Derived precipitable water vapour from GNSS and radiosonde data using time series and spatial least-square

ABSTRACT Precipitable water vapour (PWV) plays an important role in rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV. In this paper, radiosonde techniques are used to compute PWV’s spatial and temporal variations and GNSS (Global Navigation Satellite Systems) using in spatial only. GNSS data (GPS and GLONASS) from eight Egyptian stations were processed for the year 2014. Five radiosonde stations for the period from 2005 to 2016 were used. Time series is constructed using the daily surface measurements of radiosonde stations. The linear trend is estimated by straight line fit over 12 years of seasonally adjusted PWV time series. The PWV in Egypt has a positive trend in time series at more than five radiosonde sites with a rate of 0.3 mm/year. The monthly cycle is a near sine curve and the stochastic errors are from 0% to 5.4% over 12 years. The comparison between PWV estimated from GNSS data using the PPP approach and radiosonde data for each station in year 2014 was done in the near station. The nearest two stations, GNSS station “MTRH” and radiosonde station “62,306”, get a bias of 0.66 mm. Three common interpolation techniques (Inverse Distance Weighting, Kriging, and Minimum Curve) are used. The biases of the three used methods were 1.65 mm, 1.96 mm and 0.61 mm, respectively. The statistical methods of Minimum Curve interpolation are found superior to other methods with mean error at Mersa-Matrouh, Aswan and Al-Arish stations reaching 0.1 mm, 1.0 mm and 0.30 mm, respectively. The minimum curve technique is recommended in spatial interpolation for the prediction of PWV amount.Abbreviations: PWV: precipitable water vapour; PPP: precise point positioning; GNSS: global navigation satellite system; ZPD: tropospheric zenith path delay; ZWD: zenith wet delay; IDW: inverse distance weighting; MC: minimum curvature; IGS: International GNSS service.