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Radiation budget components at surface and at top of atmosphere for convective cloud cases in Central Europe
Phys. Chem. Earth, Vol. 23, No. 5-6, pp. 611-617, 1998 1998 Elsevier Science Ltd. All rights reserved
Pergamon PI I: S0079-1946(98)00087- l
0079-1946/98/$-see front matter
Radiation Budget Components at Surface and at Top of Atmosphere for Convective Cloud Cases in Central Europe Franz H. Berger I and Sven Jagdhuhnz 1Institute for Hydrology and Meteorology, Dresden University of Technology, Piennerstr. 9, D-01737 Tharandt, Gcrrnany 2Institute for Meteorology, Free University Berlin, CarI-Hcinrich-Bccker-Weg 6-10, D-12165 Berlin, Germany Received 11 June 1997; accepted 22 December 1997
A b s t r a c t . The paper is focused on the determination of radiation budget components at surface as well as at top of atmosphere using remotely sensed data for a few convective cloud cases between 1990 and 1993. The target area for this investigation is Central Europe and covers an area of approx. 1800 x 1800 km 2. Preliminary results from heating rate computations will further be given. To infer the individual radiation budget components at surface from NOAA-AVHRR and Meteosat data, an inverse remote sensing technique was applied. This techniques uses partly look-up tables, which are generated for different atmospheric conditions. For the atmospheric radiative transfer a delta two-stream approximation scheme was used. The tables consider different variables, like solar zenith angle, cloud optical depth, cloud base height, and for the longwave standard temperature and humidity profiles. The cloud optical properties were computed with the same delta two-stream approximation scheme, where a cloud classificationwas carried out in advance to distinguish between cloud types. This information was used to define the microphysical cloud properties. For the atmospheric conditions monthly means of horizontal visibility and relative humidity were taken into account. The radiation budget components at top of atmosphere were computed using a narrow-to-broadband conversion considering all geometrical conditions. Finally, the heating rates for four atmospheric layers were also calculated based on the inverse remote sensing technique. © 1998 Elsevier Science Ltd. All rights reserved
1
INTRODUCTION
The radiation fluxes at the surface are the main important components of the energy exchange between Co~ndence
to: Franz H. Berger 611
atmosphere and land or sea (Chahine, 1992). In the last 30 years many methods using satellite data have been developed to infer surface radiation budget components (Schmetz, 1989; Sellers et al., 1990; Eymard and Taconet, 1995). The algorithms can be separated in empirical, in physical and in combined physical methods including numerical models (Brisson et al., 1994). The empirical methods are based on regressions between simultaneous and co-located satellite radiances and measured insolation at surface (Fritz and Rao, 1967; Tarpley, 1979; Klink and Dollhopf, 1986). The physical methods use radiances at satellite related to optical cloud properties based on intensive radiative transfer calculations, like the method by Laszlo and Pinker (1993). This method was applied to ISCCP C1 data, where the broadband radiances measured at satellite were used to relate these to insolation or absorbed shortwave fluxes at surface. Li and Leighton (1993) developed a linear relationship between the planetary albedo and the absorbed shortwave surface fluxes. They showed that this simple parameterization is primarily dependent on the solar zenith angle and secondly on cloud precipitable water or cloud type and independent on cloud optical thickness or surface characteristics, if ERBE data were analysed. Summarizing the current state in determining shortwave radiation budget components at surface, the methods are applied to low-resolution data sets, where assumptions, like low spatial variability of surface characteristics or averaged cloud characteristics, can be made. Concerning the longwave spectra, no relations like in the shortwave are possible. Nevertheless, these methods are very sensitive to individual cloud types, their heights and optical thicknesses, and to temperature and humidity profiles in the atmosphere. These parameters were derived from other data sources, like synoptical observations or vertical sounder data (Gupta, 1989). The purpose of this paper is to demonstrate the use of remotely sensed data for the determination of sur-
612
F.H. Bergcr and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases 08/01/1991 13:28 UTC
ss'~
i
-
,i
Ss'HCIoud O p t i c a l D e p t h too~oo ....... ~ 7S.O0 ..........~ 80.00 i~-, SO.O0 40.00 30.00
so'~
2S.00 20.00 15.00 10.00 8,00 S.O0
!
