Skip to main content
SpringerLink
Log in

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

  • Regular Issue
  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • 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. https://doi.org/10.1007/s11069-016-2407-9.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s11069-012-0491-z.

    Article  Google Scholar 

  • AydoÄŸan, B. (2017). Offshore wind power atlas of the Black Sea region. Journal of Renewable and Sustainable Energy,9, 013305. https://doi.org/10.1063/1.4976968.

    Article  Google Scholar 

  • AydoÄŸan, B., & Ayat, B. (2018). Spatial variability of long-term trends of significant wave heights in the Black Sea. Applied Ocean Research,79, 20–35. https://doi.org/10.1016/j.apor.2018.07.001.

    Article  Google Scholar 

  • Barnston, A. G., & Livezey, R. E. (1987). Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Monthly Weather Review,115, 1083–1126.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Climate Prediction Center (CPC). (2011). Northern hemisphere teleconnection patterns. (http://www.cpc.ncep.noaa.gov/data/teledoc/telecontents.html)

  • 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. https://doi.org/10.1002/qj.828.

    Article  Google Scholar 

  • 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 BrnÄ›, Beskydy,4, 133–146.

    Google Scholar 

  • Dyer, A. J. (1974). A review of flux-profile relationships. Boundary Layer Meteorology,7, 363–372.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Ganea, D., Mereuta, E., & Rusu, L. (2018). Estimation of the near future wind power potential in the Black Sea. Energies. https://doi.org/10.3390/en11113198.

    Article  Google Scholar 

  • Ganea, D., Mereuta, E., & Rusu, E. (2019). An evaluation of the wind and wave dynamics along the European coasts. Marine Science and Engineering. https://doi.org/10.3390/jmse7020043.

    Article  Google Scholar 

  • Georgopoulou, E., Mirasgedis, S., Sarafidis, Y., et al. (2018). Climatic preferences for beach tourism: an empirical study on Greek islands. Theoretical and Applied Climatology. https://doi.org/10.1007/s00704-018-2612-4.

    Article  Google Scholar 

  • Gilbert, R. O. (1987). Statistical methods for environmental pollution monitoring. New York: Van Nostrand Reinhold Company Inc.

    Google Scholar 

  • 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. https://doi.org/10.1002/asl.113.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s00704-009-0152-7.

    Article  Google Scholar 

  • Kendall, M. G. (1938). A new measure of rank correlation. Biometrika,30(1–2), 81–93.

    Article  Google Scholar 

  • Kendall, M. G. (1970). Rank correlation methods (4th ed.). London: Griffin.

    Google Scholar 

  • Kostianoy, A. G., & Kosarev, A. N. (2008). The Black Sea environment. Berlin Heidelberg: Springer.

    Book  Google Scholar 

  • 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. https://doi.org/10.1016/j.rse.2019.01.034.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s00376-010-0018-z.

    Article  Google Scholar 

  • Mann, H. B. (1945). Nonparametric tests against trend. Econometrica,13(3), 245–259.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s12562-014-0799-6.

    Article  Google Scholar 

  • Onea, F., & Rusu, E. (2012). Wind energy assessments along the Black Sea basin. Meteorological Applications,21(2), 316–329. https://doi.org/10.1002/met.1337.

    Article  Google Scholar 

  • Özsoy, E., & Ãœnlüata, Ãœ. (1997). Oceanography of the Black Sea: a review of some recent results. Earth-Science Reviews,42, 231–272.

    Article  Google Scholar 

  • Rusu, L., Bernardino, M., & Guedes Soares, C. (2014). Wind and wave modelling in the Black Sea. Journal of Operational Oceanography,7(1), 5–20. https://doi.org/10.1080/1755876X.2014.11020149.

    Article  Google Scholar 

  • 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. https://doi.org/10.3390/w10070924.

    Article  Google Scholar 

  • 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. https://doi.org/10.1175/2010BAMS3001.1.

