Validation of precipitation obtained from GPM and H-SAF satellite data with relation to Ukrainian ground weather stations' data

  • O. S. Zabolotna
  • O. O. Kryvoshein
  • O. A. Kryvobok
Keywords: precipitation, satellite data, ground data, comparison


The main objective of this study is to validate H-SAF and GPM satellite precipitation data for the territory of Ukraine. Validation was carried out by comparing satellite data with data from ground weather stations of Ukrainian Hydrometeorological Center and included the following stages: data collection and processing, bringing the data to the same spatial and temporal resolution, calculation of correlation coefficients and construction of confusion matrices. Correlation coefficients were calculated for each of the stations for two studied periods (the first period - April-September 2020, the second period - April-September 2021). In addition, to ensure a more detailed analysis, confusion matrices were constructed based on division of precipitation into classes of different intensity. The comparative analysis showed that a larger number of stations (117) has a correlation coefficient of 0.5 - 0.8 with relation to GPM data, and, as for HSAF precipitation data, a larger number of stations (59) has a low correlation coefficient (0 - 0.3). Confusion matrices were calculated for the following four classes of rainfalls (mm): “0-2”, “2-5”, “5-10”, “>10”. The confusion matrices coefficients showed that low-intensity precipitation or “no precipitation”, as well as high-intensity precipitation, can be determined by a satellite with high accuracy as opposed to the ground-based weather station measurements. Thus, according to the "specificity" indicator, a precipitation class >10 mm has the highest level of correspondence of satellite data (H-SAF, GPM Late, GPM Early) to ground data. The low value of the "specificity" for the range of 0-2 mm is explained by the fact that satellite methods are able to detect very low values of precipitation intensity, while the station shows their absence – 0 mm. Thus, according to the values of the confusion matrices, we see that a large part of the values of ground measurements of precipitation in the range of 0-2 mm are shown by the satellite method as “2-5 mm” class. We can also see that the “2-5 mm” class by satellite has the most confusion with the 0-2 mm class by station (for H-SAF, GPM Late, GPM Early). But based on the high values of the "recall" for the range of 0-2 mm (for H-SAF, GPM Late, GPM Early), we can conclude that when the station does not show this amount of precipitation (0-2 mm), then the satellite also shows another class of values. The values of "precision" coefficient show that the satellite measurements are actually reliable. This means that presence or absence of precipitation may be determined precisely, since the highest value of the "precision" coefficient is typical for low and high amounts of precipitation (on average 0.76 and 0.66, respectively). Detected by satellites, heavy precipitation or no precipitation are also confirmed in most cases by ground stations. Based on the results of the validation, GPM and H-SAF satellite precipitation data products can be used for rainfall monitoring and considered as an additional source of meteorological information.


Data | NASA Global Precipitation Measurement Mission. Available at: (Accessed 31.08.2021)

EUMETSAT | Monitoring the weather and climate from space | EUMETSAT. Available at: (Accessed 31.08.2021)

Global Precipitation Mission (GPM). Ground Validation System. Validation Network Data Product User’s Guide. Volume 2, November 16, 2015.

Soto-Berelov, M, Jones, S., Farmer, E., & Woodgate, W. (2015). Review of validation standards of Earth Observation derived biophysical products.

Kryvoshein, O.O. (2013). Porivniannia nazemnykh vymiriv soniachnoi radiasii z suputnykovymy danymy v mezhakh oblastei Ukrainy za period 2001-2009rr. [Comparison of terrestrial measurements of solar radiation with satellite data within the regions of Ukraine for the period 2001–2009]. Journal of Cartography, 9, pp.93-103. (in Ukr)

Ground Validation | NASA Global Precipitation Measurement Mission. Available at: (Accessed 31.08.2021)

Mathew R., Schwaller & RobertMorris, K. (2011). A Ground Validation Network For The Global Precipitation Measurement Mission. Journal Of Atmospheric And Oceanic Technology, 28 (March).

Luiz Octavio Fabriciodos Santos, Carlos Alexandre Santos Querino, Juliane Kayse Albuquerqueda Silva Querino, Altemar Lopes Pedreira Junior, Aryanne Resendede Melo Moura, Nadja Gomes Machado & Marcelo Sacardi Biudes. (2019). Validation of rainfall data estimated by GPM satellite on Southern Amazon regio. Revista Ambiente&Água, vol. 14(1).

Fatemeh Fadia Maghsood, Hossein Hashemi, Seyyed Hasan Hosseini & Ronny Berndtsson.(2020). Ground Validation of GPM IMERG Precipitation Products over Iran. Remote Sens., 12(1).

Justice, C., Belward, A., Morisette, J., Lewis, P., Privette, J. & Baret, F. (2000). Developments in the 'validation' of satellite sensor products for the study of the land surface. Remote sensing, vol. 21(17).

