Forecast Comparative of Rainfall and Temperature in Kerman County Using LARS-WG6 Models

Document Type : Research Article


1 MSc Watershed Science and Engineering, Faculty of Natural Resource, University of Tehran

2 Professor, Faculty of Natural Resource, University of Tehran

3 Msc Student of Nature Engineering, Faculty of New Sciences and Technologies, University of Tehran


Assessment of climate change in arid and semiarid areas where water crisis is taken it is a matter of special importance. Therefore, the purpose of this study was to investigate climate change forecasting in Kerman city using general atmospheric circulation models available in LARS-WG6 software (EC-EARTH, GFDL-CM, HadGEM2-ES, MIROC5 and MPI-ESM-MR) under scenarios RCP4.5 and RCP8.5 for the period (2020–2050) and estimate its maximum precipitation over the various return periods during the base period (1961–2010) and future (2020–2050) using the Gamble distribution. The results showed that all five models have the same response in increasing the minimum and maximum temperatures in the city so that the maximum increase in the minimum temperature in GFDL-CM, HadGEM2-ES, MIROC5 and MPI-ESM-MR models is the results were 3.56, 2.73, 2.33 and 2.30 degrees Celsius, respectively. Also, the maximum temperature in the RCP4.5 scenario in May, September, May, September and July, respectively, in EC-EARTH, GFDL-CM, HadGEM2-ES, MIROC5 and MPI-ESM-MR models, respectively, increased by 2.20, 2.82, 2.46, 1.98 and 2.38 °C, respectively. Precipitation decreased by 19.05% and 4.62% in EC-EARTH and MIROC5 models, respectively. The results show that maximum precipitation will occur with higher rainfall in all models except MPI-ESM-MR. Finally, it can be concluded that with increasing return period, the maximum amount of probable precipitation increased under RCP4.5 and RCP8.5 scenarios and was more severe under RCP8.5 scenario.


