Estimating sensible and latent heat fluxes from a temperate broad-leaved forest using the Simple Biosphere (SiB) model

AGRICULTURAL AND FOREST METEOROLOGY ELSEVIER

Agricultural and Forest Meteorology 84 (1957) 285-295

Estimating sensible and latent heat fluxes from a temperate broad-leaved forest using the Simple Biosphere (SiB) model K. Schelde "*, F.M. Kelliher b, W.J. Massman c, K.H. Jensen a a Institute of Hydrodynamics and Hydraulic Engineering, Technical University of Denmark, Lyngby DK-2800, Denmark b Manaaki Whenua-Landcare Research, P.O. Box 69, Lincoln, New Zealand c US Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO 80526, USA

Received 4 September 1995; accepted 7 February 1996

Abstract

Sensible ( H ) and latent heat (~tE) flux densities from a well-watered, broad-leaved forest of Nothofagus trees were estimated using the simple biosphere (SiB) model. Model inputs included micrometeorological measurements made at a reference height (36m) just above the canopy and site parameters such as the tree canopy leaf area index of seven. Half-hourly diurnal courses of modelled H and AE were generally in good agreement with eddy covariance flux measurements ( + 30W m -2 on average) over six late-summer days of variable weather conditions. The most important model variables determining these fluxes were the bulk leaf boundary-layer resistance (rb), proportional to leaf size, for H and canopy (stomatal) resistance (re), regulated by radiation interception and air saturation deficit, for AE. Recent developments in the modelling of r c for different vegetation types are discussed. Maximum daily ground (forest floor) evaporation rate (Eg) was 0.5 mmday-J, accounting for up to 20% of forest evaporation. Initial model estimates of Eg in the forest were nearly 50% less than those of lysimeter measurements. However, agreement between measured and modelled Eg was only about + 0.05 mm day- 1 after reduction of the trunk space eddy diffusive resistance (r d) based on a comparison with other values in the literature. © 1997 Elsevier Science B.V. All rights reserved.

Keywords: Sensible heat fluxes; Latent heat fluxes; Temperate broad-leaved forest; Simple Biosphere Model

1. I n t r o d u c t i o n General circulation models (GCMs) require accurate and realistic Earth surface representation to define the lower boundary condition (Garratt, 1993; Garratt et al., 1993). Climate simulations are especially sensitive to the diurnal variation in surface * Corresponding author, at: Danish Institute of Plant and Soil

Science, Research Centre Foulum, P.O. Box 23, DK-8830 Tjele, Denmark, e-mail: [email protected],

partitioning of available energy into sensible and latent heat fluxes (e.g. Rowntree, 1991; Dickinson et al., 1991). For vegetated surfaces, this variation can be profoundly influenced by biological factors including stomatal regulation of evaporation. The G C M thus requires a surface sub-model incorporating both climatology and biology. One suitable model is the Simple Biosphere (SiB) model (Sellers et al., 1986; Sellers et al., 1989). It was developed for use in a GCM or, as in this paper, it can be run separately using prescribed climate variables measured at a

0168-1923/97/$17.00 © 1997 Elsevier Science B.V. All rights reserved. PII S 0 1 6 8 - 1 9 2 3 ( 9 6 ) 0 2 3 5 7 - X

