,660
10
2.80 (Aug. 2000)∗
18.2——
MB 4,000
11.5
2.63 (Jun. 2004)
21.05
20
16
MM 2,58525∗∗∗
3.44 (Jul. 2004)
31.56
30
25
SM
1,828
8.1
3.56 (Jun. 2004)
19.5
1410
∗
Toba and Ohta (2002), ∗∗ Hamada et al. (2003), ∗∗∗ Apparent mean tree height of tall conifers.
Site

2.3. Calculation of d and z0

It indicates that the scalar is carried by the eddies effecIn a condition of neutral stability, mean wind profile tively in the northern forest consists of conifers. Thesecharacteristics in z0 , however, did not appear in noris written in logarithmic low with height as follows:
malized values of z0 /h (Table 2). It shows that theu∗ z − dln(1) normalization of z0 with h is not valid in comparison
U (z) =kz0of the characteristics among different forests. Hence,hereafter, d/h and z0 are compared among 5 forest sites
where k is the von Kármán constant (= 0.4). When
together with forest structure factors.
the slope of kU (z) to u∗ were obtained at two height(α = kU (za )/u∗ at za and β = kU (zb )/u∗ at zb ), then Table 2: Comparison of d and z0 among different forestd and z0 could be calculated as follows:sites together with normalized values (June 2004).
Site d (m)d/hz0 (m) z0 /hzb (eα /eβ ) − zaza − dYL
9.42
0.52
2.48
0.14
d=,
z=(2)
0eα /eβ − 1eαYP
7.34
0.73
1.45
0.15
MB
9.78
0.85
0.67
0.06
The data under the conditions of neutral stability,
MM19.25
0.77
1.78
0.07
|zSAT /L| ≤ 0.05, were selected for the calculation.
SM5.21
0.64
0.92
0.11
On the other hand, for the YP site where only25
Zero-plane displacement d (m)the eddy correlation data was available, the methodof Toda and Sugita (2003) were used in calculation ofd and z0 . The data was filtered by stability (−15 ≤zSAT /L ≤ 0), wind speed (U (zSAT ) ≥ 1), sensible
heat flux H (H ≥ 100 W m−2 ), latent heat flux lE(0 ≤ lE ≤ 1000 W m−2 ), and steadiness of temperature T (◦ C) (variation in 30 minutes |dT30min | ≤ 0.5◦
C 30min−1 ). Further more, the daytime data (from10:00 to 14:00) are picked up. In this study, d and z0
calculated for temperature are adopted.

(a) Zero-plane displacement d20MM15MB

10YLYPd = 0.70h

SM52

R = 0.86
0

3. Result and discussion

05101520

2530

Tree height h (m)3.1. Comparison of roughness parameters among different forests

3.0Roughness length z 0 (m)(b) Roughness length z 0
Table 2 shows d and z0 for each observational site
YL
2.5in June 2004, together with normalized values devided
by h. In many cases, d and z0 are parameterized as
2.0
simple function of h (Brutsaert, 1982), and tipicallyMMYP
1.5d = (2/3)h and z0 = (1/8)h are used (Garratt, 1992).
Figure 2 is the scatter diagrams of d (a) and z0 (b)1.0SMagenst h in June 2004. The regression coefficient wasz 0 = 0.10hMB
20.70 for d and 0.10 for z0 , which is consistent with above
R = 0.32
0.5
parameterization. From fig. 1(a), d strongly depends
0.0on h, and hence the normalization with h is necessary
051015202530in comparison of d among different forests. However,
Tree height h (m)z0 was not correlated with h. z0 was large in YL, YPand MM site, that include coniferous trees, whereas Fig. 2: Scatter diagrams of d (a) and z0 (b) against hsmall in MB and SM site, that consist of broad-leaved (June 2004).
trees. The large z0 is result in the small aerodynamic
Figure 3 is the scatter diagram of d/h and z0 against
resistance ra (m s−1 ):the stand density. d/h increased with stand density,µ¶2
whereas z0 decreased. d/h was strongly correlated withz−d1ln.
(3) h (R2 = 0.95) compared with the correlation between
ra = 2k U (z)
z0

3.0

MB

0.8

2.0

YP

0.7

YP

1.0MMd/hz0d/h

YP
MM

0.7
SM

1.5
1.0

0.5

0.001000

2000

3000

4000

5000

−1Stand density (trees ha )Fig. 3: Scatter diagrams of d/h and z0 against standdensity.

