Macrophysical and optical properties of midlatitude cirrus clouds from four ground‐based lidars and collocated CALIOP observations
Author(s) -
Dupont J.C.,
Haeffelin M.,
Morille Y.,
Noël V.,
Keckhut P.,
Winker D.,
Comstock J.,
Chervet P.,
Roblin A.
Publication year - 2010
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2009jd011943
Subject(s) - lidar , cirrus , middle latitudes , environmental science , cloud base , cloud height , remote sensing , cloud top , consistency (knowledge bases) , meteorology , cloud computing , optical depth , latitude , aerosol , atmospheric sciences , geology , cloud cover , geography , geodesy , mathematics , computer science , geometry , operating system
Ground‐based lidar and Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) data sets gathered over four midlatitude sites, two U.S. and two French sites, are used to evaluate the consistency of cloud macrophysical and optical property climatologies that can be derived by such data sets. The consistency in average cloud height (both base and top height) between the CALIOP and ground data sets ranges from −0.4 km to +0.5 km. The cloud geometrical thickness distributions vary significantly between the different data sets, due in part to the original vertical resolutions of the lidar profiles. Average cloud geometrical thicknesses vary from 1.2 to 1.9 km, i.e., by more than 50%. Cloud optical thickness distributions in subvisible, semitransparent, and moderate intervals differ by more than 50% between ground‐ and space‐based data sets. The cirrus clouds with optical thickness below 0.1 (not included in historical cloud climatologies) represent 30–50% of the nonopaque cirrus class. An important part of this work consists in quantifying the different possible causes of discrepancies between CALIOP and surface lidar. The differences in average cloud base altitude between ground and CALIOP data sets can be attributed to (1) irregular sampling of seasonal variations in the ground‐based data, (2) day‐night differences in detection capabilities by CALIOP, and (3) the restriction to situations without low‐level clouds in ground‐based data. Cloud geometrical thicknesses are not affected by irregular sampling of seasonal variations in the ground‐based data but by the day‐night differences in detection capabilities of CALIOP and by the restriction to situations without low‐level clouds in ground‐based data.
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