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Investigation of the surface temperature using meteosat satellite images
Adv. Space Res. Voi. 14, No. 3, pp. 0)31--(3)35, 1994 Printed in Great Britain. All righ~ reset'ved.
0273-1177/94 $6.00 + 0.00 Copyright © 1993 COSPAR
INVESTIGATION OF THE SURFACE TEMPERATURE USING METEOSAT SATELLITE IMAGES J. Ker6nyi
Satellite Research Laboratory of Hungarian Meteorological Service, H-1675 Budapest, P.O. Box 32, Hungary
ABSTRACT The brightness temperature of the surface-air system can be determined from the METEOSAT IR window, but the surface temperature cannot be established directly. Therefore a radiative transfer model based on radiosonde data was used to estimate the atmospheric correction. Comparing the longwave radiances, which are calculated by the model and received by the satellite, the surface temperature can be determined. For the determination of surface temperature tO large area the bi-harmonic spline interpolation of radiosonde data was resolved to projection grid.
INTRODUCTION The establishment of surface temperature is an important mission. For example, in agricultural applications it improves prediction of damaging frost and the best time of planting. Satellite images permit the estimation of the surface temperatures over broad areas, and remote areas for which surface methods are impractical. The geostationary METEOSAT satellite observes the Earth in three channels in the infrared window (10.5-12.5 ~tm), in the visible (0.5-0.9 lun) and a water vapour absorption band (5.7-7.1 Ixm). The longwave radiance can be determined from the brightness values using the calibration coefficient of METEOSAT. Atmospheric gases absorb energy radiated from the surface, and radiate according to their own temperature, which is typically lower than the surface temperature. Consequently, the radiance detected by satellite is less than the surface radiance, and the apparent surface temperature will be too low. The correct temperature of the surface must be estimated using an atmospheric correction scheme, such as the one presented in this paper.
THE APPLIED MODEL A radiative transfer model originated by Karol and Frolkisz /1/ and developed by PrfLgerand Kov~s/2/, was taken as the basis for the atmospheric correction. The effects of atmospheric gases, aerosols and clouds on the energy budget and the short- and longwave radiances can be investigated using the model. It is static and one dimensional (vertical). The model is horizontally averaged, with 16 levels of compution from 1000 hPa at the surface to 0.64 hPa at about 60 km from the surface. In the troposphere the difference between these levels is 100 hPa. The temperature and humidity profiles for the model are calculated from radiosonde data. At the determination of longwave radiance is applied
Ffj) = e B(T0) P(j) + ~_..B(Tk) D0,k) (3)31
(1)
(3)32
J. Ker6nyi
where B (TO), B (Tk) the integrated Planck functions at the surface, and at the boundary atmospheric of layer k, P(j) is the integrated transmission function of the atmosphere between the surface and level j, e is the emissivity. D(j, k) = P(j, k) - P(j, k-l) is the integrated differential transmission function of the layers. Optically active atmospheric gases were taken into account in defining the longwave transmission functions. Absorption by these gases was approximated using exponential empirical transmission functions, dependent on the optical mass re(j) and pressure p(j) of the gases: POd) = exp(-g(i) m(i) / (1 + h(i) mfj) / p(j))l/2)
(2)
P(i,j) = exp(-r(i) m(j))
(3)
j=l...n
i=l...v
where g(i), h(i), r(i) are the transmission parameters, j is the serial number of layers from the surface, i is the serial number of spectral intervals. Equation (2) gives the transmission function for strong absorption bands of the gases, whereas equation (3) gives the transmission function for weak bands. The spectral window for the model is 0.2-100 I~m. The longwave interval (4-100 Ixm) is divided into 17 parts. The interval between 10.4-12.95 ~tm corresponds to the METEOSAT IR window. Effects of H20 and CO 2 gases and the aerosols are taken into account by the model. The optical thickness is used to estimate scattering by aerosols.