L
4.00 2.00
1
1.00 0.50 0.25 0.10 0.05 0.00 0.00
Fig. 1. Cloud Optical Thickness (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRRdata
face radiation budget components on a high temporal and spatial scale. To infer these components from highresolution satellite data, like for NOAA-AVHHR data with a nadir resolution of 1.2 km 2, a more detailed physical method could be developed. It is important to note that the scheme can also be applied in a modified version to Meteosat data with a lower spatial, but higher temporal resolution. 2
METHOD
The scheme to infer radiation budget components, separately for NOAA-AVHRR and Meteoeat data, can be divided into a few separate modules: - pr~proceesing, like calibration and transformation into a stereographic projection - cloud classification, including sunglint and snow detection -
simple landuse classification
- determination of cloud optical properties -
-
determination of radiation budget components at surface and heating rates in different atmospheric layers determination of top of atmosphere radiation fluxes.
After calibration and transformation into a stereographic projection, the first step in the analysis scheme is a detailed cloud classification, comparable for NOAAAVHRR and Meteosat data, which is based on the maximum likelihood method and classifies more than twenty cloud classes (Berger, 1995). Especially high clouds with different optical depths can be classified. To use the classification scheme on an automatic basis, the training areas for the maximum likelihood method have to be independent on location. Therefore, the tropopanse temperatures for latitude belts based on Oort's climatology (1983) were taken into account. The classifiedcloud
types were used to define their microphysical properties and their base heights related to synoptical observations (Stephens, 1978; Stephens et al.,1984). Concerning further microphysical properties, especially for ice clouds, a modified asymmetry parameter of 0.7 is assumed to be constant over all wavelengths (Stephens et al., 1990). For all water clouds a wavelength dependent asymmetry parameter between 0.77 until 0.93 is considered, dependent on the droplet spectrum assigned to water clouds. To detect snow and sunglint, a threshold technique by Derrien et al. (1993) adapted for the Baltic Sea and for Central Europe was introduced to analyse NOAAAVHRR data. In a further step a simple threshold technique could be used to distinguish between surface types
like sea surface, bare soil, and two vegetated surfaces, which are representative for grassland and for forest.
F. H. Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases
The results inferred from the N O A A - A V H R R will also be used in the Meteosat analysis stream, where such a determination is not possible. Deriving cloud optical properties and surface radiation budget components from remotely sensed data, additional information about atmospheric conditions are needed. Therefore, synoptical observations were analysed with respect to relativehumidity, horizontal visibilitynear the surface and cloud base height. In the next steps, cloud optical thickness and surface radiation budget components were inferred with an inverse remote sensing technique. This technique is based on the direct satellitemeasurements (radiancesat satellitelevel)and on comprehensive radiativetransfercalculationsvarying allrequested parameters. For the present study a large set of atmospheric and cloudy conditions was taken into account. For the solutionof the radiative transfer a delta-two-stream approximation is used with a 40 layers atmosphere for differentgeometrical conditions. Considering differentcloud and surface types, relations between broadband shortwave reflectancesat top of atmosphere or shortwave reflectancesat top of atmosphere for individual satellitebands and cloud optical depths could be determined. These results show that increasing solar zenith angles and/or increasing cloud depths lead to a non-linear increase of shortwave reflectances (Berger et al.,1996). In Figure 1, an example of derived cloud opticalthicknesses from N O A A - A V H R R data is plotted for August 1, 1991 13:28 U T C (instantaneous measurement). All these data (1.2 kin2 resolution) are averaged over an 18x18 k m 2 area, where clear-skyregions can be detected by black areas. Figure 1 shows further differentclouds (increasing cloud optical depth related to an increasing whiteness) and deep convective clouds over Germany and Austria, where the optical depth is larger than 70. Also a few smaller convective cells near the river Elbe can be seen. The main criteriato distinguish between deep convective clouds from shallow convective clouds are cloud reflectances,cloud top temperatures, and the two-dimensional (horizontal)spatialcloud shape. "finns, deep convective clouds reflectmore solar radiation than shallow convective clouds and emit due to their significant lower cloud top temperature less thermal infrared radiation. Also their larger horizontal extension is considered and can be seen in Figure 1 as coherent white/grey areas, where over France scattered cloud fields representing shallow convective clouds (heterogeneous grey/white regions) can be found. Using the resultsfrom the radiative transfer calculations, further simillarrelations (look-up tables) for surface radiation budget components could be established. These tables consider as an additional parameter the derived cloud optical depth. For August 1, 1991 the absorbed solar radiationat surface is displayed in Figure 2. It considers also the results from the simple landuse classification and shows a reduction of absorbed shortwave
613
