Assessment of Climate Change in Bojnourd Station in 2016-2050 using Downscaling Models LARS WG and SDSM

Document Type : Research Article

Authors

1 Associate Professor, Faculty of Geography and Environmental Sciences, Hakim University of Sabzevar, Iran

2 Associate Professor, Faculty of New Science and Technologies, University of Tehran, Iran

3 Ph.D. Student, Faculty of Geography and Environmental Sciences, Hakim University of Sabzevar, Iran

4 M.Sc. Student, Faculty of New Science and Technologies, University of Tehran, Iran

Abstract

The climate of the land has always been changing over time but the current trend in climate change has become important due to the role of humans which has been unprecedented over the past years. In this study, The LARS WG and SDSM models are used to evaluate the climate change at Bojnourd station for downscaling climate and both models evaluate A and B scenarios but also used RCP new scenario in SDSM. The result of the status of the station showed temperature mean station is 13.52 c but after 2000, the temperature of the station is higher than its long-term average. The results of the LARS WG model show that precipitation will increase at the station in year 2050. In scenario B1, the amount of precipitation increase almost 16 mm more than base precipitation to 2050 and all season’s precipitation are increasing in this scenario. In scenario A2, the increase in this scenario reaches almost 256mm. In total, the SDSM model downloading to increase precipitation and this increase showed A1 and B2 scenarios more than RCP scenarios, therefore In the scenario A2 value is 289mm, the scenario B2 is 294 mm, the scenario RCP 2.6 is 264 mm, the scenario 4.5 RCP this is 273 mm and in the RCP scenario of 264 mm. In the case of temperature in the LARS WG model, the minimum temperature increases in both cases. The maximum winter temperature rise is 0.8 c in the A2 scenario. In both scenarios, the maximum temperature in March, April and May is the highest increase compared to other months. The SDSM model shows that the maximum and minimum annual temperatures of this model are lower temperatures than the base period. But the monthly increase in the months of March, April and May is the minimum and maximum increase, which indicates the matching of the results of both models.

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References

[1].   Mozafari gh, shafiei sh. predictive and spatial analysis drought in Yazd province in the period from 2030 to 2011 AD using general circulation models of the atmosphere International Conference on Architecture. International Conference on Architecture, Urbanism, Civil Engineering, Art, Environment Future Horizons & Retrospect. tehran. 2015:1-9. [Persian]
[2].   kelanki m and karandish f. Forecasting the long-term effects of climate change on climatic components in the region wet, journal of Water and Irrigation Engineering,2015,20(5),131-148. [Persian]
[3].   Tirgarfakheri f, arezomandi f. Application downscaling of GCMs to create a map of rainfall on the southern shores of the Caspian. International Symposium on Environmental and Water Resources Engineering. tehran: Environmental and Water Resources Engineering. 2015:1-10.[Persian]
[4].    Mazafari gh,moradi h,khodaqoli m. Evaluation of drought conditions in Sistan and Balouchestan province during 1391 – 1410 Using the finer scale of exponential data of the general circulation model of the atmosphere.Quarterly Journal of Geographical Information.2014;93.[Persian]
[5].   Falah ghalhari gh. Climate data downscaling. Publisher sokhan gostar. Second volume.[Persian]
[6].   Lüliu L, Zhaofei L, Xiyan R, Thomas F, Ying X. Hydrological impacts of climate change in the Yellow River Basin for the 21st century using hydrological model and statistical downscaling model. Quaternary International.2011; 244(2):211-220.
[7].   Saadatfar A, Barani H, Bahremand A, Massah Bavani A, Sepehry A, Abedi A. Statistical Downscaling HadCM3 Model for Detection and Perdiction of Seasonal Climatic Variations (Case Study: Khabr Rangeland, Kerman, Iran). Journal of Rangeland Science. 2013; 3(3).[Persian]
[8].   Aida T, Thamer A, Abdul H, MalekM, Mashohor S. Potential Impacts of Climate Change on Precipitation and Temperature at Jor Dam Lake, Pertanika.J. Sci. & Technol. 2016;24 (1): 213 – 224.
[9].   Goodarzi E, Massah Bavani A, Dastorani M, Talebi A. Evaluating effect of downscaling methods; change-factor and LARS-WG on surface runoff (A case study of Azam-Harat River basin, Iran).Desert.2014; 19(2): 99-109.[Persian]
[10].       Rashid M, Mukand S. Future changes in extreme temperature events using the statistical downscaling model (SDSM) in the trans-boundary region of the Jhelum river basin.2014; 5(66): 56–66.
[11].       Arun Mondalp, Deepak K,  Kundu S. Change in rainfall erosivity in the past and future due to climate change in the central part of India.2016;4(3):186-194.
[12].       Rezaei m, nohtani m, abkar a, mehri mirkazehi m. Performance Evaluation of Statistical Downscaling Model (SDSM) in Forecasting Temperature Indexes in Two Arid and Hyper Arid Regions (Case Study: Kerman and Bam). Journal of Watershed Management Research.2014; 4(14): 113-177.[Persian]
[13].       kelanki m and karandish f. Forecasting the long-term effects of climate change on climatic components in the region wet, journal of Water and Irrigation Engineering,2015,20(5),131-148. [Persian]
[14].        Dehqan z, fathian f,eslamian s. Comparative evaluation of SDSM, IDW and LARS-WG models to simulate and fine-scale the temperature and precipitation.Water and Soil Journal.2013; 29(5).[Persian]
[15].       Semenov M, Barrow E. LARS-WG A Stochastic Weather Generator for Use in Climate Impact Studies. 2002.
[16].       Wilby R, Dawson C, Barrow E. SDSM – a decision support tool for the assessment of regional climate change impacts. Environmental and Modelling Software.2002; 17: 145-157.
[17].       Falah ghalhari gh. Climate data downscaling. Publisher sokhan gostar. First volume.[Persian]
Iranian journal of Ecohydrology
Volume 6, Issue 1
April 2019
Pages 99-109

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History

  • Receive Date: 23 August 2018
  • Revise Date: 24 November 2018
  • Accept Date: 24 November 2018
  • First Publish Date: 21 March 2019
  • Publish Date: 21 March 2019

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