    Article  Google Scholar 

  • 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. https://doi.org/10.1175/JCLI-D-12-00823.1.

    Article  Google Scholar 

  • 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.

  • Schlitzer, R. (2019). Ocean data view. https://odv.awi.de. Accessed 12 Oct 2019.

  • Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s Tau. Journal of the American Statistical Association,63, 1379–1389.

    Article  Google Scholar 

  • Shadid, S. (2011). Trends in extreme rainfall events of Bangladesh. Theoretical and Applied Climatology,104(3–4), 489–499. https://doi.org/10.1007/s00704-010-0363-y.

    Article  Google Scholar 

  • 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. https://doi.org/10.1098/rsta.2017.0240.

    Article  Google Scholar 

  • Sterl, A., & Caires, S. (2005). Climatology, variability and extrema of ocean waves: the Web-based KNMI/ERA-40 wave atlas. International Journal of Climatology. https://doi.org/10.1002/joc.1175.

    Article  Google Scholar 

  • 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. https://doi.org/10.1016/j.ocemod.2013.12.006.

    Article  Google Scholar 

  • 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 

  • 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. https://doi.org/10.1175/2011JCLI4198.1.

    Article  Google Scholar 

  • Tuller, S. E. (2004). Measured WS trends on the west coast of Canada. International Journal of Climatology,24, 1359–1374. https://doi.org/10.1002/joc.1073.

    Article  Google Scholar 

  • 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 

  • 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. https://doi.org/10.5194/nhess-12-961-2012.

    Article  Google Scholar 

  • 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. https://doi.org/10.4194/1303-2712-v14_4_17.

    Article  Google Scholar 

  • Wallace, J. M., & Gutzler, D. S. (1981). Teleconnections in the geopotential height field during the Northern hemisphere winter. Monthly Weather Review,109, 784–812.

    Article  Google Scholar 

  • 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. https://doi.org/10.1175/1520-0426.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s10236-006-0094-x.

    Article  Google Scholar 

  • Young, I. R., Zieger, S., & Babain, A. (2011). Global trends in wind speed and wave height. Science,332(6028), 451–455. https://doi.org/10.1126/science.1197219.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s11069-017-2783-9.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Zeng, X., Dickinson, R. E., & He, Y. (1998). Effect of surface sublayer on surface skin temperature and fluxes. Journal of Climate,11, 537–550.

    Article  Google Scholar 

  • 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. https://doi.org/10.1002/2016JC011905.

    Article  Google Scholar 

  • Zheng, C. W., Pan, J., & Li, C. Y. (2016). Global oceanic wind speed trends. Ocean and Coastal Management,129, 15–24. https://doi.org/10.1016/j.ocecoaman.2016.05.001.

    Article  Google Scholar 

Download references

Acknowledgements

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 information

Authors and Affiliations

  1. Istanbul Water and Sewerage Administration (ISKI), 34060, Eyüp/Istanbul, Turkey

    Tunay Çarpar

  2. Department of Civil Engineering, Yildiz Technical University, 34220, Esenler/Istanbul, Turkey

    Berna Ayat

  3. Department of Civil Engineering, Gebze Technical University, 41400, Gebze/Kocaeli, Turkey

    Burak AydoÄŸan

Authors
  1. Tunay Çarpar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Berna Ayat
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Burak AydoÄŸan
    View author publications

    You can also search for this author in PubMed Google Scholar

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.

Corresponding author

Correspondence to Berna Ayat.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Çarpar, T., Ayat, B. & Aydoğan, B. Spatio-Seasonal Variations in Long-Term Trends of Offshore Wind Speeds Over the Black Sea; an Inter-Comparison of Two Reanalysis Data. Pure Appl. Geophys. 177, 3013–3037 (2020). https://doi.org/10.1007/s00024-019-02361-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-019-02361-7

Keywords

Search

Navigation