1.0
MB

0.9
0.8

MM0.7

YPSMYL

0.5

2.0YPd/h−1Figure 6 shows the seasonal variation of d/h in fiveresearch sites from July 2003 to August 2004. The MBand MM site had heavy snowfall in winter; hence, thesnowdepth hs (m) was included and d/h was calculated as (d − hs )/(h − hs ). In the MB, MM and SM
site, d/h changed seasonally: small in winter and large
in summer. This change corresponded to the seasonalchange of PAI shown in fig. 8, which is consistent withthe parameterization such as Choudhury and Monteith(1998). Here, the PAI in the MB and MM site shown infig. 8 was estimated from the downward PAR measured
on the tower top and the forest floor, which was fitted
to the PAI data measured with LAI-2000. The change
in d/h was large in SM site compared with that in MBand MM site. The coefficient of variation CV (%) was
4.5% in MB site, 4.3% in MM site, and 6.4% in SMsite. On the other hand, in the YL site, there was noapparent seasonal change of d/h in spite of its foliationin this period. In the YP site, which consits of evergreen conifer, d/h was fluctuated although there was nofoliation. As the result, the seasonal variation in d/happeared in the forest including deciduous broadleaved
trees, and it was not clear in coniferous forest.

0.6
MM50

2.5

YL

MM

0.7
YP

1.5

SM

1.0
SM

0.6
MB

0.5

YL

0.5

0.0z 0 (m)

0.8

40

Fig. 5: Scatter diagrams of d/h and z0 against plantarea per tree.

3.0
MBd/hz030

Plant area per tree (m tree )d/hFigure 4 is the scatter diagram of d/h and z0
against PAI. d/h seems to have negative correlation
with PAI, which is inconsistent with the parameterization of some models (e.g., Choudhury and Monteith,1998), although PAI of the YL and YP site was estimated by different way from that of the other sites.
This indicates that d/h and z0 cannot be estimatedonly from PAI data.
In the dense forest, the foliage is concentrated on
the top of the trees, and hence PAI becomes small.
On the other hand, in the sparse forest, the foliage
is vertically distributed because solar radiation penetrates deep into the forest, and hence PAI may becomelarge. Here, the plant area per tree As (m2 tree−1 ) isintroduced, which is expected to represent the verticalstructure of the forest. Figure 5 is the scatter diagramof d/h and z0 against As . d/h decreased with As , although the results for the YL and YP sites were lessreliable. This suggests that the vertical structure ofthe forest has an effect on the aerodynamic roughness,and the parameterization of this structure is importantin evaluating d/h and z0 .
0.9

203.2. Seasonal variation in roughness parameters

0.5

MBYL

102

SM

0.6

0.002.0

YP

0.5

YL

0.5z 0 (m)

0.8

MB

2.5YL1.5SMSM

3.0MBd/hz0MM0.60.9

2.5

YLMMz 0 (m)0.9d/hz0 and h (R2 = 0.56). This result suggests that thedence forest inhibit the momentum from penetrating
into the forest, and make the surface smoother. Hencethe stand density is one of the effective forest structure
factors to estimate d and z0 . At the YL site in the boreal forest, d/h was the smalllest and z0 was the largest
in these sites because of its small stand density.

0.4JASONDJFMAMJJAMonth of year (July 2003 to August 2004)

Fig. 6: Seasonal variation of d/h in five research sites.

