Precipitable Water Comparisons Over Ghana using PPP Techniques and Reanalysis Data

Abstract

Atmospheric Water vapor is an important greenhouse gas and contributes greatly in maintaining the Earth’senergy balance. This critical meteorological parameter is not being sensed by any of the 22 synoptic weatherstations in Ghana. This study presents a highly precise tool for water vapor sensing based on the concept GlobalNavigation Satellite Systems (GNSS) meteorology and tests the computed results against global reanalysis data.Conventional approaches used to sense the atmospheric water vapor or precipitable water (PW) such as such asradiosondes, hygrometers, microwave radiometers or sun photometers are affected by meteorological conditionsand expensive. Whereas GNSS meteorological concept offers an easier, inexpensive and all-weather technique toretrieve Precipitable Water (PW) or Integrated water vapor (IWV) from zenith tropospheric delays (ZTD) overa reference station. This study employed precise point positioning (PPP) techniques to quantify the extendof delays on the signal due to the troposphere and stratosphere where the atmospheric water vapor resides.Stringent processing criteria were set using an elevation cut-off of 5 degrees, precise orbital and clock products,nominal tropospheric correction and mapping functions. The delays which are originally slanted are mappedunto the zenith direction and integrated with surface meteorological parameters to retrieve PW or IWV. ThegLAB software, Canadian Spatial Reference System (CSRS) and Automatic Precise Positioning Service (APPS)online PPP services were the approaches used to compute ZTD. PW values obtained were compared with JRA,ERA-interim and NCEP global reanalysis data. Correlation analysis were run on the logged station data usingthe three approaches and global reanalysis data. The obtained results show stronger correlation between theretrieved PW values and those provided by the ERA-interim. Finally, the study results indicate that with amore densified network of GNSS base stations the retrieved PW or IWV will greatly improve numerical weatherpredictions in Ghana.