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Abstract. The climatic and health effects of aerosols are strongly dependent on the intra-annual variations in their loading and properties. While the seasonal variations of regional aerosol optical depth (AOD) have been extensively studied, understanding the temporal variations in aerosol vertical distribution and particle types is also important for an accurate estimate of aerosol climatic effects. In this paper, we combine the observations from four satellite-borne sensors and several ground-based networks to investigate the seasonal variations of aerosol column loading, vertical distribution, and particle types over three populous regions: the Eastern United States (EUS), Western Europe (WEU), and Eastern and Central China (ECC). In all three regions, column AOD, as well as AOD at heights above 800m, peaks in summer/spring, probably due to accelerated formation of secondary aerosols and hygroscopic growth. In contrast, AOD below 800m peaks in winter over WEU and ECC regions because more aerosols are confined to lower heights due to the weaker vertical mixing. In the EUS region, AOD below 800m shows two maximums, one in summer and the other in winter. The temporal trends in low-level AOD are consistent with those in surface fine particle (PM_2.5) concentrations. AOD due to fine particles ( < 0.7µm diameter) is much larger in spring/summer than in winter over all three regions. However, the coarse mode AOD ( > 1.4µm diameter), generally shows small variability, except that a peak occurs in spring in the ECC region due to the prevalence of airborne dust during this season. When aerosols are classified according to sources, the dominant type is associated with anthropogenic air pollution, which has a similar seasonal pattern as total AOD. Dust and sea-spray aerosols in the WEU region peak in summer and winter, respectively, but do not show an obvious seasonal pattern in the EUS region. Smoke aerosols, as well as absorbing aerosols, present an obvious unimodal distribution with a maximum occurring in summer over the EUS and WEU regions, whereas they follow a bimodal distribution with peaks in August and March (due to crop residue burning) over the ECC region. 

Abstract This paper presents a new retrieval method for inferring the vertical profile of cirrus cloud effective particle size by using solar reflected line spectra in the 1.38‐μm band. The retrieval method is based on the maximum‐photon penetration principle coupled with the constrained linear inversion. This approach takes advantage of the vertical stratification of cirrus cloud effective particle size as well as absorption lines of water vapor of different intensity, which contain rich information on the vertical structure of cloud particle size. Reflected radiances at different wavenumbers provide the effective‐size information at different heights within cirrus associated with photon different penetration depths. Assuming a vertical profile of effective size monotonically decreasing toward cloud top and using results based on “exact” radiative transfer computations, we perform retrieval of the effective size for a number of model cirrus to check for algorithm accuracy. The retrieved profile of effective size is close to the model profile for cirrus optical depth less than about eight with an uncertainty range of 2.2–4.2 μm. In addition, we further carry out a sensitivity study involving the retrieved effective size in connection with different water vapor profiles and demonstrate that the difference from the model is only several percent except for the cloud top if an appropriate wavenumber set is selected. The results from this study suggest that the present method can be applied to realistic remote sensing of the vertical profile of cirrus cloud particle size. 

Abstract We extend a stochastic aerosol‐snow albedo model to explicitly simulate dust internally/externally mixed with snow grains of different shapes and for the first time quantify the combined effects of dust‐snow internal mixing and snow nonsphericity on snow optical properties and albedo. Dust‐snow internal/external mixing significantly enhances snow single‐scattering coalbedo and absorption at wavelengths of <1.0 μm, with stronger enhancements for internal mixing (relative to external mixing) and higher dust concentrations but very weak dependence on snow size and shape variabilities. Compared with pure snow, dust‐snow internal mixing reduces snow albedo substantially at wavelengths of <1.0 μm, with stronger reductions for higher dust concentrations, larger snow sizes, and spherical (relative to nonspherical) snow shapes. Compared to internal mixing, dust‐snow external mixing generally shows similar spectral patterns of albedo reductions and effects of snow size and shape. However, relative to external mixing, dust‐snow internal mixing enhances the magnitude of albedo reductions by 10%–30% (10%–230%) at the visible (near‐infrared) band. This relative enhancement is stronger as snow grains become larger or nonspherical, with comparable influences from snow size and shape. Moreover, for dust‐snow external and internal mixing, nonspherical snow grains have up to ~45% weaker albedo reductions than spherical grains, depending on snow size, dust concentration, and wavelength. The interactive effect of dust‐snow mixing state and snow shape highlights the importance of accounting for these two factors concurrently in snow modeling. For application to land/climate models, we develop parameterizations for dust effects on snow optical properties and albedo with high accuracy.