Ziyue Huang, Hanyu Lu, Ziqiang Ma, Yining Shi, Yang Han, Hao HU, Jun Yang. 2024: A nonspherical cloud scattering database using aggregates of roughened bullet rosettes model for the advanced radiative transfer modeling system (ARMS). Adv. Atmos. Sci., https://doi.org/10.1007/s00376-024-4117-7
Citation: Ziyue Huang, Hanyu Lu, Ziqiang Ma, Yining Shi, Yang Han, Hao HU, Jun Yang. 2024: A nonspherical cloud scattering database using aggregates of roughened bullet rosettes model for the advanced radiative transfer modeling system (ARMS). Adv. Atmos. Sci., https://doi.org/10.1007/s00376-024-4117-7

A nonspherical cloud scattering database using aggregates of roughened bullet rosettes model for the advanced radiative transfer modeling system (ARMS)

  • Accurate satellite data assimilation under all-sky conditions requires enhanced parameterization of scattering properties for frozen hydrometeors in clouds. This study aims to develop a nonspherical scattering look-up table that contains the optical properties of five hydrometeor types: rain, cloud water, cloud ice, graupel, and snow, for the Advanced Radiative Transfer Modeling System (ARMS) at frequencies below 220 GHz. To compute the single-scattering properties of solid cloud particles, the discrete dipole approximation (DDA) method is employed, modeling these particles as aggregated roughened bullet rosettes. The bulk optical properties of the cloud layer are derived by integrating the single-scattering properties with a modified Gamma size distribution, specifically for distributions with 18 effective radii. The bulk phase function is then projected onto a series of generalized spherical functions, applying the delta-M method for truncation. The results indicate that simulations using the newly developed nonspherical scattering look-up table show good agreement with observations under deep convection conditions. In contrast, assuming spherical solid cloud particles leads to excessive scattering at mid-frequency channels and insufficient scattering at high-frequency channels. This improvement in radiative transfer simulation accuracy for cloudy conditions will better support the assimilation of all-sky microwave observations into numerical weather prediction models.
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