Comparative assessment between historical and future trends in the daily maximum temperature parameter over selected stations of Iran

Document Type : Scientific and Research

Authors

1 Ph.D in Climatology, Department of Physical Geography and Environmental Planning, University of Sistan and Baluchestan, P. O. Box 987-98135, Zahedan, Iran

2 Associate Professor of Climatology, Department of Physical Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran

3 Associate Professor of Meteorology, Department of Meteorology Engineering, Istanbul Technical University, Maslak Istanbul 34469, Turkey

4 Professor of Climatology, Department of Physical Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran

Abstract

Objective of this study is to determine whether there are significant changes in maximum temperature trends between the current (1981-2010) and future (2011-2099) periods. To this end, statistical downscaling is used to project future changes in the maximum temperatures according to A2 and B2 scenarios of HADCM3 in the 7 selected stations of Iran. The possibilities of an accelerating trend are detected in the maximum temperature at 95% confidence level using of Mann–Kendall and Sen’s slope methods. The results showed that there is an increasing tendency in the maximum temperature trends over Iran, especially in the northern highlands for the future decades of the 21st century than the last three decades. The highest trend slopes in annual maximum temperatures are found by 0.69, 0.68, and 0.62°C per decade at Isfahan, Tabriz, and Tehran stations based on A2 scenario for the future decades (2011-2099), respectively, while the lowest trend slope is found at B-Abbas station that is equivalent to 0.14°C per decade based on B2 scenario. It is important to mention that the rate of warming trend will be accelerating based on temperature-time relations in coming decades. In this point, the future occurrences of desirable daily temperatures could be exposure in the southern coasts of Iran where it will be affected by more capacity of atmospheric humidity.

