Projected Changes in Iran Temperature Based on Different Scenarios RCP

Darand, Mohammad; Hamidi, Samira

doi:10.22111/jneh.2020.33698.1642

Projected Changes in Iran Temperature Based on Different Scenarios RCP

Document Type : Research Article

Authors

Mohammad Darand ¹
Samira Hamidi ²

¹ Associate Professor of Climatology, Faculty of Natural Resources, University of Kurdistan, Iran & Board Member of Department of Zrebar Lake Environmental Research,Kurdistan Studies Institute, University of Kurdistan, Iran. Email:

² M.Sc. Student of Climatology, University of Kurdistan, Iran

10.22111/jneh.2020.33698.1642

Abstract

The aim of the current study is spatiotemporal analysis of changes in minimum, maximum and mean air temperature over Iran based on Representative Concentration Pathway (RCP) of the fifth report of IPCC. To do this, three datasets have been used: 1) Daily maximum, minimum and mean air temperature data for 42 synoptic stations during 1/1/1979 to 31/12/2005, 2) National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) data for 26 variables, and 3) Representative Concentration Pathway (RCP) scenarios data during 1/1/2006 to 31/12/2100. The model was calibrated using predictors from the NCEP/NCAR reanalysis datasets over the base period 1979–2005. The selected downscaling model structure has been done by a recommended method by Mahmood and Babel (2013) which is a combination of the correlation matrix, partial correlation, and P-value was used. Due to the bias, downscaled temperature data forced by CanESM2 model was corrected using a bias correction technique for each station. Finally, changes in the characteristics of temperature were estimated for the future period (2006–2100) based on the future scenarios RCP2.6, RCP4.5 and RCP8 compared to the base period (1979–2005). The projected changes were assessed with the nonparametric modified Mann-Kendal trend test and Sen Slope estimator at 95% confidence level. The results showed great reliability of SDSM downscaled model structure and screening of variables. The findings illustrated that minimum, maximum and mean air temperature were projected to increase. The projected increases was larger in semi western part of country. Minimum air temperature projected to increase 0.35, 0.6 and over 1 ℃ based on the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Maximum air temperature increases rapidly after 2070 decade and projected to increase more than 1℃ rather than base period (1979-2005). The projected changes showed that warming of Iran’s air temperature more over 0.5 ℃ after 2040 and reached to 1.5 ℃ by the end of twenty first century.

Keywords

References

References (in Persian)

Abbassnia, M., Tavossi, T., Khosravi, M. (2017). A comprehensive assessment of seasonal changes in future maximum temperature of Iran during the warm period based on GCM Models. Geographical planning of spac quarterly journal, 7(25), 121-134. [In Persian]

Alijani, B. (2006). Climate of Iran, seventh edition. Payam Noor University Publications. Tehran. 221 p. [In Persian]

Asakereh, H., Shahbaee Kotenaee, A., Foroumadi, M. (2019). Evaluating Changes and Forecasting Minimum Temperature in the West of Mazandaran Province Using Statistical Downscaling Model SDSM. Journal of Water and Soil Science, 23(1),101-119. doi:10.29252/jstnar.23.1.8 [In Persian]

Dastranj, A., Shahbazi, A., Mohsenisaravi, M., Salehnasab, A., Jafari, S. (2016). Climate Modeling and comparison of changes in climatic parameters using SDSM in the northern and southern sides of the Alborz. Iranian Journal of Watershed Management Science and Engineering, 10 (32),11-26. URL: http://jwmsei.ir/article-1-614-fa.html [In Persian]

Karimi, M., Sotoodeh, F., Rafati, S. (2018). Analysis of changes trend and forecasting extreme temperature in southern Caspian Sea. Applied research in geographic sciences, 48, 79-93. doi:10.29252/jgs.18.48.79. [In Persian]

Masoodian, A. (2011). Climatology of Iran. First Edition, Sharia Toos publications, Mashhad, 288p. [In Persian]

Nikbakht Shahbazi, A. (2018). Climate change impact assessment on agricultural crop virtual water under RCPs Scenarios in Khozestan province. Journal of the Earth and Space Physics, 44(2), 363-378. doi: 10.22059/JESPHYS.2018.234830.1006907 [In Persian]

Salajegheh, A., Rafiei Sardoii, E., Moghaddamnia, A., Malekian, A., Araghinejad, Sh., Khalighi Sigarodi, Sh., Pourjam A.S. (2017). Performance assessment of LARS-WG and SDSM downscaling models in simulation of precipitation and temperature. Iranian journal of soil and water research, 2(386), 253-262. doi:10.22059/IJSWR.2017.62601 [In Persian]

Sedaghat Kerdar, A., Rahimzadeh, F. (2007). Variation of growing season length (GSL) over second half of 20th in Iran. Pajouhesh Sazandegi, 75, 182-193. [In Persian]

References (in English)

Abbasnia, M., Toros, H., (2016), Future changes in maximum temperature using the statistical downscaling model (SDSM) at selected stations of Iran. Modeling Earth Systems and Environment, 2(2), 68.doi: 10.1007/s40808-016-0112-z.

