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Produced by the NASA Center for Aerospace Information (CASI)
W

Unc la s

G3/43 19931

Department of Meteorology

College of Earth and Mineral Sciences

The Pennsylvania State University

University Park, PA 16802

( NASA -CH-175606) [A 827HCL ECF BSTI N ITING

SCIL H OISTURb AVAILABILITY) Semiannual

Report (Pennsylvania State Univ.) 15 p

dC A02/X1 !:1 CSCL 081M

A Semi-Annual Report

to the

National Aeronautics and Space Administration

for Grant Number

NAG 5-184

rrn n <

V_

Cc

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22 March 1985

i
Abstract

The PI has developed a method for estimating values of soil moisture

based on measurements of infrared surface temperature. A central element in

the method of producing the soil moisture values is a boundary layer model.

Although it has been shown that soil moistures determined by this method using

satellite measurements do correspond in a coarse fashion to the antecedent

precipitation, the accuracy and exact physical interpretation (with regard to

ground water amounts) are not well-known. This area of ignorance, which

currently impedes the practical application of the method to problems in

hydrology, meteorology and agriculture, is largely due to the absence of

corresponding surface measurements.

Preliminary field measurements made over France have led to the development of a promising vegetation formulation by the French (Taconet et al., 

1985), which has been incorporated in the model of the PI. It is necessary,

however, to test the vegetation component, and indeed the entir-t method, over

a wide variety of surface conditions and crop canopies.

Ste. ji ;l
1. Background

The relationship found between moisture availability derived from

satellite measurements and the precipitation for regions over the middle west,

(described in previous reports and in articles by Carlson (1984),

Carlson et al. (1984), Flores and Carlson (1985)), has been an encouraging 

result, in view of the relatively large pixel size and imprecision of the GOES

temperature measurements. Nevertheless, the question persists: what are we

really measuring with the satellite thermal channel? In the past year we have

had the opportunity for the first time of addressing this question by using

AVHRR thermal infrared temperature measurements in conjunction with ground

measurements of soil moisture and surface energy fluxes. These ground 

measurements were made during three field experiments over France. The first

two were made during July and September 1983 over a region called the Beauce.

The third and most elaborate experiment was carried out wring September 1984

over a region of the southwest of France as part of a project called

..meso-gers," named after the region of Gers in which the field program was

conducted. The PI is currently taking a sabbatical from Penn State in France

where he is working with various French scientists on the development of the

infrared method for remote sensing of soil moisture using <'ata gathered during

these field experiments.

2. Summary of Investigation in Progress

The 1983 French field program consisted of a principal measurement site

at Voves in the Beauce and a secondary site about 20 km away at Montigny. The

Beauce is one of the primary agricultural regions in Fran--e. In the :..ea of

e^.r,
Voves, the principal crop is wheat, although there is also some corn.

Measurements were made by means of a sodar from which one can obtain the

surface heat fluxes appropriate to horizontal scales of about 1 km

(Weill et al., 1980). Surface heat fluxes were also determined from wind and

temperature measurements made by means of instruments mounted on a frame at

two levels near the ground (Itier, 1980).

In a review article Carlson (1984) stated that a possible serious

weakness of existing ground-atmosphere models is the inadequate treatment of

vegetation. Deardorff (1978) proposed a model for a vegetative canopy which

has been used in various forms. Deardorff's model, however, is rather

cumbersome to apply because it contains a complex structure based on a

large number of empirical parameters drawn from different studies over

different types of crop cultures. In practice, many of these parameters are

difficult to determine, and those given by Deardorff rest largely untested.

NevEtheless, the Deardorff formalism opened a highly fruitful approach to the

problem of modeling vegetation.

While at the University of California at Davis, R. Bernard o: the

CNET/CRPE in France (private communication) developed a simplified version of

the Deardorff model based on more current measurements made at Davis. Tests 

with the revised vegetation component combined with a one-dimensional

atmosphere-substrate model based on one of Ther-y and LaCarrere (1983) have

proven encouraging in light of the measurements made over the Beauce in 1983.

In particular, Taconet et al. (1985; also private communication) were able to

demonstrate that their model is capable of simulating the evolution of the
daily heat flux profile measured over the Beauce during a 5-day period in

July. Our adaptation of the vegetation model of Bernard in the CM has

produced almost identical results.

The heat flux measurements for the three of the five days during the

period 11-15 July 1983, are shown in Figs. 1-3. The remarkable aspect of

these measurements is a rather dramatic increase in the surface sensible heat

flux between the 11th and the 15th. In these figures we also present the

distriblrtion of surface sensible heat fluxes obtained with the versi .-i of the

CM without vegetatioa parameterization. All the model simulations 1 7.dke use of

one afternoon (- 1400 (AIT) NCAA- • 7 infrared satellite temperature cirrected for

attenuation by atmospheric water vapor and carbon dioxide.

