Results of adaptation and verification of the coupled numerical models set for predicting the variation of oceanographic features in the North-Western part of the Black Sea

  • D. V. Kushnir
  • Yu. S. Tuchkovenko
  • Yu. I. Popov
Keywords: the Black Sea, North-Western part, oceanographic features, numerical modelling, models verification, forecast


In 2014 Ukraine lost the Ukrainian National Automated System of Marine Forecasting for the Black Sea that was created and operated at the premises of Marine Hydrophysical Institute of the National Academy of Sciences of Ukraine located in the Crimea. Within the framework of research works aimed at establishing a new marine forecasting system a possibility of employing the internationally acclaimed set of coupled numerical models Delft3D-FLOW + SWAN (the Simulating WAves Nearshore) for operational forecasting of the short-term (5 to 10 days) spatio-temporal variability of oceanographic features in the Ukrainian part of the Sea of Azov and the Black Sea Basin is considered. To ensure operation of the models set in the forecasting mode it was suggested to use a prediction of variability of meteorological characteristics at the air-sea interface obtained with the help of the numerical weather forecast model GFS (Global Forecast System). This paper presents the results of verification of Delft3D-FLOW and SWAN numerical models which were adapted to the conditions of the North-Western part of the Black Sea and its Odesa area in the version of meteorological data (fields of wind speed and direction, atmospheric pressure) assimilation from the GFS forecast archive. A technique of telescoping the spatial curvilinear computational grids with different resolution capacity was used in the process of models set adaptation to the conditions of the prognostic area. The models were verified by comparing modelling results with observational data on sea level variability in the ports of Odesa area of the North-Western part of the Black Sea (Chornomorsk, Odesa, Yuzhnyi), as well as with data on wind speed and direction, drift currents and characteristics of wind-induced waves recorded over the studied periods by the gauges of stationary hydrometeorological buoy which was mounted in the Bay of Odessa. Based on the analysis of the results of verification of coupled numerical models Delft3D-FLOW + SWAN set it was concluded that the set of coupled models has good prospects of being used in the system of operational forecasting of the variability of oceanographic parameters of the sea environment in the Ukrainian part of the Sea of Azov and the Black Sea Basin in the version of assimilation of meteorological information obtained from the GFS global forecast model.


Copernicus. European Union's Earth Observation Programme. Available at: about-copernicus (Accessed: 16 January 2019).

Copernicus Marine Environment Monitoring Service (CMEMS). Available at: (Accessed 16 January 2019).

Kubryakov A.S., Korotaev G.K., Dorofeev V.L. et al. (2012). Black Sea coastal forecasting system. Ocean Sci., 8, pp. 183-196.

Korotaev, G.K., Demyshev, S.G. & Dorofeev, V.L. (2013). Arkhitektura i rezul'taty raboty mezhdunarodnogo Chernomorskogo tsentra morskikh prognozov, sozdannogo na baze MGI NAN Ukrainy v ramkakh proekta Evropeyskogo Soyuza «Moy Okean» [The architecture and the results of the work of the International Black Sea Center for Marine Forecasts, created on the basis of the State Hydrophysical Institute of National Academy of Science of Ukraine in the framework of the European Union project “My Ocean”]. Ekolohichna bezpeka pryberezhnykh ta shelfovykh zon ta kompleksne vykorystannia resursiv shelfu [Ecological safety of coastal and offshore areas and complex use of the shelf resources], 27, pp. 128-133. (in Russ.)

Demyshev, S.G. & Korotaev, G. K. (1992). Chislennaya energosbalansirovannaya model' baroklinnykh techeniy okeana s nerovnym dnom na setke S [Numerical energy balanced model of baroclinic ocean currents with uneven bottom on a C-grid]. In: Chislennye modeli i rezul'taty kalibrovochnykh raschetov techeniy v Atlanticheskom okeane [Numerical models and results of gauge calculations of currents in the Atlantic Ocean]. Moscow: IVM RAS, pp. 163-231. (in Russ.)

