Investigation of Global Warming Case of Antalya

Antalya is one of the most important cities of Turkey in terms of agriculture, tourism and population. In this study, the global warming case of Antalya was investigated by using the monthly mean maximum, monthly mean minimum and monthly mean temperature data of Elmalı, Korkuteli, Antalya, Manavgat and Gazipaşa meteorology stations between 1970 and 2017. For this aim, trend analyses were performed by Mann Kendall Rank Correlation method and beginnings of trends were determined. Run, interquartile range and autocorrelation tests were applied before trend analysis test. 99.99% confidence interval was used for all tests. Run test results indicated that the data is homogenous. According autocorrelation test results, there is not autocorrelation in tha data except monthly mean minimum temperature data of Antalya station for August. Therefore, prewhitening was used for monthly mean minimum temperature data of Antalya station for August. The 12-month average value of the increasing trend was calculated as 98.33% for the mean temperature, 88.33% for the mean maximum temperature and 80% for the mean minimum temperature. The 12-month average value of the statistically significant increasing trend was calculated as 10% for the mean temperature, 5% for the mean minimum temperature and 0% for the mean maximum temperature. If 95% confidence level was used for Mann-Kendall test, the 12-month average value of the statistically significant increasing trend was calculated as 61.9% for the mean temperature, 34.5% for the mean maximum temperature and 51.2% for the mean minimum temperature. These results show that there is global warming in Antalya. The beginnings of statistically significant trends vary between 1992 and 2009. While water consumption is increasing due to increase in agriculture, tourism and population in Antalya, the global warming detected in this study shows that both water consumption and losses in water resources will increase further. Precautions are suggested in the results section.

Investigation of Global Warming Case of Antalya

Antalya is one of the most important cities of Turkey in terms of agriculture, tourism and population. In this study, the global warming case of Antalya was investigated by using the monthly mean maximum, monthly mean minimum and monthly mean temperature data of Elmalı, Korkuteli, Antalya, Manavgat and Gazipaşa meteorology stations between 1970 and 2017. For this aim, trend analyses were performed by Mann Kendall Rank Correlation method and beginnings of trends were determined. Run, interquartile range and autocorrelation tests were applied before trend analysis test. 99.99% confidence interval was used for all tests. Run test results indicated that the data is homogenous. According autocorrelation test results, there is not autocorrelation in tha data except monthly mean minimum temperature data of Antalya station for August. Therefore, prewhitening was used for monthly mean minimum temperature data of Antalya station for August. The 12-month average value of the increasing trend was calculated as 98.33% for the mean temperature, 88.33% for the mean maximum temperature and 80% for the mean minimum temperature. The 12-month average value of the statistically significant increasing trend was calculated as 10% for the mean temperature, 5% for the mean minimum temperature and 0% for the mean maximum temperature. If 95% confidence level was used for Mann-Kendall test, the 12-month average value of the statistically significant increasing trend was calculated as 61.9% for the mean temperature, 34.5% for the mean maximum temperature and 51.2% for the mean minimum temperature. These results show that there is global warming in Antalya. The beginnings of statistically significant trends vary between 1992 and 2009. While water consumption is increasing due to increase in agriculture, tourism and population in Antalya, the global warming detected in this study shows that both water consumption and losses in water resources will increase further. Precautions are suggested in the results section.

