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Browsing Doctoral by Author "Acheampong, Akwasi Afrifa"

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    Retrieval of integrated water vapour from GNSS signals for numerical weather predictions
    (2016-10-25) Acheampong, Akwasi Afrifa
    Atmospheric Water vapour is an important greenhouse gas and contributes greatly in maintaining the Earth's energy balance. This critical meteorological parameter is not sensed by any facility in Ghana contributing weather data to the Global Telecommunication System of WMO. This thesis presents a highly precise tool for water vapour sensing based on the concept of Global Navigation Satellite Systems (GNSS) meteorology and tests the computed results against global reanalysis data. Conventional approaches used to sense the atmospheric water vapour or precipitable water (PW) or Integrated Water Vapour such as radiosondes, hygrometers, microwave radiometers or sun photometers are a ected by meteorological conditions, expensive and have coverage limitations. However, GNSS meteorological concept o ers an easier, inexpensive and all-weather technique to retrieve PW or IWV from Zenith Tropospheric Delays over a reference station with very high temporal resolutions. This study employed precise point positioning (PPP) techniques to quantify the extent of delays on the signal due to the troposphere and stratosphere media where the atmospheric water vapour resides. The KNUST GPS Base station was used to log dual-frequency signals for approximately 260 days between the months of February 2013 to December 2014. Stringent processing criteria were set using an elevation cut-o of 5 o , precise orbital and clock products, Antex les, nominal tropospheric correction and mapping functions. The delays which were originally slanted are mapped unto the zenith direction and integrated with surface meteorological parameters to retrieve PW or IWV. This research work investigated the applications of ground-based GNSS to meteorology and gives all correction models implemented in PPP and for Tropospheric delay estimation.The gLAB software was used for ZTD computations. PW values obtained were compared with ERA-Interim, Japanese Meteorological Agency Reanalysis (JRA) and National Centres for Environmental Prediction (NCEP) global reanalysis data. Correlation analysis were run on computed PW from logged GNSS datasets and downscaled reanalysis data. The obtained results show stronger correlation between the retrieved PW values and those provided by the ERAinterim. The computed amount of ZTDs varies perfectly with weather pattern in the country. Again, a linear-model was derived that could predict PW based on ZTD with standard errors of 6.01 mm for JRA, 5.40 mm for ERA-Interim and 6.34 mm for NCEP reanalysis data. Finally, the study results indicate that with a more densi ed network of GNSS base stations the retrieved PW or IWV will greatly improve numerical weather predictions and more speci cally precipitation forecasting in Ghana.