radiation below clouds up to 50 Wm -2 (only ~ radiation / dark grey) in Figure 2). Only small differences between the deep convective cloud and the smaller shallow convective cells near the river Elbe can be observed due to their similiar cloud optical depths. Under thinner clouds (observed over France) the absorbed shortwave radiation is about 300 / 400 Wm -2. Comparisons of the satellite inferred results with ground based observations show reasonable agreements, where in general a slight underestim_~tion of the satellite results can be noticed (Berger et al., 1996; Mecklenburg, 1996). Concerning the longwave components, simple empirical relations could be found for cloudy conditions to modify the clear-sky estimates. The first, very preliminary assumption has assumed that the outgoing longwave radiation at surface below the clouds is the same as for the nearest clear-sky pixel. The derived empirical relationships are based on the decrease of outgoing longwave radiation due to cloud occurrence, cloud optical thickness, and spatial resolution (Mecklenburg, 1996; Sedlak, 1996). These relations could also be applied to define more accurately cloud base temperatures, depending on their climatological altitudes. Thus, the net radiation at surface, the main relevant component of the surface energy exchange could be computed as the sum of all four components (Fig. 3). For clear-sky conditions, high net radiation can be observed over sea surfaces (up to 800 Wm -2 - light grey) as well as over land surfaces (up to 700 Win-2). The differences can be explained by the different surface reflectances, which can also be seen in Figure 2. Below clouds the net radiation is reduced up to 50 Wm -2 (dark grey in Figure 3), which corresponds mainly to the net shortwave radiation (Fig. 2). The loss due to the outgoing thermal radiation below clouds, especially below thick clouds, will be partly compensated by the atmospheric thermal radiation emitted by these clouds. To infer the radiation budget components at top of atmosphere, which allows a more detailed description of the energy cycle in a limited area, the reflected shortwave radiation and outgoing longwave radiation could be calculated using a narrow to broadband conversion. This conversion includes the individual filter response functions. For the solar spectrum the spectral solar insolation at top of atmosphere and geometrical conditions (Berger, 1995) were additionaUy taken into account. Adding the net solar radiation and the outgoing longwave radiation, the net radiation at top of atmosphere can be computed. Therefore, in clear-sky areas a high absorbed radiation (in white) is available for the Earth-atmosphere system (Fig. 4). This can be explained by low reflected shortwave radiation and by large outgoing longwave radiation at top of the atmosphere. Where in the case of clouds, a reduced available radiation (grey) must be stated. This depends mainly on their high reflectances (reduced net solar radiation) and on their reduced emitted longwave radiation due
614
F . H . Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases
08/0111991 13:28 UTC tbsofbed Solar Radiation
ss'~
Surface[wm~ ........ ~ 1000
IO0
~'N
250
~'N
•
~,
~
~.
~
Fig. 2. Absorbed Solar Radiation at Surface (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
b
b
m
d
08/01/1991 13:28 UTC h N I m
U ~ e [Wnrq " "T
1000
710
I
I
Fig. 3. Net Radiation at Surface (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
F. H. Berger and S. Jagdhuhn: Radiation Budget Components for ConvectiveCloud Cases
b
~
rn
m
m
615
08/0111991 13:28 UTC ~t R~llatlon
at Top
A ~
[Wm-~] 1000
750
$00 45"1~
250
40";~
Fig. 4. Net Radiation at Top of Atmosphere (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
to the lower temperatures of cloud tops related to the clear-sky atmosphere. In the last two Figures, Figure 5 and Figure 6, the net heating rates for two atmospheric layers are plotted. These preliminary results show large differences between these two layers, especially for the cloudy pixels (deep convective cloud versus shallow convective cells). The results are computed as the sum of the shortwave heating and of the longwave cooling / heating, where the shortwave absorption always produces heating and the longwave emission produces cooling. For these specific layers, significant differences could be found, although the influence of these clouds on the surface radiation budget was similiar: In the case of the thick deep convective cloud the main heating occurs in the 450 to 600 hPa layer, where for the smaller cells near the river Elbe the main heating occurs in the 600 to 1000 hPa layer. This difference can be explained by the two different cloud structures and cloud top/base heights.
ferent atmospheric conditions, but give more detailed information about the spatial variability of the radiation field. In ongoing studies, the surface topography and the surface parameters, like the slope or elevation, will also be included in the computation of surface radiation budget components. In further steps, regional and spatial patterns will be studied for convective cloud cases. Concerning the heating rates, additional information from numerical weather models about cloud base heights, cloud top heights and cloud structure in general will be used to compute more accurate heating rates. This alIows further the validation of modelled spatial variabilites of energy fluxes and of flux divergences in the atmosphere. Acknowledgements. This study was supported by the BMBF (German Ministry of Education and Research) under contract 07 VWK 01-06. References
3
SUMMARY
Berger, F., Inferenceof'the climaticefficiencyof cloudsfromsatellite measurements, Int. J. of Remote Sensing, 16(15), 29032926, 1995.
