Cloud Statistics from Calipso Lidar Data for the ... - espace-tum.de

TECHNISCHE UNIVERSITÄT MÜNCHEN
Abstract
Ingenieurfakultät Bau Geo Umwelt
Master of Science
Cloud Statistics from Calipso Lidar Data for the Performance Assessment
of a Methane Space Lidar
by Nico Trebbin
In this thesis a performance assessment for the future German-French climate monitoring
initiative, Methane Remote Sensing Lidar Mission (MERLIN), proposed by DLR and
CNES in 2010 was undertaken. A general space lidar performance issue is the obstruction
by optically dense clouds. For this purpose cloud free statistics, the global cloud top
flatness and global cloud top distributions were derived from the Cloud-Aerosol Lidar
and Infrared Pathfinder Satellite Observation (CALIPSO) level 2, 333 m and 5 km lidar
cloud-layer products between 01 January 2007 and 01 January 2008. Merging both data
sets together thereby allowed the best possible simulation of near global and seasonal
real world atmospheric conditions that a spaceborne Integrated Path Differential Absorption
(IPDA) lidar like MERLIN will encounter. With 40.5 % overall global cloud
free fraction, a cloud gap distribution which is following a power-law distribution with
exponent α = 1.51 ± 0.01 together with a mean cloud gap length of 7.41 km and about
200 daily global cloud top flatness events, the analysis reveals a dominance of small
cloud gaps which is confirmed by a low median cloud gap length of only 1 km. While
the cloud free fraction results were compared and confirmed with Aqua Moderate Resolution
Imaging Spectroradiometer (MODIS) seasonal and annual cloud fraction data,
the power-law distribution of cloud gaps was confirmed by an extensive statistical analysis
using maximum likelihood estimation, Kolmogorov-Smirnov statistics and likelihood
ratio tests. Taking 605 x 10 8 individual CALIPSO measurements of the year 2007 with
a horizontal resolution of 333 m and computing cloud gap and cloud free statistics for 2 ◦
x 2 ◦ latitude/longitude grid points thereby identified regional and seasonal changes in
the probability of spaceborne lidar surface detection. The analysis reveals that MERLIN
will be able to perform near global methane mixing ratio column retrievals.