286

K. Schelde et al. /Agricultural and Forest Meteorology 84 (1997) 285-295

reference height above the surface although this mode of operation ignores potentially important atmospheric feedbacks (e.g. Jacobs and De Bruin, 1992). SiB is widely known amongst climatologists, but other biophysically based simplified canopy-atmosphere models (SCAMs) for use in GCMs are also under development (e.g. Raupach, 1991). SiB has been found to model the diurnal variation in the surface energy balance well when compared with measurements made over stands of agricultural crops, conifer forest and tropical rain forest (Sellers and Dorman, 1987; Sellers et al., 1989). However, these studies do not include measurements partitioning fluxes into plant canopy and understorey-soil components. Vegetation changes can dramatically alter the partitioning of surface fluxes with implication for the resulting climate (e.g. Xue and Shukla, 1993). Soil evaporation can be substantial beneath a developing crop canopy (e.g. Leuning et al., 1994). In forests, the understorey often accounts for a signiflcant proportion of total evaporation (see review by Black and Kelliher (1989)). Surprisingly, there are few energy balance studies that include measurements of total, plant canopy and soil fluxes. In this paper, we utilise the only available forest data set of this kind in a test of the SiB model, Our model test draws upon a comprehensive set of energy balance measurements made over six consecutive, late-summer days in 1991 in a temperate broad-leaved forest (Kelliher et al., 1992; Ktistner et al., 1992). As these two references completely describe the measurement techniques and results, only a brief summary is needed here. Total evaporation ( E ) and sensible heat ( H ) were measured using the eddy covariance technique; tree transpiration ( F ) was estimated by xylem sap flow measurements, and forest floor evaporation (Eg) was determined from the weight loss of lysimeters. Tree canopy energy storage rate ( J ) was estimated from changes of canopy air temperature and measurements of biomass water content, and ground heat flux density (G) was measured using a network of heat flux plates and thermocouples. In addition, environmental variables (net radiation (Rn), visible irradiance, wind direction, wind speed, and relative humidity) were recorded at 30min intervals. Agreement between half-hourly values of ( H + AE) and available energy (R n - J - G) was generally good ((/-/+ A E )

= 0.97(R n - J - G) - 14 (W m -2), R 2 = 0.90 for 126 30min averages during 12-17 March). However, (R n - J - G) tended to exceed ( / - / + A E ) by 5 0 - 1 5 0 W m -2 during periods of intermittent cloudiness, reflecting significant differences in sampling area between eddy fluxes and available energy in a variable radiation regime (Kelliher et al., 1992). The remote and pristine measurement site was located near Maruia in the South Island of New Zealand (42°13'S, 172°15'E, 400m elevation; for the year ending 30 April 1991, rainfall was 2054mm on 197days and average air temperature was 9.4°C). The vertically structured tree canopy of this undisturbed old-growth N o t h o f a g u s (beech) forest was complex with emergents up to 36 m tall, 1.7 m diameter and 400 years old. Tree social position, assessed by emergence of crown from the general canopy level, strongly affected the individual contributions to canopy evaporation in this natural forest, with 50% emanating from emergents, which made up only 3 - 4 % of the tree population. Although the tree canopy was closed and one-sided leaf area index was equal to seven, forest floor evaporation was 10-20% of the total, with rates up to 0.5 mm day- ~ (Kelliher et al., 1992). These features, particularly the vertical complexity of the canopy and the significance of forest floor evaporation, made this data set ideal for our SiB model test. We briefly describe SiB in the following section, concentrating on model parameter estimation and data requirements for our test. The test begins with a comparison of modelled above-canopy (total) sensible and latent heat fluxes with eddy covariance measurements made by Kelliher et al. (1992). Modelled forest floor evaporation rates are then compared with the lysimeter measurements of Kelliher et al. We next consider tree canopy evaporation. Direct measurements are not possible, but two alternative approaches are examined. The first is a 'top-down' method based on the difference between total and forest floor evaporation measurements. The second is a 'bottom-up' method summing tree sap flow measurements made in a small representative plot by KSstner et al. (1992). Different scales of measurement are needed to obtain stand-level integration for testing of a model. Along with the comparisons listed here we discuss the resistances involved in calculating the fluxes and refer to other estimates of

287

K. S c h e l d e e t al. / A g r i c u l t u r a l a n d F o r e s t M e t e o r o l o g y 8 4 ( 1 9 9 7 ) 2 8 5 - 2 9 5

the same resistances. Finally, we examine the sensitivity of SiB to parameter adjustment,

into sensible ( H ) and latent heat ( A E ) goes to heat storage, according to the energy balance equation: OT~,g 0t = n00, -

2. The SiB model

-,

ecg

(i)

where C is heat capacity, T is surface temperature, and c and g are for canopy and ground, respectively. The calculation of H and AE uses eddy diffusion formulae with electrical analogues indicating the ratios of temperature and vapour pressure gradients to aerodynamic and surface resistances in Fig. 1. The model thus includes simplifying assumptions regarding within canopy turbulent transfer. Calculations begin with definition of initial plant canopy (T~) and ground surface (Tg) temperatures, and Rnc and Rng° The various resistances are estimated, as will be described below, and an 'implicit backward method'

SiB is a one-dimensional energy, heat and mass transfer model with two canopy layers and three soil layers• In our test, as no separate ground cover is present at Maruia, model calculations involve only one canopy layer. Accordingly, the effective model structure is as shown in Fig. 1. The three soil layers are a 'near-surface' 0•02 m deep layer of organic forest floor, a 0•58 m layer of rooted (sandy loam) soil, and a 1 m layer of freely drained sandy loam soil• The net all-wave radiation (R n) not dissipated

ATMOSPHERE

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Fig. 1. Electrical analogues for the vertical transfer of latent and sensible heat fluxes ( A E and H , respectively) used in the Simple Biosphere (SiB) model (figure after Xue et al. (1991)). Other symbols are defined in the text.