DETERMINATION OF SURFACE TEMPERATURE BY THE MODEL Because surface temperatures cannot be established directly from radiance measured by the satellite, they are calculated from the above-mentioned model. The model, using the radiosonde d~t__a,determines the longwave radiance at the top of atmosphere. The radiance measured by satellite and the data calculated by model were compared, and the measured values were greater than the calculated data. The reason for these deviations is probably that the model doesn't use the surface temperature (TO) itself, but rather the value measured by radiosonde near the surface. Accordingly, correction for the radiosonde near-surface temperature is needed. To do is, it was assumed that the calculated and measured radiances must be equal. An iteration method was employed for the near-surface temperature. The starting point was increased by 0.5 degrees, than the model calculated the longwave radiance using this corrected temperature. This method was continued until the difference between the measured and the calculated radiance values was less than the required precision. The temperatures determined by the iteration method represent the actual surface temperature. Emissivities were assumed to be unity in every case. This assumption is best for water and snow surfaces, therefore these surfaces were investigated fast. For actual rock and vegetated surfaces the assumed emissivity may be incorrect and must be estimated to calculate accurate temperatures. An error of only 1% in emissivity causes 1K error in the determination of surface temperature. However, if the emissivity does equal unity, the surface temperature will be underestimated. There are only two radiosonde stations in Hungary. A bi-harmonlc spline interpolation was used to estimate atmospheric parameters from radiosonde data from surrounding lands/3/. To determine the temperature and humidity profiles the following equation was used:
V-
k(a,b) = 1/2 ~_..~(i) [(a - x(i))2 + (b - y(i))2] ln[(a - x(i))2 + (b - y(i))2] + 10 + 1 la + 12b
(4)
SurfaceTemperaturehem METEOSAT
....... +,+.... o .........
I le(m,l)
ic(m~)
~YY~];
~l
0
0)33
,
"<'> Y'-i
Pq
1 O
x(m) 0
~(m,
x,m) y(m)
00
oj
[ ~(~)I U~J -
yg
(lq [ k;(m)I
=
(5)
hoo°_i
c(ij) = e(,j,i)= [(x(i) - xfj))2 + (y(i) + y(j))211/2 In[(x(i) - x(j))2 + (y(i) - yfj))2]l/2
(6)
where (x(i),y(i)) is the coordinate of tic radiosonde point, and (a,b) is the coordinate of the projected gridpoint Data interpolated by this method were found grid intersections, which covered Hungary. On the basis of these data the surface temperature of an actual point can be calculated using the method discussed above. The effects of variable emissivity weren't taken into account because of different conditions of soil in.the gridpoints. Therefore, the results do not give real surface temperatures.
RESULTS The two Hungarian radiosonde stations are in the suburbs of Budapest and Szeged. In these points, the calculated surface temperature is suspect because of nearness of towns. To determine temperatures for other areas of +Hungary, the bi-harmonic spline interpolation was applied, and pseudo-sondes were produced for each projection gridpoint. From these data, surface temperatures could be approximated. One area examined closely was Lake Balaton, and there the temperature was found in clear weather in all cases. A projected gridpoint is near the Si6fok Observatory at Lake Balaton, for which measured temperatures were available for comparison.
K 315 310 305
t
300
e
295
X
290
41 l
265 280 275
41 X 0
# X 0
9 14 Ma~ch
,1~ 14:3-0
l Z
l ][
0
O
t
t
X 0
X 0
e X @
X 0
0 X
X
0
0
, Z
O t
X
0
0
0
10 17 2 2 AInU
5 14 25 " 2 16 2 4 M~' June
9 20 July
Fig. 1. Temperaturevaluesof Balaton(x = measuredtzmpexamm,o = calculated temperature, • = calculatedtemperaturewith a~ospheric correction)
9 I0 Augu.~
(3)34
J. KerSnyi
The calculated temperatures were typically 2-3 K greater than the measured water temperatures. The difference derived from the water temperature at the observatory is measured in depth of 1.5 metres. A possible reason for the difference is that the measurement occurred at a point, whereas the satellite temperatures are averaged over large areas. The envirous of Szarvas Agrometeorology Observatory was chosen for the other investigation region, because it is situated on lowland territory and near Szeged radiosonde station. Comparing the measured and calculated temperatures, the calculated values were lower than the measured data.