This study shows that meteorological satellite data can be used to infer radiation budget components at top of atmosphere as well as at surface. The inaccuracies of the inferred results are larger than routine ground based observations due to their assumptions about dif-
Berger, F., Jagdhuhn, S., Rockel, B., and Stuhlmann, P~., Radiation Budget Components inferred from NOAA-AVHRRand Meteceat Data for the Baltic Sea, in IRS'96: Current problems in atmospheric radiation, 1996.
Brimon, A., Le Borgne, P., Marsoiun, A., and More~m, T., Surface irradiances calculated from Meteo~t sensor data during
616
F . H . Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases
08/01/1991 13:28 UTC ~IET Heating / Cooling Rates .ayer 450-600 hPa [K~ 1] 10 9 II
7
8 5
4$ "~
4
2 /
[.......... 0
~
m
~
Fig. 5. Atmospheric Net Heating Rate for the Layer 450 to 600 hPa (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
08/0111991 13:28 UTC ~
m
m
m
~IET Heating I Cooling Rates .ayer 600-1000 hPa [ K d ' l | 10 9 S 7 6 S 45"N
4 3 2 1
40"N i
0
Fig. 6. Atmospheric Net Heating Rate for the Layer 600 to 1000 hPa (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR dsta
F. H. Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases SOFIA-ASTEX, Int. J. o.f Remote Senaing, 15(1), 197-205, 1994. Chahine, M., The hydrological cycle and its influence on climate, Nature, 359,373-380, 1992. Derrien, M., Farki, B., Harang, L., Legleau, H., Noyalet, A., Pochic, D., and Sairouni, A., Automatic Cloud Detection Applied to NOAA-11/AVHRR Imagery, Rein. Sens. Environ., ~(6, 246-267, 1993. Eymard, L. and Taconet, O., The methods inferring surface fluxes from satellite data, and their use for atmosphere model validation, Int. J. o] Remote Sensing, 16(11), 1907-1930, 1995. F-Yitz~S. and Rao, K., On the infrared transmission through cirrus clouds and the estimation of relative humidity from satellites, J. Appl. Meteor., 6(6), 1088-1096, 1967. Gupta, S., A parameterization for longwave surface radiation from sun-synchronous satellite d&ta~ J. Ciim., 2, 305-320, 1989. Klink, J. and Dollhopf, K., An evaluation of sateliite-based insolation estimates for Ohio, J. Ciim. Appi. Meteor., 25, 1741-1751, 1986. Laszlo, I. and Pinker, R., Shortwave cloud-radiative forcing at the top of the atmosphere, at the surface and of the atmospheric column as determined from ISCCP C1 data, J. Geoph. Res., 98(D2), 2703-2713, 1993. Li, Z. and Leighton, H., Global climatologies of solar radiation budget at the surface and in the atmosphere from 5 years of ERBE data, J. Geoph. Res., 98(D3), 4919-4930, 1993. Mecklenburg, S., Die Anderun9 der langwelligen Ausstroldung
617
nach dem Auflreten yon Wolken in Abh~ngigkeit t~a def~t opt/schen Eigenschaflen, Master's thesis, Institut f'tir Hydrologie und Meteorologie der Technischen UniversitRt Dresden, 1996. Oort, A., Global atmospheric circulation statistic, Tech. Rep. Prof. Paper 14, NOAA, 1983. Schmetz, J., Towards a surface radiation climatology: Retrieval of downward irradiances from satellite, Atmospheric Researeh, ~8, 287-321, 1989. Sedlak, I., Studie zur 8er~cksichtigun 9 yon 8ew~lmngsdaten aus Satellitenbfldern in emem eindimensionalen G~n~chich~rnodell, Master's thesis, Meteorologisches Institut der Freien Universit~t Berlin, 1996. Sellers, P., Rasool, S., and Bolle, H.-J., A Review of Satellite Data Algorithms for Studies of the Land Surface, Bull. Amer. Meteor. Soc., 71(10), 1429-1447, 1990. Stephens, G., Radiation profiles in extended water clouds. If: Parameterization schemes, J. Atmos. Sci., 85, 2123--2132, 1978. Stepheus, G., Ackermann, S., and Smith, E., A shortwave parameterization revised to improve cloud absorption, J. Atmos. Sci., 41,687-690, 1984. Stepheus, G., Tsay, S.-C., Stackhouse, P., and Flatan, P., The relevance of the microphysical and radiative properties of cirrus clouds to climate and climatic feedback, J. Atmos. Sci., ~(7(14), 1742-1753, 1990. Tarpley, J., Estimating incident solar radiation at the surface from geostationary satellite data, J. Appl. Meteor., 18, 1172-1181, 1979.
