Spatial integration of surface latent heat flux and evaporation mapping

Adv. SpaceRes. Vol. 9, No. 7, pp. (7)25%(7)264, 1989 Printed in Great Britain. All rights reserved.

0273-1177/89$0.00 +.50 Copyright© 1989COSPAR

SPATIAL I N T E G R A T I O N OF S U R F A C E L A T E N T H E A T FLUX AND E V A P O R A T I O N MAPPING J. P. L a g o u a r d e * a n d Y. B r u n e t * * *INRA, Bioclimatologie, BP 91, 84140 Montfavet, France **INRA, Bioclimatologie, 78850 Thiverval-Grignon, France

ABSTRACT Two different methods of computing regional evaporation from N O A A - - A V H R R data are compared on a 250 x 250 km area for a particular day of the H A P E X - M O B I L H Y experiment. In the first one, the daily evaporation is linearly related to the surface temperature at 14h 00 U T ; in the other one, a simple planetary boundary layer model is used. The obtained differences are discussed, and a few improvements proposed. 1. INTRODUCTION Much scientific work is currently being done to develop methods aimed at estimating the fluxes between the soil and the atmosphere from satellite remote sensed data. Important applications are the monitoring of water stresses for a~ronomical purposes, and the providing of realistic values of fluxes at-the scale of 100 x 100 km for climatological studies, or at the w a t e r - catchment scale in hydrology. For operational use, simplified algorithms requiring only few input data or parameters and consuming little computer time must be looked for. Such is the case of the simplified linear relationship : ETd - RNd = A - B (Ts - Ta) relating daily evaporation ET~ to daily net radiation RNd and the instantaneous difference between surface "Is and air Ta temperatures at 12h00 UT /6,11/. A second way of estimating the fluxes is to use a simplified model of the planetary boundary layer /3/. These two methods are first described and briefly discussed. An example of evapotranspiration mapping from N O A A - A V H R R data is then given on the S o u t h - W e s t of France within the general framework of the H A P E X - M O B I L H Y experiment /1/, allowing a comparison between the two algorithms. 2. T H E SIMPLIFIED RELATIONSHIP F O R ESTIMATING DAILY EVAPOTRANSPIRATION The simplified relationship previously mentioned was first established from experimental data. For a natural grassland, SEGUIN-et al. /11/ found A = 1.0 and B = 0.25 (ETn and RNd being converted in equivalent mm of evaporated water per day). SEGUIN and ITIER / 1 2 / then justified the relationship by means of a theoretical analysis and showed the coefficients A and B to be strongly dependent on the roughness length Zo of the canopy.

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J.P. Lagouarde and Y. Brunet

A systematic study of the sensitivity of A and B to zo has recently been done / 8 / using evaporation and surface temperature data simulated by a new agrometeorological model, MAGRET, (acronym for Modrle AGRomrtrorologique d Evaporation et de Temprrature) described in detail in /7/. But for operational purposes, as N O A A - A V H R R satellite data are acquired at about 14h00 UT, and since only maximum air temperature Ta max is currently available in the meteorological networks, the relationship studied was : ETd - RNd = A - B (Ts 1, - T . . . . ) Simulations were performed with actual meteorological data from 4 stations with contrasted soil and climatic conditions, and A and B were determined statistically for different assumed values of the roughness length (0.1 to 10 cm). The relationships were established both at the daily and the t e n - d a y scale (considering in this case for each term of the relationship its mean value on 10 days long periods) : the coefficients obtained are not significantly different, but the scatter is obviously larger and the precision less good at the dally scale, due to the fact that the wind speed is not explicitely introduced in the relation. A is found to be a constant (A = 0.5 ram/day) while the change of B with roughness is well described by a hyperbolic relationship : 0.185 log zo + 2.455 B

(B in mm/day*C, Zo in cm).

=

- 1.836 log z o + 10.0 The resulting relationships for estimating ETd are plotted together on figure 1. Because it is based on classical network meteorological data at 2 m, the algorithm cannot be applied to canopies taller than about 1 m (or roughness length greater than 15 ern). A possible adaptation to taller canopies, and even forests, could be searched for in a similar way by introducing air temperature at a higher level. 2 0 i

"~-2 LU -3

-5 -6 -2

0

2

~

6

8

tO 12 11, 15 16 20 22 24 rs/z - rama x (°C)

Figure 1 : Simplified algorithm of estimation of daily evaporation for various roughness lengths 3. T H E SIMPLE PLANETARY B O U N D A R Y - L A Y E R

MODEL

The model is based on the simple description of the d a y - t i m e planetary boundary layer !)roposed by TENNEKES and DRIEDONKS /13/. The PBL can be idealized, as shown in gure 2, for potential temperature 0 as well as specific humidity q and horizontal wind speed components U and V : the PBL is supposed to be well enough mixed for these variables to be height independant. At the top of it, they present a discontinuity and a constant gradient above in the stable free atmosphere. The PBL is forced at the bottom by P E N M A N MONTEITH type surface equations, integrated throughout the surface layer. Provided that initial conditions and input parameters such as the free atmosphere gradients can be inferred from radio-soundings, the {ntegration of the model gives the evolu~on of the variables and PBL height.