Although one is tempted to dispute the rapid increase in the measured

heat flux values between the 11th and the 15th, it is difficult to deny the

consistency of the ground measurements with respect to time and the similarity

between the sodar and tower heat flux measurements. Independent ground water

measurements made in the general area show a steady decrease with time in the

water conterit of the soil until mi.d-July, after which the soil water content

remained at a very low level until harvest. This decrease in soil water

occurred durir; both 1982 and 1983 and is probably a normal consequence of the

fact that evaporation exceeds precipitation and runoff during the growing

season. According to the model, there was a decrease in the value of w (the

volumetric water content) (from 0.20 to 0.14 to 0.09) between the llth and

15th of July (Figs. 1-3).

Although the phenological reasons for this rapid drying are not clear,

one can in terms of the model equations explain the striking increase with
time between the 11th and the 15th (shown in Figs. 1-3) of the sensible heat

fluxes. The coefficient of transfer for latent heat flux (LE) from the

foliage (cv) is given in the following expression:

LE - cv (g s (T f ) - qaf) (1)

where gs(Tf) is the specific humidity at saturation at the temperature of the

foliage (T f ) and q a f is an interfoliage (airspace) specific humidity. Now

Taconet et al. (1985) let

cv ° c fh %(1 + cfli ' RST) (2)

where cfh is the transfer coefficient for sensible heat between the foliage

and the interfoliage air spaces. Thus, for ve g etation RST represents a

resistance and takes the place of the moisture availability parameter. RST

appears explicitly in the foliage equation, instead of the moisture

availability (M), which totally governs the surface mositure resistance in the

non-vegetated version of the model. The resistance RST is the key to the

greater response of the surface sensible heat flux in the case of the

vegetation component. Taconet et al. define RST as

RST - RO( 1

 + S ( 0.9w? + O.lwg ) LAI

800 +

1.2w0

2 YS (3)

Here S is the downward global solar radiation (expressed in w m -2 ), wo is a

reference value of soil moisture (loosely equated ro that at the wilting point
for the vegetation) and w and w2 are the shallow-soil (10 cm) and deep-soil

volumetric water contents (Deardorff, 1978). PS is a shelter factor which is

related to the leaf area ind, c (LAI). RO is a seasonal stomatal factor which

appears, according to measurements made by Perrier et al. (1980), to remain

relatively constant with time over the growing season (except for a stepwise

incre, ;e to a new plateau in June). RO is evidently related to the phenology

of the crop and probably to the long-term water stress on the plant3. The

moisture availability (M) is defined explicitly only with respect to the

evaporation from the ground surface underneath the plant canopy by the

w

definition M = . wmax being the value of w for a saturated soil (here

max

taken as 0.35); the initial value of w is set equal to w2. The value of

RST effectively limits the plant evaporation (which dominates that from the

ground in situations of dense vegetation, even in situations of ground water

saturation. This restriction on p lant eva p oration even where M = 1.0

constitutes the most im p ortant difference between the old and new version of

the CM . I 

The heat fluxes calculated with the non-vegetation version of the CM also

show a modest increase during the four-day period, from a maximum of about

95 w m-2 on the 11th to about 140 w m_ 2 on the 15th, corresponding to a

decrease in the volumetric soil moisture content (w g ) from 0.15 to 0.09

(Figs. 1-3). This increase in the surface heat flux even with the non- 

vegetation version is a consequence of tha fact that the measured surface

temperatures from the satellite increased during the period (with respect to

the model initial temperatures as given by the radiosonde data). The

I Somewhat better agreement between model and measurement; can be achieved by

an adjustment of the transfer coefficient for heat in accordance with values

recommended by T3conet, et al., 1985.
vegetation model, however, increased the sensitivity of the surface heat

fluxes and soil moisture to the measured increase in reductive surface

temperature.

At present we are performing detailed simulations with the new version of

the CM and comparing the output to that from the model of Taconet et al. The

results from the two models appear to be very similar. We anticipate making

tests with both models using the data obtained during the 1984 field

experiment. The 1984 (meso-gers) program was far more elaborate than those of

1983. Instead of two there was a network of six sodars located at the corners

of triangles of differing dimensions. At two of these sites local measurements of heat flux (made as over the Beauce, from instrumented towers) azd of

soil moisture and radiative surface temperature were made. On clear days,

there were flights by instrumented aircraft, including a helicopter capable

of making microwave (radar) measurements of soil moisture. Though heavily

cultivated, the region of Gers is much hillier than the Beauce and corn is the

dominant crop in the region of the experiment.