Pergamon PI I: S0079-1946(98)00087- l
0079-1946/98/$-see front matter
Radiation Budget Components at Surface and at Top of Atmosphere for Convective Cloud Cases in Central Europe Franz H. Berger I and Sven Jagdhuhnz 1Institute for Hydrology and Meteorology, Dresden University of Technology, Piennerstr. 9, D-01737 Tharandt, Gcrrnany 2Institute for Meteorology, Free University Berlin, CarI-Hcinrich-Bccker-Weg 6-10, D-12165 Berlin, Germany Received 11 June 1997; accepted 22 December 1997
A b s t r a c t . The paper is focused on the determination of radiation budget components at surface as well as at top of atmosphere using remotely sensed data for a few convective cloud cases between 1990 and 1993. The target area for this investigation is Central Europe and covers an area of approx. 1800 x 1800 km 2. Preliminary results from heating rate computations will further be given. To infer the individual radiation budget components at surface from NOAA-AVHRR and Meteosat data, an inverse remote sensing technique was applied. This techniques uses partly look-up tables, which are generated for different atmospheric conditions. For the atmospheric radiative transfer a delta two-stream approximation scheme was used. The tables consider different variables, like solar zenith angle, cloud optical depth, cloud base height, and for the longwave standard temperature and humidity profiles. The cloud optical properties were computed with the same delta two-stream approximation scheme, where a cloud classificationwas carried out in advance to distinguish between cloud types. This information was used to define the microphysical cloud properties. For the atmospheric conditions monthly means of horizontal visibility and relative humidity were taken into account. The radiation budget components at top of atmosphere were computed using a narrow-to-broadband conversion considering all geometrical conditions. Finally, the heating rates for four atmospheric layers were also calculated based on the inverse remote sensing technique. © 1998 Elsevier Science Ltd. All rights reserved
1
INTRODUCTION
The radiation fluxes at the surface are the main important components of the energy exchange between Co~ndence
to: Franz H. Berger 611
atmosphere and land or sea (Chahine, 1992). In the last 30 years many methods using satellite data have been developed to infer surface radiation budget components (Schmetz, 1989; Sellers et al., 1990; Eymard and Taconet, 1995). The algorithms can be separated in empirical, in physical and in combined physical methods including numerical models (Brisson et al., 1994). The empirical methods are based on regressions between simultaneous and co-located satellite radiances and measured insolation at surface (Fritz and Rao, 1967; Tarpley, 1979; Klink and Dollhopf, 1986). The physical methods use radiances at satellite related to optical cloud properties based on intensive radiative transfer calculations, like the method by Laszlo and Pinker (1993). This method was applied to ISCCP C1 data, where the broadband radiances measured at satellite were used to relate these to insolation or absorbed shortwave fluxes at surface. Li and Leighton (1993) developed a linear relationship between the planetary albedo and the absorbed shortwave surface fluxes. They showed that this simple parameterization is primarily dependent on the solar zenith angle and secondly on cloud precipitable water or cloud type and independent on cloud optical thickness or surface characteristics, if ERBE data were analysed. Summarizing the current state in determining shortwave radiation budget components at surface, the methods are applied to low-resolution data sets, where assumptions, like low spatial variability of surface characteristics or averaged cloud characteristics, can be made. Concerning the longwave spectra, no relations like in the shortwave are possible. Nevertheless, these methods are very sensitive to individual cloud types, their heights and optical thicknesses, and to temperature and humidity profiles in the atmosphere. These parameters were derived from other data sources, like synoptical observations or vertical sounder data (Gupta, 1989). The purpose of this paper is to demonstrate the use of remotely sensed data for the determination of sur-
612
F.H. Bergcr and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases 08/01/1991 13:28 UTC
ss'~
i
-
,i
Ss'HCIoud O p t i c a l D e p t h too~oo ....... ~ 7S.O0 ..........~ 80.00 i~-, SO.O0 40.00 30.00
so'~
2S.00 20.00 15.00 10.00 8,00 S.O0
!
L
4.00 2.00
1
1.00 0.50 0.25 0.10 0.05 0.00 0.00
Fig. 1. Cloud Optical Thickness (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRRdata
face radiation budget components on a high temporal and spatial scale. To infer these components from highresolution satellite data, like for NOAA-AVHHR data with a nadir resolution of 1.2 km 2, a more detailed physical method could be developed. It is important to note that the scheme can also be applied in a modified version to Meteosat data with a lower spatial, but higher temporal resolution. 2
METHOD
The scheme to infer radiation budget components, separately for NOAA-AVHRR and Meteoeat data, can be divided into a few separate modules: - pr~proceesing, like calibration and transformation into a stereographic projection - cloud classification, including sunglint and snow detection -
simple landuse classification
- determination of cloud optical properties -
-
determination of radiation budget components at surface and heating rates in different atmospheric layers determination of top of atmosphere radiation fluxes.
