Impact of the variational assimilation of ground-based GNSS zenith total delay into AROME-Morocco model

Abstract

The impact of assimilating zenith total delay (ZTD) observations from the Moroccan ground-based Global Navigation Satellite System (GNSS) network into the high-resolution operational model AROME-Morocco (2.5 km) is assessed over one month. The objective is to investigate the impact on moisture field and rainy event forecasts in a three-dimensional variational (3D-Var) data assimilation framework with a 3-hour cycling. As a first step, a pre-processing of ZTD observations is performed for quality control and bias correction and it points out that all GNSS stations available in the network can be potentially assimilated. Then, two parallel experiments, with and without assimilation of GNSS ZTD, are performed during February–March 2018, for 48-hour lead times. Compared against other observation systems of humidity (radiosonde and surface network), a small and beneficial improvement is found in the atmospheric moisture short-range forecast, despite the limited number of GNSS stations over Morocco. The impact of assimilating GNSS ZTD data on precipitation forecasts is evaluated both subjectively and objectively. The objective precipitation scores against daily rain gauge observations show that the impact is mixed, positive for larger rainfall accumulations and neutral to negative for smaller rainfall accumulations. A specific evaluation for a case study of a rain event highlights an improvement in terms of intensity and location of precipitating areas when GNSS ZTD observations are assimilated.

Keywords

• data assimilation
• ground-based gnss
• zenith total delay
• mesoscale modelling
• numerical weather prediction