Keywords

References

1. Abbasnia, M.; Toros, H. (2016). Future changes in maximum temperature using the statistical downscaling model (SDSM) at selected stations of Iran. Journal of Modeling Earth Systems and Environment 2(2): 1-7.
2. Abbasnia, M.; Tavousi, T.; Khosravi, M.; Toros, H. (2016). Investigation of interactive effects between temperature trend and urban climate during the last decades: a case study of Isfahan-Iran. European Journal of Science and Technology, 4(7): 81-74.
3. Croitoru, A.E.; Piticar, A. (2013). Changes in daily extreme temperatures in the extra-Carpathians
regions of Romania. International Journal of Climatology, 33: 1987–2000.
4. Darand, M.; Masoodian, A.; Nazaripour, H.; Mansouri Daneshvar, M.R. (2015). Spatial and temporal trend analysis of temperature extremes based on Iranian climatic database (1962–2004). Arabian Journal of Geosciences, 8: 8469-8480.
5. EEA (2008). Impact’s of Europe changing climate in 2008. Indicator based assessment; European Environment Agency reports, 4, 242 pp.
6. Gray, B.R.; Lyubchich, V.; Gel, Y.R.; Rogala, J.T.; Robertson, D.M.; Wei, X. (2016). Estimation of river and stream temperature trends under haphazard sampling. Statistical Methods and Applications, 25(1): 89-105.
7. Hamdi, M.R.; Abu-Allaban, M.; Al-Shayeb, A.; Jaber, M.; Momani, N.M. (2009). Climate change in Jordan: a comprehensive examination approach. American Journal of Environmental Sciences, 5(1): 58–68.
8. Huang, J.; Zhang, J.; Zhang, Z.; Xu, C.; Wang, B.; Yao, J. (2011). Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method. Stochastic Environmental Research and Risk Assessment, 25(6): 781-792.
9. Insaf, T.Z.; Lin, S.; Sheridan, S.C. (2013). Climate trends in indices for temperature and precipitation across New York State, 1948–2008. Air Quality, Atmosphere & Health 6(1): 247-257.
10. IPCC (2013). Climate change 2013; The physical science basis. Contribution of working group I to the fifth assessment, Report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York USA, 1550 pp.
11. IPCC (2007). Climate Change: the physical science basis. Contribution of working group I to the fourth assessment, Report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York USA, 331 pp.
12. IRIMO (2012). Summary reports of Iran’s extreme climatic events. Ministry of roads and urban development, Iran Meteorological Organization. (Via: www.cri.ac.ir)
13. Jones, P.D.; Moberg, A. (2003). Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001. Journal of Climate, 16(2): 206-223.
14. Kendall, M.G. (1975). Rank correlation method, 4th edn. Charles Griffin, London, 202 pp.
15. Kim, H.S.; Chung, Y.S.; Tans, P.P.; Yoon, M.B. (2015). Climatological variability of air temperature and precipitation observed in South Korea for the last 50 years. Air Quality, Atmosphere & Health: 1-7.
16. Kumar, M.; Denis, D.M.; Suryavanshi, S. (2016). Long-term climatic trend analysis of Giridih district, Jharkhand (India) using statistical approach. Modeling Earth Systems and Environment, 2(116): 1-10.
17. Liu, Z.; Xu, Z. (2015). Climate change scenarios generated by using GCM outputs and statistical downscaling in an arid region. Desert, 20(2): 101-115.
18. Mahmood, R.; Babel, M.S. (2014). Future changes in extreme temperature events using the statistical downscaling model (SDSM) in the trans-boundary region of the Jhelum river basin. Weather and Climate Extremes, 5: 56-66.
19. Mann, H.B. (1945). Non-parametric tests against trend. Econometrical, 13: 245-259.
20. Masoodian, S.A. (2007). Trend analysis on temperature of Iran during the last half century. Geographical Research Quarterly, 38(3): 29-45.
21. Mojarrad, F.; Basati, S. (2014). Analysis of spatial and temporal variations of maximum temperatures in Iran. Journal of Spatial Planning, 18(2): 129-152.
22. Piticar, A.; Ristoiu, D. (2012). Analysis of air temperature evolution in northeastern Romania and evidence of warming trend. Carpathian Journal of Earth and Environmental Sciences, 7(4): 97-106.
23. Refat Nasher, N.M.; Uddin, M.N. (2013). Maximum and minimum temperature trends variation over northern and southern part of Bangladesh. Journal of Environmental Science and Natural Resources, 6(2): 83-88.
24. Saboohi, R.; Soltani, S.; Khadagholi, M. (2012). Trend analysis of temperature parameters in Iran. Theoretical and Applied Climatology, 109: 529–547.
25. Salmi, T.; Määttä, A.; Anttila, P.; Ruoho-Airola, T.; Ammell, 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. Publications of Air Quality, 31: 7-35.
26. Salon, S.; Cossarini, G.; Libralato, S.; Gao, X.; Solidoro, C.; Giorgi, F. (2008). Downscaling experiment for the Venice lagoon. I. Validation of the present-day precipitation climatology, Climate Research, 38(1): 31-41.
27. Semenov, M.A.; Stratonovitch, P. (2010). Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Research, 41(1): 1-12.
28. Smadi, M.M. (2006). Observed abrupt changes in minimum and maximum temperatures in Jordan in the 20th century. American Journal of Environmental Sciences, 2(3): 114–120.
29. Tabari, H.; Hosseinzadeh Talaee, P. (2011). Analysis of trends in temperature data in arid and semi-arid regions of Iran. Global and Planetary Change, 79: 1–10.
30. Toros, H. (2012). Spatial‐temporal variation of daily extreme temperatures over Turkey. International Journal of Climatology, 32(7): 1047-1055.
31. Whan, K.; Alexander, L.V.; Imielska, A., et al. (2014). Trends and variability of temperature extremes in the tropical Western Pacific. International Journal of Climatology, 34(8): 2585-2603.
32. Wilby, R.L.; Dawson, C.W. (2013). The statistical downscaling model: insights from one decade of application. International Journal of Climatology, 33(7): 1707-1719.
33. Wilby, R.L.; Dawson, C.W.; Barrow, E.M. (2002). SDSM- A decision support tool for the assessment of regional climate change impacts. Environmental Modeling and Software, 17(2): 145-157.
Natural Environment Change
Volume 2, Issue 2
July 2016
Pages 89-98

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