POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator

Abstract

This paper introduces a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), for evaluating cloud‐resolving models (CRMs). POLARRIS is composed of forward (POLARRIS‐f) and inverse (retrieval and diagnostic) components (iPOLARRIS) to generate not only polarimetric radar observables (Zh, Zdr, Kdp, ρhv) but also radar‐consistent geophysical parameters such as hydrometeor identification, vertical velocity, and rainfall rates retrieved from CRM data. To demonstrate its application and uncertainties, POLARRIS is applied to simulations of a mesoscale convective system over the Southern Great Plains on 23 May 2011, using the Weather Research and Forecasting model with both spectral bin microphysics (SBM) and the Goddard single‐moment bulk 4ICE microphysics. Statistical composites reveal a significant dependence of simulated polarimetric observables (Zdr, Kdp) on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. The simulated polarimetric variables differ considerably between the SBM and 4ICE microphysics in part due to the differences in their ice particle size distributions as revealed by comparisons with aircraft measurements. Regardless of these uncertainties, simulated hydrometeor identification distributions overestimate graupel and hail fractions, especially from the simulation with SBM. To minimize uncertainties in forward model, the particle shape and orientation angle distributions of frozen particles should be predicted in a microphysics scheme in addition to the size distributions and particle densities.

The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

“…Minimum size (µm) Maximum size (µm) Bin spacing (µm) Ice phase hydrometeors are assumed to be composed of ice and air in an ice matrix, and their effective dielectric constant is computed using the Maxwell Garnet mixing formula (Maxwell Garnet, 1904). The output radar reflectivity (Z hh ) for all hydrometeor species is the equivalent radar reflectivity, for which the computations adopt a dielectric factor of 0.92 for all hydrometeor species.…”

An Evaluation of Relationships between Radar-Inferred Kinematic and Microphysical Parameters and Lightning Flash Rates in Alabama Storms

“…Needless to say, cloud-resolving numerical models have their own random and bias errors in estimating the various kinematic and microphysical fields and those bias errors typically do not match observational studies, resulting in the need to apply scaling factors or other adjustments to apply observational-based relations to numerical models [43,45]. A suggestion for future work to mitigate impacts of observational radar error on flash rate parameterizations and their use in numerical cloud models is to adapt a self-consistent analysis and parameter retrieval framework with similar assumptions and the ability to generate self-consistent kinematic and microphysical parameters between radar and cloud-resolving modeling systems [94,95]. As part of this self-consistent radar-model analysis framework, it would be helpful to quantify more carefully the likely error sources of the input observations, perhaps as part of a data assimilation approach [95].…”

What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

“…Efforts to develop additional PRFOs have renewed over the past several years (Augros et al [68], Wolfensberger and Berne [69], Matsui et al [70], Mendrok et al [71], and Oue et al [72]). Augros et al [68] created a PRFO for the French nonhydrostatic mesoscale research NWP model Meso-NH (Lafore et al [73]).…”

“…Matsui et al [70] introduced a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), which generates polarimetric radar variables as well as vertical Doppler velocity, rain rate, and a synthetic hydrometeor classification product retrieved from cloud-resolving model output. The Cloud Resolving Model Radar Simulator (CR-SIM) (Oue et al [72]) produces polarimetric and Doppler radar moment variables and lidar observables for a wide range of radar and optical frequencies.…”