پیش‌نگری تغییرات بارش و دمای ایستگاه سینوپتیک تبریز طی دوره 2100 – 2020 مقاله

نویسنده: شهبازی کیا، سعید ؛ یاراحمدی، جمشید ؛ استواری، یاسر ؛ میرزایی، سلمان ؛

پژوهش های اقلیم شناسی زمستان 1401 - شماره 52 ، ج (وزارت علوم/ISC (‎18 صفحه - از 125 تا 142 )

کلیدواژه ها: تبریز تغییراقلیم SDSM CanESM2 مقیا سکاهی CanESM2 SDSM Downscaling Tabriz Climate Change

چکیده:

چکیده : موضوع گرمایش زمین، تغییر اقلیم و خشکسالی از چالش‌های مهم حال حاضر جهان به‌ شمار می‌آیندکه می‌توانند باعث وقوع نوسانات گسترده‌ در شرایط آب و هوایی کره زمین شوند. مناطقی با اقلیم مدیترانه‌ای و نیمه خشک وابستگی زیادی به میزان دما و بارش داشته و در نتیجه در برابر تغییر اقلیم دچار ناهنجاری می‌گردند. ایران از جمله کشورهای واقع در مناطق نیمه خشک و خشک جهان است که نسبت به تغییر اقلیم حساسیت بیشتری را نشان می‌دهد. گرمایش جهانی ناشی از افزایش غلظت گازهای گلخانه‌ای و تغییر کاربری اراضی موجب تغییرات آشکاری در فراسنج‌های اقلیمی ایران از جمله افزایش دما، کاهش بارش و افزایش فراوانی رخداد پدیده‌های مخرب جوی-اقلیمی در کشور شده است. این تحقیق با هدف آشکارسازی تغییرات آتی دما و بارش حوضه آبخیز لیقوان اجرا شده است. برای این منظور، از ریز مقیاسسازی نمایی آماری مدل SDSM و مدل CanESM2 تحت سناریوهای تغییر اقلیم RCP2.6، RCP4.5 و RCP8.5 بر روی داده های بلندمدت ایستگاه سینوپتیک تبریز(1951-2020) استفاده شده است. نتایج نشان داد‌‌ که در چهار دوره 20 ساله(2020-2100) و بر اساس سه سناریوی موجود، دما افزایشی و بارش کاهشی خواهد بود. این افزایش دما برای حداقل دما گاها تا 14.35 درجه سانتیگراد (ماه ژانویه با سناریوی RCP8.5 و دوره زمانی) 2100-2081) خواهد بود. بررسی وضعیت بارش در چهار دوره و سه سناریو نشان می‌ دهد میزان بارش در ماههای اکتبر، نوامبر، دسامبر و آوریل افزایشی و در بقیه ماهها کاهشی خواهد بود.

abstract:The issue of global warming, climate change and drought are among the major challenges facing the world today, which can cause widespread fluctuations in the Earth's climate. Areas with Mediterranean and semi-arid climates are highly dependent on temperature and precipitation and as a result are affected by climate change. Iran is one of the countries in the semi-arid and arid regions of the world that is more sensitive to climate change. Global warming due to increasing greenhouse gas concentrations and land use change has caused obvious changes in Iran's climatic parameters, including increasing temperature, decreasing rainfall and increasing the incidence of destructive atmospheric-climatic phenomena in the country. This research has been carried out with the aim of detecting future changes in temperature and precipitation in Liqvan watershed. For this purpose, statistical Downscaling of SDSM model and CanESM2 model under RCP2.6, RCP4.5 and RCP8.5 climate change scenarios on long-term data of Tabriz Synoptic Station (1951-2020) has been used. The results show that in four periods of 20 years (2020-2100) and based on the three existing scenarios, the temperature will increase and the precipitation will decrease. This temperature increase for the minimum temperature will sometimes be up to 14.35 ° C (January with RCP8.5 scenario and time period (2100-2081). Examination of rainfall in four periods and three scenarios shows that the amount of rainfall in October, November, December and April will increase and in the remaining months will decrease. In the present study, climatic parameters of temperature and precipitation were simulated using multiple linear model of SDSM and general circulation models of barley using data of Tabriz city for Liqvan watershed. In this research, the output of canESM2 model under scenarios RCP8.5, RCP4.5, RCP2.6 has been used for future periods. The results showed that temperature data correlated better with observational data (compared to rainfall data), this is because temperature variability is less than rainfall and temperature is a parameter with a normal possible distribution. One of the reasons for the decrease in rainfall correlation is that different factors affect rainfall and on the other hand, rainfall is a discrete variable. These results are consistent with the results of Sajjad Khan et al. (2006), Sarvar et al. (2010) and Nouri and Alam (2014). Therefore, solving the correlation problem in the development of future climate change models should be considered. Also, the results of this research are in line with the results of most researchers such as trainee et al. (2009), Sajjad Khan et al. (2006), Sarvar et al. (2010), Mino et al. (2012), Chima et al. (2013), Dehghanipour et al. (2011). And Shakeri et al. (2021) agree that the SDSM model has a good ability to small-scale temperature and precipitation data. Climate change can cause temporal and spatial changes in climate variables. The characteristics of these variables can have detrimental effects on ecosystem components. According to the results, it was found that during the 21st century, temperature is increasing and precipitation is decreasing. In Tabriz station, in general, precipitation will decrease in the three scenarios studied and in only one scenario and for the period 2100-2080, there will be an increase in precipitation. Also, rainfall will generally increase in winter and the rest of the seasons will decrease. These results are consistent with the results of Golmohammadi and Masah Bavani (2011) which introduced the period 2069-2040 as a period with increased rainfall in Qarasu basin but with the results of Rajabi and Shabanloo (2012) using the SDSM model in Kermanshah region in Western Iran has considered the period 2070-2070 to be drier, there is a difference, so that according to the results of the present study at Tabriz station, from May to September, we will have a decrease in rainfall for all periods and scenarios. Figures 8 and 9 show the changes in monthly and annual rainfall in the RCP scenarios and the four periods compared to the base period, which show a decrease in precipitation in most months except October, November and December compared to the base period. Changes in the average minimum temperature of Tabriz station in all months except October, November and December will increase in future periods. Figures 11 and 12 show the monthly and annual minimum temperature changes in the RCP scenarios and the four periods compared to the base period, which show an increase in the minimum temperature compared to the observation period, which is more than the other scenarios in RCP 8.5. .

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