TOMOREF Operator for Assimilation of GNSS Tomography Wet Refractivity Fields in WRF DA System

Abstract

Global Navigation Satellite System (GNSS) tomography is a technique that aims to obtain a3-D field of humidity in the troposphere. It is based on observations of GNSS signal delays betweensatellites and ground-based receivers. The technique has been developed in recent years, showing positiveresults in the monitoring of severe weather events. The previous studies on assimilation into the numericalweather prediction models are based on available observation operators which are not adjusted to theGNSS tomography data. In this study, we demonstrate an observation operator TOMOREF dedicated to theassimilation of the GNSS tomography-derived 3-D fields of wet refractivity in a Weather Research andForecasting (WRF) Data Assimilation (DA) system. The new tool has been tested based on wet refractivityfields derived during a heavy precipitation event. The results were validated using radiosonde observations,synoptic data, ERA5 reanalysis, and radar data. In the presented experiment, a positive impact of the GNSStomography data assimilation on the forecast of relative humidity (RH) has been noticed (an improvementof root-mean-square error up to 0.5%). Moreover, the validation of the precipitation forecasts reveals thepositive impact of the GNSS data assimilation within 1 hr after assimilation (the mean bias values arereduced up to 0.1 mm). Additionally, it was observed that assimilation of GNSS tomography data has agreater influence on the WRF model than the Zenith Total Delay (ZTD) observations, which proves thepotential of the GNSS tomography data for weather forecasting.