160
R. Stuhlmann
Long-Wave Cloud Forcing W/m2
o
10
20
30
40
60
60
Figure 7.6: Monthly mean longwave cloud forcing (C FLW ) for April 1985.
applicable these models are, for instance, to derive reliable estimates of DSR from the satellites
data is given by Schmetz (1991).
QRAD = DSR· (1 - as) + DLR - £s(JT~
(7.7)
Meanwhile, these techniques have been improved in a way to firstly produce more accurate results on the incoming solar radiation at the surface, and secondly to also estimate the long- wave
radiation budget at the surface (e.g.: Bishop and Rossow, 1991; Darnell et a!., 1992; Pinker and
Laszlo, 1992; Stuhlmann et a!., 1990; Zhang et a!., 1994). For the later, so far, only preliminary
results are published, since no information about the cloud base height distribution is available from operational satellite data. Lately, the World Climate Research Program (WCRP)
Radiation Projects Office formed the Global Energy and Water Cycle Experiment (GEWEX)
Surface Radiation Budget Project to meet a community need for a global, long-term record of
the surface radiation budget. The SRB Project is now retrieving fluxes of short-wave surface
radiation over the globe from the ISCCP data with a spatial resolution of 2.5 0 x 2.5 0 latitude
and longitude (Alberta et a!., 1994; Charlock et al., 1993; Whitlock et a!', 1993). The SRB
project will shortly extend the retrievals to the long-wave.
To look solely at the surface radiation budget, does not directly allow a separation of the
effect of clouds (type, amount, optical thickness) from that of others like solar zenith angle,
surface albedo, temperature profile or absorption characteristics of the clear-sky atmosphere.
To estimate the effect of clouds on QRAD(S) the concept of cloud forcing, developed for the
radiation budget at the top of the atmosphere, can also be applied to the surface data (Gupta
et al., 1993; Laszlo and Pinker, 1993; Rieland and Stuhlmann, 1993; Rossow and Zhang, 1995) .
C F(S) = QRAD(S) - Q~AD(S) = C Fsw(S) + C FLW(S)
(7.8)
R. Stuhlmann
Long-Wave Cloud Forcing W/m2
o
10
20
30
40
60
60
Figure 7.6: Monthly mean longwave cloud forcing (C FLW ) for April 1985.
applicable these models are, for instance, to derive reliable estimates of DSR from the satellites
data is given by Schmetz (1991).
QRAD = DSR· (1 - as) + DLR - £s(JT~
(7.7)
Meanwhile, these techniques have been improved in a way to firstly produce more accurate results on the incoming solar radiation at the surface, and secondly to also estimate the long- wave
radiation budget at the surface (e.g.: Bishop and Rossow, 1991; Darnell et a!., 1992; Pinker and
Laszlo, 1992; Stuhlmann et a!., 1990; Zhang et a!., 1994). For the later, so far, only preliminary
results are published, since no information about the cloud base height distribution is available from operational satellite data. Lately, the World Climate Research Program (WCRP)
Radiation Projects Office formed the Global Energy and Water Cycle Experiment (GEWEX)
Surface Radiation Budget Project to meet a community need for a global, long-term record of
the surface radiation budget. The SRB Project is now retrieving fluxes of short-wave surface
radiation over the globe from the ISCCP data with a spatial resolution of 2.5 0 x 2.5 0 latitude
and longitude (Alberta et a!., 1994; Charlock et al., 1993; Whitlock et a!', 1993). The SRB
project will shortly extend the retrievals to the long-wave.
To look solely at the surface radiation budget, does not directly allow a separation of the
effect of clouds (type, amount, optical thickness) from that of others like solar zenith angle,
surface albedo, temperature profile or absorption characteristics of the clear-sky atmosphere.
To estimate the effect of clouds on QRAD(S) the concept of cloud forcing, developed for the
radiation budget at the top of the atmosphere, can also be applied to the surface data (Gupta
et al., 1993; Laszlo and Pinker, 1993; Rieland and Stuhlmann, 1993; Rossow and Zhang, 1995) .
C F(S) = QRAD(S) - Q~AD(S) = C Fsw(S) + C FLW(S)
(7.8)