Spatio-Seasonal Variations in Long-Term Trends of Offshore Wind Speeds Over the Black Sea; an Inter-Comparison of Two Reanalysis Data

  • Tunay Çarpar
  • Berna AyatEmail author
  • Burak Aydoğan
Regular Issue


Spatio-seasonal variability of long-term trends in mean and 95th percentile wind speeds for the term between 1979 and 2016, over the Black Sea is presented. Our aim is to contribute the existing literature by presenting the inhomogeneous spatial distribution of the long-term trends in both moderate and severe wind speeds on a monthly basis. The analysis is conducted by using two different data; European Centre for Medium-Range Weather Forecasts-ERA-Interim and U.S. National Centers for Environmental Prediction-Climate Forecast System Reanalysis (CFSR) to perform a comparative analysis. The non-parametric Mann–Kendall and Sen’s Slope methods are used to determine the trends and their significance over the Black Sea. CFSR winds presented higher interannual variability than the ERA-Interim. ERA-Interim indicates that annual mean and 95th percentile wind speeds have decreasing trends down to − 0.17%/year and − 0.20%/year in the Sea of Azov, while they have an increasing trend up to 0.35%/year and 0.38%/year in the eastern part, respectively. Results indicate that wind speeds are increasing over 28% ~ 36% of the Black Sea surface area while the wind speeds are decreasing over 2% ~ 4% of the surface area. Pacific North American Oscillation presented an influence almost all over the Black Sea with statistically significant correlation coefficients over 0.5. North Atlantic Oscillation dominates over the southwestern, western and northern Black Sea with inverse correlation coefficients over 0.6. ERA-Interim and CFSR data illustrated a similar distribution pattern over the Black Sea in means of the relation of variations in wind speeds to the teleconnection indices.


Long-term trend wind speed Black Sea teleconnection spatiotemporal variability monthly variability 



This study is funded by the Scientific and Technological Research Council of Turkey, TUBITAK (Grant Number: 116M061) and European Union Era.Net RusPlus (Grant Number: BS STEMA 42/2016). Authors thank the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing ERA-Interim wind data, National Oceanic and Atmospheric Administration (NOAA) National Weather Service for providing CFSR wind data, and the EMODnet Bathymetry Portal for shoreline data.

Author contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Tunay Çarpar, Berna Ayat and Burak Aydoğan. The first draft of the manuscript was written by Tunay Carpar and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.