I<, 315 Z
310
X
305 Z |
300
X
295 X O
265 280 275
| 0
, 9
0
X
x q)
z e
0
0
X
O
•
Z
O
0
0
X qj
O
aJ
0
0
O
9.0
2
10
ql
r
o
290
X
¢
o
,
0
: 22
i
blotch
: : : ', : 9 15 25 5
April
: : 1625
M~v
' 8
9
June
Ju~'
August
Fig. 2. Temperaturevaluesof Szarvas (x = measuredtemperature,o = calculated temperature, • = calculatedtemperaturewith atmosphericcorrection)
The early spring surface temperatures agree within 1-2 K, but the differences increase gradually with the growth of vegetation, to 4-5 K by summer. If the emissivity is unity the calculated surface temperature will be lowered. The difference between the calculated and measured temperature can be explained if the surface has different emissivities than found for the examined region. In this way the radiation of different types of soil appears in integral. Therefore the satellite measurements give average values, which are typical to the totality of surfaces. On the other hand the surface temperatmes are measured in one point on bare soil in Szarvas.
SUMMARY S u m m a r i z i n g , o n the basis of METEOSAT digital images using the radiative-transfer model the surface temperature can be determined. The results obtained so far are promising in spite of deviations. In case of water surface, the difference between the measured and the calculated temperature was no more than 2-3 K, which was derived from the disposition of the mentioned two types of measurements. At the surface in early spring, the temperature difference was only 1-2 If,, although the difference increased with the growth of plants, due to neglecting emissivity and the different measurements method.
Stwface T
~
from METEOSAT
0)35
In the future, determination of surface temperature will be made better. In one respect the effect of emission will be taken into account and investigated. On the other hand, because the model is founded on the radiosonde d~_~ in the period between the measurement the determination of temperature and humidity profiles (pseudo-sonde) is necessary. It will be resolved using the SMHI LAM model, and the radiative transfer model can then be used to determine the actual surface temperature. REFERENCES
1. I. L. Karol i V. A. Frolkisz, Energobalanszovaja radiacionno-konvektivnaja model globalgono ldimata,
Meteorologija i Gidrologija 8, 59--68 (1984). 2. T. Pr~ger and E. Kov~cs, Investigation of the climate modifying effects of atmospheric trace gases and aerosol particles by a radiative convective model, Id6j~r~, 153-162 (1988). 3. A. Horv~h and T. Pr6ger, A meso-scale objective analysis for meteorological fields, Id6jdrds, 23-37 (1990).
0273-1177/94 $6.00 + 0.00 Copyright © 1993 COSPAR
INVESTIGATION OF THE SURFACE TEMPERATURE USING METEOSAT SATELLITE IMAGES J. Ker6nyi
Satellite Research Laboratory of Hungarian Meteorological Service, H-1675 Budapest, P.O. Box 32, Hungary
ABSTRACT The brightness temperature of the surface-air system can be determined from the METEOSAT IR window, but the surface temperature cannot be established directly. Therefore a radiative transfer model based on radiosonde data was used to estimate the atmospheric correction. Comparing the longwave radiances, which are calculated by the model and received by the satellite, the surface temperature can be determined. For the determination of surface temperature tO large area the bi-harmonic spline interpolation of radiosonde data was resolved to projection grid.
INTRODUCTION The establishment of surface temperature is an important mission. For example, in agricultural applications it improves prediction of damaging frost and the best time of planting. Satellite images permit the estimation of the surface temperatures over broad areas, and remote areas for which surface methods are impractical. The geostationary METEOSAT satellite observes the Earth in three channels in the infrared window (10.5-12.5 ~tm), in the visible (0.5-0.9 lun) and a water vapour absorption band (5.7-7.1 Ixm). The longwave radiance can be determined from the brightness values using the calibration coefficient of METEOSAT. Atmospheric gases absorb energy radiated from the surface, and radiate according to their own temperature, which is typically lower than the surface temperature. Consequently, the radiance detected by satellite is less than the surface radiance, and the apparent surface temperature will be too low. The correct temperature of the surface must be estimated using an atmospheric correction scheme, such as the one presented in this paper.
