Parameterized Forward Operators for Simulation and Assimilation of Polarimetric Radar Data with Numerical Weather Predictions

Abstract

Many weather radar networks in the world have now provided polarimetric radar data (PRD) that have the potential to improve our understanding of cloud and precipitation microphysics, and numerical weather prediction (NWP). To realize this potential, an accurate and efficient set of polarimetric observation operators are needed to simulate and assimilate the PRD with an NWP model for an accurate analysis of the model state variables. For this purpose, a set of parameterized observation operators are developed to simulate and assimilate polarimetric radar data from NWP model-predicted hydrometeor mixing ratios and number concentrations of rain, snow, hail, and graupel. The polarimetric radar variables are calculated based on the T-matrix calculation of wave scattering and integrations of the scattering weighted by the particle size distribution. The calculated polarimetric variables are then fitted to simple functions of water content and volume-weighted mean diameter of the hydrometeor particle size distribution. The parameterized PRD operators are applied to an ideal case and a real case predicted by the Weather Research and Forecasting (WRF) model to have simulated PRD, which are compared with existing operators and real observations to show their validity and applicability. The new PRD operators use less than one percent of the computing time of the old operators to complete the same simulations, making it efficient in PRD simulation and assimilation usage.

A New Melting Model and Its Implementation in Parameterized Forward Operators for Polarimetric Radar Data Simulation With Double Moment Microphysics Schemes

“…The polarimetric radar variables for all species are computed using Equations 9-12 from Mahale et al (2019) for rain and Equations 7-10 above for all other species. Subsequently, the final variables for a grid box containing multiple species are obtained through summation across all species, following Equations 22-25 provided by Zhang et al (2021).…”

“…PFOs are a set of parameterized relations between the polarimetric radar variables and the model state parameters, which are derived through scattering calculations and fitting procedures. The PFOs used in this study were developed and documented in Zhang et al (2021), which are summarized as follows.…”

“…In this study, two distinct implementations of parameterized polarimetric radar forward operators are applied, focusing on the simulation of polarimetric radar variables for the real MCS case. Both implementations employ the Zhang et al (2021) parameterized polarimetric radar forward operators described in Section 2.4.1. However, the original implementation, PFO_Old, utilizes the "old" melting model of described in Section 2.4.2, while the updated implementation, PFO_New, utilizes the new melting model described in Section 2.4.3.…”

“…introduced a melting model to account for the presence of melting ice particles by assuming mixed-phase particles to exist only when rain and dry ice species coexist and redistributing the mixing ratios of the rain and dry species to form the mixed-phase species. This melting model was used in Zhang et al (2021) for PRD simulations. However, assumed the N t of the melting species to be that of the corresponding dry species.…”

Assimilation of Polarimetric Radar Data in Simulation of a Supercell Storm with a Variational Approach and the WRF Model

“…Recently, Zhang et al [53] (hereafter Z21) developed a new set of simplified and parameterized PRD observation operators which can link NWP model state variables and PRD for DA use, and verified its validity and applicability by applying an ideal case and a real case respectively. They found that the parameterized operators yield results consistent with that of rigorous calculation in J10.…”