Journal of Geosciences and Geomatics
ISSN (Print): 2373-6690 ISSN (Online): 2373-6704 Website: Editor-in-chief: Maria TSAKIRI
Open Access
Journal Browser
Journal of Geosciences and Geomatics. 2019, 7(4), 201-211
DOI: 10.12691/jgg-7-4-5
Open AccessReview Article

Evaluation of Five Tropospheric Delay Models on Global Navigation Satellite System Measurements in Southern Nigeria

Dodo J. D.1, , Ekeanyanwu U. O.2 and Ono M. N.2

1Centre for Geodesy and Geodynamics, National Space Research and Development Agency, Toro, Nigeria

2Department of Surveying and Geoinformatics, Nnamdi Azikiwe University, Awka

Pub. Date: September 15, 2019

Cite this paper:
Dodo J. D., Ekeanyanwu U. O. and Ono M. N.. Evaluation of Five Tropospheric Delay Models on Global Navigation Satellite System Measurements in Southern Nigeria. Journal of Geosciences and Geomatics. 2019; 7(4):201-211. doi: 10.12691/jgg-7-4-5


Throughout Nigeria, the structure and facilities needed for the operation of a Global Navigation Satellite System (GNSS) based Continuously Operating Reference Stations (CORS) has been set up at different locations in the country generally known as NIGerian Reference GNSS NETwork (NIGNET) for surveying and mapping. Different researchers have conducted investigations into the effect of the troposphere over the NIGNET. This study aims at comparing analytically the effect of five different a priori tropospheric models on GNSS signals in Southern Nigeria with a view to obtaining the best-fit model. The objectives include evaluation of the global tropospheric models in the baseline and position domain; and determining the best model for southern Nigeria. Observational data used were obtained from Office of Surveyor General of Nigerian Mapping Agency (OSGoF). GPS data were obtained from October 2010, to April 2011. Six processing strategies were employed these include; application of no model, application of five global tropospheric delay models (Black, Davis et al, Hopfield, Neil and Saastamoinen) models using Trimble Total Control software version 2.73. Each of the strategies went through free and constrained adjustments and the results were compared. The five models investigated show no significance difference in their performance; better improvements in the position domain were achieved by the application of the Niell model compared to the rest of the models. The Niell model produced a better mitigation of the tropospheric delay, with an average percentage improvement of 67.1%; while Davis et al, the modified Hopfield and Saastaminen models have 70%, 71.1% and 71.7% percentage improvement respectively. The result also indicates that, the Neill model gave the best result and a better improvement in the entire network with the lowest mean average zenith tropospheric delay (ZTD) of 2.535m and least average RMSE of 0.67m. The specific objective of this study is to determine the best tropospheric delay for the study area and to recommend to practicing Surveyor on the model to be used. The research shows that, the Neil model gives the best result when compared with other model. Hence, it is recommended when processing GNSS observations for tropospheric delay to obtain a more accurate result.

