Izvestiya, Atmospheric and Oceanic Physics

, Volume 54, Issue 9, pp 1249–1256 | Cite as

A Regression Model of Microwave Emission of a Water Surface at 37.5 GHz

  • D. S. SazonovEmail author


This paper presents the functional dependence of the microwave emission of a rough water surface at a frequency of 37.5 GHz (wavelength of ~8 mm). The MiROSE model (Microwave Rough Ocean Surface Emission model) is based on the experimental studies of the own thermal radio emission of the water surface, which were carried out in 2005 and 2007 on the oceanographic platform of the Black Sea Hydrophysical Experimental Facility of the Russian Academy of Sciences. This paper demonstrates the steps of the simulation for selecting the optimal functions to describe the incident angle, wind, and temperature dependences of the increment of the own water surface emission. The following parameters can be calculated on the basis of the proposed model: the increment of the brightness temperature, radio-brightness contrast, and radio-brightness temperature for horizontal and vertical polarizations of the received emission. The model is applicable to water temperatures ranging from 12.5 to 25°C, wind speeds of 3–13 m/s, and incident angles of 30°–80° measured from the nadir.


remote sensing radio-brightness temperature radio-brightness contrast modeling radiometer microwave emission angular dependence of wind-speed sensitivity wind-speed retrieving 



This work was supported by the Russian Foundation for Basic Research, grant no. 15-05-08401_a.


