skip to main content

Modelling Precipitable Water Vapour (PWV) Over Nigeria from Ground-Based GNSS

*Bawa Swafiyudeen  -  Ahmadu Bello University, Zaria, Nigeria, Nigeria
Usman Ibrahim Sa'i  -  Ahmadu Bello University, Zaria, Nigeria, Nigeria
Adamu Bala  -  Ahmadu Bello University, Zaria, Nigeria, Nigeria
Aliyu Zailani Abubakar  -  Ahmadu Bello University, Zaria, Nigeria Department of geomatics (Lecturer 11), Nigeria
Adamu Abubakar Musa  -  Department of Surveying and Geoinformatics, Nuhu Bammalli Poly, Zaria, Kaduna, Nigeria, Nigeria
Nura Shehu  -  Department of Surveying and Geoinformatics, Nuhu Bammalli Poly, Zaria, Kaduna, Nigeria, Nigeria

Citation Format:
Abstract

Global Navigational Satellite System (GNSS) over the past and present time has shown a great potential in the retrieval of the distribution of water vapour in the atmosphere.  Taking the advantage of the effect of the atmosphere on GNSS signal as they travel from the constellation of satellite to ground-based GNSS receivers such that information (water vapour content) about the atmosphere (mostly from the troposphere) can be derived is referred to as GNSS meteorology. This paper presents the spatiotemporal variability of Precipitable Water Vapour (PWV) retrieved from ground–based Global Navigation Satellite System (GNSS) stations over Nigeria for the years 2012 to 2013. In this paper, the GNSS data were processed using GAMIT (ver. 10.70). The GNSS PWV were grouped into daily and monthly averages; the variability of the daily and monthly GNSS PWV were compared and validated with the daily and monthly PWV from National Centre for Environmental Prediction (NCEP) and monthly Rainfall data for the study years respectively. The results revealed that the spatiotemporal variability of PWV across Nigeria is a function of geographic location and seasons. The result shows that there is temporal correlation between GNSS PWV, NCEP PWV and rainfall events. The research also affirms that GNSS PWV could be used to improve weather forecasting/monitoring as well as climate monitoring.

Fulltext View|Download
Keywords: NCEP, GNSS, Water Vapour, NigNet, Rainfall

Article Metrics:

  1. Bawa, S., Ojigi, L. M., & Dodo, J. D. (2017). GPS velocity time series of NigNET CORS. Nigeria Association of Geodesy (NAG) General Assembly/Scientific Conference Rivers State University, Port-Harcourt, Nigeria, 24–27.

  2. Bevis, M., Businger, S., Chiswell, S., Herring, T. A., Anthes, R. A., Rocken, C., & Ware, R. H. (1994). GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water. Journal of Applied Meteorology, 33(3), 379–386. [https://doi.org/10.1175/1520-0450(1994)033%3c0379:gmmzwd%3e2.0.co;2">Crossref]

  3. Bevis, M., Businger, S., Herring, T. A., Rocken, C., Anthes, R. A., & Ware, R. H. (1992). GPS Meteorology: Remote sensing of atmospheric water vapor using the global positioning system. Journal of Geophysical Research, 97(D14), 15787. [https://doi.org/10.1029/92jd01517">Crossref]

  4. Boutiouta, S., & Lahcene, A. (2013). Preliminary study of GNSS meteorology techniques in Algeria. International Journal of Remote Sensing, 34(14), 5105–5118.

  5. Chen, B., & Liu, Z. (2015). A comprehensive evaluation and analysis of the performance of multiple tropospheric models in China region. IEEE Transactions on Geoscience and Remote Sensing, 54(2), 663–678.

  6. Davis, J. L., Herring, T. A., Shapiro, I. I., Rogers, A. E. E., & Elgered, G. (1985). Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length. Radio Science, 20(6), 1593–1607. [https://doi.org/10.1029/rs020i006p01593">Crossref]

  7. Godah, W., Szelachowska, M., Ray, J. D., & Krynski, J. (2020). Comparison Of Vertical Deformations Of The Earth’s Surface Obtained Using Grace-Based GGMS And GNSS Data--A Case Study Of South-Eastern Poland. Acta Geodyn. Geomater, 17, 169–176.

