Downscaling of Precipitation and Temperature Using CanESM2 Model Based on RCP Scenarios (case study: Horrood River)

Document Type : Research Article

Authors

1 Assistant Professor, Faculty of Agriculture, Lorestan University, Khorramabad, Iran

2 PhD student of Water Structures Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran

3 Associate Professor, Faculty of Agriculture, Lorestan University, Khorramabad, Iran

4 Associate Professor, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran

10.22059/ije.2022.346258.1664

Abstract

In this study, the effects of climate change on meteorological parameters in the Horrood river in lorestan Province, using CanESM5 model under RCP scenarios (RCP2.6, RCP4.5 and RCP8.5) was evaluated based on the sixth IPCC report in three time periods including the near future (2026-2050), the middle future (2051-2075) and the distant future (2076-2100). The statistical downscaling model (SDSM) was used to predict precipitation and mean temperature in the baseline period 1970-2005 at Kaka Reza and Dehno synoptic stations. The results of this study, in both Kaka Reza and Dehno stations, indicated a decreasing in precipitation and an increasing in average temperature under the all three RCP scenarios over the future period, so that in the distant future (2076-2100), under the RCP8.5 scenario (i.e. the pessimistic one), at Kaka Reza and Dehno synoptic stations, the precipitation showed the highest decreased by 36 and 39 percent in monthly scale and 30.36 and 33.35 percent in annual scale respectively and the mean temperature showed the highest increased by 17.5 and 17.1 in monthly scale and 9.32 and 9.06 in annual scale respectively. Finally, the results of this study showed that the climate change will affect precipitation and temperature in the Horrood river basin.

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References

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Iranian journal of Ecohydrology
Volume 9, Issue 3
October 2022
Pages 657-673

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History

  • Receive Date: 31 March 2022
  • Revise Date: 30 April 2022
  • Accept Date: 30 June 2022

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