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• Machine learning excelled at extrapolating optical properties of non-spherical particles with larger size parameters. • Deep Neural Networks (DNN) outperformed the improved geometric optics method for particles with moderate size parameters, accounting for edge effects. • DNN efficiently computed optical properties of super-spheroids across a wide range of size parameters. This study investigates the use of machine learning techniques, specifically deep neural networks (DNN), to compute the optical properties of non-spherical particles across a wide range of size parameters. The approach involves training a DNN using a T-matrix database of super-spheroids with size parameters below 50. The DNN is then able to predict optical properties for size parameters beyond this limit, with exceptional accuracy observed for size parameters between 50–100. These predictions outperform the improved geometric optics method (IGOM). To further enhance accuracy and broaden the range of size parameters, databases are merged, combining the T-matrix results for small (0.1–50) and some moderate size parameters (50–100), the DNN predicted values for moderate size parameters (50–100), and the IGOM results for large size parameters (>100). This merged database is used to train a new DNN. This comprehensive training enables the neural networks to calculate the optical properties for super-spheroids across the entire size parameter spectrum, considering various shape parameters and refractive indices. This technique effectively bridges the gap between full-electromagnetic wave results and geometric-optics approximations, providing an efficient method for computing the optical properties of non-spherical particles from Rayleigh to geometric optics domains. Notably, the DNNs automatically consider edge effects, eliminating the need for deriving complex analytical formulas for non-spherical particles. [ABSTRACT FROM AUTHOR]

To derive the bulk radiative properties of ice clouds, aircraft contrails and snow grains, which are fundamental to atmospheric radiative transfer calculations in downstream applications, it is necessary to accurately simulate the scattering of light by individual ice particles. An ice particle optical property database reported in 2013 (hereafter, TAMUice2013) is updated (hereafter, TAMUice2016) to incorporate recent advances in computation of the optical properties of nonspherical particles. Specifically, we employ the invariant imbedding T-matrix (II-TM) method to compute the optical properties of particles with small to moderate size parameters. Both versions use the Improved Geometric Optics Method (IGOM) to compute the optical properties of large ice crystals, but TAMUice2016 improves the treatment of inhomogeneous waves inside the scattering particles in the case where ice is absorptive such as at infrared wavelengths. To bridge the gap between the extinction efficiencies computed from the II-TM and the IGOM, TAMUice2016 includes spectrally dependent higher order terms of the edge effect in addition to the first order counterpart considered in TAMUice2013. Furthermore, the differences between TAMUice2013 and TAMUice2016 are quantified with respect to the computation of the bulk optical properties of ice clouds. [ABSTRACT FROM AUTHOR]

Understanding the inherent optical properties (IOPs) of coccoliths and coccolithophores is important in oceanic radiative transfer simulations and remote sensing implementations. In this study, the invariant imbedding T-matrix method (II-TM) is employed to investigate the IOPs of coccoliths and coccolithophores. The Emiliania huxleyi ( Ehux ) coccolith and coccolithophore models are built based on observed biometric parameters including the eccentricity, the number of slits, and the rim width of detached coccoliths. The calcification state that specifies the amount of calcium of a single coccolith is critical in the determination of the size–volume/mass relationship (note, the volume/mass of coccoltihs at different calcification states are different although the diameters are the same). The present results show that the calcification state, namely, under-calcification, normal-calcification, or over-calcification, significantly influences the backscattering cross section and the phase matrix. Furthermore, the linear depolarization ratio of the light scattered by coccoliths is sensitive to the degree of calcification, and provides a potentially valuable parameter for interpreting oceanic remote sensing data. The phase function of an ensemble of randomly oriented coccolithophores has a similar pattern to that of individual coccoliths, but the forward scattering is dominant in the coccolithophores due to the large geometric cross sections. The linear depolarization ratio associated with coccolithophores is found to be larger than that for coccoliths as polarization is more sensitive to multiple scattering than the phase function. The simulated coccolithophore phase matrix numerical results are compared with laboratory measurements. For scattering angles larger than 100°, an increase of the phase function with respect to the scattering angle is confirmed based on the present coccolithophore model while the spherical approximation fails. [ABSTRACT FROM AUTHOR]

Abstract: 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-TM+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-TM+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 2.13μm) 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 12μm, 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 10Wm−2. [Copyright &y& Elsevier]

Abstract: The invariant imbedding T-matrix method (II-TM) is employed to compute the optical properties of randomly oriented ice crystals of various shapes including hexagonal columns, hollow columns, droxtals, bullet rosettes and aggregates. The II-TM is shown to be numerically stable and capable of obtaining the single-scattering properties of hexagonal ice crystals with size parameters up to 150. The 22° and 46° halo peaks in the phase function of compact hexagonal ice crystals begin to emerge at a size parameter of approximately 80 and tend to become insensitive to particle size as the corresponding size parameter approaches 150. Furthermore, the II-TM solutions are shown to be in agreement with their counterparts based on the discrete dipole approximation (DDA) method and the pseudo-spectral time-domain (PSTD) method. In addition, the accuracy of the improved geometric-optics method (IGOM) is examined for randomly oriented hexagonal ice crystal cases over a wide size-parameter range from the resonant to geometric-optics regimes. The II-TM is also used to study the effects of particle surface roughness and internal inclusions on the single-scattering properties of ice particles. [Copyright &y& Elsevier]

• The optical properties of dust particles associated with three sets of refractive indices were compared in a spectrum region (650–1135 cm−1). • The refractive indices have a clear impact on the spectrum slope of brightness temperature. • The refractive index impacts on bright temperature are essentially associated with the height of dust layer and the aerosol optical thickness. In this paper, we modeled dust impacts on atmospheric radiative transfer in the thermal infrared region of 650–1135 cm−1 by using the radiative transfer for TOVs model (RTTOV). We assessed three sets of Asian dust refractive indices (the Volz refractive index implemented in the RTTOV as default, and the Gobi and Taklamakan refractive indices) for brightness temperature simulations. The US 76 standard profile was employed to represent the atmospheric status. Three scenarios of high (532.6~575.2 hPa), middle (661~703.6 hPa) and low (786.3~825.8 hPa) dust layers and four cases of aerosol optical thickness (AOT) (0.1, 0.5, 1.0, and 1.5 at 1000 cm−1) were considered in the simulations. It was found that the refractive indices have a clear impact on simulating the values and the spectral slope of brightness temperature in the mid-thermal infrared band. Brightness temperature difference (BTD) for different refractive indices (Gobi/Taklamakan–Volz) increases with the height of dust layer and the AOT. The BTD reaches ~4 K for the high dust layer (532.6~575.2 hPa) and the AOT of 1.5. Most BTDs (0.5–4 K) are much larger than the noise-equivalent temperature difference of high-spectral resolution infrared sounders. Even for the AOT of 0.1, BTDs for different refractive indices could be close to or larger than 0.2 K. This study emphasizes the requirement of accurate refractive indices according to dust origins for improving brightness temperature simulations and provides valuable references for potential improvement of dust retrievals. [ABSTRACT FROM AUTHOR]