288

K. ScheMe et al. /Agricultural and Forest Meteorology 84 (1997) 285-295

is used with the energy balance and eddy diffusion equations to update T~ and Tg to calculate H and AE (Sellers et al., 1986). Working from the above-canopy reference height (zr) downwards (Fig. 1), we define three aerodynamic resistances; namely, r a is the eddy diffusive resistance above the plant canopy, r b is the 'bulk' boundary-layer resistance of leaves in the plant canopy for the transfer of sensible heat and water vapour located at a height representative of the centre of transfer 'action' (ha), and r d is the eddy diffusive resistance between the ground and the plant canopy. Above the canopy, the wind profile is assumed to be log-linear above a transition height (Zm) (Garratt, 1978). At the top of the canopy, at height z2, the momentum transfer coefficient ( K m) is proportional to an extrapolation of the log-linear wind profile and K m varies linearly between z2 and za. Within the canopy, g m is directly proportional to wind speed, whereas in the tree trunk space, a l o g linear wind profile is again assumed. Eqs. (23)-(28b) of Sellers et al. (1986) describe details of the calculation of K m, which follows commonly used micrometeorological theory (Monteith and Unsworth, 1990). The wind profile is defined with boundary conditions at the top and base of the canopy (continuity of shear stress and wind speed), and assuming a triangular leaf area density distribution with height (Sellers et al., 1989). The Nothofagus tree canopy foliage was located between the heights of 8 and 30 m. Integrating the inverse of g m between heights h a and Zr (Fig. 1) gives r a and between the ground roughness length and h a gives r d. A bulk boundary-layer resistance for the canopy assumes that the boundary-layer resistances of individual leaves act in parallel. From the general experimental form of relationship between boundary-layer resistance and local wind speed (u) found for individual leaves (Monteith and Unsworth, 1990), r b is written

1 rb

fz2Ld nIl2 = Jz, - - d z

Ps Ct

U~/2

=

Ci

(2)

where L d is leaf area density, p~ is a shelter factor to account for mutual sheltering effects amongst leaves in the canopy, and c t is a leaf sensible heat and water vapour transfer coefficient (for individual leaf

i, c t = rbiLi u~/2 where L i is leaf area), c i is a constant obtained by integrating between the two heights assuming neutral atmospheric conditions, and u 2 is wind speed at height z2. We next discuss the two diffusion resistances that represent the canopy and ground surface layers. Based on Jarvis (1976), the SiB stomatal resistance (r s) of individual leaves in the canopy is determined from a multiplicative-constraint function (Sellers et al., 1986). According to Massman and Kaufmann (1991), and our earlier modelling experience for emergent trees in the Nothofagus forest (Schulze et al., 1995), the influence of temperature stress may be regarded as negligible. We also recognise that soil water content did not limit tree transpiration during our model test period (Kelliher et al., 1992). Accordingly, the stomatal resistance function takes the form r~ =

[a

]

- + c f(D) - 1 b+ Q

=

rsminf( Q )

1f ( D )

-

1

(3) where Q is photosynthetically active irradiance and D is air saturation deficit determined from air ternperature and vapour pressure. Functions f (between zero and unity) account for the constraint on rs~in imposed by Q and D. Stomatal light function parameters a, b and c (c equalling lrsmin) are given in Table 1 and f(D) is equal to (1 - h D D ) with h D being a plant species dependent coefficient. With analogy to Eq. (2), the bulk canopy resistance is calculated by integration of Eq. (3) involving a leaf angle distribution function and assuming that the stomatal resistances of individual leaves in the canopy act in parallel. The ground or forest floor diffusive resistance (rg) was calculated from an empirical expression, obtained from a fit to the soil evaporation data of Camillo and Gumey (1986). It is written rg = ~(1 W +) where ~ and ~b are constants and W is the weighted relative wetness (water content divided by water content at saturation)of the two upper soil layers. The above resistance equations include some of the required model parameters (see Table 1 for a complete list). Others such as leaf size (30 mm × 20mm) for the calculation of r b came from Kelliher et al, (1992), K~istner et al. (1992), and other refer-