Alexander, L.V., Arblaster, J.M., (2017), Historical and projected trends in temperature and precipitation extremes in Australia in observations and CMIP5. Weather and Climate Extremes, 15, 34–56.doi: 10.1016/j.wace.2017.02.001.

Almazroui, M., Sajjad-Saeed, M.N.I., Alkhalaf, A.K., Dambul, R., (2017), Assessment of Uncertainties in Projected Temperature and Precipitation over the Arabian Peninsula Using Three Categories of Cmip5 Multimodel Ensembles. Earth Systems and Environment, 23, 1-20. doi: 10.1007/s41748-017-0027-5.

Buchignani, E., Mercogliano, P., Panitz, H.J., Montesarchio, M., (2018), Climate change projections for the Middle East North Africa domain with COSMO-CLM at different spatial resolutions. Advances in Climate Change, 9, 66-80. doi: 10.1016/j.accre.2018.01.004.

Change, I.P.O.C., (2007), Climate change 2007: the physical science basis: summary for policymakers. Geneva: IPCC.

Darand, M., Pazhooh, F., Saligheh, M., (2019), Trend analysis of tropospheric specific humidity over Iran during 1979–2016. International Journal of Climatology, 39(10), 4058-4071. doi: 10.1002/joc.6059

Dorji, S., Herath, S., Mishra, B.K. (2017). Future climate of colombo downscaled with SDSM-neural network. Climate, 5(1), 24. doi: 10.3390/cli5010024.

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. doi: 10.1007/s00477-010-0441-9.

Katiraie‐Boroujerdy, P. S., Akbari Asanjan, A., Chavoshian, A., Hsu, K. L., Sorooshian, S. (2019). Assessment of seven CMIP5 model precipitation extremes over Iran based on a satellite‐based climate data set. International Journal of Climatology, 39(8), 3505-3522. doi:10.1002/joc.6035

Khadka, D., Pathak, D. (2016). Climate change projection for the Marsyangdi river basin, Nepal using statistical downscaling of GCM and its implications in geo-disasters. Geo-environmental Disasters, 3(1), 15. doi: 10.1186/s40677-016-0050-0.

Mahmood, R., Babel, M.S. (2013). Evaluation of SDSM developed by annual and monthly sub-models for downscaling temperature and precipitation in the Jhelum basin, Pakistan and India. Theoretical and applied climatology, 113(1-2), 27-44. doi: 10.1007/s00704-012-0765-0.

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 (6), 56–66. doi:10.1016/j.wace.2014.09.001

Mansouri Daneshvar, M.R., Ebrahimi, M., Nejadsoleymani, H. (2019). An overview of climate change in Iran: facts and statistics. Environmental systems research. 8, 7. doi: 10.1186/s40068-019-0135-3.

Parvaze, S., Ahmad, L., Parvaze, S., Kanth, R.H. (2017). Climate change projection in Kashmir Valley (J and K). Current World Environment, 12(1), 107. doi: 10.12944/CWE.12.1.13

Salzmann, N., Frei, C., Vidale, P.L., Hoelzle, M ., (2007).The application of Regional Climate Model output for the simulation of high-mountain permafrost scenarios. Global Planet Change, 56(1–2), 188–202.doi: 10.1016/j.gloplacha.2006.07.006.

Tabari, H., Hosseinzadeh Talaee, P. (2013). Moisture index for Iran: Spatial and temporal analyses. Global and Planetary Change, 100: 11-19. doi: 10.1016/j.gloplacha.2012.08.010.

Vaghefi, S.A., Keykhai, M., Jahanbakhshi, F. et al. (2019). The future of extreme climate in Iran. Scientific Reports 9, 1464. doi: 10.1038/s41598-018-38071-8.

Vallam, P., Qin, X.S. (2017). Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes. Theoretical and Applied Climatology, 134(1-2), 669-688. doi: 10.1007/s00704-017-2299-y.

Wilby, R.L., Dawson, C.W., Barrow, E.M. (2002). SDSM–adecision support tool for the assessment to fregional climate change impacts. Environmental Modelling Software, 17(2), 145-157. doi:10.1016/S1364-8152(01)00060-3.