Ld. Fowler et al., Use of a GCM to explore sampling issues in connection with satellite remote sensing of the Earth radiation budget, J GEO RES-A, 105(D16), 2000, pp. 20757-20772
Collocated in time and space, top-of-the-atmosphere measurements of the Ear
th radiation budget (ERB) and cloudiness from passive scanning radiometers,
and lidar- and radar-in-space measurements of multilayered cloud systems,
are the required combination to improve our understanding of the role of cl
ouds and radiation in climate. Experiments to fly multiple satellites "in f
ormation" to measure simultaneously the radiative and optical properties of
overlapping cloud systems are being designed. Because satellites carrying
ERB experiments and satellites carrying lidars- or radars-in space have dif
ferent orbital characteristics, the number of simultaneous measurements of
radiation and clouds is reduced relative to the number of measurements made
by each satellite independently. Monthly averaged coincident observations
of radiation and cloudiness are biased when compared against more frequentl
y sampled observations due, in particular, to the undersampling of their di
urnal cycle. Using the Colorado State University General Circulation Model
(CSU GCM), the goal of this study is to measure the impact of using simulta
neous observations from the Earth Observing System (EOS) platform and compa
nion satellites flying lidars or radars on monthly averaged diagnostics of
longwave radiation, cloudiness, and its cloud optical properties. To do so,
the hourly varying geographical distributions of coincident locations betw
een the afternoon EOS (EOS-PM) orbit and the orbit of the ICESAT satellite
set to fly at the altitude of 600 km, and between the EOS PM orbit and the
orbits of the PICASSO satellite proposed to fly at the altitudes of 485 km
(PICA485) or 705 km (PICA705), are simulated in the CSU GCM for a 60-month
time period starting at the idealistic July 1, 2001, launch date. Monthly a
veraged diagnostics of the top-of-the-atmosphere, atmospheric, and surface
longwave radiation budgets and clouds accumulated over grid boxes correspon
ding to satellite overpasses are compared against monthly averaged diagnost
ics obtained from hourly samplings over the entire globe. Results show that
differences between irregularly (satellite) and regularly (true) sampled d
iagnostics of the longwave net radiative budgets are the greatest at the su
rface and the smallest in the atmosphere and at the top-of-the-atmosphere,
under both cloud-free and cloudy conditions. In contrast, differences betwe
en the satellite and the true diagnostics of the longwave cloud radiative f
orcings are the largest in the atmosphere and at the top-of-the atmosphere,
and the smallest at the surface. A poorer diurnal sampling of the surface
temperature in the satellite simulations relative to the true simulation co
ntributes a major part to sampling biases in the longwave net radiative bud
gets, while a poorer diurnal sampling of cloudiness and its optical propert
ies directly affects diagnostics of the longwave cloud radiative forcings.
A factor of 8 difference in the number of satellite overpasses between PICA
705 and PICA485 and ICESAT leads to a systematic factor of 3 difference in
the spatial standard deviations of all radiative and cloudiness diagnostics
.