WAVE CLIMATE IN SUBARCTIC SEAS FROM VOLUNTARY OBSERVING SHIPS: 1900-2020
Аннотация и ключевые слова
Аннотация (русский):
Wave climate in the North Atlantic and subarctic seas is investigated based on data from Voluntary Observing Ships for the period 1900-2020. The proposed approach differs from any previous studies of the given region as a detailed climatology and long-term trends were performed separately for wind sea and swell characteristics. The method allows for tracing Arctic climate tendencies of the last century and analyzing the reasons behind the observed changes taking place.

Ключевые слова:
Subarctic seas, visual wave observations, wind sea and swell climatology, long-term trends
Список литературы

1. Badulin, S. I., V. G. Grigorieva (2012) , On discriminating swell and wind-driven seas in voluntary observing ship data, J. Geophys. Res.: Oceans, 117, p. 1-13, https://doi.org/10.1029/2012JC007937

2. Badulin, S., V. Grigorieva, et al. (2018) , Wave steepness from satellite altimetry for wave dynamics and climate studies, Russian Journal of Earth Sciences, 18, no. 4, https://doi.org/10.2205/2018ES000638

3. Davidan, I. N., L. I. Lopatukhin (1982) , Towards the Storms, 136 pp., Hydrometeoizdat, Leningrad (in Russian)

4. Freeman, E., S. D. Woodruff, et al. (2017) , ICOADS release 3.0: a major update to the historical marine climate record, Int. J. Climatol., 37, no. 5, p. 2211-2232, https://doi.org/10.1002/joc.4775

5. Gavrikov, A., S. K. Gulev, et al. (2020) , RAS-NAAD: 40-year high resolution North Atlantic atmospheric hindcast for multipurpose applications (New dataset for the regional meso-scale studies in the atmosphere and the ocean), J. Appl. Meteor. Climatol., 59, p. 793-817, https://doi.org/10.1175/JAMC-D-19-0190.1

6. Grigorieva, V. G., S. I. Badulin (2016) , Wind wave characteristics based on visual observations and satellite altimetry, Oceanology, 56, no. 1, p. 19-24, https://doi.org/10.1134/S000143701601004

7. Grigorieva, V. G., S. K. Gulev, A. V. Gavrikov (2017) , Global historical archive of wind waves based on voluntary observing ship data, Oceanology, 57, p. 229-231, https://doi.org/10.1134/S000143701702006

8. Grigorieva, V.! G., S. K. Gulev, V. D. Sharmar (2020) , Validating Ocean Wind Wave Global Hindcast with Visual Observations from VOS, Oceanology, 60, no. 1, p. 9-19, https://doi.org/10.1134/S0001437020010130

9. Gulev, S. K., L. Hasse (1998) , North Atlantic wind waves and wind stress from voluntary observing data, J. Phys. Oceanogr., 28, p. 1107-1130, https://doi.org/10.1175/1520-0485(1998)028%3C1107:NAWWAW%3E2.0.CO;2

10. Gulev, S. K., V. Grigorieva, et al. (2003) , Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data, J. Geophys. Res.: Oceans Atmos., 108, no. 7, p. 3236-3257, https://doi.org/10.1029/2002JC001437

11. Gulev, S. K., V. Grigorieva (2004) , Last century changes in ocean wind wave height from global visual wave data, Geophys. Res. Lett., 31, p. L24302, https://doi.org/10.1029/2004GL021040

12. Gulev, S. K., V. Grigorieva (2006) , Variability of the winter wind waves and swell in the North Atlantic and North Pacific as revealed by the Voluntary Observing Ship data, J. Climate, 19, p. 5667-5785, https://doi.org/10.1175/JCLI3936.1

13. Gulev, S. K., T. Jung, E. Ruprecht (2007) , Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part II. Impact on trends and interannual variability, J. Climate, 20, p. 302-315, https://doi.org/10.1175/JCLI4008.1

