Abstract and keywords
Abstract (English):
Sea ice loss in the Arctic region is one of the well documented consequences of climate change that also affects local atmospheric dynamics and wind-driven surface gravity waves. In this study, we perform the comparative assessment of linear trends in mean and extreme characteristics of 10-m winds and sea ice concentrations from ERA5, ERA-Interim, MERRA2 and NCEP CFSR reanalyses as well as significant wave heights from wind wave hindcasts performed with the spectral wave model WAVEWATCH III forced by these reanalyses in 1980-2019. The largest decline in sea ice concentration in all four reanalyses is observed in autumn and summer in the Chukchi and Beaufort Seas. In winter, all reanalyses and hindcasts agree on positive trends in both 10-m winds and wave heights in the Bering, Okhotsk and Labrador Seas. In spring, all datasets show negative trends in extreme wave heights in the North Pacific Ocean and positive trends in mean winds and wave heights in the western North Atlantic. In summer, positive trends in extreme 10-m winds and wave heights are observed in the Northeast Atlantic, and positive trends in extreme wave heights are revealed in the Sea of Okhotsk. In autumn, positive trends in both mean and extreme winds are observed in the Chukchi and Beaufort Seas as well as along the western coast of Greenland, which coincides with areas with the largest decline in sea ice concentrations. Positive trends in wind speed and wave heights in the Bering Seas are also revealed in all datasets.

Ice retreat, wave-ice interaction, wind, trends, Arctic

1. Ardhuin, F., W. E. Rogers, A. V. Babanin, et al. (2010), Semiempirical dissipation source functions for ocean waves. Part I: Definition, calibration, and validation, J. Phys. Oceanogr., 40, No. 1, 1,917- 1,941

2. Blackport, R., J. A. Screen, K. van der Wiel, et al. (2019), Minimal influence of reduced Arctic sea ice on coincident cold winters in mid-latitudes, Nat. Clim. Chang., 9, 697-704

3. Casas-Prat, M., X. L. Wang, N. Swart (2018), CMIP5-based global wave climate projections including the entire Arctic Ocean, Ocean Modelling, 123, 66-85

4. Cavaleri, L., B. Fox-Kemper, M. Hemer (2012), Wind waves in the coupled climate system, Bull. Amer. Meteor. Soc., 93, 1651-1661

5. Collins, M., et al. (2013), Long-term climate change: Projections, commitments and irreversibility, Climate Change 2013: The Physical Science Basis, T. F. Stocker et al. (Eds.) p. 1029-1136, University Press, Cambridge

6. Dai, A., D. Luo, M. Song, et al. (2019), Arctic amplification is caused by sea-ice loss under increasing CO 2 , Nat. Commun., 10, 121

7. Dee, D. P., et al. (2011), The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Quart. J. Roy. Meteor. Soc., 137, 553-597

8. Dobrynin, M., J. Murawsky, S. Yang (2012), Evolution of the global wind wave climate in CMIP5 experiments, Geophys. Res. Lett., 39, L18606

9. Dumont, D., A. Kohout, L. Bertino (2011), A wave-based model for the marginal ice zone in9 of 11 ES2002 sharmar and markina: evaluation of interdecadal trends ES2002 cluding a floe breaking parameterization, J. Geophys. Res., 116

10. Fennig, K., M. Schr¨oder, et al. (2020), A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures, Earth Syst. Sci. Data, 12, 647-681

11. Francis, J. A., S. J. Vavrus (2012), Evidence linking Arctic amplification to extreme weather in mid-latitudes, Geophys. Res. Lett., 39, L06801

12. Gelaro, R., W. McCarty, M. J. Su´arez, et al. (2017), The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419-5454

13. Helfand, H. M., S. D. Schubert (1995), Climatology of the Simulated Great Plains LowLevel Jet and Its Contribution to the Continental Moisture Budget of the United States, J. Climate, 8, 784-806

14. Hersbach, H., B. Bell, P. Berrisford (2020), The ERA5 global reanalysis, Q. J. R. Meteorol. Soc., 146, 1999-2049

15. Khon, V. C., I. I. Mokhov, et al. (2014), Wave heights in the 21st century Arctic Ocean simulated with a regional climate model, Geophys. Res. Lett., 41, 2956-2961

16. Korablina, A., A. Kondrin, V. Arkhipkin (2017), Numerical simulations and statistics of surges in the White and Barents seas, Russ. J. Earth Sci., 17, ES4004

