From model to radar variables: a new forward polarimetric radar operator for COSMO

Abstract

Abstract. In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows estimation of the full Doppler spectrum, as well a melting scheme which allows representing the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational onemoment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

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]).…”

“…Beam broadening and bending are accounted for along with attenuation in rain. Wolfensberger and Berne [69] developed an advanced PRFO for COSMO, and Mendrok et al [71] reported on the progress to add polarimetric capabilities to the Efficient Modular Volume scanning RADar Operator (EMVORADO; Zheng et al [74]) in COSMO and the ICOsahedral Nonhydrostatic model (ICON). These PRFOs include the effects of beam broadening, with the latter two computing Doppler radar variables (including the Doppler spectrum in Wolfensberger and Berne [69]).…”

“…Wolfensberger and Berne [69] developed an advanced PRFO for COSMO, and Mendrok et al [71] reported on the progress to add polarimetric capabilities to the Efficient Modular Volume scanning RADar Operator (EMVORADO; Zheng et al [74]) in COSMO and the ICOsahedral Nonhydrostatic model (ICON). These PRFOs include the effects of beam broadening, with the latter two computing Doppler radar variables (including the Doppler spectrum in Wolfensberger and Berne [69]). Similar to Jung et al [51] and Dawson et al [64], the Wolfensberger and Berne forward operator generates an artificial class of melting particles.…”

Combined use of volume radar observations and high-resolution numerical weather predictions to estimate precipitation at the ground: methodology and proof of concept

“…These errors are of three kinds: (i) measurement errors of the radar moments (Z, Z dr , φ dp ), (ii) conversion errors in the quantitative precipitation estimation of the precipitation from the radar moments and (iii) extrapolation errors in the determination of the precipitation falling at the ground from the estimations obtained at beam heights. In recent years, significant progress has been made to reduce the first two types of errors by better controlling the quality of the polarimetric parameters (calibration of Z and Z dr , adaptive smoothing of φ dp , attenuation correction) (Bringi et al, 2001;Gourley et al, 2009;Yu et al, 2018) and by combining the polarimetric moments to estimate the precipitation with minimal uncertainty (Ryzhkov et al, 2005;Tabary et al, 2011;Figueras i Ventura et al, 2012). However, the final step of estimating the precipitation at the ground remains a major challenge in particular in mountainous regions where lower beams can be partially or totally blocked (Creutin et al, 1997;Smith, 1998).…”

“…Previous studies have shown that synthetic yet realistic radar observations can be obtained by applying a radar simulator to model outputs (Caumont et al, 2006;Jung et al, 2008;Pfeifer et al, 2008;Ryzhkov et al, 2011;Wolfensberger and Berne, 2018). The VPR estimation and correction is a major step in radar data processing that determines the quality of radar precipitation that would be observed at the ground.…”