After calibration and transformation into a stereographic projection, the first step in the analysis scheme is a detailed cloud classification, comparable for NOAAAVHRR and Meteosat data, which is based on the maximum likelihood method and classifies more than twenty cloud classes (Berger, 1995). Especially high clouds with different optical depths can be classified. To use the classification scheme on an automatic basis, the training areas for the maximum likelihood method have to be independent on location. Therefore, the tropopanse temperatures for latitude belts based on Oort's climatology (1983) were taken into account. The classifiedcloud
types were used to define their microphysical properties and their base heights related to synoptical observations (Stephens, 1978; Stephens et al.,1984). Concerning further microphysical properties, especially for ice clouds, a modified asymmetry parameter of 0.7 is assumed to be constant over all wavelengths (Stephens et al., 1990). For all water clouds a wavelength dependent asymmetry parameter between 0.77 until 0.93 is considered, dependent on the droplet spectrum assigned to water clouds. To detect snow and sunglint, a threshold technique by Derrien et al. (1993) adapted for the Baltic Sea and for Central Europe was introduced to analyse NOAAAVHRR data. In a further step a simple threshold technique could be used to distinguish between surface types
like sea surface, bare soil, and two vegetated surfaces, which are representative for grassland and for forest.
F. H. Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases
The results inferred from the N O A A - A V H R R will also be used in the Meteosat analysis stream, where such a determination is not possible. Deriving cloud optical properties and surface radiation budget components from remotely sensed data, additional information about atmospheric conditions are needed. Therefore, synoptical observations were analysed with respect to relativehumidity, horizontal visibilitynear the surface and cloud base height. In the next steps, cloud optical thickness and surface radiation budget components were inferred with an inverse remote sensing technique. This technique is based on the direct satellitemeasurements (radiancesat satellitelevel)and on comprehensive radiativetransfercalculationsvarying allrequested parameters. For the present study a large set of atmospheric and cloudy conditions was taken into account. For the solutionof the radiative transfer a delta-two-stream approximation is used with a 40 layers atmosphere for differentgeometrical conditions. Considering differentcloud and surface types, relations between broadband shortwave reflectancesat top of atmosphere or shortwave reflectancesat top of atmosphere for individual satellitebands and cloud optical depths could be determined. These results show that increasing solar zenith angles and/or increasing cloud depths lead to a non-linear increase of shortwave reflectances (Berger et al.,1996). In Figure 1, an example of derived cloud opticalthicknesses from N O A A - A V H R R data is plotted for August 1, 1991 13:28 U T C (instantaneous measurement). All these data (1.2 kin2 resolution) are averaged over an 18x18 k m 2 area, where clear-skyregions can be detected by black areas. Figure 1 shows further differentclouds (increasing cloud optical depth related to an increasing whiteness) and deep convective clouds over Germany and Austria, where the optical depth is larger than 70. Also a few smaller convective cells near the river Elbe can be seen. The main criteriato distinguish between deep convective clouds from shallow convective clouds are cloud reflectances,cloud top temperatures, and the two-dimensional (horizontal)spatialcloud shape. "finns, deep convective clouds reflectmore solar radiation than shallow convective clouds and emit due to their significant lower cloud top temperature less thermal infrared radiation. Also their larger horizontal extension is considered and can be seen in Figure 1 as coherent white/grey areas, where over France scattered cloud fields representing shallow convective clouds (heterogeneous grey/white regions) can be found. Using the resultsfrom the radiative transfer calculations, further simillarrelations (look-up tables) for surface radiation budget components could be established. These tables consider as an additional parameter the derived cloud optical depth. For August 1, 1991 the absorbed solar radiationat surface is displayed in Figure 2. It considers also the results from the simple landuse classification and shows a reduction of absorbed shortwave
613
