پیش‌نگری نمایه‌های حدی دما بر اساس سناریوهایrcp در شمال شرق کشور

یافته‌های هیات بین‌الدولی تغییر اقلیم نشان از افزایش میانگین و مقادیر حدی دما تحت شرایط گرمایش جهانی دارد. در این بین شرق کشور منطقه‌ای مستعد برای کاشت گیاه زعفران می‌باشد. از آنجا که این گیاه حساس به مقادیر حدی دما می‌باشد، لذا در این تحقیق چشم‌انداز رخدادهای حدی دمایی منطقه در سه دوره آینده نزدیک (2050-2026)، میانه (2075-2051) و دور (2100-2076) تحت سناریوهای واداشت تابشی rcp مورد مطالعه قرار گرفت. برای برآورد چشم‌انداز آینده از داده‌های مدل mpi-esm-lr از سری مدل‌های cmip5 که با استفاده از روش آماری bcsd ریزمقیاس شده بودند، استفاده شد. با استفاده از نرم‌افزار rclimdex، نمایه‌های حدی استخراج گردیدند. نتایج این پژوهش نشان دادند که در سه دوره آینده نزدیک، میانه و دور و تحت هر دو سناریوی rcp4.5 و rcp8.5، شاخص های حدی گرم افزایش وشاخص حدی سرد کاهش می‌یابند. همچنین شاخص های بیشینه دمای حداکثر روزانه (txx)، کمینه ماهانه دمای حداکثر روزانه (txn)، تعداد شب‌های حاره ای (tr20)، کمینه ماهانه دمای حداکثر روزانه (txn) در همه ایستگاه ها روند افزایشی داشته است، در حالی‌که درصد روزهایی که دمای حداکثر کمتر از صدک دهم باشد (tx10p)که نشان‌دهنده کاهش روزهای سرد می باشد، برای همه ایستگاه ها داری روند منفی است. شیب تغییرات شاخص های مورد بررسی در سناریویrcp8.5  در ایستگاه‌های مورد مطالعه بیشتر از شیب تغیییرات ﺳﻨﺎرﯾﻮی rcp4.5 ﺧﻮاﻫﺪ ﺑﻮد، که این شیب تغییرات در اغلب شاخص‌ها در آینده دور بیشتر از آینده نزدیک می باشد.

Temperature Extreme Indices Projection Based on RCP Scenarios in Northeast of Iran

Introduction: Global warming causes alteration of climate extreme indices and increased severity and frequency of incidence of meteorological extreme events. In most climate change studies, only the potential trends or fluctuations in the average long run of climatic phenomena have been examined. However, the study of affectability and pattern change of extreme atmospheric events is also important. Changes in climatic elements especially extreme temperature factors have a significant influence on the performance of farming systems. Accordingly, understanding changes in temperature parameters and extreme temperature indices is the prerequisite to sustainable development in agriculture and should be considered in management processes. Investigation of extreme values for planning and policy for the agricultural sector, water resource, environment, industry, and economic management is important. Materials and Methods: To evaluate the extreme temperature indices trend, some indices of temperature, recommended by the CCl/CLIVAR Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI), were considered using Rclimdex software. In this study, daily minimum and maximum temperature data retrieved from MPIESMLR global climate model were used to predict future climate extreme events over the next three periods of 20262050, 20512075, and 20762100 based on IPCC scenarios of RCP4.5 and RCP8.5 of the studied area, covering South Khorasan province and southern part of Razavi Khorasan province, located in the east of Iran.  The modified BCSD method was used to downscale extreme temperature data. Results and Discussion: Results showed an increasing trend of warm climate extreme. According to the output of Rclimdex for RCP4.5 scenario in the period of 20262050, it was observed that SU25 index, summer days, has a positive trend at all studied stations. This index was found to be significant and increased at all stations in the midterm future period, and it had an increasing trend in the far future period, which was not significant. The number of Tropical Nights (TR20) index had a positive trend at all. In the midterm future period, there was a significant increasing trend for some stations, while there were some negative and insignificant trends at some stations in the far future. The maximum monthly daily maximum temperature (TXx) and the maximum monthly daily minimum temperature (TNx) indices also had an increasing trend at all stations, and the midterm future period had a significant increasing trend, while the trend was decreasing in the far future period. Results for temperature extreme indices under RCP8.5 scenario showed that SU25 index had a positive trend at all stations studied in the near future, midterm, and far future period. Index of tropical nights (TR20) had an upward trend, which was significant in midterm and far future periods at most stations. Percentage of days in which maximum temperature is below than 10th percentile (TX10P), indicating a decrease in cold days, had a negative trend for all stations in the near future period. In the midterm and far future periods, this trend was significant at all stations. The maximum monthly daily maximum temperature (TXx) and the maximum monthly daily minimum temperature (TNx) indices also had an increasing trend at all stations and all three periods, and the trend was significant in the midterm future. Conclusion: Minimum and maximum daily temperatures of MPIESMLR global climate model were used to predict climatic extreme events during three future periods of 20262050, 20512075, and 20762100 under RCP4.5 and RCP8.5 scenarios at some stations located in South Khorasan province and southern part of Khorasan Razavi province. During the three studied future periods, extreme temperature indices changed significantly. The results showed that in both periods over the future years under the both scenarios, hot extreme indices would increase and cold extreme indices would decrease. It was observed that hot extreme indices, such as summer day index, the number of tropical nights, warm days and nights increased, while cold extreme indices had a decreasing trend in the period of study, which shows a decrease in the severity and frequency of cold events.