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. A comparison of polar stratospheric cloud (PSC) occurrence from 2006 to2010 is presented, as observed from the ground-based lidar station at McMurdo(Antarctica) and by the satellite-borne CALIOP lidar (Cloud-Aerosol Lidarwith Orthogonal Polarization) measuring over McMurdo. McMurdo (Antarctica) isone of the primary lidar stations for aerosol measurements of the NDACC (Network forDetection of Atmospheric Climate Change). The ground-based observations havebeen classified with an algorithm derived from the recent v2 detection andclassification scheme, used to classify PSCs observed by CALIOP. A statistical approach has been used to compare ground-based and satellite-based observations, since point-to-point comparison is often troublesome dueto the intrinsic differences in the observation geometries and the imperfectoverlap of the observed areas. A comparison of space-borne lidar observations and a selection of simulationsobtained from chemistry–climate models (CCMs) has been made by using a series ofquantitative diagnostics based on the statistical occurrence of different PSCtypes. The distribution of PSCs over Antarctica, calculated by severalCCMVal-2 and CCMI chemistry–climate models has been compared with the PSCcoverage observed by the satellite-borne CALIOP lidar. The use of severaldiagnostic tools, including the temperature dependence of the PSCoccurrences, evidences the merits and flaws of the different models. Thediagnostic methods have been defined to overcome (at least partially) thepossible differences due to the resolution of the models and to identifydifferences due to microphysics (e.g., the dependence of PSC occurrence on T−TNAT ). A significant temperature bias of most models has been observed, as well as alimited ability to reproduce the longitudinal variations in PSC occurrencesobserved by CALIOP. In particular, a strong temperature bias has been observedin CCMVal-2 models with a strong impact on PSC formation. The WACCM-CCMI(Whole Atmosphere Community Climate Model – Chemistry-Climate ModelInitiative) model compares rather well with the CALIOP observations, althougha temperature bias is still present.

Comparison of Antarctic polar stratospheric cloud observations by ground-based and space-borne lidar and relevance for chemistry–climate models