14. Gulev, S. K., M. Latif, et al. (2013) , North Atlantic Ocean control on surface heat flux on multidecadal timescales, Nature, 499, p. 464-467, https://doi.org/10.1038/nature12268

15. Kent, E. C., N. A. Rayner, et al. (2019) , Observing requirements for long-term climate records at the ocean surface, Front. Mar. Sci., 6, p. 441, https://doi.org/10.3389/fmars.2019.00441

16. Khimchenko, E. E., D. I. Frey, E. G. Morozov (2020) , Tidal internal waves in the Bransfield Strait, Antarctica, Russian Journal of Earth Sciences, 20, p. ES2006, https://doi.org/10.2205/2020ES000711

17. Lavrova, O. Yu., A. G. Kostianoy, et al. (2011) , Complex Satellite Monitoring of the Russian Seas, 470 pp., IKI RAN, Moscow

18. Lopatukhin, L., A. Buhanovskij, et al. (2003) , Reference Data of Wind and Waves Climate of the Barents, Okhotsk, and Caspian Seas. Russian Maritime Register of Shipping, SPB, Saint-Petersburg (in Russian)

19. Lopatukhin, L., V. Rozhkov, et al. (2002) , The Spectral Wave Climate in the Barents Sea, OMAE2002-28397, 2, p. 283-289, https://doi.org/10.1115/OMAE2002-28397

20. Markina, M. Y., A. V. Gavrikov (2016) , Wave climate variability in the North Atlantic in recent decades in the winter period using numerical modeling, Oceanology, 56, p. 320-325, https://doi.org/10.1134/S0001437016030140

21. Markina, M., J. Studholme, S. Gulev (2019) , Ocean Wind Wave Climate Responses to Wintertime North Atlantic Atmospheric Transient Eddies and Low-Frequency Flow, J. Climate, 32, p. 5619-5638, https://doi.org/10.1175/JCLI-D-18-0595.1

22. Marchenko, A. V., E. G. Morozov (2016) , Surface manifestations of the waves in the ocean covered with ice, Russian Journal of Earth Sciences, 16, p. ES1001, https://doi.org/10.2205/2016ES000561

23. Portilla, J., F. O. Torres, J. Monbaliu (2009) , Spectral partitioning and identification of wind sea and swell, J. Atmos. Ocean. Technol., 26, p. 107-122, https://doi.org/10.1175/2008JTECHO609.1

24. Reistad, M., O Breivik, et al. (2011) , A high-resolution hindcast of wind and waves for the North Sea, the Norwegian Sea, and the Barents Sea, J. Geophys. Res., 116, p. C05019, https://doi.org/10.1029/2010JC006402

25. Saprykina, Y. V., S. Y. Kuznetsov (2018a) , Method of analysis of nonstationary variability of wave climate of Black Sea, J. Phys. Oceanogr., 4, p. 156

26. Saprykina, Y., S. Kuznetsov (2018b) , Analysis of the variability of wave energy due to climate changes on the example of the Black Sea, Energies, 11, no. 8, p. 2020, https://doi.org/10.3390/en11082020

27. Sen, P. K. (1968) , Estimates of the regression coefficient based on Kendall's tau, Journal of the American Statistical Association, 63, no. 324, p. 1379-1389, https://doi.org/10.1080/01621459.1968.10480934

28. Stroeve, J. C., V. Kattsov, et al. (2012) , Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations, Geophys. Res. Lett., 39, no. 16, https://doi.org/10.1029/2012GL052676

29. Theil, H. (1950) , A rank-invariant method of linear and polynominal regression analysis (parts 1-3), Ned. Akad. Wetensch. Proc. Ser. A, 53, p. 386-392

30. Vignudelli, S., A. G. Kostianoy, P. Cipollini (eds.), et al. (2011) , Coastal Altimetry, 578 pp., Springer-Verlag, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-12796-0

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