Constraining microphysics assumptions on the modeling of Atmospheric Rivers using GNSS Polarimetric Radio Occultations

Abstract. Improving the representation of precipitation in weather and climate models remains a major challenge, particularly due to uncertainties in microphysical parameterizations that govern hydrometeor characteristics and behavior. The Polarimetric Radio Occultation (PRO) technique enhances the standard Radio Occultation (RO) method by offering vertical profiles of both precipitation structure and thermodynamic atmospheric variables. PRO achieves this by utilizing two orthogonal polarizations – horizontal (H) and vertical (V) – to measure the differential phase shift (ΔΦ), which represents the difference in phase delay between the two of them. This study focuses on assessing the sensitivity of the PRO technique to the vertical structure of hydrometeors under different microphysical assumptions. To explore this sensitivity, simulations are conducted using the Weather Research and Forecasting (WRF) model, with particular attention to the effects of different microphysics schemes on the simulated ΔΦ. The study also incorporates the Atmospheric Radiative Transfer Simulator (ARTS) particle database to characterize hydrometeors based on their scattering properties. Atmospheric Rivers (ARs) are used as a case study. The ΔΦ values simulated under different microphysics schemes are compared to GNSS-PRO observational data from PAZ and Spire satellites, providing a means to evaluate the performance of the WRF microphysics parameterizations. A simplified forward operator is built in terms of water content (WC) and x-parameter (factor relating WC and specific differential phase shift, Kdp), and the best value for x is obtained through optimization techniques after comparing with actual ΔΦ observations. The lowest cost function values systematically correspond to Goddard and WSM6 microphysics (75 % of the cases). Similarly, the best choice for the x-parameter values approach ∼0.1 mm (kg m−2)−1. Once compared to the results from the ARTS particle database, the particle habits that best represent such relationship are bullet rosettes and snow aggregates.