مقياس‌كاهي آماري برونداد دماي كمينه مدل‌هاي اقليمي تحت سناريوهاي RCP در غرب ايران

Statistical downscaling of climate models projection of minimum temperature under RCP scenarios in Western of Iran

ﻧﻈﺮ ﺑﻪ ﺗﺎﺛﯿﺮ ﻣﺸﻬﻮد ﭘﺪﯾﺪهﻫﺎي زﯾﺎنﺑﺎر ﺳﺮﻣﺎزدﮔﯽ و ﯾﺨﺒﻨﺪان ﺑﺮ ﺗﻮﻟﯿﺪات زراﻋﯽ و ﺑﺎﻏﯽ اﯾﺮان، در ﭘﮋوﻫﺶ ﺣﺎﺿﺮ، ﺑﻪ ﺑﺮرﺳﯽ ﭼﺸﻢاﻧﺪاز ﺗﻐﯿﯿﺮات دﻣﺎي ﮐﻤﯿﻨﻪ در در 17 اﯾﺴﺘﮕﺎه ﻫﻮاﺷﻨﺎﺳﯽ ﺳﻪ اﺳﺘﺎن ﮐﺮدﺳﺘﺎن، ﮐﺮﻣﺎﻧﺸﺎه و اﯾﻼم در ﻏﺮب اﯾﺮان ﭘﺮداﺧﺘﻪ ﺷﺪ. ﺑﺪﯾﻦ ﻣﻨﻈﻮر ﺑﺎ اﺳﺘﻔﺎده از دو ﻣﻮﻟﺪ داده آﻣﺎري LARS-WG و SDSM ﭘﯿﺶﻧﮕﺮي دﻣﺎي ﮐﻤﯿﻨﻪ دو ﻣﺪل اﻗﻠﯿﻢ ﺟﻬﺎﻧﯽ HadGEM2 و CanESM2 ﺗﺤﺖ ﺳﻪ ﺳﻨﺎرﯾﻮي واداﺷﺖ ﺗﺎﺑﺸﯽ RCP4.5 ،RCP2.6 و RCP8.5 ﻣﻘﯿﺎسﮐﺎﻫﯽ و اﺳﺘﻔﺎده ﺷﺪﻧﺪ. ﺑﺮ اﯾﻦ اﺳﺎس، ﭼﺸﻢاﻧﺪاز ﺗﻐﯿﯿﺮات دﻣﺎي ﮐﻤﯿﻨﻪ در دوره آﺗﯽ )2050-2021( ﻧﺴﺒﺖ ﺑﻪ دوره ﭘﺎﯾﻪ )2018-1989( ﻣﻮرد ﺑﺮرﺳﯽ ﻗﺮار ﮔﺮﻓﺖ. ﺑﻪﻣﻨﻈﻮر ارزﯾﺎﺑﯽ ﻋﻤﻠﮑﺮد ﻣﻮﻟﺪﻫﺎي ﻫﻮاﺷﻨﺎﺳﯽ، از ﻣﻌﯿﺎرﻫﺎي MAE ،RMSE ،MSE و R2 اﺳﺘﻔﺎده ﺷﺪ. ﻧﺘﺎﯾﺞ ﺣﺎﺻﻞ ﻧﺸﺎن داد ﮐﻪ ﻣﺪلﻫﺎي ﻣﻮرد ﺑﺮرﺳﯽ ﺑﺎ دﻗﺖ ﺑﺎﻻﯾﯽ ﻗﺎدر ﺑﻪ آﺷﮑﺎرﺳﺎزي روﻧﺪ دﻣﺎي ﮐﻤﯿﻨﻪ در ﻣﻨﻄﻘﻪ ﻣﻮرد ﻣﻄﺎﻟﻌﻪ ﻫﺴﺘﻨﺪ. ﺑﺎ اﯾﻦ وﺟﻮد، ﻣﺪل SDSM از دﻗﺖ ﺑﯿﺸﺘﺮي ﻧﺴﺒﺖ ﺑﻪ ﻣﺪل LARS-WG ﺑﺮﺧﻮردار اﺳﺖ. ﻧﺘﺎﯾﺞ ﺣﺎﺻﻞ از ﭼﺸﻢاﻧﺪاز ﺗﻌﯿﯿﺮات دﻣﺎي ﮐﻤﯿﻨﻪ ﻧﺸﺎن داد ﮐﻪ ﺑﺮ اﺳﺎس ﻫﺮ دو ﻣﺪل، ﻣﯿﺰان دﻣﺎي ﮐﻤﯿﻨﻪ در دوره آﯾﻨﺪه ﻧﺴﺒﺖ ﺑﻪ دوره ﭘﺎﯾﻪ ﺑﻪﻃﻮر ﻣﺘﻮﺳﻂ ﺑﯿﻦ 0/6 ﺗﺎ 1/5 درﺟﻪ ﺳﻠﺴﯿﻮس در ﻣﻨﺎﻃﻖ ﻣﻮرد ﻣﻄﺎﻟﻌﻪ اﻓﺰاﯾﺶ ﻣﯽﯾﺎﺑﺪ. از ﻧﻈﺮ ﻣﮑﺎﻧﯽ ﻧﯿﺰ ﺑﯿﺸﺘﺮﯾﻦ ﺗﻐﯿﯿﺮات ﻣﺮﺑﻮط ﺑﻪ ﻣﻨﺎﻃﻖ ﺳﺮدﺳﯿﺮ واﻗﻊ در ﺷﻤﺎل ﻣﺤﺪوده ﻣﻄﺎﻟﻌﺎﺗﯽ ﺑﻪ وﯾﮋه اﯾﺴﺘﮕﺎهﻫﺎي ﺳﻘﺰ و زرﯾﻨﻪ اوﺑﺎﺗﻮ اﺳﺖ. ﯾﺎﻓﺘﻪﻫﺎي ﭘﮋوﻫﺶ در ﻣﺪﯾﺮﯾﺖ رﯾﺴﮏ ﯾﺨﻨﺒﻨﺪان و ﺑﺮﻧﺎﻣﻪرﯾﺰيﻫﺎي اﻗﻠﯿﻤﯽ ﮐﺸﺎورزي ﻣﻨﻄﻘﻪ ﻣﻔﯿﺪ ﺧﻮاﻫﺪ ﺑﻮد.

Considering the significant effect of chilling and frost phenomenon on agricultural production in Iran, the aim of this study is projection of minimum temperature in three provinces of Kurdistan, Kermanshah and Ilam, Western of Iran. For this purpose, the data of 17 meteorological stations during the baseline period of (1989-2018) were collected. Then, the HadGEM2 and CanESM2 climate models outputs were statistically downscaled using LARS-WG and SDSM weather generators under three climate change scenarios of RCP2.6, RCP4.5 and RCP8.5 during future period (2021–2050) and compared with observed data. The performance of the two weather generators, were compared using MSE, RMSE, MAE and R2 indices. The results indicated the good accuracy of both statistical models in simulating the minimum temperature in the study area; however the SDSM model performed better than the LARS-WG. The projected changes of minimum temperature compared to the baseline period revealed a significant increase varying between 0.6 – 1.5 oC in study stations. The most significant change was observed in northern parts of study region especially in the Saqhez and Zarineh stations. The findings of this study can be used in frost risk management and agroclimatic planning in the region.