An appraisal of the ECMWF ReAnalysis5 (ERA5) model in estimating and monitoring atmospheric water vapour variability over Nigeria

    Swafiyudeen Bawa   Affiliation
    ; Olalekan Adekunle Isioye Affiliation
    ; Mefe Moses   Affiliation
    ; Lukman Abdulmumin   Affiliation


This study research the performance of the ERA5 reanalysis model in estimating and monitoring the variability of atmospheric water vapour content over Nigeria. The ERA5 is a fifth-generation reanalysis model recently released by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA5 model comes with excitingly high spatial and temporal resolution when compared to earlier models like the ERA-Interim and ERA-40. However, like the previous models, the ERA5 comes with numerous modelling uncertainties arising from data fusion methods and observation schemes, which often affects its performance at the different regions of the Earth. In this study, ERA5 precipitable water vapour (PWV) was validated with GNSS PWV from permanent GNSS stations in Nigeria NIGNET for the period of 2012–2013. The performance of ERA5 was investigated at sub-daily, diurnal, and seasonal scales in relation to KöppenGeiger climate classification using standard statistical metrics (namely, coefficient of correlation (r), Root mean square error (RMSE), Reliability index (RI), Mean absolute errors (MAE) and mean bias). The r, RI, RMSE, MAE and mean bias values at sub-daily, diurnal and seasonal scales were computed as, (0.8670, 0.882, 0.979), (3.697 mm, 3.400 mm, 7.014 mm), (1.015, 1.019, 1.008), (2.769 mm, 2.706 mm, 1.939 mm) and (0.826 mm, 2.033 mm, 1.739 mm), respectively. The results indicate the strongest performance of ERA5 at seasonal scale with more than 95% agreement. The pattern of variability of ERA5 within the different climate zones of Nigeria showed good consistency with GNSS PWV and Köppen-Geiger climate classification. The study recommended the use of ERA5 in the retrieval of historic PWV records and near real-time GNSS applications.

Keyword : ERA5, Köppen-Geiger, NIGNET, PWV

How to Cite
Bawa, S., Isioye, O. A., Moses, M., & Abdulmumin, L. (2022). An appraisal of the ECMWF ReAnalysis5 (ERA5) model in estimating and monitoring atmospheric water vapour variability over Nigeria. Geodesy and Cartography, 48(3), 150–159.
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Oct 4, 2022
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Abimbola, O. J., Falaiye, O. A., & Omojola, J. (2017). Estimation of precipitable water vapour in Nigeria using NIGNET GNSS/GPS, NCEP-DOE reanalysis II and surface meteorological data. Journal of Physical Science, 28(2), 19–29.

Acheampong, A. A., Fosu, C., Amekudzi, L. K., & Kaas, E. (2015). Comparison of precipitable water over Ghana using GPS signals and reanalysis products. Journal of Geodetic Science, 5(1).

Ansari, K., Corumluoglu, O., Panda, S. K., & Verma, P. (2018). Spatiotemporal variability of water vapor over Turkey from GNSS observations during 2009–2017 and predictability of ERA-Interim and ARMA model. The Journal of Global Positioning Systems, 16(1), 8.

Bawa, S., Ojigi, L. M., Dodo, J. D., & Lawal, K. M. (2021). Strain rate field on the Nigeria lithosphere derived from GNSS velocity. Applied Geomatics, 13, 179–193.

Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., & Wood, E. F. (2018). Present and future Köppen-Geiger climate classification maps at 1-km resolution. Scientific Data, 5(1), 1–12.

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. 2.0.CO;2><0379:GMMZWD>2.0.CO;2

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: Atmospheres, 97(D14), 15787–15801.

Blewitt, G., Hammond, W. C., & Kreemer, C. (2018). Harnessing the GPS data explosion for interdisciplinary science. Eos, 99.

Boehm, J., Werl, B., & Schuh, H. (2006). Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. Journal of Geophysical Research, 111, B02406.

Choy, S., Wang, C.-S., Yeh, T.-K., Dawson, J., Jia, M., & Kuleshov, Y. (2015). Precipitable water vapor estimates in the Australian region from ground-based GPS observations. Advances in Meteorology, 2015, 956481.