[1]. Dosio A. Projection of temperature and heat waves for Africa with an ensemble of CORDEX Regional Climate Models. Climate Dynamics. 2017 Jul 1; 49(1-2):493-519.
[2]. Nicholls N, Seneviratne S, Reichstein M, Sorteberg A, Vera C, Zhang X. Changes in Climate Extremes and their Impacts on the 1 Natural Physical Environment 2. In Managing the risks of extreme events and disasters to advance climate change adaptation 2012 (pp. 109-230). Cambridge University Press Cambridge, UK, and New York, NY, USA.
[3]. Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM. Climate change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. 2013 Sep; 1535.
[4]. Zheng H, Chiew FH, Charles S, Podger G. Future climate and runoff projections across South Asia from CMIP5 global climate models and hydrological modelling. Journal of Hydrology: Regional Studies. 2018 Aug 1; 18:92-109.
[5]. Dong TY, Dong WJ, Guo Y, Chou JM, Yang SL, Tian D, Yan DD. Future temperature changes over the critical Belt and Road region based on CMIP5 models. Advances in Climate Change Research. 2018 Mar 1; 9(1):57-65.
[6]. Wu J, Xu Y, Gao XJ. Projected changes in mean and extreme climates over Hindu Kush Himalayan region by 21 CMIP5 models. Advances in Climate Change Research. 2017 Sep 1; 8(3):176-84.
[7]. Shiferaw A, Tadesse T, Rowe C, Oglesby R. Precipitation extremes in dynamically downscaled climate scenarios over the Greater Horn of Africa. Atmosphere. 2018 Mar; 9(3):112.
[8]. Timbal B, Fernandez E, Li Z. Generalization of a statistical downscaling model to provide local climate change projections for Australia. Environmental Modelling & Software. 2009 Mar 1; 24(3):341-58.
[9]. Yang W, Andréasson J, Phil Graham L, Olsson J, Rosberg J, Wetterhall F. Distribution-based scaling to improve usability of regional climate model projections for hydrological climate change impacts studies. Hydrology Research. 2010 Jun; 41(3-4):211-29.
[10]. Shagega FP, Munishi SE, Kongo VM. Prediction of future climate in Ngerengere river catchment, Tanzania. Physics and Chemistry of the Earth, Parts A/B/C. 2019 Aug 1; 112:200-9.
[11]. Gaitán E, Monjo R, Pórtoles J, Pino-Otín MR. 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. 2019 Feb 10; 650:2778-95.
[12]. Zhang H, Wang B, Li Liu D, Zhang M, Feng P, Cheng L, Yu Q, Eamus D. Impacts of future climate change on water resource availability of eastern Australia: A case study of the Manning River basin. Journal of hydrology. 2019 Jun 1; 573:49-59.
[13]. Sadidi, J, Jafari Godneh M, Sajedi Hosseini H, Hamzadehzadeh G. Investigation of Trend and Forecasting of Climate Change (Temperature Component) in Arid and Semi-Arid Areas (Case Study: Kerman Province). 14th Iranian Geographical Society Congress, Tehran, Iran Geographical Association. 2019. [Persian].
[14]. Sobhani B, Mohammadi M, Taymouri M. Prediction of droughts in Zanjan province during the period 2050-2011 using statistical exponential exponential model (LARS-WG). Geographical Studies of Arid Regions. 2017; 7(28): 59-42. [Persian].
[15]. Karimi M, Nabizadeh A. Evaluation of Climate Change Impacts on Climate Parameters of Lake Urmia Watershed during 2040-2011 Using LARS-WG Model. Journal of Geography and Planning. 2018; 22(65): 285-267. [Persian].
[16]. Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA. The next generation of scenarios for climate change research and assessment. Nature. 2010 Feb; 463(7282):747-56.
[17]. Watanabe M, Suzuki T, O’ishi R, Komuro Y, Watanabe S, Emori S, Takemura T, Chikira M, Ogura T, Sekiguchi M, Takata K. Improved climate simulation by MIROC5: mean states, variability, and climate sensitivity. Journal of Climate. 2010 Dec; 23(23):6312-35.
 [18]. Dunne JP, John JG, Adcroft AJ, Griffies SM, Hallberg RW, Shevliakova E, Stouffer RJ, Cooke W, Dunne KA, Harrison MJ, Krasting JP. GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: Physical formulation and baseline simulation characteristics. Journal of climate. 2012 Oct; 25(19):6646-65.
[19]. Collins WJ, Bellouin N, Doutriaux-Boucher M, Gedney N, Hinton T, Jones CD, Liddicoat S, Martin G, O’Connor F, Rae J, Senior C. Evaluation of the HadGEM2 model. Hadley Centre Technical Note HCTN 74, Met Office Hadley Centre, Exeter, UK. 2008.
[20]. Raddatz TJ, Reick CH, Knorr W, Kattge J, Roeckner E, Schnur R, Schnitzler KG, Wetzel P, Jungclaus J. Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century?. Climate Dynamics. 2007 Nov 1; 29(6):565-74.
[21]. Babaei Fini A, Qasemi A, Fatahi A. Investigating the Impact of Climate Change on the Trend of Iran Earth's Limit Rainfall Profiles. Journal of Spatial Analysis of Environmental Hazards. 2014; 1(3): 103-85. [Persian].
[22]. Mohammadloo M, Tahmasebipour N. Assessing the Impacts of Climate Change on Climate Classifications in Parts of Northwestern Iran. Rainwater Surface Systems. 2018; 5(17): 46-35. [Persian].
[23]. Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein-Tank A, Peterson T, Plummer N. Global changes in climatic extremes during the second half of the 20th century. Report of WMO CCL/CLIVER working group on climate change. 2000.
[24]. Rao AR, Srinivas VV. Regionalization of watersheds by hybrid-cluster analysis. Journal of Hydrology. 2006 Mar 1; 318(1-4): 37-56.
[25]. Khosravian M, Fallah Ghalahari Gh, Entezari A, Sarvestani R. Investigation of the Performance of SDSM Statistical Exponential Model in Predicting Temperature Parameters in Three Different Climates (Case Study: Mashhad, Shiraz and Ramsar). Journal of Geographical Sciences. 2018; 29: 164-148. [Persian].
[26]. Abbasi F, Babaian A, Habibi M, Goli Mokhtari L, Melbousi SH, Askari SH. Assessing the Impact of Climate Change on Iran's Temperature and Precipitation in the Next Decades, Using the MAGICC-SCENGEN Model. Natural Geography Research. 2010; 72: 109-91. [Persian].
[27]. Ghazavi R., Nadimi M, Omidvar A, Imani R. Investigation of Future Climate Impacts on Discharge Changes in Ardabil Harochai Rivers Using SWAT and LARS-WG Model. Hydrogeomorphology. 2018; 15: 74-55. [Persian].
[28]. Jahangir M, Sadatinejad S.J, Haghighi P. Predicting of Temperature Parameters under the CanEMS2 Model (Case Study: Lar Synoptic Station). Journal of Extension and Development of Watershed Management. 2018; 6(22): 45-53. [Persian].