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.

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþ IGOM are considered as a benchmark because the II-TM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþ IGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 μm) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 μm, biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10 W m À 2 .

Cavities under urban roads have increasingly become a great threat to the traffic safety in many cities. As a quick, effective, and high-resolution geophysical method, ground penetrating radar (GPR) has been widely used to detect and image near-surface objects. However, the interpretation of field GPR data is still challenging. For example, it is hard to distinguish reflections caused by road cavities or other urban utilities by a conventional 2D GPR survey. The superiority of 3D GPR in data interpretation is demonstrated by a laboratory experiment. Two pipes and a glass-made cavity buried in a sandpit show similar hyperbolic reflections in the 2D GPR profiles, and are hard to be discriminated. In contrast, their geometric shapes and dimensions are readily identified in the 3D image reconstructed from the synthetic 3D GPR dataset. Thus, a car-mounted 3D GPR system with two antenna arrays oriented in different polarization directions is developed, and has detected over 100 cavities in three Chinese cities over the past one year. The field data of two of the cavities are presented. As a result, the cavity depth, horizontal size and height can be accurately estimated from the 3D GPR dataset. Both laboratory and field experimental results indicate that 3D GPR possesses a great potential in detection and recognition of road cavities and utilities in the complicated urban environment.

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The Moon reflects sunlight like a huge mirror hanging in the sky at night, which presents the obviously periodical changes in its luminance or irradiance due to Sun‐Earth‐Moon geometry variation. The potential effect of the periodical changes in lunar phase angle on nighttime Day/Night Band (DNB) radiative transfer simulation in the presence of cloud has seldom been reported thus far. In this study, a radiative transfer model is developed by coupling the lunar light source with various Sun‐Earth‐Moon geometries. To elucidate the stability of DNB‐averaged cloud bulk scattering properties, we simulate nighttime reflectance and radiances under four typical lunar phase angles (0°, 45°, 90°, and 135°) from 7 April 2016 to 8 May 2016 (e.g., two lunar cycles). Explicit simulation analyses indicated that DNB‐averaged cloud bulk scattering properties exhibit weak sensitivity to lunar phase angles. The maximum DNB reflectance differences between any and 90° lunar phase angles are less than 0.05% (0.01%) in the presence of water (ice) clouds, indicating a negligible effect of periodically changes on lunar spectral irradiances. Our findings suggest that the differences of reflectance at lunar phase angle = 90° are less than approximately 0.05% (water cloud)/0.01% (ice cloud), much smaller than 11% radiometric calibration uncertainties of DNB. This means that these differences could be ignored in both nighttime cloud property retrieval and DNB radiative transfer modeling.