TOMOREF Operator for Assimilation of GNSS Tomography Wet Refractivity Fields in WRF DA System. Issue 17 (4th September 2020) - Trzcina, Estera
Abstract: Global Navigation Satellite System (GNSS) tomography is a technique that aims to obtain a 3‐D field of humidity in the troposphere. It is based on observations of GNSS signal delays between satellites and ground‐based receivers. The technique has been developed in recent years, showing positive results in the monitoring of severe weather events. The previous studies on assimilation into the numerical weather prediction models are based on available observation operators which are not adjusted to the GNSS tomography data. In this study, we demonstrate an observation operator TOMOREF dedicated to the assimilation of the GNSS tomography‐derived 3‐D fields of wet refractivity in a Weather Research and Forecasting (WRF) Data Assimilation (DA) system. The new tool has been tested based on wet refractivity fields 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 GNSS tomography data assimilation on the forecast of relative humidity (RH) has been noticed (an improvement of root‐mean‐square error up to 0.5%). Moreover, the validation of the precipitation forecasts reveals the positive impact of the GNSS data assimilation within 1 hr after assimilation (the mean bias values are reduced up to 0.1 mm). Additionally, it was observed that assimilation of GNSS tomography data has a greater influence on the WRF model than the Zenith Total Delay (ZTD) observations, which proves the potential of the GNSS tomography data for weather forecasting. Key Points: TOMOREF operator for assimilation of the 3‐D fields of wet refractivity was developed Mean bias of precipitation is reduced up to 0.1 mm within 1 hr after assimilation The use of the TOMOREF operator decreases the relative humidity root‐mean‐square up to 0.5%