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Investigating recent changes in the wind speed trends over Turkey

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The wind has considerable effects on the ecosystem and evaporation as an essential parameter of the hydrological cycle. Therefore, determining historical changes in the wind will help to specify these effect levels. Although there are studies on the determination of wind speed trends by several researchers in Turkey, it is necessary to investigate the changes in the trend structure with recent data. For this purpose, the trends of monthly surface wind speed data from 1970 to 2021 belonging to 199 meteorology observation stations in Turkey are determined in the present study. The nonparametric Mann–Kendall test and Sen’s slope method are used in the trend analysis accounting for serial correlation effects. The trend analysis results of wind speed data are evaluated temporally and spatially for seven geographical regions within Turkey. As a result of this study, a prominent part of stations in Turkey shows a decrease or significant decrease trend. In addition, as a result of comparisons made with previous studies, it is determined that the trend structure of the wind speed in the country has changed. In the annual and monthly wind speeds, it is observed that the number of stations has a "significant trend" decreased considerably.
Czasopismo
Rocznik
Strony
1305--1319
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
  • Department of Civil Engineering, Harran University, Sanliurfa 63050, Turkey
  • Department of Engineering, University of Durham, South Road, Durham DH1 3LE, UK
autor
  • Department of Civil Engineering, Harran University, Sanliurfa 63050, Turkey
  • Department of Engineering, University of Durham, South Road, Durham DH1 3LE, UK
Bibliografia
  • 1. Azorin-Molina C, Rehman S, Guijarro JA, McVicar TR, Minola L, Chen D, Vicente-Serrano SM (2018) Recent trends in wind speed across Saudi Arabia, 1978–2013: a break in the stilling. Int J Climatol 38:e966–e984. https://doi.org/10.1002/joc.5423
  • 2. Birsan MV, Nita IA, Craciun A, Sfîcă L, Radu C, Szep R, Keresztesi A, Micheu MM (2020) Observed changes in mean and maximum monthly wind speed over Romania since ad 1961. Rom Rep Phys 72(1):702
  • 3. Citakoglu H, Minarecioglu N (2021) Trend analysis and change point determination for hydro-meteorological and groundwater data of Kizilirmak basin. Theor Appl Climatol 145(3–4):1275–1292. https://doi.org/10.1007/s00704-021-03696-9
  • 4. Dadaser-Celik F, Cengiz E (2014) Wind speed trends over Turkey from 1975 to 2006. Int J Climatol 34(6):1913–1927. https://doi.org/10.1002/joc.3810
  • 5. Demir V (2022) Trend analysis of lakes and sinkholes in the Konya closed basin, in Turkey. Nat Hazards 112(3):2873–2912. https://doi.org/10.1007/s11069-022-05327-6
  • 6. Diao W, Zhao Y, Dong Y, Zhai J, Wang Q, Gui Y (2020) Spatiotemporal variability of surface wind speed during 1961–2017 in the Jing-jin-ji region, China. J Meteorol Res 34(3):621–632. https://doi.org/10.1007/s13351-020-9119-5
  • 7. Eymen A, Köylü U (2018) Seasonal trend analysis and arima modeling of relative humidity and wind speed time series around Yamula Dam. Meteorol Atmos Phys 131(3):601–612. https://doi.org/10.1007/s00703-018-0591-8
  • 8. Gavrilov MB, Tošić I, Marković SB, Unkašević M, Petrović P (2016) Analysis of annual and seasonal temperature trends using the Mann-Kendall test in Vojvodina, Serbia. IdRojárás 120(2):183–198
  • 9. Gocic M, Trajkovic S (2013) Analysis of changes in meteorological variables using Mann–Kendall and Sen’s slope estimator statistical tests in Serbia. Global Planet Change 100:172–182. https://doi.org/10.1016/j.gloplacha.2012.10.014
