Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment.

In the framework of the Multidisciplinary drifting Observatory for the Study of Arctic Climate Polarstern expedition, the Leibniz Institute for Tropospheric Research, Leipzig, Germany, operated the shipborne OCEANET-Atmosphere facility for cloud and aerosol observations throughout the whole year. OCEANET-Atmosphere comprises, amongst others, a multiwavelength Raman lidar, a microwave radiometer, and an optical disdrometer. A cloud radar was operated aboard Polarstern by the US Atmospheric Radiation Measurement program. These measurements were processed by applying the so-called Cloudnet methodology to derive cloud properties. To gain a comprehensive view of the clouds, lidar and cloud radar capabilities for low- and high-altitude observations were combined. Cloudnet offers a variety of products with a spatiotemporal resolution of 30 s and 30 m, such as the target classification, and liquid and ice microphysical properties. Additionally, a lidar-based low-level stratus retrieval was applied for cloud detection below the lowest range gate of the cloud radar. Based on the presented dataset, e.g., studies on cloud formation processes and their radiative impact, and model evaluation studies can be conducted.

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Modeling the scattering properties of mineral aerosols using concave fractal polyhedra.

The single-scattering properties of concave fractal polyhedra are investigated, with particle size parameters ranging from the Rayleigh to geometric-optics regimes. Two fractal shape parameters, irregularity and aspect ratio, are used to iteratively construct "generations" of irregular fractal particles. The pseudospectral time-domain (PSTD) method and the improved geometric-optics method (IGOM) are combined to compute the single-scattering properties of fractal particles over the range of size parameters. The effects of fractal generation, irregularity, and aspect ratio on the single-scattering properties of fractals are investigated. The extinction efficiency, absorption efficiency, and asymmetry factor, calculated by the PSTD method for fractal particles, with small-to-moderate size parameters, smoothly bridges the gap between those size parameters and size parameters for which solutions given by the IGOM may be used. Somewhat surprisingly, excellent agreement between values of the phase function of randomly oriented fractal particles calculated by the two numerical methods is found, not only for large particles, but in fact extends as far down in equivalent-projected-area size parameters as 25. The agreement in the case of other nonzero phase matrix elements is not as good at so small a size. Furthermore, the numerical results of ensemble-averaged phase matrix elements of a single fractal realization are compared with dust particle measurements, and good agreement is found by using the fractal particle model to represent data from a study of feldspar aerosols.

Microbial alignment in flow changes ocean light climate.

The growth of microbial cultures in the laboratory often is assessed informally with a quick flick of the wrist: dense suspensions of microorganisms produce translucent "swirls" when agitated. Here, we rationalize the mechanism behind this phenomenon and show that the same process may affect the propagation of light through the upper ocean. Analogous to the shaken test tubes, the ocean can be characterized by intense fluid motion and abundant microorganisms. We demonstrate that the swirl patterns arise when elongated microorganisms align preferentially in the direction of fluid flow and alter light scattering. Using a combination of experiments and mathematical modeling, we find that this phenomenon can be recurrent under typical marine conditions. Moderate shear rates (0.1 s(-1)) can increase optical backscattering of natural microbial assemblages by more than 20%, and even small shear rates (0.001 s(-1)) can increase backscattering from blooms of large phytoplankton by more than 30%. These results imply that fluid flow, currently neglected in models of marine optics, may exert an important control on light propagation, influencing rates of global carbon fixation and how we estimate these rates via remote sensing.

Influence of crystal tilt on solar irradiance of cirrus clouds.

The single and multiple scattering and absorption properties of hexagonal ice columns with different degrees of particle orientation are modeled in the solar spectral range by means of a ray-tracing single-scattering code and a Monte Carlo radiative-transfer code. The scattering properties are most sensitive to particle orientation for the solar zenith angles of 50 degrees (asymmetry parameter) and 90 degrees (single-scattering albedo). Provided that the ice columns are horizontally oriented, the usual assumption of random orientation leads to an overestimation (underestimation) of the reflected (transmitted) solar broadband radiation at high Sun elevation and to an underestimation (overestimation) at medium solar zenith angles. The orientation effect is more (less) pronounced in scattering and transmission (absorption) for smaller ice crystals.

Use of equivalent spheres to model the relation between radar reflectivity and optical extinction of ice cloud particles.

The effect of ice crystal size and shape on the relation between radar reflectivity and optical extinction is examined. Discrete-dipole approximation calculations of 95-GHz radar reflectivity and ray-tracing calculations are applied to ice crystals of various habits and sizes. Ray tracing was used primarily to calculate optical extinction and to provide approximate information on the lidar backscatter cross section. The results of the combined calculations are compared with Mie calculations applied to collections of different types of equivalent spheres. Various equivalent sphere formulations are considered, including equivalent radar-lidar spheres; equivalent maximum dimension spheres; equivalent area spheres, and equivalent volume and equivalent effective radius spheres. Marked differences are found with respect to the accuracy of different formulations, and certain types of equivalent spheres can be used for useful prediction of both the radar reflectivity at 95 GHz and the optical extinction (but not lidar backscatter cross section) over a wide range of particle sizes. The implications of these results on combined lidar-radar ice cloud remote sensing are discussed.