Figure 7 shows the seasonal variation of z0 . In theMB and MM site, z0 showed clear seasonal change:
Plant area index
large in winter and small in summer. However, thisFig. 4: Scatter diagrams of d/h and z0 against plant change was not apparent in SM site. CV was 19.6% in
MB site, 15.2% in MM site and 10.8% in SM site. This
area index.
2.0

2.5

3.0

3.5

4.0

z 0 (m)sugests that the evergreen trees in the SM site affected in PAI was consistent with that predicted by the modthe aerodynamic roughness even though the deciduous els. However, d/h was underestimated by both models,
trees was defoliated.
and the seasonal variation of the observged d/h was
small compared with that predicted using the modelof Yamazaki et al. (1992). As pointed out in section
3.0
3.1., d/h cannot be described only by PAI because PAI
YL
2.5
may indicate vertically-distributed foliage. FurtherMM
more, the birch tree has small dense branches in the2.0
crown space; hence, these branches are also expected
1.5
YP
to affect d/h after defoliation. Accurate evaluation ofSM
1.0
such forest structure factors is necessary.
0.5
PAIJASONDJFMAMJJAMonth of year (July 2003 to August 2004)

d/hFig. 7: Seasonal variation of z0 in five research sites.
4.0
SM

3.5
MB

3.0
PAI

2.5

Observed

2.0

Yamazaki et al. (1992)

4.0

1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0

3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0JMM

Choudhury and Monteith (1988)

PAIMB

0.0

AS

O N DJF M A M

JJA

Month of year (July 2003 to August 2004)

1.5Fig. 9: Comparison of d/h among observed and modelpredicted values together with PAI in the MB site.

1.0
0.50.0
JA

S

ON

DJFM

A M

JJ

A

Acknowledgments

The authors would like to thank Dr. Motomu Todaof Hokkaido University, who presented PAI data of theFig. 8: Seasonal variation of PAI in MB, MM and SM MB site, Dr. Kyoko Kato of JST/CREST, Hokkaidosite.
University, who presented forest structure factors ofthe MB and MM sites, and Mr. Ken-ichi Daikoku of
3.3. Comparison of d/h between obser- Nagoya University, who presented PAI data of the SMvation and model prediction
site.
As mentioned above, the change of d/h corresponedto that of PAI, and this relationship was parameterReferencesized in some previous study. Here, the observed d/hBrutsaert,W., Evaporation into the Atmosphere, Theory,was compared with that predicted from the models
History, and Applications, D. Reidel, Boston, MA,
presented by Choudhury and Monteith (1998) and Ya299 pp, 1982.
mazaki et al. (1992).
Cloudhury, B. and J. Monteith, A four-layer model for theChoudhury and Monteith (1998) parameterized d/hheat budget of homogeneous land surfaces. Quart.
as follows:J. Roy. Meteorol. Soc., 114, 373-398,1988.
´³Garratt, J., The Atmospheric Boundary Layer, Cambridge¡¢d(4)= ln 1 − X 1/6 + 0.03 ln 1 + X 6
University Press, New York, NY, 316 pp, 1992.
hMonth of year (July 2003 to August 2004)

Hamada, S., T. Ohta, T. Hiyama, T. Kuwada, T. Takahashi

and T. C. Maximov, Hydrometeorological behaviour
where X = 0.2PAI. This model parameterized d/h onlyof pine and larch forests in eastern Siberia. Hydrol.
from PAI. On the other hand, Yamazaki et al. (1992)
Process., 18, 23-39, 2004.
wrote d/h as follow equation:
Toba, T. and T. Ohta, Modeling the characteristics of inµ¶·µ¶¸
terception loss in forests. J. Japan Soc. Hydrol. &dh12k 2c∗
h12k 2=1−−
exp 1 − 2 1 −−
Water Resour., 15, 345-362, 2002 (in Japanese withhhc∗
2khc∗
English abstract).
(5)Toda, M. and M. Sugita, Single level turbulence measurewhere h1 is the height of the bottom of crown (m),ments to determine roughness parameters of comc∗ = cd ah, cd is the drag coefficient (= 0.2) and a isplex terrain. J. Geophys. Res., 108(D12), 4643,
the plant area density (m−1 ). This model simply indoi: 10.1029/2002JD002573, 2003.
cludes the vertical structure of the forest.
Yamazaki, T., J. Kondo and T. Watanabe, A heat-balance
Figure 9 shows the seasonal variation of observed
model with a canopy of one or two layers and its
d/h in MB site together with predicted values andapplication to field experiment. J. Appl. Meteorol.,
PAI. The trend in the observed d/h with the change
31, 86-103, 1992.