tropospheric delay model saastamoinen Niell hopfield davis et al black model

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit


[1]  Russel, R. (2010). The toposphere, Window to the Universe. Retrieved from accessed January 10, 2017.
[2]  Saastamoinen, J, “Atmospheric Correction for Troposphere and Stratosphere in Radio Ranging of Satellites”, Geophysical Monograph, American Geophysical Union, Washington D.C. 247-252. 1972.
[3]  Hopfield, H. S, “Two Quartic Tropospheric Refractivity Profile for Correcting Satellite Data”. Journal of Geophysical Research 74(18), 4487-4499. 1969.
[4]  Niell, A.E, “Global Mapping for the Atmospheric Delay at Radio Wavelenghts”, Journal of Geophysical Research 111 (B2), 3227-3246. 1996.
[5]  Davis, J. L., Herring, T. A., Shapiro, I. I., Rogers, A. E. E., & Elgered, G. “Geodesy by radio interferometry: Effects of atmospheric modelling on estimates of baseline length. Radio Science, 20(6), 1593-1607. 1985.
[6]  Opaluwa, Y. D., Adejare, Q. A., Suleyman, Z. A. T., Abazu, I. C., Adewale, T. O., Odesanmi, A. O., & Okorocha, V. C. “Comparative analysis of five standard dry tropospheric delay models for estimation of dry tropospheric delay in GNSS positioning”. American Journal of Geographic Information System. 2(4), 121-131. 2013.
[7]  Jorge, M. A., Lawrence, L., Yu-Ting, T., and Terry, M. “Analysing the Zenith Tropospheric Delay Estimates in On-line Precise Point Positioning (PPP) Services and PPP Software Packages” Sensors (Basel). 18(2): 580. 2018.
[8]  Sobhy, A., Y. “Modeling investigation of wet tropospheric delay error and precipitable water vapor content in Egypt” The Egyptian Journal of Remote Sensing and Space Sciences 19, 333-342. 2016.
[9]  Mendes, V.B., and Langley, R.B., “Tropospheric zenith delay prediction accuracy for airborne GPS high-precision positioning. In: Proceedings of The Institute of Navigation 54th Annual Meeting, pp. 337-347, Denver, CO, U.S.A., 1-3 June. 1998.
[10]  Bevis, M., Businger, S., Herring, T.A., Rocken, C., Anthes, R.A., Ware, R.H., “GPS meteorology: sensing of atmospheric water vapor using the global positioning system” J. Geophys. Res. 97 (D14), 15787-15801. 1992.
[11]  Businger, S., Chiswell, S.R., Bevis, M., Duan, J., Anthes, R.A., Rocken, C., Ware, R.H., Exner, M., Solheim, F.S., “The promise of GPS in atmospheric monitoring”. Bull. Am. Meteorol. Soc. 77 (1), 5-18. 1996.
[12]  Dodo, J. D., Ojigi, L. M., & Tsebeje, S. Y. “Determination of the best-fit tropospheric delay model on the Nigerian permanent GNSS network”. Journal of Geosciences and Geomatics, 3(4), 88-95. 2015.
[13]  Hofmann-Wellenhof, B., Lichtenegger, H. and Collins, J, GPS, Theory and Practice, Springer-Verlag Wien, New York. 2001
[14]  Ahn, Y. W., Lachapelle, G., Skone, S. and Sahm, S. “Analysis of GPS RTK Performance using External NOAA Tropospheric Corrections Integrated with a Multiple Reference Station Approach”, GPS Solution, 10, 171-186. 2006.
[15]  Hongxing Z., Yunbin, Y., Wei L., Ying L., and Yanju C. “Assessment of Three Tropospheric Delay Models (IGGtrop, EGNOS and UNB3m) Based on Precise Point Positioning in the Chinese Region”. Sensors (Basel) 16(1), 122. 2016.
[16]  Don, K., Sunil, B., Langley, R. B., Dare, P. “Performance of Long-Baseline real-Time Kinematic Applications by Improving Tropospheric Delay Modelling”, ION GNSS International Technical Meeting of the satellite Division. Long Beach, California, USA. 2004.
[17]  Satirapod, C., and Chalermwattanachai, P, “Impact of Different Tropospheric Models on GPS Baseline Accuracy: Case Study in Thailand”, Journal of Global Positioning Systems, 4(1-2), 36-40. 2005.
[18]  Roberts, C., and Rizos, C, “Mitigating Differential Troposphere for GPS-based Valcano Monitoring”, 5th International Symposium on Satellite Navigation Technology and Applications. Canberra, Australia. 2001.
[19]  Dodo, J. D., and Kamarudin, M. N. “Investigation on the Impact of Tropospheric Models on baseline precision in a local GPS network: Case of the Malaysian RTKnet”, Journal of Geomatics. 2 (1), 137-142. 2008.
[20]  Saastamoinen, J, “Contribution to the theory of Atmosphere Refraction”, Bulletin of Geodesique (105, 106, 107): 279-298, 383-397, 13-34. 1973.
[21]  Leick, A, GPS Satellite Surveying, USA: John Willey & Sons, Inc, 2004.
[22]  Thayer, G. D. “An improved equation for the radio refractive index of air”. Radio Science, 9(10), 803-807. 1974.
[23]  Guochang, X, GPS Theory, Algorithms and Application, Springer-Verlag Berlin Heidelberg, New York. 2003.
[24]  Black, TH. L. “The New NMC Mesoscale Eta Model: Description and Forecast Examples” Weather and Forecasting, Vol. 9, pp. 265-278, June 1994.
[25]  Seeber, G. Satellite Geodesy. Walter GeGruyter 2003.
[26]  Mendes, V.B. “Modeling the neutral-atmosphere propagation delay in radiometric space techniques”. Doctor of Philosophy, University of New Brunswick, Frederiction, Canada. 1999.
[27]  Jatau, B., Fernandes, R.M.S., Adebomehin, A., and Goncalves, N “NIGNET-The New Permanent GNSS Network of Nigeria”, FIG Congress 2010 Facing the Challenges – Building the Capacity Sydney, Australia, 11-16 April 2010.
[28]  Vollath, U., Buecherl, A., Landau, H., Pagels, C. and Wagner, B, “Multi-Base RTK Positioning Using Virtual Reference Stations”,Institute of Navigation, ION GPS-2000, Salt Lake City, 22-19 September, 123-131.2000.
[29]  “Ocean Tide Loading” Available: http://www.oso.cha. [AccessedSept. 20, 2009].
[30]  “The Earth Orientation Parameters and the Ionosphere models” Available: [Accessed: Sept. 21, 2009].
[31]  Dodo, J. D. “The Geocentric Datum of Nigeria (GDN2012)”. A Technical Report, Office of the Surveyor General of Nigeria. Abuja. 2012.
[32]  Tajul, A. M., Lim, S., Yan, T. and Rizos, C. “Mitigation of Distance-Dependent Errors for GPS Network Positioning”. International Global Navigation Satellite Systems Society IGNSS Symposium, Surfers Paradise, Australia. 2006.
[33]  Péter, B. “The evaluation of troposphere models applied in the Hungarian Active GNSS Network” The Council of European Geodetic Surveyors 2012.