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Article

Atmospheric Water Vapour Determination Using Gps Signals for Numeric Weather Prediction in Tanzania

1Department of Geospatial Sciences and Technology (DGST), School of Earth Sciences Real Estate Business and Informatics (SERBI), Ardhi University, Dar Es Salaam, Tanzani


Journal of Geosciences and Geomatics. 2023, Vol. 11 No. 3, 88-96
DOI: 10.12691/jgg-11-3-3
Copyright © 2023 Science and Education Publishing

Cite this paper:
Mlawa, A., Saria, E. E. Atmospheric Water Vapour Determination Using Gps Signals for Numeric Weather Prediction in Tanzania. Journal of Geosciences and Geomatics. 2023; 11(3):88-96. doi: 10.12691/jgg-11-3-3.

Correspondence to: Saria,  E. E, Department of Geospatial Sciences and Technology (DGST), School of Earth Sciences Real Estate Business and Informatics (SERBI), Ardhi University, Dar Es Salaam, Tanzani. Email: saria.elifuraha@gmail.com

Abstract

Atmospheric water vapour (AWV) is one of the parameters that affect GNSS signals in the troposphere, however this parameter is very important conservatory gas which helps to maintaining Earth’s energy balance and the hydrological cycle. The AWV is one of the fundamental meteorological parameter in numeric weather prediction. In many years this parameter has been computed using conventional methods including radiosondes, microwave radiometer, and hygrometers. However, these methods are facing numerous challenges including inadequacy, low spatial and temporal resolution and high maintenance cost. Given the high investment required and maintenance cost, the Tanzania Meteorological Agency (TMA) had only four radiosondes across the country. With advances in technology Global Navigation Satellite system (GNSS) are replacing the conventional methods due to its capability to determine Precipitable Water (PW) or Integrated Water Vapour (IWV) at low cost. The aim of this study is to use a yearlong GNSS data from Dodoma CORS station in Tanzania to compute PW or IWV and compare with global weather models. The results from this comparison will help TMA to decide on better methods for weather prediction. In this study, the datasets were processed using gLAB and GAMIT/GLOBK software based on two processing strategies weather free and weather dependent approaches. The results from this processing were analyzed against Global weather model particularly the products from ECMWF Reanalysis - Interim (ERA-Interim). The result shows that GNSS results from gLAB and GAMIT/GLOBK have good agreement with a correlation <0.98 while between GNSS and the ERA-Interim model values shows a correlation <0.96. Given these correlations, this study provides great indication of how GNSS data can be used to retrieve the key meteorological values for weather prediction in Tanzania and provide great assistance to the Tanzania Meteorological Agency (TMA).

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