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   عملکرد خروجی مدل Canesm2در پیش‎آگاهی مشخصه آب و هوا در یاسوج توسط Sdsm  
   
نویسنده جهانگیر محمد حسین ,مشیدی ضحی
منبع پژوهشهاي دانش زمين - 1400 - دوره : 12 - شماره : 47 - صفحه:117 -130
چکیده    در این پژوهش بارش، بیشینه و کمینه دمای ایستگاه همدید یاسوج با استفاده از خروجی مدل canesm2، تحت سناریوی rcp2.6، rcp4.5 و rcp8.5 از ریزگردان آماری sdsm، برای سه دوره 15 ساله 2035-2020، 2036-2051 و 2067-2052 شبیه‎سازی شده است. ابتدا دوره آماری 20051987، به عنوان دوره پایه انتخاب شد. نتایج، روند افزایشی دما و بارش را در این ایستگاه همدید می‎دهد. روند افزایشی بارش در دوره 2035-2020 محسوس‌تر خواهد بود. دوره 2067-2052 نسبت به دو دوره دیگر خشک‎تر بوده و بیشترین میزان بارش در فصل زمستان برآورد گردید. بیشترین برآورد میزان بارش مربوط به ماه فوریه تحت سناریوی rcp2.6 می‌باشد. بیشترین تغییرات دمای کمینه مربوط به فصل پاییز و پایین‎ترین دمای کمینه مربوط به ماه ژانویه برآورد گردید که نسبت به دوره پایه 4.6 درجه افزایش را نشان می‌دهد. بیشترین تغییرات دمای بیشینه مربوط به فصل بهار دوره 2035-2020 است که در ماه آوریل 6.32 درجه سانتیگراد افزایش دما خواهیم داشت. همچنین ماه جولای دوره 2051-2036، بالاترین دمای بیشینه برآوردی در کل سال های آتی مورد مطالعه در این ایستگاه می‌باشد.
کلیدواژه یاسوج، Canesm2، Rcp2.6، Rcp4.5، Rcp8.5
آدرس دانشگاه تهران, دانشکده علوم و فنون نوین, گروه انرژی‌های نو و محیط زیست, ایران, دانشگاه تهران, دانشکده علوم و فنون نوین, گروه انرژی‌های نو و محیط زیست, ایران
 
   Evaluation of CanESM2 output capability in simulation of Yasuj weather predictor by SDSM  
   
Authors Jahangir Mohammad Hossein ,Moshayedi Zoha
Abstract    Extended abstractIntroductionClimate plans are used in macroplanning, especially for natural disasters (Rezaei et al., 2015). Statistical microdistribution methods are more efficient due to easy and cheap calculations (Diersing, 2009). One of the statistical models is the SDSM model, which is the relationship between largescale predictors and localscale predictors based on multiple linear regression methods. According to research, the SDSM model has an acceptable accuracy in clustering micro data. On the other hand, due to the importance of Yasuj station and its location in Karun catchment area and the need for planning to manage water resources in this basin, the present study uses CanESM2 output, which is one of the climate change models of CMIP5. The IPCC, simulates and examines climate and temperature variables at Yasuj station from 2020 to 2067.​​Study AreaYasuj is a city in southwestern Iran, the capital of Kohgiluyeh and BoyerAhmad Province, located on the banks of Bashar River, at the hillsides of the Dena Peak. Yasuj city is located in a cold climate region and has a temperate climate that tends to be cold.Study MethodThe SDSM microcontroller model was developed in 2002 in the UK by Wilby and Dawson. This model is based on daily local climate data (temperature and precipitation) and largescale NCEP regional data. The canESM2 model is the fourth generation of climate models developed by the Canadian Center for Climate Modeling and Analysis (CCCMA) and networks the earth in the form of cells measuring 128 x 64 (Charron 2016). In this study, NCEP observational data were used to compile monthly models and canESM2 model outputs were used to predict the amount of variables using SDSM software. NCEP atmospheric variables enter the regression equation of the SDSM model. After selecting the predictors, the observational data of the Yasuj Synoptic Station and the data of the National Center for Predicting Environmental Variables of Canada (NCEP) were calibrated. Then, in order to ensure the calibrated model, temperature and precipitation for the period 20352020 were simulated and by comparing the observed and simulated data, the efficiency of the model for Yasuj station was investigated.Results and DiscussionIn this study, based on the observed data and the global model canESM2, the mean minimum and maximum temperature and average precipitation during the three periods of 20352020, 20512036 and 20672052 were compared with the base period of 20052007 under three RCP2 scenarios. RCP2.6, RCP4.5 and RCP8.5 were simulated for Yasuj station and the accuracy of the model was evaluated. The maximum agreement is at the minimum and maximum temperatures of the observed and simulated data, which show the appropriate and acceptable efficiency of simulating the desired climatic parameters for the period. In general, the amount of precipitation will increase in all studied future periods. This increase will be more evident than RCP2.6 according to the RCP4.5 and RCP8.5 scenarios. In general, the maximum minimum temperature during the period 20352020 shows an increasing anomaly of about 0.5 degrees and in the future periods 20512036 and 20672052 it shows a decrease compared to the base period. The lowest minimum temperature is estimated for January 20352020 under the RCP8.5 scenario.The maximum temperature of Yasuj station during the periods shows an increase. Incremental changes are less in June and August and more in January to May as well as in October, November and December. Of course, these changes are more noticeable in November and April. The highest temperature in the coming years will be related to July of 20512036 under the RCP4.5 scenario.ConclusionAccording to the results, it was found that precipitation in the coming years will show an increasing anomaly, which is faster in the first period and slower in the final periods.Slight changes in precipitation along with increasing temperature have affected the quality of water resources. This is due to the importance of this station in Karun catchment. Therefore future planning of water resources management should deal with the least quantitative and qualitative effects of water resources in the basin.
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