  • 10. Gumus V, Soydan N, Simsek O, Algin H, Akoz M, Yenigun K (2017) Seasonal and annual trend analysis of meteorological data in Sanliurfa, Turkey. Eur Water 59:131–136
  • 11. Haktanir T, Citakoglu H (2014) Trend, independence, stationarity, and homogeneity tests on maximum rainfall series of standard durations recorded in Turkey. J Hydrol Eng 19(9):5014001. https://doi.org/10.1061/(asce)he.1943-5584.0000973
  • 12. Hamed KH (2008) Trend detection in hydrologic data: the Mann-Kendall trend test under the scaling hypothesis. J Hydrol 349(3–4):350–363. https://doi.org/10.1016/j.jhydrol.2007.11.009
  • 13. Kendall MG (1948) Rank correlation methods. Griffin, London
  • 14. Kousari MR, Ahani H, Hakimelahi H (2013) An investigation of near surface wind speed trends in arid and semiarid regions of Iran. Theor Appl Climatol 114(1–2):153–168. https://doi.org/10.1007/s00704-012-0811-y
  • 15. Laapas M, Venäläinen A (2017) Homogenization and trend analysis of monthly mean and maximum wind speed time series in Finland, 1959–2015. Int J Climatol 37(14):4803–4813. https://doi.org/10.1002/joc.5124
  • 16. Li Z, Zn X, Cw Z (2021) Observation analysis of wind climate in China for 1971–2017 under the demand of wind energy evaluation and utilization. Energy Rep 7:3535–3546. https://doi.org/10.1016/j.egyr.2021.06.012
  • 17. Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245–259. https://doi.org/10.2307/1907187
  • 18. Minola L, Azorin-Molina C, Chen D (2016) Homogenization and assessment of observed near-surface wind speed trends across Sweden, 1956–2013. J Clim 29(20):7397–7415. https://doi.org/10.1175/jcli-d-15-0636.1
  • 19. Mohsin T, Gough WA (2009) Trend analysis of long-term temperature time series in the Greater Toronto area (GTA). Theor Appl Climatol 101(3–4):311–327. https://doi.org/10.1007/s00704-009-0214-x
  • 20. Natarajan N, Rehman S, Shiva N, Vasudevan M (2021) Evaluation of wind energy potential of the state of Tamil Nadu, India based on trend analysis. FME Trans 49(1):244–251. https://doi.org/10.5937/fme2101244N
  • 21. Nobel PS (1981) Wind as an Ecological Factor book section, Ch 16. pp. 475–500. https://doi.org/10.1007/978-3-642-68090-8_16
  • 22. Rehman S (2012) Long-term wind speed analysis and detection of its trends using Mann–Kendall test and linear regression method. Arab J Sci Eng 38(2):421–437. https://doi.org/10.1007/s13369-012-0445-5
  • 23. Salas JD (1980) Applied modeling of hydrologic time series. Water Resources Publication, Littleton 10.1002/9781118445112.stat07809
  • 24. Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Associ 63(324):1379–1389
  • 25. Simsek O (2021) Hydrological drought analysis of Mediterranean basins, Turkey. Arab J Geosci 14(20):1–17. https://doi.org/10.1007/s12517-021-08501-5
  • 26. Suhaila J, Yusop Z (2017) Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia. Meteorol Atmos Phys 130(5):565–581. https://doi.org/10.1007/s00703-017-0537-6
  • 27. Von Storch H, Navarra A (1999) Analysis of climate variability: applications of statistical techniques. In: von Storch H, Navarra A (eds) Proceedings of an autumn school organized by the commission of the European community on Elba from October 30 to November 6, 1993. Springer Science and Business Media, Berlin
  • 28. Wu J, Shi Y (2021) Changes in surface wind speed and its different grades over China during 1961–2020 based on a high-resolution dataset. Int J Climatol 42(7):3954–3967. https://doi.org/10.1002/joc.7453
  • 29. Yagbasan O, Demir V, Yazicigil H (2020) Trend analyses of meteorological variables and lake levels for two shallow lakes in central Turkey. Water 12(2):414. https://doi.org/10.3390/w12020414
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bd4e9e28-8e6d-40ee-9141-0e040b775d25
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