Surface Latent Heat Flux and EvaporationMapping

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Freeatmosphere/ /V= OO

E

'7---:"

h

Mixed layer I----. "s-~7~;;-\

layer

....

e2: Structure of the planetary boundary EKES and DRIEDONKS, 1981)

layer for potential

temperature

(after

For given surface parameters albedo a, emissivity E and roughness length Zo, the only unknown is the surface resistance rs. As it has been shown that a constant daily r, value allows to simulate correctly the behaviour of the surface and PBL variables and fluxes /-3/, the method consists in adjusting rs so that the model gives the same temperature at 14h00 as that measured by the satellite. Evaporation can then be computed throughout the day. The method has been validated against 3 data sets / 2 / obtained under contrasted conditions. An example of modelled and measured surface temperature and latent heat flux is shown in figure 3.

-", t3

z5

600 ~ ,

,tO

5O0 E

Q

"- 35

'i'5¢'.

30

400

_'!,'..'.

300 tu

25

200

20

I00

15 I0

if ,

6

~

#

!

i

.

i

i

4OO

10 12 I,~ 16 1 8 2 0 2 2

time

Figure 3 : Comparison between modelled (o) and measured (e) surface temperature (dotted lines) and evaporation (continuous lines). Bambey, Senegal, August 13, 1985 4. MAPPING OF DAILY ACTUAL EVAPORATION Both methods were used for the 27 June 1986 in South-West France (250 x 250 kin) taking advantage of the various measurement networks set for the HAPEXMOBILHY program (automatic evaporation SAMER* and meteorological PATAC** stations). The derived maps of evaporation are then compared.

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J.P. Lagouarde and Y. Brunet

4.1. Input data Surface temperature Ts is computed from N O A A - A V H R R radiative temperatures T4 and T5 in infrared bands 4 and 5, using a "split-window" method / 5 / to correct atmospheric effects, with a new set of coefficients : T, = 2.84 + 3.77 T4 - 2.77 T~ A map of dominant vegetation types made by PHULPIN et al. / 1 0 / is u s e d : the classification is based on the analysis of the seasonal evolution of N O A A - A V H R R derived normalized difference vegetation index (NDVI). An improvement is achieved for the cereal class by discriminating dominant wheat and dominant maize regions. Ten classes are finally established : they are listed on table 1 with the values of the relevant parameters we retained for our purposes (after /9/). These parameters depend on the stage o~ vegetation and would obviously be different at other dates. The case of ocean and b u i l t - u p areas is not analyzed here.

Surface

type

(dominant)

z

(cm)

B

A

£

O

Water B u i l t - u p areas Bare soils Wineyards, orchards Scrub Grassland Wheat Maize R e s i n o u s trees D e c i d u o u s trees

0.2 i0.0 i0.0 2.0 8.0 5.0 80.0 i00.0

0.17 0.50 0.50 0.30 0.46 0.39

0.25 0.20 0.20 0.20 0.20 0.20

0.94 0.95 0.96 0.98 0.95 0.95

-

0.12

0.98

-

0.15

0.97

Table 1 : Dominant vegetation types To be run, the simplified method also requires maps of daily net radiation RNn and maximum air temperature. The analysis of RNd measured on SAMER stations corresponding to very different types of crops and conditions (irrigated and non irrigated) shows variations less than _+ 0.5 mm/day. We therefore take here a constant RNo, equal to 5.4 mm/day. This is acceptable for a feasibility study but for practical purposes, RNd haapping is necessary : it could be done using remote sensed data /4/. Maximum air temperature isotherms have been manually drawn at M6t6orologie Nationale (Toulouse) ; this is facilitated by the large number of sta'tions (about 140) available in this experiment. A large variation in air temperature from 22* C to 32 C is observed when going west to East, due to the ocean influence. The isotherms were discretized and a rasterization was done at the N O A A - A V H R R resolution (1 km), using crossed linear interpolations. A radio-sounding and the hourly evolution of global radiation are required to run the PBL model.

