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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: This note reports on the effects of the polarization state of an incident quasi-monochromatic parallel beam of radiation and the orientation of a hexagonal ice particle with respect to the incident direction on the extinction process. When the incident beam is aligned with the six-fold rotational symmetry axis, the extinction is independent of the polarization state of the incident light. For other orientations, the extinction cross-section for linearly polarized light can be either larger or smaller than its counterpart for an unpolarized incident beam. Therefore, the attenuation of a quasi-monochromatic radiation beam by an ice cloud depends on the polarization state of the beam if ice crystals within the cloud are not randomly oriented. Furthermore, a case study of the extinction of light by a quartz particle is also presented to illustrate the dependence of the extinction cross-section on the polarization state of the incident light. [Copyright &y& Elsevier]

• Impacts of cloud scattering properties on FY-3D HIRAS simulations are assessed in ARMS and CRTM. • ARMS and CRTM simulated brightness temperatures are compared with HIRAS observations to provide quantitative evaluation. • Spherical ice cloud approximation has been found to be not appropriate for ARMS model simulations. Cloudy sky spectral radiance at the top of the atmosphere has always been an important while difficult variable to simulate for fast radiative transfer models. In this paper, we focus on examining the impacts of cloud scattering properties on the spectral radiance signature of the High-spectral Resolution Infrared Atmospheric Sounder (HIRAS) onboard the Fengyun-3D (FY-3D) satellite by using the Advanced Radiative transfer Modeling System (ARMS) and the Community Radiative Transfer Model (CRTM). Cloud scattering properties used in the radiative transfer models are critical for modeling the spectral radiance under cloudy sky, which involves choices of appropriate cloud particle models and particle size distributions, etc. Multiple FY-3D HIRAS observations over Southern China and Southeast Asia with ice or liquid water cloud cover on 6 May 2018 are examined, respectively. Vertical atmospheric profiles are derived from the Modern-Era Retrospective analysis for Research and Applications, Version 2 reanalysis product. Cloud property retrievals from the Moderate Resolution Imaging Spectroradiometer are used. Cloud scattering property parameterization schemes based on spherical and nonspherical cloud particle shapes are implemented for liquid water and ice clouds in ARMS and CRTM, respectively. Results show that both ARMS and CRTM can well simulate the radiance at the HIRAS spectral ranges under liquid water cloud condition as compared with the HIRAS observation with mean absolute error (MAE) of brightness temperature of less than 1 K. However, for ice cloud conditions, ARMS model using assumed spherical ice properties exhibits large biases between simulation and observation. CRTM with nonspherical ice properties using 16-stream approximation shows MAE less than 1 K and MAE of about 1 K using 2-stream approximation. [ABSTRACT FROM AUTHOR]

• An advanced radiative transfer modeling system has been developed for satellite data assimilation and remote sensing applications. • It focuses on the radiative transfer components for applications to Fengyun satellites. • The accuracy is validated against other model results and the measurements. An advanced radiative transfer modeling system (ARMS) has been developed for satellite data assimilation and remote sensing applications. It inherits the capability of other fast radiative transfer models developed mainly for US and European satellite programs but focuses on the radiative transfer components that are specific for the assimilation of the Fengyun satellites and those sensors not included in existing models. The ARMS forward operator includes a fast transmittance module, a new particle absorption and scattering look-up table, surface emissivity and polarimetric radiative transfer solver. The particle optical properties of aerosols and ice clouds are calculated based on a super-spheroidal T-matrix model. The polarimetric two-stream approximation is adopted as the preferred solver to simulate the Stokes vector and their Jacobians. The simulations of ARMS are compared with those of other models and observations of Fengyun satellites, respectively. The comparison shows close agreement between ARMS and other existing fast radiative transfer models. Therefore, ARMS has robust simulation capabilities for existing satellite sensors. [ABSTRACT FROM AUTHOR]