radiation below clouds up to 50 Wm -2 (only ~ radiation / dark grey) in Figure 2). Only small differences between the deep convective cloud and the smaller shallow convective cells near the river Elbe can be observed due to their similiar cloud optical depths. Under thinner clouds (observed over France) the absorbed shortwave radiation is about 300 / 400 Wm -2. Comparisons of the satellite inferred results with ground based observations show reasonable agreements, where in general a slight underestim_~tion of the satellite results can be noticed (Berger et al., 1996; Mecklenburg, 1996). Concerning the longwave components, simple empirical relations could be found for cloudy conditions to modify the clear-sky estimates. The first, very preliminary assumption has assumed that the outgoing longwave radiation at surface below the clouds is the same as for the nearest clear-sky pixel. The derived empirical relationships are based on the decrease of outgoing longwave radiation due to cloud occurrence, cloud optical thickness, and spatial resolution (Mecklenburg, 1996; Sedlak, 1996). These relations could also be applied to define more accurately cloud base temperatures, depending on their climatological altitudes. Thus, the net radiation at surface, the main relevant component of the surface energy exchange could be computed as the sum of all four components (Fig. 3). For clear-sky conditions, high net radiation can be observed over sea surfaces (up to 800 Wm -2 - light grey) as well as over land surfaces (up to 700 Win-2). The differences can be explained by the different surface reflectances, which can also be seen in Figure 2. Below clouds the net radiation is reduced up to 50 Wm -2 (dark grey in Figure 3), which corresponds mainly to the net shortwave radiation (Fig. 2). The loss due to the outgoing thermal radiation below clouds, especially below thick clouds, will be partly compensated by the atmospheric thermal radiation emitted by these clouds. To infer the radiation budget components at top of atmosphere, which allows a more detailed description of the energy cycle in a limited area, the reflected shortwave radiation and outgoing longwave radiation could be calculated using a narrow to broadband conversion. This conversion includes the individual filter response functions. For the solar spectrum the spectral solar insolation at top of atmosphere and geometrical conditions (Berger, 1995) were additionaUy taken into account. Adding the net solar radiation and the outgoing longwave radiation, the net radiation at top of atmosphere can be computed. Therefore, in clear-sky areas a high absorbed radiation (in white) is available for the Earth-atmosphere system (Fig. 4). This can be explained by low reflected shortwave radiation and by large outgoing longwave radiation at top of the atmosphere. Where in the case of clouds, a reduced available radiation (grey) must be stated. This depends mainly on their high reflectances (reduced net solar radiation) and on their reduced emitted longwave radiation due
614
F . H . Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases
08/0111991 13:28 UTC tbsofbed Solar Radiation
ss'~
Surface[wm~ ........ ~ 1000
IO0
~'N
250
~'N
•
~,
~
~.
~
Fig. 2. Absorbed Solar Radiation at Surface (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
b
b
m
d
08/01/1991 13:28 UTC h N I m
U ~ e [Wnrq " "T
1000
710
I
I
Fig. 3. Net Radiation at Surface (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
F. H. Berger and S. Jagdhuhn: Radiation Budget Components for ConvectiveCloud Cases
b
~
rn
m
m
615
08/0111991 13:28 UTC ~t R~llatlon
at Top
A ~
[Wm-~] 1000
750
$00 45"1~
250
40";~
Fig. 4. Net Radiation at Top of Atmosphere (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
to the lower temperatures of cloud tops related to the clear-sky atmosphere. In the last two Figures, Figure 5 and Figure 6, the net heating rates for two atmospheric layers are plotted. These preliminary results show large differences between these two layers, especially for the cloudy pixels (deep convective cloud versus shallow convective cells). The results are computed as the sum of the shortwave heating and of the longwave cooling / heating, where the shortwave absorption always produces heating and the longwave emission produces cooling. For these specific layers, significant differences could be found, although the influence of these clouds on the surface radiation budget was similiar: In the case of the thick deep convective cloud the main heating occurs in the 450 to 600 hPa layer, where for the smaller cells near the river Elbe the main heating occurs in the 600 to 1000 hPa layer. This difference can be explained by the two different cloud structures and cloud top/base heights.
ferent atmospheric conditions, but give more detailed information about the spatial variability of the radiation field. In ongoing studies, the surface topography and the surface parameters, like the slope or elevation, will also be included in the computation of surface radiation budget components. In further steps, regional and spatial patterns will be studied for convective cloud cases. Concerning the heating rates, additional information from numerical weather models about cloud base heights, cloud top heights and cloud structure in general will be used to compute more accurate heating rates. This alIows further the validation of modelled spatial variabilites of energy fluxes and of flux divergences in the atmosphere. Acknowledgements. This study was supported by the BMBF (German Ministry of Education and Research) under contract 07 VWK 01-06. References
3
SUMMARY
Berger, F., Inferenceof'the climaticefficiencyof cloudsfromsatellite measurements, Int. J. of Remote Sensing, 16(15), 29032926, 1995.