K. ScheMe et al. /Agricultural and Forest Meteorology 84 (1997) 285-295

289

Table 1 Parameters and values used in the Maruia temperate broad-leaved forest test of the Simple Biosphere (SiB) model Parameter

Symbol

Value

Reference height Height of canopy base, top Height of maximum leaf alea density Ground roughness length Leaf area index Canopy cover fraction Leaf length, leaf width Leaf angle distribution factor Live leaf reflectance (VIS, NIR) Live leaf transmittance (VIS, NIR) Soil reflectance (VIS, NIR) Stomatal light parameters Air saturation deficit parameter Rooting depth Thickness of soil layers Soil potential parameter Soil potential at saturation Soil porosity Saturated hydraulic conductivity Soil resistance constants

Zr (m) z=, z2 (m) zc (m) zs (m) Lt Vc zien, Zwid (m)

36 8, 30 24 0.05 7 0.90 0.03, 0.02 0.1 0.10, 0.45 0.05, 0.25 0.11, 0.23 9000, 6, 250 0.35 0.6 0.02, 0.58, 1.0 5 - 0.4 0.47 1.0E - 5 101840, 0.0027

XL a t$ as a, b, c h o (kPa- J ) Zd (m) d i , d 2 , d 3 (m) B ~bs (m) 0s K s (m s - i ) ~, ~b

ences. The value of the air saturation deficit stress parameter ( h D ) w a s estimated to be 0.35 k P a - l from the leaf conductance measurements performed at the top and bottom of the canopy (Fig. 8(A) of KiSstner et al. (1992)). Leaf optical properties, leaf angle orientation and the ,~tomatal radiation response parameters were based ,an the Quercus alba L. study of Dorman and Sellers (1989). Some parameters, including forest floor water content in the 'nearsurface' layer, were estimated from unpublished data (F.M. Kelliher, 1992). Some parameters could only be approximated. An example is the height of maximum leaf area densi~Ly, set to 80% of tree height or 24m. Finally, although SiB is a 24h model, we report only daylight results in this paper because the measurements showed that Nothofagus stomata are virtually closed during darkness, and air saturation deficit and forest floor evaporation rate were found to be minimal at night.

R , being an input variable to the model (Fig. 2). Components J and G were adequately simulated by the model (Fig. 2); however, 'measured' canopy

~Rn-G-J(SiB) ..... G (SiB)

--a--R.-G-J(ObS) ....o-~ G (obs)

--J(SiB)

-e--J(obs)

700 600

3so 3o0

~. 500 'E 400 ~ -? a00~ ~, 200 ~ 100 0: -loo

250

~. 1so -~ 100 so 0 ,

8

3. The SiB model test and sensitivity analysis

Measured and modelled diurnal courses of the a v a i l a b l e e n e r g y ( R n - J - G) were virtually identical over the 6 days, reflecting the major constituent

A

2o0

,

~

10

,

,

12

,

,

14

t

,

16

~

t

-so

18

Time of day

Fig. 2. Observed ( A ) and modelled (bold black line) available energy (R n - G - J ) on 13 March 1991. Also included in the figure are the observed and modelled soil heat flux (G; grey) and canopy energy storage rate ( J ; black) on 13 March 1991.

K. Scheldeet al./ AgriculturalandForestMeteorology84 (1997)285-295

290

energy storage exceeded modelled J. In the tall

Nothofagus forest, m a x i m u m and minimum estimates of J were ___60Wm -2 about sunrise and sunset, respectively. At these times, ( J + G ) was similar in magnitude but opposite in sign to R . so that there was little available energy. Generally though, ( J + G ) accounted for about 10% of the available energy (Kelliher et al., 1992). For three representative days, including the partly cloudy 13 March, measured and modelled diurnal courses of sensible heat flux were generally in agreement (Fig. 3). There was a proportional relationship between H and ( R n - J - G ) reflecting the underlying energy balance. However, modelled H significantly exceeded the measurements during intermittently cloudy periods on 13 March when the energy balance closure assumed in SiB did not hold equally well for the measured energy balance (observed ( R n - J - G ) exceeded observed ( H + A E ) by approximately 1 0 0 W m -2 on 13 March (Kelliher et al., 1992)). In Table 2, the total daily fluxes of modelled and observed sensible heat and evaporation are given, Also included in Table 2 are the computed bias and root mean square differences (RMSD) between modelled (subscript SiB) and observed (subscript obs) fluxes on all 6 days. Bias and R M S D are defined as follows: N [F(i)sis _ F(i)obs] bias = ~ N (4) i= l

