IMPLEMENTATION OF SELF-SIMILAR RAYLEIGH-GANS APPROXIMATION INTO PASSIVE MICROWAVE RADIATIVE TRANSFER SIMULATIONS

D. Kim¹, D. Shin¹

¹Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea

Abstract

Cloud microphysics (MP) assumptions play a critical role in passive microwave radiative transfer (RT) simulations. Particularly, realistic assumptions for frozen hydrometeors and physical consistency throughout the simulation are essential for achieving accuracy. Morrison and Milbrandt (2015) proposed a method to capture the inhomogeneity of frozen hydrometeors using flexible particle size distribution (PSD) and density parameterizations. Meanwhile, particle-scattering models such as the Discrete Dipole Approximation (DDA) have been used to calculate the single-scattering properties of nonspherical particles explicitly. However, incorporating these advanced MP assumptions into Radiative Transfer Models (RTMs) while preserving physical consistency remains challenging. Neglecting either realism or consistency of MP assumptions can introduce significant uncertainty in simulated brightness temperatures (TBs).

This study presents a method to reconcile the realism and consistency of MP assumptions throughout the RT simulation. MP configuration based on the Prediction of Particle Properties (P3) scheme is incorporated into the RTM scattering module to represent the inhomogeneous PSD and density of frozen hydrometeors. For the single-scattering properties of nonspherical particles, we employ a scattering database based on the Self-Similar Rayleigh-Gans Approximation (SSRGA; Ori et al., 2021). To improve physical consistency, the optimal habit selection method by Kim et al. (2024) is applied. This method also enables a flexible representation of nonspherical particle shapes. Input atmospheric fields from Weather Research and Forecasting (WRF) model simulations with the P3 scheme are utilized to maintain physical consistency with the RTM.

Results show that the combined implementation of the P3-based density parameterization, the SSRGA scattering database, and the optimal habit selection method effectively reconciles the realism and consistency of MP assumptions in RT simulations. The simulated TBs show good agreement with Global Precipitation Measuring Mission (GPM) Microwave Imager (GMI) TB measurements. Consequently, this approach shows promise for RTM applications in cloud-precipitation property retrievals and all-sky data assimilation.

References

1. H. Morrison and J. A. Milbrandt, “Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part I: Scheme description and idealized tests,” J. Atmos. Sci., vol. 72, no. 1, pp. 287–311, 2015.

2. D. Ori, L. Terzi, M. Karrer and S. Kneifl, “snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh-Gans approximation”, Geosci. Model Dev., vol. 14, pp. 1511-1531, 2021.

3. J. Kim, D.-B. Shin and D. Kim, “Effects of inhomogeneous ice particle habit distribution on passive microwave radiative transfer simulations,” IEEE Trans. Geosci. Remote Sens., vol. 62, 2024.