This study shows that meteorological satellite data can be used to infer radiation budget components at top of atmosphere as well as at surface. The inaccuracies of the inferred results are larger than routine ground based observations due to their assumptions about dif-
Berger, F., Jagdhuhn, S., Rockel, B., and Stuhlmann, P~., Radiation Budget Components inferred from NOAA-AVHRRand Meteceat Data for the Baltic Sea, in IRS'96: Current problems in atmospheric radiation, 1996.
Brimon, A., Le Borgne, P., Marsoiun, A., and More~m, T., Surface irradiances calculated from Meteo~t sensor data during
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F . H . Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases
08/01/1991 13:28 UTC ~IET Heating / Cooling Rates .ayer 450-600 hPa [K~ 1] 10 9 II
7
8 5
4$ "~
4
2 /
[.......... 0
~
m
~
Fig. 5. Atmospheric Net Heating Rate for the Layer 450 to 600 hPa (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR data
08/0111991 13:28 UTC ~
m
m
m
~IET Heating I Cooling Rates .ayer 600-1000 hPa [ K d ' l | 10 9 S 7 6 S 45"N
4 3 2 1
40"N i
0
Fig. 6. Atmospheric Net Heating Rate for the Layer 600 to 1000 hPa (August 1, 1991, 13:28 UTC) derived from NOAA-AVHRR dsta
F. H. Berger and S. Jagdhuhn: Radiation Budget Components for Convective Cloud Cases SOFIA-ASTEX, Int. J. o.f Remote Senaing, 15(1), 197-205, 1994. Chahine, M., The hydrological cycle and its influence on climate, Nature, 359,373-380, 1992. Derrien, M., Farki, B., Harang, L., Legleau, H., Noyalet, A., Pochic, D., and Sairouni, A., Automatic Cloud Detection Applied to NOAA-11/AVHRR Imagery, Rein. Sens. Environ., ~(6, 246-267, 1993. Eymard, L. and Taconet, O., The methods inferring surface fluxes from satellite data, and their use for atmosphere model validation, Int. J. o] Remote Sensing, 16(11), 1907-1930, 1995. F-Yitz~S. and Rao, K., On the infrared transmission through cirrus clouds and the estimation of relative humidity from satellites, J. Appl. Meteor., 6(6), 1088-1096, 1967. Gupta, S., A parameterization for longwave surface radiation from sun-synchronous satellite d&ta~ J. Ciim., 2, 305-320, 1989. Klink, J. and Dollhopf, K., An evaluation of sateliite-based insolation estimates for Ohio, J. Ciim. Appi. Meteor., 25, 1741-1751, 1986. Laszlo, I. and Pinker, R., Shortwave cloud-radiative forcing at the top of the atmosphere, at the surface and of the atmospheric column as determined from ISCCP C1 data, J. Geoph. Res., 98(D2), 2703-2713, 1993. Li, Z. and Leighton, H., Global climatologies of solar radiation budget at the surface and in the atmosphere from 5 years of ERBE data, J. Geoph. Res., 98(D3), 4919-4930, 1993. Mecklenburg, S., Die Anderun9 der langwelligen Ausstroldung
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nach dem Auflreten yon Wolken in Abh~ngigkeit t~a def~t opt/schen Eigenschaflen, Master's thesis, Institut f'tir Hydrologie und Meteorologie der Technischen UniversitRt Dresden, 1996. Oort, A., Global atmospheric circulation statistic, Tech. Rep. Prof. Paper 14, NOAA, 1983. Schmetz, J., Towards a surface radiation climatology: Retrieval of downward irradiances from satellite, Atmospheric Researeh, ~8, 287-321, 1989. Sedlak, I., Studie zur 8er~cksichtigun 9 yon 8ew~lmngsdaten aus Satellitenbfldern in emem eindimensionalen G~n~chich~rnodell, Master's thesis, Meteorologisches Institut der Freien Universit~t Berlin, 1996. Sellers, P., Rasool, S., and Bolle, H.-J., A Review of Satellite Data Algorithms for Studies of the Land Surface, Bull. Amer. Meteor. Soc., 71(10), 1429-1447, 1990. Stephens, G., Radiation profiles in extended water clouds. If: Parameterization schemes, J. Atmos. Sci., 85, 2123--2132, 1978. Stepheus, G., Ackermann, S., and Smith, E., A shortwave parameterization revised to improve cloud absorption, J. Atmos. Sci., 41,687-690, 1984. Stepheus, G., Tsay, S.-C., Stackhouse, P., and Flatan, P., The relevance of the microphysical and radiative properties of cirrus clouds to climate and climatic feedback, J. Atmos. Sci., ~(7(14), 1742-1753, 1990. Tarpley, J., Estimating incident solar radiation at the surface from geostationary satellite data, J. Appl. Meteor., 18, 1172-1181, 1979.