Russian Federation
GRNTI 37.01 Общие вопросы геофизики
GRNTI 37.15 Геомагнетизм и высокие слои атмосферы
GRNTI 37.25 Океанология
GRNTI 37.31 Физика Земли
GRNTI 38.01 Общие вопросы геологии
This study is aimed at expanding the number of measured parameters to analyze the features of the formation of surface waves under the influence of wind. The paper develops an original approach to obtaining information on the variability of the short-wave part of the wave spectrum (examples are given for wavelengths from about 50 cm to 2 cm in 6 intervals) and the long-wave component of the wave spectrum (> 1 m) in marine conditions. To illustrate the approach, a six-frequency underwater acoustic wave gauge was simulated, which measures the slope variance of the large-scale waves, compared to the radiation wavelength, for each radiation frequency. The work is caried out a theoretical analysis of slope variance retrieved from reflected acoustic pulses for different radiation frequencies depending on the near-surface wind speed and swell wave height. For comparison, a study of a new parameter, the differential slope variance, is carried out, which contains information about short waves in the intervals of cut-off wavenumbers corresponding to the radiation frequencies. It is shown that the use of differential slope variances of the large-scale waves makes it possible to get clear of the influence of swell in the case of mixed waves and obtain a better correlation with the wind speed. The paper proposes a method for retrieving the exponent of the spectral slope in the intervals of cut-off wavelength corresponded to the radiation frequencies. Within this method, it is possible to retrieve the cut-off wavenumbers for each radiation frequency.
Air/sea interactions, Instruments and techniques, Ocean observing systems, Ocean remote sensing statistically rough wave, scattering surface, antenna radiation pattern, Kirchhoff approximation, quasi-specular scattering, slope variance, height variance, significant wave height, multifrequency remote sensing, underwater acoustic wave gauge, small-scale waves, height spectrum, slope spectrum, swell.
1. Apel, J. R. (1994), An improved model of the ocean surface wave vector spectrum and its effects on radar backscatter, Journal of Geophysical Research: Oceans, 99(C8), 16269-16291.
2. Bass, F.G., and I.M. Fuks. (1979), Scattering of Waves by Statistically Rough Surfaces. Pergamon Press, Oxford.
3. Brown, G. (1977), The average impulse response of a rough surface and its applications, IEEE Trans. Antennas Propag., 25, 67-74.
4. Birch, R., D. B. Fissel, K. Borg, V. Lee, and D. English (2004), The capabilities of Doppler current profilers for directional wave measurements in coastal and nearshore waters, paper presented at Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600), 9-12 Nov. 2004.
5. Cox, C., W. Munk (1954), Measurements of the roughness of the sea surface from photographs of the sun glitter, J. Opt. Soc. Amer., 44, No. 11, 838-850. doi https://doi.org/10.1364/JOSA.44.000838
6. Danilytchev, M., B. Kutuza, A. Nikolaev (2009), The application of sea wave slope distribution empirical dependencies in estimatioin of interaction between microwave radiation and rough sea surface, IEEE Transactions on Geoscience and Remote Sensing, 47, No. 2, 652-66. doihttps://doi.org/10.1109/TGRS.2008.2004410
7. Elfouhaily, T., B. Chapron, K. Katsaros, and D. Vandemark (1997), A unified directional spectrum for long and short wind-driven waves, J. Geophys. Res., 102, 15781-15796.
8. Freilich, M. H., B. A. Vanhoff (2003), The relation between winds, surface roughness, and radar backscatter at low incidence angles from TRMM Precipitation Radar measurements, Journal of Atmospheric and Oceanic Technology, 20, No. 4, 549-562. doi https://doi.org/10.1175/1520-0426(2003)20<549:TRBWSR>2.0.CO;2
9. GPM (2014), GPM Data Utilization Handbook. First Edition, 92 pp. JAXA, Tokyo.
10. NDBC (2009), Handbook of Automated Data Quality Control Checks and Procedures.
11. Hasselmann, K. (1973), Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP), Erganzungsheft zur Deutschen Zeitschrift, 95.
12. Hwang, P. A., and D. W. Wang (2004), An empirical investigation of source term balance of small scale surface waves, Geophysical Research Letters, 31(15).
13. Hwang, P. A. (2005), Wave number spectrum and mean square slope of intermediate-scale ocean surface waves, Journal of Geophysical Research: Oceans, 110(C10).
14. Karaev, V., M. B. Kanevsky, and E. Meshkov (2008), The effect of sea surface slicks on the Doppler spectrum width of a backscattered microwave signal, Sensors, 8, 3780-3801. doihttps://doi.org/10.3390/s8063780.
