Water vapor over Europe obtained from remote sensors and compared with a hydrostatic NWP model

Abstract

Due to its high-variability water vapor is a crucial parameter in short-term numerical weather prediction. Integrated water vapor (IWV) data obtained from a network of groundbased Global Positioning System (GPS) receivers mainly over Germany and passive microwave measurements of the Advanced Microwave Sounding Unit (AMSU-A) are compared with the high-resolution regional weather forecast model HRM of the Deutscher Wetterdienst (DWD). Time series of the IWV at 74 GPS stations obtained during the first complete year of the GFZ/GPS network between May 2000 and April 2001 are applied together with colocated forecasts of the HRM model. The low bias (0.08 kg/m 2) between the HRM model and the GPS data can mainly be explained by the bias between the ECMWF analysis data used to initilize the HRM model and the GPS data. The IWV standard deviation between the HRM model and the GPS data during that time is about 2.47 kg/ m 2 . GPS stations equipped with surface pressure sensors show about 0.29 kg/ m 2 lower standard deviation compared with GPS stations with interpolated surface pressure from synoptic stations. The NOAA/NESDIS Total Precipitable Water algorithm is applied to obtain the IWV and to validate the model above the sea. While the mean IWV obtained from the HRM model is about 2.1 kg/ m 2 larger than from the AMSU-A data, the standard deviations are 2.46 kg/ m 2 (NOAA-15) and 2.29 kg/ m 2 (NOAA-16) similar to the IWV standard deviation between HRM and GPS data.