: Station Automatique de Mesure de l'Evapotranspiration R6elle ** PATAC : Pr6visions Am61ior6es, Techniques d'Affinement de la Climatologie * SAMER

Surface Latent Heat Flux and Evaporation Mapping

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4.2. Data processing The vegetation map and rasterized air temperature are geometrically corrected to be exactly superimposed with N O A A - A V H R R derived T~ image. The simplified algorithm is applied to each pixel, finally producing a daily evaporation map. A unique radio-sounding recorded at the centre of the 250 x 250 km study area (Lubbon site) and the global radiation measured in Castelnau, South of the area, are used to run the model. For every vegetation class, simulations are performed with the input parameters given in table 1 ; by tuning the surface resistance as previously described, we then establish a direct eorrespondance between T~ at 14h00 and daily evaporation outputs. The set of charts thus derived is directly applied to the N O A A - A V H R R data to produce a ETd map. Evaporation is not computed over ocean and is set to zero over b u i l t - u p areas. At present evaporation of forest is estimated only with the PBL method. 4.3. Results Both methods yield the same regional patterns over the whole area, and the same classification of the evaporation per vegetation class (see table 2). ETo computed with the simplified method is on the average higher by 1 mm ; the differences depend on vegetation type and localization along a West-~-ast l i n e : the further from the sea, the higFier the difference (from about 0 to 2 mm). The main possible sources of difference can be listed as follows : - S i m p l i f i e d m e t h o d : RNd is kept constant over the whole a r e a ; the regression coefficients are windspeed independant ; the interpolated T~ leads to very small differences T, - T. (about 3 degrees) on the S o u t h - East corner of the image, where most maize and wheat fields are located. - PBL model : a unique radio-sounding recorded at the centre of the image is used, which may account for the observed W e s t - E a s t gradient ; albedo values are assumed ; the model is one dimensional and fairly sensitive to parameters such as the temperature gradient in the free atmosphere.

Simplified method R e s i n u o u s trees D e c i d u o u s trees Grassland Maize Wheat Wineyards, orchards

3.9 3.5 3.4 2.8

PBL m o d e l

3.5 2.7 3.1 2.6 2.5 2.4

Table 2 : Evaporation of the main vegetation classes in ram/day 5. CONCLUSION This feasibility study looks successful and gives reasonable estimates of regional evaporation. The possible errors previously listed should be reduced once some extra-information is used, such as an albedo map (METEOSAT), other radio-soundings (Bordeaux and Toulouse) and spatialization of RN~. This will be done in the future, with more attention ~iven to the H A P E X - M O B I L H Y square itself, where evaporation was measured on different sites.

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J.P. Lagouardeand Y. Brunet

References 1. J.C. Andre et al., Evaporation over land- surfaces : first results from HAPEX-MOBILHY special observing period. Accepted for publication in Annales Geogphysicae, vol. 6, n" 5 (1988) 2. Y. Brunet, J.P. Lagouarde, M. Nunez, Une nouvelle m6thode d'estimation de l'6vaporation r6gionale ~ partir de mesures de temp6ratures de surface dans l'infra-rouge thermique. ESA SP-287. p. 473-476 (1988) 3. Y. Brunet, M.R. Raupach, A purposes. To be published (1988)

surface model for large-scale

atmospheric modelling

4. G. Dedieu, P.Y. Desehamps and Y, Kerr, Satellite estimation of solar irradiance at the surface of the Earth and of surface albedo using a physical model applied to Meteosat data. J. Clim. Appl. Met., 26, n ° 1, 7 9 - 8 7 (1987) 5. P.Y. Desehamps, Th. Phulpin, Atmospheric correction of infrared measurements of sea surface temperature using channels at 3,7, 11 and 12 ixm. Bound. Layer Meteor., 18, 131-143 (1980) 6. R.D. Jackson, RJ. Ret,inato and S.B. Idso, Wheat canopy temperature : a practical tool for evaluating water requireme'nts. Water Res. Res., 13(3), 651-656 (1977) 7. J.P. Lagouarde, E. Choisnel, A new agrometeorological model for evaporation and surface temperature. Submitted for publication to Agric. and Forest Meteorol (1988) 8. J.P. Lagouarde, Use of N O A A - A V H R R data combined with an agrometeorological model for evaporation mapping. Submitted for publication to Int. J. Rein. Sensing (1988) 9. J.L Monteith, Vegetation and the Academic Press. 439 p (1976)

atmosphere. Vol. 2 :

Case

studies.

Monteith Ed.

10. T. Phulpin, ,.I.P. Jullien, D. Lasselin, Etude de la r6ponse de la v6g&ation ~ l'aide de donn~es NOAA ourant HAPEX-MOBILHY. ESA SP-287. p. 469-472 (1988) 11. B. Seguin, S. Baelz, J.M. Monl!et and V. Petit, Utilisation de la thermographie IR ,pour l'estimation de l'6vaporation r6gional'e. I. Mise au point m6thodologique sur le site de la t.rau. Agronomic113_ 118 (1982)2(1)'7 - 1 6 , II. R~sultats obtenus ~ _partir de donn6es de satellite. Agronomie 2(2), 12. B. Seguin, B. Itier, Using midday surface temperature to estimate daily evaporation from satellite thermal IR data. Int. J. Rem. Sensing., vol. 4, n* 2, 371-383 (1983) 13. H. Tennekes, A.G.M. Driedonks, Basic entrainment equations for the atmospheric boundary layer. Boundary-Layer Meteorol., 20, 515-531 (1981)