RMSD=(~[F(i)siB-F(i)obs]2}l/2 i=l ~t*

(5)

where F is flux and N is the number of observations per day. Table 2 shows that bias on H is about + 30 W m - 2, with the model predictions being larger than measured values on most days except for 15 March, and that R M S D values for H are 4 4 9 3 W m -2. These figures indicate reasonable agreement between modelled and measured H in reference to midday sensible heat fluxes of 4 0 0 W m -2 and in view of the closure of the observed energy balance as discussed in the Introduction. On average, just over 50% of the available energy of the forest was dissipated as sensible heat, giving a daily average Bowen ratio ( H / A E ) of about unity. Kelliher et al. (1992) noted that much lower Bowen ratios in the range 0 . 3 - 0 . 8 were usually found above dry canopies in North American, European and tropical broad-leaved forests. They concluded that the much smaller leaves of Nothofagus have relatively smaller leaf boundary-layer resistances and more efficient sensible heat transfer per unit available energy. Typical SiB model values of r b were 3 5 s m - 1 (Fig. 4), somewhat lower than the nominal value of 17 s m - l approximated by KiSstner et al. (1992). In any case, this brief discussion indicates a need to have an understanding of the involved transfer processes, and for the inclusion o f input parameters such as leaf size and r b i f a model of H is to be successful. Unfortunately, it probably does not bode well for the employment of general physiognomic characteristics of vegetation (i.e. use of a modal broad-leaved forest) in global simulation exercises with a GCM.

Table 2 Dally totals of modelled (subscript SiB) and observed (subscript obs) heat fluxes and computed bias and root mean square differences (RMSD) during 12-17 March 1991 at Maruia; H is sensible heat and AE is latent heat 12 March 07:00-19:30 h

13 March 07z00-19:00h

14 March 07:00-19:30h

15 March 12:30-19:30h

16 March 10:30-19:30h

17 March 07:30-19:30h

//siB (MJm-2 day- i) /'/obs (MJm-2 day- l ) Bias[/./] (Win- 2) RMSD[H ] (Wm -2 )

9.4 8.4 20 56

7.5 6.0 35 60

5.6 3.6 42 93

5.2 5.7 - 17 44

6.8 5.2 47 83

9.8 8.8 24 58

AEsiB (MJm -2 day - j )

5.6 6.0 .... 7 44

5.2 5.0 7 27

5.2 4.9 6 86

3.9 5.0 -40 61

4.5 4.1 12 40

6.1 5.6 12 63

Ages (MJ m-:2 day "l ) Bias[ AE] (Wm -2 ) RMSD[ AE] (Wm -2 )

K. Schelde et al. /Agricultural and Forest Meteorology 84 (1997) 285-295 --4--H(obs) -o--~E(obs)

H (sia)

XE(SiB)

- -

500.

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.

-

A " ~

x

March 12 .rc.12 ~

zoo 200 ~: 100 o~

. . . . . . . . .

-100 /

~

~,

March13 400. a00. ~ 200. j loo 0. . . . . . . . . . . -100 500 -

March17

4 0 0 ~ , , a00. 200.

~: 10o. 0 :

/8

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,, ,, ,, ,, ,, : ~ ~ : 10 12 14 16 18