THE APPLIED MODEL A radiative transfer model originated by Karol and Frolkisz /1/ and developed by PrfLgerand Kov~s/2/, was taken as the basis for the atmospheric correction. The effects of atmospheric gases, aerosols and clouds on the energy budget and the short- and longwave radiances can be investigated using the model. It is static and one dimensional (vertical). The model is horizontally averaged, with 16 levels of compution from 1000 hPa at the surface to 0.64 hPa at about 60 km from the surface. In the troposphere the difference between these levels is 100 hPa. The temperature and humidity profiles for the model are calculated from radiosonde data. At the determination of longwave radiance is applied
Ffj) = e B(T0) P(j) + ~_..B(Tk) D0,k) (3)31
(1)
(3)32
J. Ker6nyi
where B (TO), B (Tk) the integrated Planck functions at the surface, and at the boundary atmospheric of layer k, P(j) is the integrated transmission function of the atmosphere between the surface and level j, e is the emissivity. D(j, k) = P(j, k) - P(j, k-l) is the integrated differential transmission function of the layers. Optically active atmospheric gases were taken into account in defining the longwave transmission functions. Absorption by these gases was approximated using exponential empirical transmission functions, dependent on the optical mass re(j) and pressure p(j) of the gases: POd) = exp(-g(i) m(i) / (1 + h(i) mfj) / p(j))l/2)
(2)
P(i,j) = exp(-r(i) m(j))
(3)
j=l...n
i=l...v
where g(i), h(i), r(i) are the transmission parameters, j is the serial number of layers from the surface, i is the serial number of spectral intervals. Equation (2) gives the transmission function for strong absorption bands of the gases, whereas equation (3) gives the transmission function for weak bands. The spectral window for the model is 0.2-100 I~m. The longwave interval (4-100 Ixm) is divided into 17 parts. The interval between 10.4-12.95 ~tm corresponds to the METEOSAT IR window. Effects of H20 and CO 2 gases and the aerosols are taken into account by the model. The optical thickness is used to estimate scattering by aerosols.
DETERMINATION OF SURFACE TEMPERATURE BY THE MODEL Because surface temperatures cannot be established directly from radiance measured by the satellite, they are calculated from the above-mentioned model. The model, using the radiosonde d~t__a,determines the longwave radiance at the top of atmosphere. The radiance measured by satellite and the data calculated by model were compared, and the measured values were greater than the calculated data. The reason for these deviations is probably that the model doesn't use the surface temperature (TO) itself, but rather the value measured by radiosonde near the surface. Accordingly, correction for the radiosonde near-surface temperature is needed. To do is, it was assumed that the calculated and measured radiances must be equal. An iteration method was employed for the near-surface temperature. The starting point was increased by 0.5 degrees, than the model calculated the longwave radiance using this corrected temperature. This method was continued until the difference between the measured and the calculated radiance values was less than the required precision. The temperatures determined by the iteration method represent the actual surface temperature. Emissivities were assumed to be unity in every case. This assumption is best for water and snow surfaces, therefore these surfaces were investigated fast. For actual rock and vegetated surfaces the assumed emissivity may be incorrect and must be estimated to calculate accurate temperatures. An error of only 1% in emissivity causes 1K error in the determination of surface temperature. However, if the emissivity does equal unity, the surface temperature will be underestimated. There are only two radiosonde stations in Hungary. A bi-harmonlc spline interpolation was used to estimate atmospheric parameters from radiosonde data from surrounding lands/3/. To determine the temperature and humidity profiles the following equation was used:
V-
k(a,b) = 1/2 ~_..~(i) [(a - x(i))2 + (b - y(i))2] ln[(a - x(i))2 + (b - y(i))2] + 10 + 1 la + 12b
(4)
SurfaceTemperaturehem METEOSAT
....... +,+.... o .........
I le(m,l)
ic(m~)
~YY~];
~l
0
0)33
,
"<'> Y'-i
Pq
1 O
x(m) 0
~(m,
x,m) y(m)
00
oj
[ ~(~)I U~J -
yg
(lq [ k;(m)I
=
(5)
hoo°_i
c(ij) = e(,j,i)= [(x(i) - xfj))2 + (y(i) + y(j))211/2 In[(x(i) - x(j))2 + (y(i) - yfj))2]l/2
(6)
where (x(i),y(i)) is the coordinate of tic radiosonde point, and (a,b) is the coordinate of the projected gridpoint Data interpolated by this method were found grid intersections, which covered Hungary. On the basis of these data the surface temperature of an actual point can be calculated using the method discussed above. The effects of variable emissivity weren't taken into account because of different conditions of soil in.the gridpoints. Therefore, the results do not give real surface temperatures.