  1. Akpinar, A., & Bingolbali, B. (2016). Long-term variations of wind and wave conditions in the coastal regions of the Black Sea. Natural Hazards,84(1), 69–92. Scholar
  2. Arkhipkin, V. S., Gippius, F. N., Koltermann, K. P., & Surkova, G. V. (2014). Wind waves in the Black Sea: results of a hindcast study. Natural Hazards and Earth Systems Sciences,14, 2883–2897.CrossRefGoogle Scholar
  3. Athanasatos, S., Michaelides, S., & Papadakis, M. (2014). Identification of weather trends for use as a component of risk management for port operations. Natural Hazards,72, 41–61. Scholar
  4. Aydoğan, B. (2017). Offshore wind power atlas of the Black Sea region. Journal of Renewable and Sustainable Energy,9, 013305. Scholar
  5. Aydoğan, B., & Ayat, B. (2018). Spatial variability of long-term trends of significant wave heights in the Black Sea. Applied Ocean Research,79, 20–35. Scholar
  6. Barnston, A. G., & Livezey, R. E. (1987). Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Monthly Weather Review,115, 1083–1126.CrossRefGoogle Scholar
  7. Cakiroglu, A. M., Cevher, N. C., & Agirbas, E. (2017). The meteorological Investigation of Turkish coasts of the Black Sea. Journal of Anatolian Environmental and Animal Sciences,2(3), 53–58.CrossRefGoogle Scholar
  8. Climate Prediction Center (CPC). (2011). Northern hemisphere teleconnection patterns. (
  9. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011). The ERA-interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society,137, 553–597. Scholar
  10. Drapela, K., & Drapelova, I. (2011). Application of Mann-Kendall test and the Sen’s slope estimates for trend detection in deposition data from Bílý Kříž (Beskydy Mts., the Czech Republic) 1997–2010. Mendelova Univerzita v Brně, Beskydy,4, 133–146.Google Scholar
  11. Dyer, A. J. (1974). A review of flux-profile relationships. Boundary Layer Meteorology,7, 363–372.CrossRefGoogle Scholar
  12. Efimov, V. V., & Anisimov, A. E. (2011). Climatic Parameters of Wind Field Variability in the Black Sea Region: numerical Reanalysis of Regional Atmospheric Circulation. Izvestiya, Atmospheric and Oceanic Physics,47(3), 350–361.CrossRefGoogle Scholar
  13. Ganea, D., Mereuta, E., & Rusu, L. (2018). Estimation of the near future wind power potential in the Black Sea. Energies. Scholar
  14. Ganea, D., Mereuta, E., & Rusu, E. (2019). An evaluation of the wind and wave dynamics along the European coasts. Marine Science and Engineering. Scholar
  15. Georgopoulou, E., Mirasgedis, S., Sarafidis, Y., et al. (2018). Climatic preferences for beach tourism: an empirical study on Greek islands. Theoretical and Applied Climatology. Scholar
  16. Gilbert, R. O. (1987). Statistical methods for environmental pollution monitoring. New York: Van Nostrand Reinhold Company Inc.Google Scholar
  17. Hasanean, H. M. (2005). Variability of teleconnections between the Atlantic subtropical high and the Indian monsoon low and related impacts on summer temperature over Egypt. Atmospheric Science Letters,6, 176–182. Scholar
  18. Healy, T. R. (2018). Coastal wind effects. In C. Finkl & C. Makowski (Eds.), Encyclopedia of coastal science. Encyclopedia of earth sciences series. New York: Springer.Google Scholar
  19. Holtslag, A. A. M., & Bruin, H. A. R. (1988). Applied modeling of the nighttime surface energy balance over land. Journal of Applied Meteorology,27, 689–704.CrossRefGoogle Scholar
  20. Jiang, Y., Luo, Y., Zhao, Z., & Tao, S. (2010). Changes in wind speed over China during 1956–2004. Theoretical and Applied Climatology,99, 421–430. Scholar
  21. Kendall, M. G. (1938). A new measure of rank correlation. Biometrika,30(1–2), 81–93.CrossRefGoogle Scholar
  22. Kendall, M. G. (1970). Rank correlation methods (4th ed.). London: Griffin.Google Scholar
  23. Kostianoy, A. G., & Kosarev, A. N. (2008). The Black Sea environment. Berlin Heidelberg: Springer.CrossRefGoogle Scholar
  24. Kubryakov, A., Stanichny, S., Shokurov, M., & Garmashov, A. (2019). Wind velocity and wind curl variability over the Black Sea from QuikScat and ASCAT satellite measurements. Remote Sensing of Environment,224, 236–258. Scholar
  25. Li, Z., Yan, Z., Tu, K., Liu, W., & Wang, Y. (2011). Changes in wind speed and extremes in Beijing during 1960–2008 based on homogenized observations. Advances in Atmospheric Sciences,28(2), 408–420. Scholar
  26. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica,13(3), 245–259.CrossRefGoogle Scholar
  27. Masuda, D., Kai, S., Yamamoto, N., et al. (2014). The effect of lunar cycle, tidal condition and wind direction on the catches and profitability of Japanese common squid Todarodes pacificus jigging and trap-net fishing. Fisheries Science,80(6), 1145–1157. Scholar
  28. Onea, F., & Rusu, E. (2012). Wind energy assessments along the Black Sea basin. Meteorological Applications,21(2), 316–329. Scholar
  29. Özsoy, E., & Ünlüata, Ü. (1997). Oceanography of the Black Sea: a review of some recent results. Earth-Science Reviews,42, 231–272.CrossRefGoogle Scholar
  30. Rusu, L., Bernardino, M., & Guedes Soares, C. (2014). Wind and wave modelling in the Black Sea. Journal of Operational Oceanography,7(1), 5–20. Scholar