291

we know that forest evaporation was dominated by tree transpiration, reflecting a combination of tree Canopy stomatal behaviour and the influence of air saturation deficit (D) as will be discussed below. The principal evaporation driving forces (R n - J G) and D are obviously related because solar radiation warms the air via sensible heat flux, but their time variation and influence did not coincide in our forest. Although total forest evaporation was well simulated by the model, daily ground or forest floor evaporation r a t e (Eg) was significantly underestimated compared with the lysimeter measurements (see Fig. 5, below). The SiB model of Eg is written as the ratio of D at the ground s u r f a c e (Dg) to the sum of rg and r d. The model underestimation o f Eg suggests an overestimation of rg and/or r d. During the test period, soil water was readily available and modelled rg was about 160sm -1, whereas r d was 1000-1500sm -[ (Fig. 4). Consequently, modelled Eg was controlled by the high magnitude of r d. A synopsis of data from the literature suggests that r d was relatively large at Maruia. Approximate calculations similar to those in SiB gave r d -" 40 s m- ~ in a Douglas-fir forest having a comparable tree leaf area index of six (Kelliher et al., 1986). Virtually identical values of r d were calculated beneath a shortgrass prairie canopy by Massman (1992). Near the ground in a sparse stand of cotton, r d was 30-264 s m- 1 according to Ham and Heilman (1991). The reason for the high r d must be sought in the wind profile assumed within the canopy. As pointed

"lqme of day

Fig. 3. Observed (lines with symbols) and modelled (plain lines) half-hourly averages of total forest sensible ( H ) and latent heat ( A E ) flux densities on three representative late-summer days at Maruia: 12, 13 and 17 M a r c h 1991.

Measured and modelled diurnal courses of forest evaporation were also in good agreement (Fig. 3 and Table 2). In particular, SiB reproduced the broad daily plateau of maximum ~tE that occurred from mid-morning until late afternoon. The variable radiation regime on 13 March (Fig. 2) did not correspond to similar changes in ~tE. During the day, AE was n o t simply proportional to the available energy, Drawing upon earlier analyses of the measurements,

30 ~ I~ I

--re

~

rb

~

rd

__ 25 ~ ¢ ~ 1 . ~

- ~ - 3000 [I

/ T 2500

,~ ~ 1 - ~ o a lO

_.+ 500 12 Time of

14

16

18

o

day

Fig. 4. Diurnal course of aerodynamic resistances (r e, r b and r d) on 13 March 1991. High resistances in the morning and in the evening are due to very low wind speeds.

292

K. ScheMe et al. // Agricultural and Forest Meteorology 84 (1997) 285-295

out by several modellers including Sellers et al. (1986), the ' K theory' may often fail within canopies, It is unknown whether a higher-order closure approach would allow a better representation of the wind profile in this case. However, when considering the gradient approach used in SiB, it involves 'adjustment coefficients' that are difficult to assess. One coefficient is introduced in the assumption that K m at height z2 is a multiple of the estimate obtained from extrapolating the log-linear K m profile above z2. The multiplication factor (G1 in Sellers et al., 1986, Sellers et al., 1989) is suggested to be in the range from 1.0 to 2.0 (Garratt, 1978; Raupach and Thom, 1981), and Massman (1987) estimated a value of G1 = 1.5 based on observed wind profiles within different canopies. Sellers et al. (1989) found G1 = 1.449 from a fit to results of Shaw and Pereira (1982) and this value was used in our SiB simulations. However, increasing G1 to 1.6 had a significant impact on the calculated within-canopy wind profile and related aerodynamic resistances, particularly on r d. Increasing G1 caused r d to drop by 40% compared with reference calculations and resulted in a better overall agreement between modelled and measured Eg during the 6days of our test (Fig. 5). There was no statistically significant variation in measured volumetric water content of the top 0.02 m

1.5

~ 1 E 0.s

0

12

13

14

15

16

17

Date Fig. 5. Observed (filled bar) and originally modelled (open bar) forest floor ('ground')evaporation rates ( E g ) o n six late-summer days (12-17 March 1991) at Maruia. Adjusted model calculations (grey bar) incorporate an adjustment of wind profile factor G1 (see text) resulting in a 40% reduction in the eddy diffusive resistance between the forest floor and the tree canopy (r d in Fig. 1). This modification was based on comparison of original r d values with those in the literature so as to change a tendency of the model to overestimatemeasured Eg.

