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Radio signals transmitted from a satellite constellation and gathered by a ground-based Global Navigation Satellite System (GNSS) receiver allow computation of zenith tropospheric delay (ZTD), which is related to the atmospheric moisture. This study investigates the impact of assimilating ZTD obtained from a ground-based GNSS network on a numerical weather prediction model analyses and subsequent forecasts quality. The numerical data assimilation experiments are performed using three-dimensional variational data assimilation system in the Weather Research and Forecasting model, at 10-km horizontal grid spacing for the entire month of July 2017. A comparison with European Centre for Medium-Range Weather Forecast analyses shows a clear positive impact of ZTD assimilation on the lower to middle tropospheric moisture, upper air temperature, and middle and upper tropospheric wind; errors are reduced by as large as 4%, when compared to the model run without ZTD assimilation. The impact on the analyses and forecast quality of surface meteorological variables is mostly neutral with some indication of positive impact on surface pressure. An improvement in the rainfall forecasts is also noticed when model assimilates ZTD observations. In addition, the impact of the formulation of forward model, which calculates model equivalent of the GNSS ZTD, has been assessed on ZTD assimilation. A revised forward model has been implemented within the Weather Research and Forecasting assimilation system. The revised forward model outperforms the original model for ZTD assimilation. Overall result implies that GNSS ZTD data has a good potential for improving the weather prediction and advocates the strengthening of the ground-based GNSS network over the Indian region, which is currently very sparse.A number of satellites are currently equipped with humidity sensors, including Microwave Humidity Sounder, Special Sensor Microwave Imager Sounder, Advanced Microwave Scanning Radiometer, the Key Points:• A revised forward model has been implemented for the assimilation of zenith tropospheric delay (ZTD) observations into the WRF model • Assimilation of ZTD using the revised forward model shows higher positive impact as compared to the original observation operator • The assimilation of ZTD from ground-based GNSS receivers has a great potential to improve the weather prediction over the Indian regionCorrespondence to:

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