3. A Plan for the Future

The problem of using the infrared method for determining the surface

energy budget and the soil moisture divides into two areas of activity: model

and measurement. With regard to the latter, the success of the vegetation

model in capturing the increase with time of the surface sensible heat fluxes

rests with the ability of the satellite to discriminate small changes in

temperature over crop surfaces with an accuracy of no worse than about a

degree centigrade. Without going into a detailed discussion of measurement

errors, a:ready presented by Carlson (1984) 0 we would like to mention Char

without proper consideration of measurements, no model is usable. These
errors fell into three categories: that due to the satellite sensor, that due

to atmospheric attenuation, and that due to sampling of the surface. There is

also the uncertainty introduced by temperature, wind and humidity errors in

the initial radiosonde data used in the model.

Excluding the problem of measurement, there remain the nagging questions

of (1) are the results obtained form one set of case studies in any way

general, (2) how cart one obtain routinely and with any degree of confidence

the necessary model input parameters (the leaf area iidex, RO, w2 and other

"constantj" expressed in equation (3)), (3) how do the model output values

of wg or M relate to the real soil moisture at various depths below the

surface, (4) what form does the resistance equation take for completely

different types of surfaces (for example, forests), (5) how do the surface

fluxes meas7ired of different scales by different instruments correGpond to

those generated ty the model using satellite surface temperatures, and

(6) what practical importance is the infrared method in providing parameters

to meteorological, agricultural and hydrological interests?

In light of the imperatives posed by the questions in (2.1), a fruitful

approach must concern itself with (1) data acquisition and interpretation of

model reslts, (2) system and model development, and (3) interaction with

scientists aith allied interests and in adjacent disciplines.

4. Conclusion

The ISLF,CP and MOBILHY progratrs offer promise for obtaining bath

satellite and ground measurements over various types of terrain and vegetation. The stated goals of ISLSCP, those of developing algorythms and

exploiting satellite measurements, are in close accord with our objectives.
The first ISLSCP Field Experimeint (FIFE) is proposed for 1986/1987. Although

it is too early now to foresee the exact outcome of this field program, we

must assume that it will yield a considerable amount of useful information.

Accordingly, we feel a sense of commitment to its aims and therefore to

playing an active role in its execution.

^-^ r
References

Carlson, T.N., 1984: Regional-scale estimates of surface moisture

availability and thermal inertia using remote thermal measurements,

Remote Sensing Reviews, 2, 1-51.

Carlson, T.N., F.G. Robe and E.M. Perry, 1984: Regional-scale estimates of

surface moisture availability from GOES satellite. Agronomy Journal_, (in

press).

Deardorff, J.W., 1978: Efficient prediction of groui ► d surface temperature and

moisture with inclusion of a layer of vegetation, J. Geophys. Res., 83,

1889-1904.

Flores, A. and 'r.N. Carlson, 1985: Estimacion de Parametros Del

Suclocambinando un Modelo de Caps Limite Con Imagenes Digitales de GOES

(submited to Meteorologica).

Perrier, A., N. Katerjc, G. Gosse et B. Itier, 1980: Etude "In situ" de

1'evaporation reele dune culture de ble, Agricultural Meteorology, 21,

295-311.

Taconet, 0., R. Bernard, and D. Vidal Madjai, 1985: Evaporation over an

agricultural region using a surface flux/temperature model based on NOAAAVHRR data (to be published in J. of Climate and Applied Meteor.)

Therry, G. and P. LaCart^re, 1983: Improving the eddy kinetic energy model

for planetary boundary layer description, Boundary Layer Meteorology, 25,

63-88.
Figure Captions

Figure 1. Surface heat fluxes (w m -2 ) as a function of time (GMT;

approximately sun time) on 11 July 1983 obtained with the CM

with vegetation component (solid curve) and without vegetation

component (dashed curve). Measurements made locally of surface

heat flux are represented by the dotted curve. Heat fluxes made

from sodar measurements at Voves (crosses) and at Montigny

(triangles) are indicated. The model fluxes correspond to surface

temperatures measured over Montigny by the AVHRR o` NOAA-7 at

1346 GMT. In the title, the symbol w and m, respectively, correspond to values of the substrate volumetric water content

(wg in equation (3)) and the surface moisture availability (M).

Figure 2. Same as Fig. 1 but for 13 July 1983 corresponding to an AVHRR

surface temperature measured over Montigny at 1501 GMT. No sodar

data was taken at Montigny.

Figure 3. Same as Fig. 1 but for 15 July 1993 corresponding to a surface

temperature measured over Montigny; nu sodar data was taken.
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