Projection of Climate Changes in Yazd Province in both the Near and Distant Future using SDSM Linear Multiple Model

Document Type : Original Article

Authors

1 Assistant Professor, Faculty of Natural Resources, Department of Ecological Engineering, University of Jiroft, Jiroft, Iran.

2 Assistant Professor, Faculty of Literature and Humanities, Department of Geography, University of Jiroft, Jiroft, Iran.

3 Ph.D., Faculty of Natural Resources, University of Hormozgan, Bandar Abbas, Iran.

4 PhD student, Faculty of Natural Resources, University of Tehran, Karaj, Iran

Abstract

In recent decades, the increase in temperature has caused widespread climate change all over the world, especially in arid and semi-arid regions of Iran and Yazd province. The purpose of this study is to project climate change in Yazd province using the CanESM2 model and new emission scenarios (RCP) during 2021-2050 (near future) and 2051-2080 (distant future) and to study the trend of changes in the baseline period using the Mann-Kendall test. The statistical indices of R2, RMSE, and NSE were used to evaluate the performance of the CanESM2 model. According to the results, the model had an appropriate performance for projecting precipitation and temperature in the future period and was classified into good and very good classes in terms of capability. Investigating the trend of the annual change of temperature and precipitation in the baseline period showed that the temperature had an increasing trend under most scenarios and stations, while the trend of the change of precipitation was no significant. The results of temperature changes in Yazd province indicated an increase of 2.2, 1.2, and 2.5 °C during 2021-2050 and 2.28, 3.19, and 4.77°C during 2051-2080 under RCP2, RCP4.5, and RCP8.5 scenarios, respectively. Changes in precipitation in Yazad province during the winter season showed a decrease in precipitation by 32, 26, and 34% during 2021-2050 and by 32, 32, and 5% during 2051-2080 under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively.