layer of forest floor during the 6day model test period (mean 0.27 m 3 m - 3, standard deviation 0.08; F.M. Kelliher, unpublished data, 1992). This was reflected in SiB by calculation of an essentially constant rg = 160 s m - ~ despite up to 0.4 mm d a y - 1 of modelled forest floor evaporation. This meant that modelled Eg was limited by a dry forest floor 'near-surface' layer whose thickness was estimated to be equal to 2 mm following Kelliher et al. (1986). In their forest floor study, Kelliher et al. determined rg by selecting a value that resulted in agreement between hourly lysimeter measurements of evaporation and calculations using the Penman-Monteith equation with accompanying micro-meteorological measurements. In their study, rg ranged from 700 to 3800sm -1 and the largest values corresponded to the entire 0.03m depth of forest floor being dry. By contrast, the forest floor was 0.10m deep and wetter at Maruia. Reflecting the available data, our SiB model estimates of rg were based on analysis of evaporation from agricultural soil. Modelling efforts would benefit from further studies of forest floor evaporation processes. From the preceding discussion of total and ground evaporation rates ( E and Eg), it is obvious that modelled tree canopy transpiration rates agreed with the 'top-down' approach measurements expressed as E - Eg (results not shown). We will now compare with the 'bottom-up' approach of summing sap flow measurements for 14 trees in a representative 337 m 2 forest plot. Although diurnal variations in modelled and measured tree canopy transpiration rates were similar, modelled values were consistently greater by 25-45% on a daily total basis (Fig. 6). Comparison of sap flow estimates with ( E - Eg) gave similar results (Kelliher et al., 1992). On 12 and 13 March, sap fluxes became positive about 1 h later than modelled tree canopy transpiration rate. This may partly reflect the use of stored water for transpiration by the Nothofagus trees, estimated as being equivalent to 30 rain of evaporation by KiSstner et al. (1992). The bulk canopy resistance (r c) was a dominant variable in t h e SiB calculation of tree transpiration rate. Transpiration r a t e s w e r e thus highest when r c was minimal (re = rcmin) although a complete calculation also includes D as indicated above. The modelled r c (Fig. 7) reached its minimum between 09:00 and 11:00 h followed by an increase during the after-

K. ScheMe et al. / Agricultural and Forest Meteorology 84 (1997) 285-295

25o

March 12

200

ls0 ~ i10o 50 o 250

e ,~,,~--~~

March 13

200

~

150

100

50 o. 25o March17 200 ~ lS0 ~

/

i

_

_

~

i loo 5o o

,

8

10

12

I 14

I

~ 16

I

I 18

~me of day Fig. 6. Observed ( O and line) and modelled (plain line) half-hourly averages of tree canopy uanspiration rate on three representative

293

mum rtot were thus l l 0 - 1 4 0 s m -1. An analogous calculation was done by Ki~stner et al. (1992), whereby rto t was estimated from the ratio of tree sap flow and above-canopy air saturation deficit (D) measurements. Strictly, employment of D in this calculation is probably best restricted to the emergent trees as significant differences between abovecanopy and ground level air saturation deficit were measured (Kelliher et al., 1992). In any case, K~Sstner et al. (1992) obtained a range of minimum rtot values from 100 to 250sm -~ depending on the canopy position of the tree, with the lowest values from emergent trees and highest from subcanopy trees. We conclude that there was reasonable agreement between these two calculations of minimum rtot in view of their approximate nature. Considering the daily course of modelled r c in comparison with the canopy resistance estimated by Ktistner et al. (1992) on the basis of sap flow densities, there is good agreement. Both display their minimum resistance in the morning between 09:00 and ll:00h; however, calculated r c exhibits a more or less constant value in the late afternoon rather than a marked decrease as does our modelled re (Fig. 7). The SiB estimate of remin is based principally on the interception of radiation by the tree canopy. By definition, retain is restricted to periods of plentiful soil water, high relative humidity and moderate ternperature (i.e. m i n i m a l stress). The m o d e l l e r m a y thus

ask (Kelliher et al., 1995): What degree of retain variability exists amongst vegetation types, and, in

late-summer days at Maruia: 12, 13 and 17 March 1991. The measurements were made by a 'bottom-up' scaling method summing sap flow rates of 14 trees in a 337m 2 representative forest plot. 300. 250.:

n o o n o w i n g to air saturation deficit ( D ) stress. Between 17:00 and 19:00h, r c generally declined as

.~ 200. = 15o. 'E

less D stress was imposed during the hours before sunset. Modelled rcmi, was 100-130sm-1; this was two orders of magnitude larger than modelled r b and

'~ 10o

r a,whichweretypic=dlyonlyabout5sm-I (Fig. 4). A total transpiration resistance ( r t o t ) Can be calculated as (re + r b + ra), recognising that an electrical

analogue of the SiB model has the three resistances placed in series (Fig:. 1). Modelled values of mini-

50 0

- - M a r c h 12 ~ M a r c h 13 --x~-March 17

~ 8

,

L 10

~

m ~

~

12

14

~

= 16

i

i 18

Timeofday Fig. 7. Diurnal course of canopy resistance re on three representative late-summer days at Maruia: 12, 13 and 17 March 1991.

