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.
Abstract. Measurements carried out by the University of Basilicata Raman lidar system (BASIL) are reported to demonstrate the capability of this instrument to characterise turbulent processes within the convective boundary layer (CBL). In order to resolve the vertical profiles of turbulent variables, high-resolution water vapour and temperature measurements, with a temporal resolution of 10 s and vertical resolutions of 90 and 30 m, respectively, are considered. Measurements of higher-order moments of the turbulent fluctuations of water vapour mixing ratio and temperature are obtained based on the application of autocovariance analyses to the water vapour mixing ratio and temperature time series. The algorithms are applied to a case study (11:30-13:30 UTC, 20 April 2013) from the High Definition Clouds and Precipitation for Climate Prediction (HD(CP) 2 ) Observational Prototype Experiment (HOPE), held in western Germany in the spring 2013. A new correction scheme for the removal of the elastic signal crosstalk into the low quantum number rotational Raman signal is applied. The noise errors are small enough to derive up to fourth-order moments for both water vapour mixing ratio and temperature fluctuations.To the best of our knowledge, BASIL is the first Raman lidar with a demonstrated capability to simultaneously retrieve daytime profiles of water vapour turbulent fluctuations up to the fourth order throughout the atmospheric CBL. This is combined with the capability of measuring daytime profiles of temperature fluctuations up to the fourth order. These measurements, in combination with measurements from other lidar and in situ systems, are important for verifying and possibly improving turbulence and convection parameterisation in weather and climate models at different scales down to the grey zone (grid increment ∼ 1 km; .For the considered case study, which represents a wellmixed and quasi-stationary CBL, the mean boundary layer height is found to be 1290 ± 75 m above ground level (a.g.l.). Values of the integral scale for water vapour and temperature fluctuations at the top of the CBL are in the range of 70-125 and 75-225 s, respectively; these values are much larger than the temporal resolution of the measurements (10 s), which testifies that the temporal resolution considered for the measurements is sufficiently high to resolve turbulent processes down to the inertial subrange and, consequently, to resolve the major part of the turbulent fluctuations. Peak values of all moments are found in the interfacial layer in the proximity of the top of the CBL. Specifically, water vapour and temperature second-order moments ( confidence in the possibility of using these measurements for turbulence parameterisation in weather and climate models.In the determination of the temperature profiles, particular care was dedicated to minimise potential effects associated with elastic signal crosstalk on the rotational Raman signals. For this purpose, a specific algorithm was defined and tested to identify and remove the ela...
Abstract. Polar stratospheric clouds (PSCs) have been observed from 2014 to 2018 from the lidar observatory at the Antarctic Concordia station (Dome C), included as a primary station in the NDACC (Network for Detection of Atmospheric Climate Change). Many of these measurements have been performed in coincidence with overpasses of the satellite-borne CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) lidar, in order to perform a comparison in terms of PSC detection and composition classification. Good agreement has been obtained, despite intrinsic differences in observation geometry and data sampling. This study reports, to our knowledge, the most extensive comparison of PSC observations by ground-based and satellite-borne lidars. The PSCs observed by the ground-based lidar and CALIOP form a complementary and congruent dataset and allow us to study the seasonal and interannual variations in PSC occurrences at Dome C. Moreover, a strong correlation with the formation temperature of NAT (nitric acid trihydrate), TNAT, calculated from local temperature, pressure, and H2O and HNO3 concentrations is shown. PSCs appear at Dome C at the beginning of June up to 26 km and start to disappear in the second half of August, when the local temperatures start to rise above TNAT. Rare PSC observations in September coincide with colder air masses below 18 km.
Polar stratospheric clouds (PSCs), which form in the polar stratosphere during winter and early spring, play an important role in the stratospheric chemistry processes which deplete stratospheric ozone in the Polar Regions (see e.g., Solomon, 1999). The PSC particles provide surfaces on which inactive forms of chlorine are converted into reactive, ozone-destroying forms. In addition, they remove nitrogen compounds that moderate the destructive impact of chlorine. Several particle types are observed in PSCs, both in liquid and solid phase, containing sulfuric acid, nitric acid, and water. All PSC particles form on the underlying sulfuric acid and water (sulfate) aerosol which blankets the stratosphere. These sulfate aerosols form from the condensation of oxidized sulfur which reaches the stratosphere from surface production of OCS and SO 2 and from volcanic outbursts and biomass burning (Kremser et al., 2016; Thomason & Peter, 2006). These stratospheric aerosols then form the condensation sites for PSCs in the polar regions. The microphysical formation processes of PSCs depend on the availability of condensation nuclei, on the temperature and on the number density of water and nitric acid molecules in the gas phase. Detailed discussions of these processes can be found in
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