Geoscience Reference
In-Depth Information
Chapter 3
Cloud Statistics from Spaceborne Lidar Systems
S. Berthier, P. Chazette, J. Pelon, and B. Baum
INTRODUCTION
The distribution of clouds in a vertical column is assessed on the global scale through
analysis of lidar measurements obtained from three spaceborne lidar systems: LITE
(Lidar In-space Technology Experiment, NASA), GLAS (Geoscience Laser Altimeter
System, NASA), and CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization).
Cloud top height (CTH) is obtained from the LITE profiles based on a simple al-
gorithm that accounts for multilayer cloud structures. The resulting CTH results are
compared to those obtained by the operational algorithms of the GLAS and CALIOP
instruments. Based on our method, spaceborne lidar data are analyzed to establish
statistics on the CTH. The resulting columnar results are used to investigate the inter-
annual variability in the lidar CTHs. Statistical analyses are performed for a range
of CTH (high, middle, low) and latitudes (polar, middle latitude, and tropical). The
probability density function (PDF) of CTH are developed. Comparisons of CTH de-
veloped from LITE, for 2 weeks of data in 1994, with International Satellite Cloud
Climatology Project (ISCCP) cloud products show that the cloud fraction observed
from spaceborne lidar is much higher than that from ISCCP. Another key result is that
ISCCP products tend to underestimate the CTH of optically thin cirrus clouds. Signifi-
cant differences are observed between LITE-derived cirrus CTH and both GLAS and
CALIOP-derived cirrus CTH. Such a difference is due primarily to the lidar signal-
to-noise ratio that is approximately a factor of three larger for the LITE system than
for the other lidars. A statistical analysis for a full year of data highlights the influence
of both the Inter-Tropical Convergence Zone and polar stratospheric clouds (PSCs).
One of the most challenging objectives of current climate research programs is in
understanding the impact of clouds on the global energy budget and hydrological bal-
ance. Indeed, clouds have a signifi cant infl uence on the Earth's radiative balance and
induce various climatic feedbacks that are not well known (e.g., Forster et al., 2007;
Stephens, 2005). One important issue is the cloud spatial and vertical distribution (e.g.,
Rossow and Schiffer, 1991). The vertical distribution of the cloud layers in an atmo-
spheric column can lead to very different assumptions of cloud overlap in numerical
models. Clouds infl uence the heating rates and the radiative energy budget. Feedbacks
due to cirrus clouds are an important issue in climate modeling as they have a signifi -
cant radiative impact which largely depends on their characteristics. Such feedbacks
become more complex if lower-level clouds are present. To properly model overlap-
ping cloud layers, it is necessary to know the thermodynamic phase of each cloud
layer in addition to the other properties such as height, optical thickness, and effective