  1. 1.
    Apel, J.R., An improved ocean surface wave vector spectrum, J. Geophys. Res., 1994, vol. 99, no. C8, pp. 16269–16291.CrossRefGoogle Scholar
  2. 2.
    Bondur, V.G. and Murynin, A.B., Methods for retrieval of sea wave spectra from aerospace image spectra, Izv., Atmos. Ocean. Phys., 2016, vol. 52, no. 9, pp. 877–887.CrossRefGoogle Scholar
  3. 3.
    Bondur, V.G., Dulov, V.A., Murynin, A.B., and Yurovsky, Yu.Yu., A Study of sea-wave spectra in a wide wavelength range from satellite and in-situ data, Izv., Atmos. Ocean. Phys., 2016, vol. 52, no. 9, pp. 888–903.CrossRefGoogle Scholar
  4. 4.
    Durden, S.L. and Vesecky, J.F., A physical radar cross-section model for a wind-driven sea with swell, IEEE J. Ocean Eng., 1985, vol. OE-10, no. 4, pp. 445–451.CrossRefGoogle Scholar
  5. 5.
    Elfouhaily, T., Chapron, B., Katsaros, K., and Vandemark, D., A unified directional spectrum for long and short wind-driven waves, J. Geophys. Res., 1997, vol. 102, no. C7, pp. 15781–15796.CrossRefGoogle Scholar
  6. 6.
    Hollinger, J.P., Passive microwave measurements of the sea surface, J. Geophys. Res., 1970, vol. 75, no. 2, pp. 5209–5213.CrossRefGoogle Scholar
  7. 7.
    Kopelevich, O.V., Burenkov, V.I., and Sheberstov, S.V., Case studies of optical remote sensing in the Barents Sea, Black Sea and Saspian Sea, Remote Sens. Eur. Seas, 2008, pp. 53–66.Google Scholar
  8. 8.
    Kuzmin, A.V., Goryachkin, Yu.A., Ermakov, D.M., Ermakov, S.A., Komarova, N.Yu., Kuznetsov, A.S., Repina, I.A., Sadovsky, I.N., Smirnov, M.T., Sharkov, E.A., and Chukharev, A.M., The Katsiveli marine hydrographic platform as a subsatellite polygon in the Black Sea, Issled. Zemli Kosmosa, 2009, no. 1, pp. 31–44.Google Scholar
  9. 9.
    Kuzmin, A.V., Repina, I.A., Sadovsky, I.N., and Selunskii, A.B., Microwave radiometric studies of the sea surface, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2015, vol. 12, no. 5, pp. 76–97.Google Scholar
  10. 10.
    Lavrova, O.Yu., Mityagina, M.I., and Kostyanoi, A.G., Sputnikovye metody vyyavleniya i monitoringa zon ekologicheskogo riska morskikh akvatorii (Satellite Methods for the Detection and Monitoring of Ecological Risk Zones of Seawater), Moscow: IKI RAN, 2016.Google Scholar
  11. 11.
    Repina, I.A., Tikhonov, V.V., Alekseeva, T.A., Ivanov, V.V., Raev, M.D., Sharkov, E.A., Boyarskii, D.A., and Komarova, N.Yu., Electrodynamic model of Arctic ice-cover radiation for solving problems in satellite microwave radiometry, Issled. Zemli Kosmosa, 2012, no. 5, pp. 29–36.Google Scholar
  12. 12.
    Sadovsky, I.N., Kuzmin, A.V., Sharkov, E.A., Sazonov, D.S., Pashinov, E.V., Asheko, A.A., and Batulin, S.A., Analysis of models of dielectric permittivity of the water environment used in remote sensing of water areas, Preprint of Space Research Institute, Russ. Acad. Sci., Moscow, 2013, no. 2172.Google Scholar
  13. 13.
    Sadovsky, I.N., Sharkov, E.A., Kuzmin, A.V., Sazonov, D.S., and Pashinov, E.V., A review of models of the integral dielectric permeability of water medium in remote sensing applications, Issled. Zemli Kosmosa, 2014, no. 6, pp. 79–92.Google Scholar
  14. 14.
    Sasaki, Ya., Asanuma, I., Muneyama, K., Naito, G., and Suzuki, T., The dependence of sea-surface microwave emission on wind speed, frequency, incidence angle, and polarization over frequency range from 1 to 40 GHz, IEEE Trans. Geosci. Remote Sens., 1987, vol. GE-25, no. 11, pp. 138–146.CrossRefGoogle Scholar
  15. 15.
    Sazonov, D.S., Correlation analysis of experimental remote-sensing data and models of microwave rough sea-surface emission, Izv., Atmos. Ocean. Phys., 2017, vol. 53, no. 9, pp. 1174–1184.CrossRefGoogle Scholar
  16. 16.
    Sazonov, D.S., Dulov, V.A., Sadovsky, I.N., Chechina, E.V., and Kuzmin, A.V., Subsatellite measurements of the asymmetry in slopes of gravity wind waves, Ukr. Metrolog. Zh., 2014, no. 1, pp. 54–58.Google Scholar
  17. 17.
    Sazonov, D.S., Kuzmin, A.V., and Sadovsky, I.N., Experimental studies of thermal radiation intensity dependence on near-water wind speed for rough sea surface, Izv., Atmos. Ocean. Phys., 2016, vol. 52, no. 9, pp. 911–919.CrossRefGoogle Scholar
  18. 18.
    Sharkov, E.A., Remote investigations of atmospheric catastrophes, Izv., Atmos. Ocean. Phys., 2011, vol. 47, no. 9, pp. 1057–1071.CrossRefGoogle Scholar
  19. 19.
    Sharkov, E.A., Radioteplovoye distantsionnoye zondirovaniye zemli: Fizicheskiye osnovy (Radiothermal Remote Sensing of the Earth: Physical Bases), Moscow: IKI RAN, 2014.Google Scholar
  20. 20.
    Sterlyadkin, V.V. and Sharkov, E.A., Differential radiothermal methods for determining the vertical profile of water vapor in the Earth’s troposphere and stratosphere, Issled. Zemli Kosmosa, 2014, no. 5, pp. 15–28.Google Scholar
  21. 21.
    Stogrin, A., Equations for calculating the dielectric constant for saline water, IEEE Trans. Microwave Theory Tech., 1971, vol. 19, no. 8, pp. 733–736.CrossRefGoogle Scholar
  22. 22.
    Trokhimovskii, Yu.G., Bolotnikova, G.A., Etkin, V.S., Grechko, S.I., and Kuzmin, A.V., The dependence of s-band sea surface brightness temperature on wind vector at normal incidence, IEEE Trans. Geosci. Remote Sens., 1995, vol. 33, no. 4, pp. 1085–1088.CrossRefGoogle Scholar
  23. 23.
    Wentz, F.J., A model function for ocean microwave brightness temperature, J. Geophys. Res., 1983, vol. 88, no. C3, pp. 1892–1907.CrossRefGoogle Scholar

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© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  1. 1.Space Research Institute, Russian Academy of SciencesMoscowRussia

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