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.

Gurbuz, G., Jin, S., & Mekik, C. (2015). Sensing Precipitable Water Vapor (PWV) using GPS in Turkey – validation and variations. Satellite Positioning – Methods, Models and Applications.

Isioye, O. A., Combrinck, L., & Botai, J. O. (2017). Retrieval and analysis of precipitable water vapour based on GNSS, AIRS, and reanalysis models over Nigeria. International Journal of Remote Sensing, 38(20), 5710–5735.

Isioye, O. A., Combrinck, L., & Botai, J. (2015). Performance evaluation of blind tropospheric delay correction models over Africa. South African Journal of Geomatics, 4(4), 502–525.

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.

Isioye, O. A., Combrinck, L., Botai, J. O., & Moses, M. (2019). Assessing the impact of variations in atmospheric water vapour content over Nigeria from GNSS measurements. South African Journal of Geomatics, 8(1), 27.

Jade, S., & Vijayan, M. S. M. (2008). GPS-based atmospheric precipitable water vapor estimation using meteorological parameters interpolated from NCEP global reanalysis data. Journal of Geophysical Research: Atmospheres, 113(D3).

Jiang, P., Ye, S., Chen, D., Liu, Y., & Xia, P. (2016). Retrieving precipitable water vapor data using GPS zenith delays and global reanalysis data in China. Remote Sensing, 8(5), 389.

Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259–263.

Landskron, D., & Böhm, J. (2018). VMF3/GPT3: Refined discrete and empirical troposphere mapping functions. Journal of Geodesy, 92(4), 349–360.

Leggett, R. W., & Williams, L. R. (1981). A reliability index for models. Ecological Modelling, 13(4), 303–312.

Mengistu Tsidu, G., 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.

Ojigi, L. M., & Opaluwa, Y. D. (2019). Monitoring atmospheric water vapour variability over Nigeria from ERA-Interim and NCEP reanalysis data. SN Applied Sciences, 1(10), 1159.

Saastamoinen, J. (1972). Atmospheric correction for the troposphere and stratosphere in radio ranging satellites. In The use of artificial satellites for geodesy (pp. 247–251). American Geophysical Union (AGU).

Shcherbakov, M. V., Brebels, A., Shcherbakova, N. L., Tyu­kov, A. P., Alex, T., Janovsky, R., & Kamaev, V. A. (2013). A survey of forecast error measures. World Applied Sciences Journal (Information Technologies in Modern Industry, Education & Society, 24, 171–176.

Ssenyunzi, R. C., Oruru, B., D’ujanga, F. M., Realini, E., Barindelli, S., Tagliaferro, G., von Engeln, A., & van de Giesen, N. (2020). Performance of ERA5 data in retrieving Precipitable Water Vapour over East African tropical region. Advances in Space Research, 65(8), 1877–1893.

Wessel, P., Luis, J. F., Uieda, L., Scharroo, R., Wobbe, F., Smith, W. H. F., & Tian, D. (2019). The generic mapping tools version 6. Geochemistry, Geophysics, Geosystems, 20(11), 5556–5564.

Xiaoming, L., Lisheng, X., Yansong, F., Yujie, Z., Jilie, D., Hailei, L., & Xiaobo, D. (2010). Estimation of the precipitable water vapor fom ground-based GPS with GAIT/GLOBK. In 2010 Second LITA International Conference on Geoscience and Remote Sensing.

Yang, H., He, C., Wang, Z., & Shao, W. (2019, June). Reliability analysis of European ERA5 water vapor content based on ground-based GPS in China. In Proceedings of the 2019 International Conference on wireless communication, network and multimedia engineering (WCNME 2019) (pp. 44–49). Atlantis Press.

Zhang, W., Zhang, H., Liang, H., Lou, Y., Cai, Y., Cao, Y., Zhou, Y., & Liu, W. (2019). On the suitability of ERA5 in hourly GPS precipitable water vapor retrieval over China. Journal of Geodesy, 93(10), 1897–1909.