پیش‌نگری نمایه‌های حدی دما بر اساس سناریوهایRCP در شمال شرق کشور

نوع مقاله : مقالات پژوهشی

نویسندگان

1 دانش آموخته دکتری هواشناسی کشاورزی گروه مهندسی آب، دانشکده کشاورزی، دانشگاه فردوسی مشهد

2 استاد گروه مهندسی آب، دانشکده کشاورزی، دانشگاه فردوسی مشهد

3 مشهد

چکیده

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، شاخص­های حدی گرم افزایش وشاخص حدی سرد کاهش می‌یابند. همچنین شاخص­های بیشینه دمای حداکثر روزانه (TXx)، کمینه ماهانه دمای حداکثر روزانه (TXn)، تعداد شب‌های حاره­ای (TR20)، کمینه ماهانه دمای حداکثر روزانه (TXn) در همه ایستگاه­ها روند افزایشی داشته است، در حالی‌که درصد روزهایی که دمای حداکثر کمتر از صدک دهم باشد (TX10P)که نشان‌دهنده کاهش روزهای سرد می­باشد، برای همه ایستگاه­ها 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.

کلیدواژه‌ها


عنوان مقاله [English]

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

نویسندگان [English]

  • S. Kouzegaran 1
  • M. Mousavi Baygi 2
  • iman babaeian 3
1 Ph.D. Graduate in Agrometeorology , Water Engineering Department, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran
2 Professor, Water Engineering Department, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran
چکیده [English]

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 MPI-ESM-LR global climate model were used to predict future climate extreme events over the next three periods of 2026-2050, 2051-2075, and 2076-2100 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 2026-2050, 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 mid-term 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 mid-term 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 mid-term 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, mid-term, and far future period. Index of tropical nights (TR20) had an upward trend, which was significant in mid-term 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 mid-term 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 mid-term future.
Conclusion: Minimum and maximum daily temperatures of MPI-ESM-LR global climate model were used to predict climatic extreme events during three future periods of 2026-2050, 2051-2075, and 2076-2100 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.

کلیدواژه‌ها [English]

  • BCSD
  • Climate change
  • Extreme indices
  • Minimum temperature
  • Maximum temperature
  1. Ahmed K.F., Wang G., Silander J., Wilson A.M., Allen J.M., Horton R., and Anyah R. 2013. Statistical downscaling and bias correction of climate model outputs for climate change impact assessment in the US northeast. Global and Planetary Change 1. 320-332.
  2. Alexander L., Zhang X., Peterson TC., Caesar J., Gleason B., Klein Tank A., Haylock M., Collins D., Trewin B., Rahimzadeh F., Taghipour A., Kumar Kolli R., Revadekar JV., Griffiths G., Vincent L., Stephenson D., Burn J., Aguilar E., Brunet M., Taylor M., New M., Zhai P., Rusticucci M., and Vazquez-Aguirre JL. 2006. Global observed changes in daily climate extremes of temperature and precipitation. Journal of Geophysical Research 111: D05109–D05109, DOI:10.1029/ 2005JD006290.
  3. Babaeian A., Fahimi Nejad A., Bagheghade M., and Bayatani F. 2014. simulates some climate extremes indices at selected stations coast of the Caspian Sea under conditions of global warming. First Iranian National Congress on Irrigation and Drainage, Conference on Water and Climate Change, Ferdowsi University of Mashhad .)In Persian with English abstract)
  4. Bonsal B.R., Zhang X., Vincent L.A., and Hogg W.D. 2001. Characteristics of daily and extreme temperature over Canada, Journal of Climate 14: 1959-1976.
  5. Choi G. et al. 2009. Changes in means and extreme events of temperature and precipitation in the Asia‐Pacific Network region, 1955–2007. International Journal of Climatology 29(13): 1906-1925.
  6. DeaGaetano A.T. 1996. Recent trends in Maximum and Minimum temperature threshold exceedences in Northern United States, Journal of Climate 9: 1646-1657.
  7. Frich P., Alexander L., Della-Marta P., Gleason B., Haylock M., Klein Tank A., and Peterson T. 2002. Global changes in climatic extremes during the second half of the 20th century. Climate Research 19: 193–212.
  8. Ghiami-Shamami F., Sabziparvar A.A., and Shinoda S. 2019. Long-term comparison of the climate extremes variability in different climate types located in coastal and inland regions of Iran. Theor Appl Climatol. 136: 875–897.
  9. Im E.S., Jung I.W., and Bae D.H. 2011. The temporal and spatial structures of recent and future trends in extreme indices over Korea from a regional climate projection. International Journal of Climatology 31(1): 72-86.
  10. IPCC. 1995. ClimateChange1994, In: Houghten JT., Meira Filno L G., Bruce J.P., Lee H., Callender, B.T., Haites E.F., Harris.
  11. IPCC. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri, R.K., and Meyer, L.A., (eds.)]. IPCC, Geneva, Switzerland; 151 pp.
  12. Jin Z., Zhuang Q., Wang J., Archontoulis S.V., Zobel Z., and Kotamarthi V.R. 2017. The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2. Global Change Biology 23(7): 2687-2704.
  13. Karl T.R., and Knight R.W. 1997. The 1995 Chicago heat wave:How likely is a recurrence. Bull. Amer. Meteor. Soc., 78: 1107–1119.
  14. Kouzegaran S., and Mousavi Baygi M. 2015. Investigation of Meteorological Extreme Events in the North-East of Iran. Journal of Water and Soil 29(3): 750-764. )In Persian with English abstract(
  15. Modaresi F., and Iraqi Sh. 2009. Investigating the Impact of Climate Change on Gorganrood River, Eighth International Seminar on River Engineering, Ahvaz, Shahid Chamran University. )In Persian with English abstract)
  16. Omidvar K., Javanshiri N., and Babaeian I. 2013. Evaluation of climate change in the period of 2030-2011 in southern Kerman province using the downscaling of GCM models. First National Meteorological Conference, Kerman, University of Industrial and Advanced Technology(.
  17. Plummer N., Salinger M.J., Nicholis N., Suppiah R., Hennessy K.J., Leighton R.M., Trewin B., Page C.M., and Lough J.M. 1999. Changes in climate extremes over the Australian region and New Zealand during the twentieth century. Climate Change 42: 183–202.
  18. Sensoy S., Türkoğlu N., Akçakaya A., Ekici M., Demircan M., Ulupinar Y., Atay H., TÜVANA. and DEMİRBAŞ H. 2013. Trends in Turkey climate indices from 1960 to 2010. In 6th international atmospheric science symposium, April -ATMOS2013.
  19. Sneyers R. 1990. On the statistical analysis of series of observation. World Meteorological Organization (WMO). Technical Note. No. 143, Geneva: 192 pp.
  20. Van Vuuren D.P., Edmonds J., Kainuma M., Riahi K., Thomson A., Hibbard K., Hurtt G.C., Kram T., Krey V., Lamarque J.F., and Masui T. 2011. The representative concentration pathways: an overview. Climatic Change 109(1-2), p.5.
  21. Zhai P., Sun A., Ren F., Liu X., Gao B., and Zhang Q. 1999. Changes of climate extremes in China. Climatic Change. 42: 203–218.
  22. Zhang X., Aguilar E., Sensoy S., Melkonyan H., Tagiyeva U., Ahmed N., Kutaladze N., Rahimzadeh F., Taghipour A., Hantosh TH., Albert P., Jin Z., Zhuang Q., Wang J., Archontoulis S.V., Zobel Z., and Kotamarthi V.R. 2017. The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2. Glob Change Biol, 23: 2687–2704.
CAPTCHA Image