Winifred Ayinpogbilla Atiah, Leonard Kofitse Amekudzi, Jeffrey Ni iArmah Aryee, Kwasi Preko & Sylvester Kojo Danuor. (2020). Validation of Satellite and Merged Rainfall Data over Ghana. West Africa. Atmosphere, 11.

Getachew Tesfaye, Tsegaye Tadesse, Berhan Gessesse & Tufa Dinku. (2017). Validation of new satellite rainfall products over the Upper Blue Nile Basin. Ethiopia. Atmos. Meas. Tech. Discuss. November 2017

Haral Feidas Validation of the H-SAF precipitation products over Greece using rain gauge data. Associate Scientist Activity hsaf. Final Report. Aristotle University of The Saloniki. July 2015.

Manish Kumar, Oivind Hodnebroe, Anne Sophie Daloz, Sumit Sen & Jagdish Krishnasamy. (2021). Measuring precipitation in Eastern Himalaya: Ground validation of eleven satellite, model and gauge interpolated gridded products. Journal of Hydrology August, 599.

Leonard K. Amekudzi, Marian A. Osei, Winifred A. Atiah, etc. (2016). Validation of TRMM and FEWS Satellite Rainfall Estimates with Rain Gauge Measurement over Ashanti Region, Ghana. Atmospheric and Climate Sciences, vol.6(4).

Ji-Hye Kim, Mi-Lim Ou, Jun-Dong Park etc. (2014). Global Precipitation Measurement (GPM) Ground Validation (GV) Prototype in the Korean Peninsula. Journal of atmospheric and oceanic technology, Vol. 31.

Commission for synoptic meteorology. Abridged final report. World meteorological organization. Geneva, 1970

Chris Cohoon & Owen Kelley. (2020). Accessing the PPS Near Real Time Data using HTTPS and the jsimpson https Server, 11 June 2020

Rodrigues Fernandes, J. L. (2015). Analysis of Classification Algorithms for Crop Detection using LANDSAT 8 images. Universidade Nova.

Kryvoshein, O.O., Kryvobok, O.A., Adamenko, T.I. (2020). Systema vyznachenia ploshch posiviv osnovnykh silskohospodarskykh kultur Ukrainy za suputnykovymy danymy [Satellite-based system of area estimation for main agricultural crops of Ukraine]. Ukrainian hydrometeorological journal, 26, pp. 78-90. (in Ukr).

Kryvobok, O.A., Kryvoshein, O.O.; Adamenko, T.I. (2018). Peculiarities of technological adaptation of the CGMS system for agricultural crop monitoring in Ukraine. Ukrainian hydrometeorological journal, 22, pp. 64-79.

Toshihisa Matsui, Takamichi Iguchi, Xiaowen Li, Mei Han etc. (2013). GPM Satellite Simulator over Ground Validation Sites. Bulletin of the American Meteorological Society, vol.94(11), pp. 1653–1660

Davide Melfi, Marco Galli, Valentina Rosati & Stefano Dietrich. (2019). HSAF Precipitation products. Conference: Satellite inspired hydrology in an uncertain future: an H SAF and HEPEX work shop. At: Reading (UK) November 2019.

Bidwell, S.W., Durning, J.F. Everett, D.F. etc. (2004). Preparations for Global Precipitation Measurement (GPM) ground validation. IGARSS 2004. International Geoscience and Remote Sensing Symposium, 2004

Perspektyvy vykorystannia suputnykovoi informatsii dlia monitorynhu dosiahnennia tsilei staloho rosvytku Ukrainy [Prospects for the use of satellite information for monitoring the achievement of Ukraine`s sustainable development goals]. Analytical report. Institute of space research of the National Academy of Sciences of Ukraine and State Space Agency of Ukraine. Kyiv, 2020 (in Ukr)

Kryvobok, O.A., Kryvoshein, O.O., Koman, M.M. & Krupa, E.O. (2018). Ukrainskii sehment systemy hrozopelenhatsii ENTLN (LIGHTNING FINDING SYSTEM) [Ukrainian segment of the ENTLN (LIGHTNING FINDING SYSTEM)]. Ukrainian Hydrometeorological Journal, 21, pp.5-20. (in Ukr)

Zabolotna, O.S., Kryvoshein, O.O. & Kryvobok, O.A. (2021). Monitorynh kilkosti opadiv za suputnykovymy danymy ta danymy hrozopelenhatsii dlia terytorii Ukrainy [Monitoring of the amount of precipitation according to the satellite data and sunderstorm forecasting data for the territory of Ukraine]. Abstracts of reports of the second Ukarinian Hydrometeorological Congress, pp.164-165. (in Ukr)

How to Cite
Zabolotna, O. S., Kryvoshein, O. O., & Kryvobok, O. A. (2023). Validation of precipitation obtained from GPM and H-SAF satellite data with relation to Ukrainian ground weather stations’ data. Ukrainian Hydrometeorological Journal, (32), 5-15.
Meteorology and Climatology