___

  • [1] V. A., Steinke, LA., Martins Palhares de Melo, M., Luiz Melo, R., Rodrigues da Franca, R., Luna Lucena, E., Torres Steinke, E., “Trend analysis of air temperature in the federal district of Brazil: 1980–2010”, Climate, 2020, doi: 10.3390/cli8080089.
  • [2] J., Tian, J., Liu, J., Wang, C., Li, H., Nie, F., Yu, “Trend analysis of temperature and precipitation extremes in major grain producing area of China”, International Journal of Climatology, 2017, doi: 10.1002/joc.4732.
  • [3] D., Fenner F, Meier D, Scherer A, Polze A., “ Spatial and temporal air temperature variability in Berlin, Germany, during the years 2001-2010”, Urban Climate, 2014, doi: 10.1016/j.uclim.2014.02.004.
  • [4] R., Saboohi, S., Soltani, M., Khodagholi, “Trend analysis of temperature parameters in Iran, Theoretical and Applied” Climatology, 2012, doi: 10.1007/s00704-012-0590-5.
  • [5] I., Ahmad, S., Zhaobo, D., Weitao, R., Ambreen, “Trend analysis of January temperature in Pakistan over the period of 1961-2006: Geographical Perspective”, Pakistan Journal of Meteorology, Vol. 7, no. 13, pp. 11-22, 2010.
  • [6] A., Toreti, F., Desiato, “Temperature trend over Italy from 1961 to 2004”, Theoretical and Applied Climatology, 2008, doi: 10.1007/s00704-006-0289-6.
  • [7] M., Domroes, A., El‐Tantawi, “Recent temporal and spatial temperature changes in Egypt”, International Journal of Climatology: A Journal of the Royal Meteorological Society, 2005, doi: 10.1002/joc.1114.
  • [8] M. I., Chidean j, Muñoz-Bulnes J, RamiroBargueño A. J., Caamaño S, Salcedo-Sanz S., “Spatio-temporal trend analysis of air temperature in Europe and Western Asia using data-coupled clustering”, Global and Planetary Change, 2015, doi: 10.1016/j.gloplacha.2015.03.006.
  • [9] S. A., Salman, S., Shahida, T., Ismail, E., Chung, A. M., Al-Abadic, “Long-term trends in daily temperature extremes in Iraq”, Atmospheric Research, vol. 198, no. 1, pp. 97-107, 2017.
  • [10] M., Karabulut, “Doğu Akdeniz’de ekstrem maksimum ve minimum sıcaklıkların trend analizi”, KSÜ Doğa Bilimleri Dergisi, Özel Sayı, pp. 37-44, 2012.
  • [11] Y., Kızılelma, M., Çelik, M., Karabulut, “İç Anadolu Bölgesinde sıcaklık ve yağışların trend analizi”, Türk Coğrafya Dergisi, vol. 64, pp. 1-10, 2015.
  • [12] E., Macana, E., Yeşilırmak, E., “Büyük Menderes Havzasında Ortalama, Maksimum Ve Minimum Sıcaklık Eğilimleri”, Journal of Adnan Menderes University Agricultural Faculty, vol. 12, no 1, pp. 73 – 80, 2015.
  • [13] S., Tokgöz, t., Partal, “Karadeniz Bölgesinde Yıllık Yağış ve Sıcaklık Verilerinin Yenilikçi Şen ve Mann-Kendall Yöntemleri ile Trend Analizi”, Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 10, no. 2, pp. 1107-1118, 2020.
  • [14] F., Cosun, m., Karabulut, “Kahramanmaraş’ta ortalama, minimum ve maksimum sıcaklıkların trend analizi” Türk Coğrafya Dergisi, vol. 53, pp. 41-50, 2009.
  • [15] A. D., Demir, Y., Demir, Ü., Şahin, R., Meral, “Bingöl İlinde Sıcaklık ve Yağışların Trend Analizi ve Tarıma Etkisi”, Türk Tarım ve Doğa Bilimleri Dergisi, vol. 4, no. 3, pp. 284-291, 2017.
  • [16] K. Saplıoğlu, M., Kilit, M., “İklim Değişikliğinin Afyon İlindeki Yağış ve Sıcaklıklara Etkisinin Araştırılması ve Trendlerinin Belirlenmesi”, Engineering Sciences , vol. 7 , no. 4 , pp., 696-705, 2012.
  • [17] P., Polat, M., Sunkar, “Rize’nin iklim özellikleri ve Rize çevresinde uzun dönem sıcaklık ve yağış verilerinin trend analizleri”, Fırat Üniversitesi Sosyal Bilimler Dergisi, 2017, doi: 10.18069/firatsbed.346684.
  • [18] A. Ülke, T., Özkoca, “Sinop, Ordu ve Samsun illerinin sıcaklık verilerinde trend analizi”, Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, doi: 10.17714/gumusfenbil.351294, 2018.
  • [19] D. R., HELSEL, R.M., HIRSCH, Statistical Methods in Water Resources, Elsevier, New York, USA, 1992.
International Scientific and Vocational Studies Journal-Cover
  • ISSN: 2618-5938
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 2017
  • Yayıncı: Umut SARAY