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Abstract. Scattering codes are used to study the optical properties of polar stratospheric clouds (PSCs). Particle backscattering and depolarization coefficients can be computed with available scattering codes once the particle size distribution (PSD) is known and a suitable refractive index is assumed. However, PSCs often appear as external mixtures of supercooled ternary solution (STS) droplets, solid nitric acid trihydrate (NAT) and possibly ice particles, making the assumption of a single refractive index and a single morphology to model the scatterers questionable.Here we consider a set of 15 coincident measurements of PSCs above McMurdo Station, Antarctica, using ground-based lidar, a balloon-borne optical particle counter (OPC) and in situ observations taken by a laser backscattersonde and OPC during four balloon stratospheric flights from Kiruna, Sweden. This unique dataset of microphysical and optical observations allows us to test the performances of optical scattering models when both spherical and aspherical scatterers of different composition and, possibly, shapes are present. We consider particles as STS if their radius is below a certain threshold value Rth and NAT or possibly ice if it is above it. The refractive indices are assumed known from the literature. Mie scattering is used for the STS, assumed spherical. Scattering from NAT particles, considered spheroids of different aspect ratio (AR), is treated with T-matrix results where applicable. The geometric-optics–integral-equation approach is used whenever the particle size parameter is too large to allow for a convergence of the T-matrix method.The parameters Rth and AR of our model have been varied between 0.1 and 2 µm and between 0.3 and 3, respectively, and the calculated backscattering coefficient and depolarization were compared with the observed ones. The best agreement was found for Rth between 0.5 and 0.8 µm and for AR less than 0.55 and greater than 1.5.To further constrain the variability of AR within the identified intervals, we have sought an agreement with the experimental data by varying AR on a case-by-case basis and further optimizing the agreement by a proper choice of AR smaller than 0.55 and greater than 1.5 and Rth within the interval 0.5 and 0.8 µm. The ARs identified in this way cluster around the values 0.5 and 2.5.The comparison of the calculations with the measurements is presented and discussed. The results of this work help to set limits to the variability of the dimensions and asphericity of PSC solid particles, within the limits of applicability of our model based on the T-matrix theory of scattering and on assumptions on a common particle shape in a PSD and a common threshold radius for all the PSDs. 

Abstract Wherever a loose bed of sand is subject to sufficiently strong winds, aeolian dunes form at predictable wavelengths and growth rates. As dunes mature and coarsen, however, their growth trajectories become more idiosyncratic; nonlinear effects, sediment supply, wind variability and geologic constraints become increasingly relevant, resulting in complex and history-dependent dune amalgamations. Here we examine a fundamental question: do aeolian dunes stop growing and, if so, what determines their ultimate size? Earth’s major sand seas are populated by giant sand dunes, evolved over tens of thousands of years. We perform a global analysis of the topography of these giant dunes, and their associated atmospheric forcings and geologic constraints, and we perform numerical experiments to gain insight on temporal evolution of dune growth. We find no evidence of a previously proposed limit to dune size by atmospheric boundary layer height. Rather, our findings indicate that dunes may grow indefinitely in principle; but growth depends on morphology, slows with increasing size, and may ultimately be limited by sand supply. 

Abstract. 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 onT−T_NAT). 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. 

Abstract Macroscopic stratospheric aerosol properties such as surface area density (SAD) and volume density (VD) are required by modern chemistry climate models. These quantities are in continuous need of validation by observations. Direct observation of these parameters is not possible, but they can be derived from optical particle counters (OPCs) which provide concentration (number density) and size distributions of aerosol particles, and possibly from ground‐based and satellite‐borne lidar observations of particle backscatter coefficients and aerosol type. When such measurements are obtained simultaneously by OPCs and lidars, they can be used to calculate backscatter and extinction coefficients, as well as SAD and VD. Empirical relations can thus be derived between particle backscatter coefficient, extinction coefficient, and SAD and VD for a variety of aerosols (desert dust, maritime aerosols, stratospheric aerosols) and be used to approximate SAD and VD from lidar measurements. Here we apply this scheme to coincident measurements of polar stratospheric clouds above McMurdo Station, Antarctica, by ground‐based lidar and balloon‐borne OPCs. The relationships derived from these measurements will provide a means to obtain values of SAD and VD for supercooled ternary solutions (STS) and nitric acid trihydrate (NAT) PSCs from the backscatter coefficients measured by lidar. Coincident lidar and OPC measurements provided 15 profile comparisons. Empirical expressions of SAD and VD as a function of particle backscatter coefficient,β, were calculated from fits of the form log(SAD/VD) = A + Blog(β) usingβfrom the lidar and SAD/VD from the OPC. The PSCs were classified as STS and NAT mixtures, ice being absent.