Assimilating Dense Ground-based GNSS ZTD Observations for Improving Afternoon Thunderstorm Prediction in Taiwan

The Global Navigation Satellite System (GNSS) zenith total delay (ZTD) can provide fast-changing moisture information and is recognized as an important observation to capture the precursor of convection initialization for improving the short-term precipitation prediction. A WRF-based convective-scale ensemble data assimilation (EDA) system has been used to assimilate the GNSS ZTD observations in Taiwan and to study its impact on predicting the afternoon thunderstorm in the Taipei basin.

In addition to the 118 GNSS stations maintained by the Central Weather Administration (CWA), there are also more than 400 non-CWA GNSS stations deployed in Taiwan for purposes like geodesy. This provides a very dense ZTD observation network in the Taipei metropolitan area with a spatial resolution of 10 km. Most importantly, some non-CWA ZTD observations are available over the coast of northwestern Taiwan and the complex terrain surrounding the Taipei Basin. A preliminary investigation of a severe afternoon thunderstorm on 24 June 2022 in the Taipei Basin shows that the non-CWA ZTD data captures the high moisture concentration before the convection initialization. Results show that assimilating these data compensates for the limitation of assimilating the CWA ZTD. Combined with the 10-meter wind, the moisture transport from upstream can be better depicted. Consequently, the location and intensity of heavy rainfall prediction are significantly improved. More results on observation error, quality control, and earlier prediction will be discussed in the presentation.