Abstract
Abstract. A comparison of polar stratospheric cloud (PSC) occurrence from 2006 to 2010 is presented, as observed from the ground-based lidar station at McMurdo (Antarctica) and by the satellite-borne CALIOP lidar (Cloud-Aerosol Lidar with Orthogonal Polarization) measuring over McMurdo. McMurdo (Antarctica) is one of the primary lidar stations for aerosol measurements of the NDACC (Network for Detection of Atmospheric Climate Change). The ground-based observations have been classified with an algorithm derived from the recent v2 detection and classification 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 due to the intrinsic differences in the observation geometries and the imperfect overlap of the observed areas. A comparison of space-borne lidar observations and a selection of simulations obtained from chemistry–climate models (CCMs) has been made by using a series of quantitative diagnostics based on the statistical occurrence of different PSC types. The distribution of PSCs over Antarctica, calculated by several CCMVal-2 and CCMI chemistry–climate models has been compared with the PSC coverage observed by the satellite-borne CALIOP lidar. The use of several diagnostic tools, including the temperature dependence of the PSC occurrences, evidences the merits and flaws of the different models. The diagnostic methods have been defined to overcome (at least partially) the possible differences due to the resolution of the models and to identify differences 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 a limited ability to reproduce the longitudinal variations in PSC occurrences observed by CALIOP. In particular, a strong temperature bias has been observed in CCMVal-2 models with a strong impact on PSC formation. The WACCM-CCMI (Whole Atmosphere Community Climate Model – Chemistry-Climate Model Initiative) model compares rather well with the CALIOP observations, although a temperature bias is still present.
Highlights
Lidar observations have been extensively used to characterize the occurrence of polar stratospheric clouds (PSCs) in the polar stratosphere
In order to illustrate how ground-based and space-borne lidar observations of PSCs compare, we show as an example the height–time evolution of PSC classes for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and McMurdo databases for the year 2006, which has the best temporal coverage with respect to the other years (2007–2010)
The differences between the simulations obtained from the chemistry–climate models (CCMs) and CALIOP observations are discussed in terms of geographical distribution, onset and decline of PSCs during polar winter and total vertical extent for nitric acid trihydrate (NAT) and ice
Summary
Lidar observations have been extensively used to characterize the occurrence of polar stratospheric clouds (PSCs) in the polar stratosphere (see e.g., Browell et al, 1990; Adriani et al, 2004; Di Liberto et al, 2014; Achtert and Tesche, 2014). Comparison between CALIOP and ground-based observations in the Antarctic stratosphere of PSCs is possible from 2006 on and has been pursued in the case of McMurdo Station by performing co-incident measurements with CALIPSO overpasses whenever possible. Due to their primary role in ozone chemistry, a correct representation of PSCs in CCMs is needed. In the present work we first compare the statistics of occurrence of different PSC classes in the stratosphere over McMurdo Station, as detected by the ground-based lidar operating there and the satellite-borne CALIOP.
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