17. Kudryavtsev, V., E. Zabolotskikh, B. Chapron (2019), Abnormal Wind Waves in the Arctic: Probability of Occurrence and Spatial Distribution, Russian Meteorology and Hydrology, 44, No. 4, 268-275

18. Lindsay, R., M. Wensnahan, et al. (2014), Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic, J. Climate, 27, 2588-2606

19. McCarty, W., L. Coy, R. Gelaro, et al. (2016), MERRA-2 input observations: Summary and initial assessment. Technical Report Series on Global Modeling and Data Assimilation, Vol. 46, NASA Tech. Rep. NASA/TM-2016-104606, 61 pp. NASA, US

20. Meredith, M., M. Sommerkorn, et al. (2019), Polar Regions, IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, H.-O. P¨ortner et al. (eds.) p. 203-320, Cambridge University press, Cambridge

21. Meucci, A., I. R. Young, et al. (2020), Comparison of Wind Speed and Wave Height Trends from Twentieth-Century Models and Satellite Altimeters, J. Climate, 33, 611-624

22. Mokhov, I. I., V. C. Khon, E. Roeckner (2007), Variations in the ice cover of the Arctic Basin in the 21st century based on model simulations: Estimates of the perspectives of the Northern Sea Route, Doklady Earth Sciences, 415, No. 1, 759-763

23. Molod, A., L. Takacs, et al. (2015), Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2, Geosci. Model Dev. , 8, 1339-1356

24. Parkinson, C. L., J. C. Comiso (2013), On the 2012 record low Arctic sea ice cover: Combined impact of preconditioning and an August storm, Geophysical Research Letters, 40, No. 7, 1356- 1361

25. Reistad, M., Ø. Breivik, et al. (2011), A highresolution hindcast of wind and waves for the North Sea, the Norwegian Sea, and the Barents Sea, J. Geophys. Res., 116, C05019

26. Sharmar, V., M. Markina (2020), Validation of global wind wave hindcasts using ERA5, MERRA2, ERA-Interim and CFSRv2 reanalyzes, IOP Conference Series: Earth and Environmental Science, 606, 012056

27. Sharmar, V., M. Markina, S. K. Gulev (2021), Global Ocean Wind-Wave Model Hindcasts Forced by Different Reanalyses: A Comparative Assessment, Journal of Geophysical Research: Oceans, 126, No. 1

28. Simmonds, I., I. Rudeva (2012), The great Arctic cyclone of August 2012, Geophysical Research Letters, 39, No. 23

29. Squire, V. A. (2007), Of ocean waves and sea-ice revisited, Cold Reg. Sci. Technol., 49, 110-133

30. Stopa, J. E., F. Ardhuin, F. Girard-Ardhuin (2016a), Wave climate in the Arctic 1992- 2014: seasonality and trends, The Cryosphere, 10, 1605-1629

31. Stopa, J. E., F. Ardhuin, et al. (2016b), Comparison and validation of physical wave parameterizations in spectral wave models, Ocean Modell., 103, 2-17

32. Stroeve, J. C., M. C. Serreze, et al. (2012), The Arctic’s rapidly shrinking sea ice cover: A research synthesis, Clim. Change, 110, 1005- 1027

33. Tolman, H. L. (2003), Treatment of unresolved islands and ice in wind wave models, Ocean Modell., 5, 219-231

34. Trigo, I. F. (2006), Climatology and inter10 of 11 ES2002 sharmar and markina: evaluation of interdecadal trends ES2002 annual variability of storm-tracks in the EuroAtlantic sector: a comparison between ERA-40 and NCEP/NCAR reanalyses, Clim. Dyn., 26, 127-143

35. Waseda, T., A. Webb, et al. (2018), Correlated Increase of High Ocean Waves and Winds in the Ice-Free Waters of the Arctic Ocean, Sci. Rep., 8, 4489

36. WW3DG (2016), WAVEWATCH III Development Group, User manual and system documentation of WAVEWATCH III R version 5.16. Tech. Note 329, 326 pp. NOAA/NWS/NCEP/ MMAB, College Park, MD, USA

37. Zhang, X., J. E. Walsh, et al. (2004), Climatology and Interannual Variability of Arctic Cyclone Activity: 1948-2002, J. Climate, 17, 2300-2317

Login or Create
* Forgot password?