Keywords


  1. Agreement, P. (2015). UNFCCC, Adoption of the Paris agreement. COP. 25th session Paris, 30.
  2. Alavinia, S. H. & Zarei, M. (2020). Analysis of Extreme Temperature Change Trend under Future Scenarios in order to Assess Climate Fluctuations (Case Study: Sanandaj and Saghez Synoptic Stations). Arid Regions Geographics Studies, 11(41), 1-16.
  3. Dash, S. S., Sahoo, B. & Raghuwanshi, N. S. (2019). A SWAT-Copula based approach for monitoring and assessment of drought propagation in an irrigation command. Ecological Engineering, 127, 417-430.
  4. Asadi Zarch, M. A. (2017). Analyzing climate change effects on drought occurrence in Yazd province, Iran. Desert Management, 5(9), 74-90. (in Farsi)
  5. Feyissa, G., Zeleke, G., Bewket, W. & Gebremariam, E. (2018). Downscaling of future temperature and precipitation extremes in Addis Ababa under climate change. Climate, 6(3), 58.
  6. Gaitán, E., Monjo, R., Pórtoles, J. & Pino-Otín, M. R. (2019). Projection of temperatures and heat and cold waves for Aragón (Spain) using a two-step statistical downscaling of CMIP5 model outputs. Science of the Total Environment, 650(2), 2778-2795.
  7. Givati, A., Thirel, G., Rosenfeld, D. & Paz, D. (2019). Climate change impacts on streamflow at the upper Jordan River based on an ensemble of regional climate models. Hydrology: Regional Studies, 21, 92-109.
  8. Gong, Z., Kawamura, K., Ishikawa, N., Goto, M., Wulan, T., Alateng, D., ... & Ito, Y. (2015). MODIS normalized difference vegetation index (NDVI) and vegetation phenology dynamics in the Inner Mongolia grassland. Solid Earth, 6(4), 1185.
  9. Haghshenas Getabi, R., Mohseni, B., Hosseini, A. & Dadashi, N. (2014). Investigation of climate change trend in Tehran province using temperature and precipitation extreme Indices. In: 5th International Conference on Integrated Natural Disaster Management. Permanent Secretariat of the Comprehensive Crisis Management Conference. Tehran, Iran. 23-24 February 2014. pp. 1-8. (in Farsi)
  10. Hawkins, E., Ortega, P., Suckling, E., Schurer, A., Hegerl, G., Jones, P., ... & Thorne, P. (2017). Estimating changes in global temperature since the preindustrial period. Bulletin of the American Meteorological Society, 98(9), 1841-1856.
  11. Intergovernmental Panel on Climate Change (IPCC). (2007). In: Solomon, S., et al. (Eds.), Climate Change 2007: 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.
  12. IPCC, (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151(10.1017).
  13. Intergovernmental Panel of Climate Change (IPCC). (2013). Working Group, I contribution to the IPCC Fifth Assessment Report Climate Change 2013: The physical science basis-summary for policymakers. Intergovernmental Panel of Climate Change, Stockholm.
  14. Jafari, M. (2008). Investigation and analysis of climate change factors in Caspian Zone forests for last fifty years. Forest and Poplar Research, 16(32), 314-326. (in Farsi)
  15. Jafary Godeneh, M., Salajeghe, A., Haghighi, P. (2020). Forecast Comparative of Rainfall and Temperature in Kerman County Using LARS-WG6 Models. Ecohydrology, 7(2), 529-538. (in Farsi)
  16. Karimi, M. & Nabizadeh, A. (2018). Assessment of climate change impacts on climate parameters of Urmia Lake basin during 2011-2040 years by using LARS-WG. Geography and Planning, 22(65), 267-285. (in Farsi)
  17. Kendall, M. G. (1975). Rank Correlation Methods. Charles Griffin, London, UK, 202, 15.
  18. Kharin, N. (2002). Vegetation degradation in Central Asia under the impact of human activities. Springer Science & Business Media. Gemany: Springer Nature.
  19. Klaus, G., Ernst, A. & Oswald, L. (2020). Psychological factors influencing laypersons’ acceptance of climate engineering, climate change mitigation and business as usual scenarios. Technology in Society, 60, 101222.
  20. Li, J., Wang, Z., Wu, X., Guo, S. & Chen, X. (2020). Flash droughts in the Pearl River Basin, China: Observed characteristics and future changes. Science of The Total Environment, 707, 136074.
  21. Mann, H.B., 1945. Non-parametric tests against trend, Econometrica 13, MathSci Net, pp. 245-259.
  22. Miao, C., Duan, Q., Sun, Q., Huang, Y., Kong, D., Yang, T. & Gong, W. (2014). Assessment of CMIP5 climate models and projected temperature changes over Northern Eurasia. Environmental Research Letters, 9(5), 055007.
  23. Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D. & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885-900.
  24. Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., Van Vuuren, D. P., ... & Meehl, G. A. (2010). The next generation of scenarios for climate change research and assessment. Nature, 463(7282), 747-756.
  25. Phillips, J. D. (2019). State factor network analysis of ecosystem response to climate change. Ecological Complexity, 40, 100789.
  26. Sadidi, J., Jafary Godeneh, M., Sajedi, H. & Hamzehzadeh, G. (2019). Investigation of trend and prediction of temperature changes in arid and semi-arid regions (Case study: Kerman province). In: 14th Congress of the Iranian Geographic Society. Tehran, Iran. 14 May 2019. pp. 1-17. (in Farsi)
  27. Saremi Naeini, M. (2017). Estimation of the Frequency of Speed and Direction of the Erosive Winds and Dust storms in the Yazd Province, by Using Windrose, Stormrose and Sandrose. Desert Management, 4(8), 96-106. (in Farsi)
  28. Soltani Gerdfaramarzy, M., Mozafari, Gh. & Shafie, Sh. (2018). Analysis of the effects of recent climatic droughts on the salinity of subterranean waters using geostatistical and GIS methods in Yazd- Ardakan Plain. Scientific-Research Quarterly of Geographical Data (SEPEHR), 27(106), 179-199. (in Farsi)
  29. Varshavian, V., Khalili, A., Ghahreman, N. & Hajjam, S. (2011). Trend analysis of minimum, maximum, and mean daily temperature extremes in several climatic regions of Iran. Earth and Space Physics, 37(1), 169-179. (in Farsi)
  30. Wilby, R. L. & Dawson, C. W. (2013). The statistical downscaling model: insights from one decade of application. Climatology, 33(7), 1707-1719.
  31. Yin, L., Dai, E., Zheng, D., Wang, Y., Ma, L. & Tong, M. (2020). What drives the vegetation dynamics in the Hengduan Mountain region, southwest China: Climate change or human activity? Ecological Indicators, 112, 1-12.
  32. Zhang, C., Wang, X., Li, J. & Hua, T. (2020). Identifying the effect of climate change on desertification in northern China via trend analysis of potential evapotranspiration and precipitation. Ecological Indicators, 112, 1-9.