294

K. Schelde et al. /Agricultural and Forest Meteorology 84 (1997) 285-295

the absence of information for some global vegetation, is it possible to estimate rcmin within limits of definable and useful accuracy? In a recent review of minimum 'total surface' (including plant canopy and soil evaporation) resistance (rsmin), Kelliher et al. (1995) concluded that rsmin is surprisingly consistent (averages were 51sin -1, 5 9 s m -1, and 3 1 s m - l plus or minus about 30% coefficients of variation for woody, natural herbaceous and agricultural species, respectively). The relationship between rsmin and plant canopy leaf area index is conservative because of the compensating decrease in plant canopy evaporation and increase in soil evaporation as leaf area index diminishes. A comparison of rcmin and rSmin is confounded by soil evaporation, and rsmin = 3 4 s m - l at Maruia based on eddy correlation and micrometeorological measurements (Hollinger et al., 1994). According to another recent review based on combining information across broad vegetation types, 76% of the variation in rSmin could be explained by linear regression with leaf nitrogen concentration (Schulze et al., 1994). Based on this regression and the vegetation distribution, global estimates of rsmin were made on a 1° × 1° grid scale. From the SiB model test, it is evident that the accuracy of modelled forest evaporation rate is most sensitive to the estimation of re. Tree canopy transpiration rate was dominant during the rain-free test, and r a and r b were small for the tall forest of small-leaved trees with a closed canopy. From Eq. (3), the model of r~ depended only on Q and D at the well-watered site. Increasing stomatal light response factor a by 30% led to a constant diurnal decrease in tree canopy transpiration rate equivalent to 10% on a daily total basis, and a 30% decrease on the same factor led to an increase in total daily canopy transpiration of 14%. Similar sensitivities were found for parameters b and c. However, there was a more proportional effect from adjustment of the D function parameter h D in agreement with the emergent tree r~ modelling exercise of Schulze et al. (1995). A 30% increase in h D led to anomalously low afternoon tree canopy transpiration rates and an 11-34% decline in daily totals. Finally, as already pointed out, soil evaporation was sensitive to the below-canopy aerodynamic resistance r d. Fig. 5 shows how a 40% reduction of r d resulted in a 20% increase in soil evaporation,

4. Conclusions The Simple Biosphere (SiB) model provided estimates of sensible and latent heat fluxes in a broadleaved forest that are in good agreement with measurements during 6days of variable weather conditions. The average bias on H and A E was 3 0 W m -2 and 1 4 W m -1, respectively, and root mean square differences ranged between 44 and 9 3 W m -2 f o r / / and between 27 and 8 6 W m -2 for AE. Biases were 5 - 8 % and RMSDs were 10-34% of typical midday heat fluxes of 400 W m-2 (sensible heat) and 2 5 0 W m -2 (latent heat). These errors seem reasonable with respect to the observed energy balance closure. The model showed a tendency to overestimate the below-canopy eddy diffusive resistance r d, causing modelled soil evaporation to be up to 50% lower than lysimeter measurements. However, evaporation in the Nothofagus stand was dominated by tree canopy transpiration. Modelled transpiration was governed by the canopy resistance, which was regulated by canopy radiation interception and the air saturation deficit at the well-watered site. The canopy was complex, with a large fraction of transpiration originating from a few dominant trees; however, a simplification of canopy structure was necessary for the model application. Still, during the test period of six dry late-summer days SiB was able to provide an adequate representation of the diurnal variation of available energy partitioning in the forest.

Acknowledgements

We wish to thank P.J. Sellers, who generously allowed us to use his version of the SiB model. Professor Dr. E.-D. Schulze and Dr. B.M.M. KiSstner kindly gave us access to their Maruia sap flow data. Superb technical assistance at Maruia was provided by J.N. Byers, J.E. Hunt, T.M. MeSeveny, R. Meserth and P.L. Weir. F.M. Kelliher is grateful to the New Zealand Foundation for Research, Science and Technology for their continued support of international atmospheric research.

K. Schelde et al. / Agricultural and Forest Meteorology 84 (1997) 285-295

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