15. Karaev, V. Y., M. E. Meshkov, and Y. A. Titchenko (2014), Underwater Acoustic Altimeter, Radiophysics and Quantum Electronics, 57(7), 488-497. doihttps://doi.org/10.1007/s11141-014-9531-8
16. Karaev, V. Y., M. A. Panfilova, M. S. Ryabkova, Y. A. Titchenko, E. M. Meshkov, and X. Li (2021), Retrieval of the two-dimensional slope field by the SWIM spectrometer of the CFOSAT satellite: Discussion of the algorithm, Russian Journal of Earth Sciences, 21(6). doihttps://doi.org/10.2205/2021es000784
17. Kuznetsova, A., M. Panfilova, Y. Titchenko, G. Baydakov, and Y. Troitskaya (2019), Study of waves at different fetches using WAVEWATCH III modeling and precipitation radar data, paper presented at OCEANS 2019 - Marseille, 17-20 June 2019. doihttps://doi.org/10.1109/oceanse.2019.8867107
18. Molkov, A., L. Dolin, I. Kapustin, and O. Shomina (2019), The retrieval of wind wave characteristics by the underwater solar path image: slope frequency spectrum, SPIE. doi https://doi.org/10.1117/12.2533010
19. Molkov, A. (2020), Retrieval of slope spectrum of sea roughness by Snell’s window imagery: theory and numerical experiment (one-dimensional sea roughness), SPIE. doi https://doi.org/10.1117/12.2573949
20. Panfilova, M. A., V. Y. Karaev, and J. Guo (2018), Oil Slick Observation at Low Incidence Angles in Ku-Band, Journal of Geophysical Research: Oceans, 123(3), 1924-1936. doi doihttps://doi.org/10.1002/2017JC013377
21. Panfilova, M., V. Karaev, L. Mitnik, Y. Titchenko, M. Ryabkova, and E. Meshkov (2020), Advanced View at the Ocean Surface, Journal of Geophysical Research: Oceans, 125(11), e2020JC016531. doi https://doi.org/10.1029/2020JC016531
22. Panfilova, M. A., A. M. Kuznetsova, Y. A. Titchenko, D. A. Sergeev, Y. I. Troitskaya, and V. Y. Karaev (2021), Methods of Comparing the Wave Model Simulation Data with the KA-BAND Radar Data, paper presented at 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 11-16 July 2021. doihttps://doi.org/10.1109/igarss47720.2021.9555041
23. Plant, W. J. (2002), A stochastic, multiscale model of microwave backscatter from the ocean, Journal of Geophysical Research: Oceans, 107(C9), 3-1-3-21. doi https://doi.org/10.1029/2001JC000909
24. Phillips, O. M. (1985), Spectral and statistical properties of the equilibrium range in wind-generated gravity waves, Journal of Fluid Mechanics, 156, 505-531. doihttps://doi.org/10.1017/s0022112085002221
25. Ryabkova, M., V. Karaev, J. Guo, and Y. Titchenko (2019), A Review of Wave Spectrum Models as Applied to the Problem of Radar Probing of the Sea Surface, Journal of Geophysical Research: Oceans, 124(10), 7104-7134. doihttps://doi.org/10.1029/2018jc014804.
26. Ryabkova, M., V. Titov, Y. Titchenko, E. Meshkov, V. Karaev, A. Yablokov, K. Ponur, R. Belyaev, and M. Panfilova (2021), Measurements of the Sea Surface Waves Parameters and the Doppler Spectrum of the Reflected Signal Using Optical and Acoustic Remote Sensing Methods, paper presented at 2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), 28 Aug.-4 Sept. 2021. doihttps://doi.org/10.23919/ursigass51995.2021.9560283
27. Tran, N., B. Chapron, D. Vandemark (2007), Effects of long waves on Ku-band ocean radar backscatter at low incidence angles using TRMM and altimeter data, IEEE Transactions on Geoscience and Remote Sensing, 4, No. 4, 542-546. doihttps://doi.org/10.1109/LGRS.2007.896329
28. TRMM (2001), TRMM Data Users Handbook (2001), 226 pp. NASDA, Tokyo.
29. Troitskaya, Y. I., and G. V. Rybushkina (2008), Quasi-linear model of interaction of surface waves with strong and hurricane winds, Izvestiya, Atmospheric and Oceanic Physics, 44(5), 621-645.
30. Titchenko, Y., V. Karaev, M. Ryabkova, A. Kuznetsova, and E. Meshkov (2019), Peculiarities of the Acoustic Pulse Formation Reflected by the Water Surface: a Numerical Experiments and the Results of Long-term Measurements Using the "Kalmar" Sonar, paper presented at OCEANS 2019 - Marseille, 17-20 June 2019. doihttps://doi.org/10.1109/oceanse.2019.8867467
31. Titchenko, Y. A., V. Y. Karaev, M. S. Ryabkova, E. M. Meshkov, K. A. Ponur, and R. V. Belyaev (2021a), Theoretical View on the Possibilities of Multi-frequency Remote Sensing of the Water Surface, paper presented at 2021 Photonics & Electromagnetics Research Symposium (PIERS), 21-25 Nov. 2021. doihttps://doi.org/10.1109/piers53385.2021.9694705
32. Titchenko, Y., V. Karaev, M. Ryabkova, K. Ponur, E. Meshkov, and R. Belyaev (2021b), Backscattering Cross-Section Incident Dependence by Reflected Pulse Shape Using a Fixed Antenna with the Wide Antenna Pattern, paper presented at 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 11-16 July 2021. doihttps://doi.org/10.1109/igarss47720.2021.9553689
33. Zapevalov A.S., I.P. Shumeyko, A.Yu. Abramovich (2020) Dependences of the characteristics of sea surface slopes on the spatial ranges of the waves creating them. Zhurnal Radioelektroniki - Journal of Radio Electronics. 2020. No. 5. Available at http://jre.cplire.ru/jre/may20/15/text.pdf. DOI: https://doi.org/10.30898/1684-1719.2020.5.15