  31. Rusu, L., Raileanu, A. B., & Onea, F. (2018). A comparative analysis of the wind and wave climate in the Black Sea along the shipping routes. Water,10(7), 924–942. Scholar
  32. Saha, S., Moorthi, S., Pan, H., Wu, X., Wang, J., Nadiga, S., et al. (2010). The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society,91, 1015–1057. Scholar
  33. Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., et al. (2014). The NCEP Climate Forecast System Version 2. Journal of Climate,27, 2185–2208. Scholar
  34. Salmi, T., Maatta, A., Anttila, P., Ruoho-Airola, T., & Amnell, T. (2002). Detecting trends of annual values of atmospheric pollutants by the Mann Kendall Test and Sen’s slope estimates the excel template application MAKESENS. Finnish Meteorological Institute, Publications on Air Quality, No. 31, Helsinki.Google Scholar
  35. Schlitzer, R. (2019). Ocean data view. Accessed 12 Oct 2019.
  36. Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s Tau. Journal of the American Statistical Association,63, 1379–1389.CrossRefGoogle Scholar
  37. Shadid, S. (2011). Trends in extreme rainfall events of Bangladesh. Theoretical and Applied Climatology,104(3–4), 489–499. Scholar
  38. Shepherd, J. G., Brewer, P. G., Oschlies, A., & Watson, A. J. (2017). Ocean ventilation and deoxygenation in a warming world: introduction and overview. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences,375, 1–9. Scholar
  39. Sterl, A., & Caires, S. (2005). Climatology, variability and extrema of ocean waves: the Web-based KNMI/ERA-40 wave atlas. International Journal of Climatology. Scholar
  40. Stopa, J. S., & Cheung, K. F. (2014). Intercomparison of wind and wave data from the ECMWF reanalysis interim and the NCEP climate forecast system reanalysis. Ocean Modelling,75, 65–83. Scholar
  41. Surkova, G. V., Arkhipkin, V. S., & Kislov, A. V. (2013). Atmospheric circulation and storm events in the Black Sea and Caspian Sea. Central European Journal of Geoscience,5(4), 548–559.Google Scholar
  42. Troccoli, A., Muller, K., Coppin, P., Davy, R., Russell, C., & Hirsch, A. L. (2012). Long-term wind speed trends over Australia. Journal of Climate,25, 170–183. Scholar
  43. Tuller, S. E. (2004). Measured WS trends on the west coast of Canada. International Journal of Climatology,24, 1359–1374. Scholar
  44. Valchev, N., Davidan, I., Belberov, Z., Palazov, A., & Valcheva, N. (2010). Hindcasting and assessment of the western Black sea wind and wave climate. Environmental Protection and Ecology,11(3), 1001–1012.Google Scholar
  45. Valchev, N., Trifonova, E., & Andreeva, N. (2012). Past and recent trends in the western Black Sea storminess. Natural Hazards and Earth System Sciences,12, 961–977. Scholar
  46. Velea, L., Bojariu, R., & Cica, R. (2014). Occurrence of extreme winds over the Black Sea during January under present and near future climate. Turkish Journal of Fisheries and Aquatic Sciences,14, 973–979. Scholar
  47. Wallace, J. M., & Gutzler, D. S. (1981). Teleconnections in the geopotential height field during the Northern hemisphere winter. Monthly Weather Review,109, 784–812.CrossRefGoogle Scholar
  48. Wang, D. W., & Hwang, P. A. (2001). An operational method for separating wind sea and swell from ocean wave spectra. Atmospheric Oceanic Technology,18, 2052–2062. Scholar
  49. Weisse, R., & Gunther, H. (2007). Wave climate and long-term changes for the Southern North Sea obtained from a high-resolution hindcast 1958–2002. Ocean Dynamics,57, 161–172. Scholar
  50. Young, I. R., Zieger, S., & Babain, A. (2011). Global trends in wind speed and wave height. Science,332(6028), 451–455. Scholar
  51. Zainescu, F., Tatui, F., Valchev, N., & Vespremeanu-Stroe, A. (2017). Storm climate on the Danube delta coast: evidence of recent storminess change and links with large-scale teleconnection patterns. Natural Hazards,87, 599–621. Scholar
  52. Zecchetto, S., & de Biasio, F. (2007). Sea surface winds over the Mediterranean Basin from satellite data (2000–04): meso- and local-scale features on annual and seasonal time scales. Journal of Applied Meteorology and Climatology,46, 814–827.CrossRefGoogle Scholar
  53. Zeng, X., Dickinson, R. E., & He, Y. (1998). Effect of surface sublayer on surface skin temperature and fluxes. Journal of Climate,11, 537–550.CrossRefGoogle Scholar
  54. Zhang, D., Cronin, M. F., Wen, C., Xue, Y., Kumar, A., & McClurg, D. (2016). Assessing surface heat fluxes in atmospheric reanalyses with a decade of data from the NOAA Kuroshio Extension Observatory. Journal of Geophysical Research: Oceans,121, 6874–6890. Scholar
  55. Zheng, C. W., Pan, J., & Li, C. Y. (2016). Global oceanic wind speed trends. Ocean and Coastal Management,129, 15–24. Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Istanbul Water and Sewerage Administration (ISKI)Eyüp/IstanbulTurkey
  2. 2.Department of Civil EngineeringYildiz Technical UniversityEsenler/IstanbulTurkey
  3. 3.Department of Civil EngineeringGebze Technical UniversityGebze/KocaeliTurkey

Personalised recommendations