Deltares. (2019). Delft3D-FLOW, source code. Delft, the Netherlands. Available at: delft3d/source-code (Accessed: 16 January 2019).

Deltares. (2019). Delft3D-FLOW – Simulation of multi-dimensional hydrodynamic flows and transport phenomena, including sediments – User Manual, Hydro-Morphodynamics, version 3.15, SVN revision 60015. Delft, the Netherlands. Available at: manuals/Delft3D-FLOW_User_Manual.pdf (Accessed: 16 January 2019).

Delft University of Technology, Faculty of Civil Engineering and Geosciences, Environmental Fluid Mechanics Section (2019). SWAN: Simulating WAves Nearshore model. Available at: (Accessed: 16 January 2019).

TU Delft (2017). SWAN – User Manual, SWAN Cycle III, version 41.20 AB. Available at: swanuse.pdf (Accessed: 16 January 2019).

US NAVY (2019). Naval Oceanographic Office. Available at: /navo_home1.aspx (Accessed: 16 January 2019).

Veeramony, J., Orzech, M.D., Edwards, K.L. et al. (2014). Navy nearshore ocean prediction systems. Oceanography, 27(3), pp. 80-91.

Valchev, N., Eftimova, P., & Andreeva, N. (2018). Implementation and validation of a multi-domain coastal hazard forecasting system in an open bay. Coastal Engineering, 134, pp. 212–228. j.coastaleng.2017.08.008

Bennett, V.C.C., Mulligan, R.P. & Hapke, C.J. (2018). A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York. Continental Shelf Research, 161, pp. 1 11.

Veeramony, J., Condon, A., & van Ormondt, M. (2017). Forecasting Storm Surge and Inundation: Model Validation. Weather and Forecasting, 32(6), pp. 2045–2063.

NCEP GFS 0.25 Degree Global Forecast Grids Historical Archive. Available at: ds084.1/#!access (Accessed: 15 April 2018).

The GFS Atmospheric Model. Available at: (Accessed: 15 April 2018).

NOAA/National Weather Service. (2019). National Centers for Environmental Prediction. Environmental Modeling Center. Available at: GFS/.php (Accessed: 16 January 2019).

Mellor, G.L. & Blumberg, A.F. (1985). Modelling vertical and horizontal diffusities and the sigma coordinate system, Monthly Weather Review, 113, pp. 1379-1383.

Hasselmann, K., Barnett, T.P., Bouws, E. et al. (1973). Measurements of wind wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Dtsch. Hydrogr. Z. Suppl, 12, A8.

Collins, J.I. Prediction of shallow water spectra. (1972). J. Geophys. Res., 77(15), pp. 2693-2707.

Madsen, O.S., Poon, Y.-K. & Graber, H.C. (1988). Spectral wave attenuation by bottom friction: Theory. Proc. 21th Int. Conf. Coastal Engineering, ASCE, pp. 492-504.

Golodov, M, Popov, Yu. & Matveev, A. (2016). Rezultaty porivnialnykh sposterezhen hidrolohichnykh ta meteorolohichnykh kharakterystyk za danymy vymiriuvan hidrometeorolohichnoho buia SWMidi-185 ta punktiv sposterezhen Hidrometeorolohichnoho biuro portu Illichivsk u 2015 rotsi [Results of comparative observations of hydrological and meteorological characteristics according to measurements of the hydro-meteorological buoy SWMidi-185 and observation points of the Hydrometeorological Bureau of the Port of Illichivsk in 2015]. Visnyk Derzhhidrohrafii [Bulletin of State Hydrographic Service of Ukraine], 1 (50), pp. 2 5. (in Ukr.)

How to Cite
Kushnir, D. V., Tuchkovenko, Y. S., & Popov, Y. I. (2019). Results of adaptation and verification of the coupled numerical models set for predicting the variation of oceanographic features in the North-Western part of the Black Sea. Ukrainian Hydrometeorological Journal, (23), 95-108.