RESULTS The two Hungarian radiosonde stations are in the suburbs of Budapest and Szeged. In these points, the calculated surface temperature is suspect because of nearness of towns. To determine temperatures for other areas of +Hungary, the bi-harmonic spline interpolation was applied, and pseudo-sondes were produced for each projection gridpoint. From these data, surface temperatures could be approximated. One area examined closely was Lake Balaton, and there the temperature was found in clear weather in all cases. A projected gridpoint is near the Si6fok Observatory at Lake Balaton, for which measured temperatures were available for comparison.
K 315 310 305
t
300
e
295
X
290
41 l
265 280 275
41 X 0
# X 0
9 14 Ma~ch
,1~ 14:3-0
l Z
l ][
0
O
t
t
X 0
X 0
e X @
X 0
0 X
X
0
0
, Z
O t
X
0
0
0
10 17 2 2 AInU
5 14 25 " 2 16 2 4 M~' June
9 20 July
Fig. 1. Temperaturevaluesof Balaton(x = measuredtzmpexamm,o = calculated temperature, • = calculatedtemperaturewith a~ospheric correction)
9 I0 Augu.~
(3)34
J. KerSnyi
The calculated temperatures were typically 2-3 K greater than the measured water temperatures. The difference derived from the water temperature at the observatory is measured in depth of 1.5 metres. A possible reason for the difference is that the measurement occurred at a point, whereas the satellite temperatures are averaged over large areas. The envirous of Szarvas Agrometeorology Observatory was chosen for the other investigation region, because it is situated on lowland territory and near Szeged radiosonde station. Comparing the measured and calculated temperatures, the calculated values were lower than the measured data.
I<, 315 Z
310
X
305 Z |
300
X
295 X O
265 280 275
| 0
, 9
0
X
x q)
z e
0
0
X
O
•
Z
O
0
0
X qj
O
aJ
0
0
O
9.0
2
10
ql
r
o
290
X
¢
o
,
0
: 22
i
blotch
: : : ', : 9 15 25 5
April
: : 1625
M~v
' 8
9
June
Ju~'
August
Fig. 2. Temperaturevaluesof Szarvas (x = measuredtemperature,o = calculated temperature, • = calculatedtemperaturewith atmosphericcorrection)
The early spring surface temperatures agree within 1-2 K, but the differences increase gradually with the growth of vegetation, to 4-5 K by summer. If the emissivity is unity the calculated surface temperature will be lowered. The difference between the calculated and measured temperature can be explained if the surface has different emissivities than found for the examined region. In this way the radiation of different types of soil appears in integral. Therefore the satellite measurements give average values, which are typical to the totality of surfaces. On the other hand the surface temperatmes are measured in one point on bare soil in Szarvas.
SUMMARY S u m m a r i z i n g , o n the basis of METEOSAT digital images using the radiative-transfer model the surface temperature can be determined. The results obtained so far are promising in spite of deviations. In case of water surface, the difference between the measured and the calculated temperature was no more than 2-3 K, which was derived from the disposition of the mentioned two types of measurements. At the surface in early spring, the temperature difference was only 1-2 If,, although the difference increased with the growth of plants, due to neglecting emissivity and the different measurements method.
Stwface T
~
from METEOSAT
0)35
In the future, determination of surface temperature will be made better. In one respect the effect of emission will be taken into account and investigated. On the other hand, because the model is founded on the radiosonde d~_~ in the period between the measurement the determination of temperature and humidity profiles (pseudo-sonde) is necessary. It will be resolved using the SMHI LAM model, and the radiative transfer model can then be used to determine the actual surface temperature. REFERENCES
1. I. L. Karol i V. A. Frolkisz, Energobalanszovaja radiacionno-konvektivnaja model globalgono ldimata,
Meteorologija i Gidrologija 8, 59--68 (1984). 2. T. Pr~ger and E. Kov~cs, Investigation of the climate modifying effects of atmospheric trace gases and aerosol particles by a radiative convective model, Id6j~r~, 153-162 (1988). 3. A. Horv~h and T. Pr6ger, A meso-scale objective analysis for meteorological fields, Id6jdrds, 23-37 (1990).