  8. Gurbuz, G., Jin, S., & Mekik, C. (2015). Sensing Precipitable Water Vapor (PWV) using GPS in Turkey - Validation and Variations. In Satellite Positioning - Methods, Models and Applications. [https://doi.org/10.5772/60025">Crossref]

  9. Herring, T. A., King, R. W., & McClusky, S. C. (2010). Introduction to GAMIT/GLOBK.

  10. Isioye, O. A., Combrinck, L., & Botai, J. (2016). Modelling weighted mean temperature in the West African region: implications for GNSS meteorology. Meteorological Applications, 23(4), 614–632. [https://doi.org/10.1002/met.1584">Crossref]

  11. Kindu, T. A. (2017). Tectonics And Crustal Deformation In Ethiopia From Continuously Operating Reference Stations.

  12. Li, Y. (2021). Analysis of GAMIT/GLOBK in high-precision GNSS data processing for crustal deformation. Earthquake Research Advances, 1(3), 100028. [https://doi.org/https:/doi.org/10.1016/j.eqrea.2021.100028">Crossref]

  13. Liu, J., Chen, X., Sun, J., & Liu, Q. (2017). An analysis of GPT2/GPT2w+ Saastamoinen models for estimating zenith tropospheric delay over Asian area. Advances in Space Research, 59(3), 824–832.

  14. Perevalova, N. P., Romanova, E. B., & Tashchilin, A. V. (2020). Detection of high-latitude ionospheric structures using GNSS. Journal of Atmospheric and Solar-Terrestrial Physics, 207, 105335. [https://doi.org/https:/doi.org/10.1016/j.jastp.2020.105335">Crossref]

  15. Saastamoinen, J. (1972). Atmospheric correction for the troposphere and stratosphere in radio ranging satellites. The Use of Artificial Satellites for Geodesy, 15, 247–251.

  16. Suresh Raju, C., Saha, K., Thampi, B. V, & Parameswaran, K. (2007). Empirical model for mean temperature for Indian zone and estimation of precipitable water vapor from ground based GPS measurements. Annales Geophysicae, 25(9), 1935–1948.

  17. Tregoning, P., Boers, R., O’Brien, D., & Hendy, M. (1998). Accuracy of absolute precipitable water vapor estimates from GPS observations. Journal of Geophysical Research: Atmospheres, 103(D22), 28701–28710. [https://doi.org/10.1029/98jd02516">Crossref]

  18. Tsai, M.-C., Yu, S.-B., Shin, T.-C., Kuo, K.-W., Leu, P.-L., Chang, C.-H., & Ho, M.-Y. (2015). Velocity Field Derived from Taiwan Continuous GPS Array (2007-2013). Terrestrial, Atmospheric & Oceanic Sciences, 26(5).

  19. Tsidu, G. M., Blumenstock, T., & Hase, F. (2015). Observations of precipitable water vapour over complex topography of Ethiopia from ground-based {GPS}, {FTIR}, radiosonde and {ERA}-Interim reanalysis. Atmospheric Measurement Techniques, 8(8), 3277–3295. [https://doi.org/10.5194/amt-8-3277-2015">Crossref]

  20. Uang-Aree, P., Kingpaiboon, S., & Khuanmar, K. (2014). Estimation of missing GPS precipitable water vapor data by zenith wet delay and meteorological data. Advanced Materials Research, 931, 703–708.

  21. Wielgosz Pawełand Hadaś, T., Kłos, A., & Paziewski, J. (2019). Research on GNSS positioning and applications in Poland in 2015--2018. Geodesy and Cartography, 87–119.

  22. Xiaoming, L., Lisheng, X., Yansong, F., Yujie, Z., Jilie, D., Hailei, L., & Xiaobo, D. (2010). Estimation of the Precipitable Water Vapor from ground-based GPS with GAMIT/GLOBK. 2010 Second IITA International Conference on Geoscience and Remote Sensing. [https://doi.org/10.1109/iita-grs.2010.5603260">Crossref]


Last update:

  1. ARCHIVING TRADITIONAL HOUSES THROUGH DIGITAL SOCIAL MAPPING: AN INNOVATION APPROACH FOR LIVING HERITAGE CONSERVATION IN JAVA

    Atiek Suprapti, Anang Wahyu Sejati, Edward Endrianto Pandelaki, Agung Budi Sardjono. JOURNAL OF ARCHITECTURE AND URBANISM, 46 (1), 2022. doi: 10.3846/jau.2022.14275

Last update: 2024-04-18 02:30:29

No citation recorded.