تاثیرات تغییر اقلیم بر پهنه بندی اقلیمی استان گلستان با روش دمارتن گسترش یافته

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیأت علمی دانشگاه علوم کشاورزی و منابع طبیعی گرگان

2 دانش‌آموخته گرایش کارشناسی ارشد مهندسی منابع آب

3 عضو هیأت علمی گروه مهندسی آب دانشگاه علوم کشاورزی و منابع طبیعی گرگان

4 عضو هیأت علمی گروه مهندسی آب دانشگاه تهران

چکیده

 افزایش گازهای گلخانه‌ای سبب شده تا آب و هوای کره زمین تحت تأثیر قرار گرفته و تغییراتی در پهنه‌های اقلیمی به وجود آورد. مطالعه حاضر با هدف بررسی این تغییرات در استان گلستان با تنوع اقلیمی زیاد، بر اساس شاخص طبقه بندی دمارتن گسترش یافته انجام شده است. بدین منظور از داده­های بارش سالانه 60 ایستگاه و نیز دمای­حداکثر و حداقل روزانه 22 ایستگاه هواشناسی در سطح  استان طی دورة آماری 1982-2010 به عنوان داده‌های اقلیمی دورة پایه و مشاهداتی استفاده شد و نیز با استفاده از مولد دادهLARS-WG  بر اساس خروجی مدل HADCM3، تحت سناریوهای مختلفA1B ,A2  وB1، داده‌های بارش و دما طی دوره­های 2011-2040، 2041-2070 و 2071-2100 تولید شدند. برای هر کدام از این سری داده‌ها، میانگین درازمدت بارش سالانه، میانگین درازمدت دمای سالانه و میانگین حداقل‌های دما در سردترین ماه سال استخراج گردید و با آزمون کردن روش‌های مختلف درونیابی، بهترین روش استخراج و مبنای انجام درونیابی قرار گرفت. با بکارگیری روش دمارتن گسترش یافته، پهنه‌های اقلیمی هر یک از سری داده‌ها به تفکیک ترسیم شدند. طبق نتایج حاصله، روش کریجینگ نسبت به دیگر روش‌ها با خطای کمتری بارش را درون‌یابی می‌کند. از روش رگرسیون وزن‌دار جغرافیایی نیز برای پهنه‌بندی دما استفاده شد. نتایج حاصل از این تحقیق نشان داد که تحت تأثیر پدیده تغییر اقلیم بارش و دما در استان گلستان افزایش می‌یابد اما مقدار آنها در دوره‌های مختلف متفاوت است بطوری که در دوره‌های آینده نزدیک (2040-2011) افزایش بارش بر دما برتری دارد و باعث مرطوب­‌تر شدن اقلیم‌ها می شود ولی در دوره اقلیم آینده دور (2100-2071) افزایش دما اثر بیشتری دارد و باعث گرم و خشک‌تر شدن اقلیم‌ها می‌شود. از بین سناریوهای اقلیمی، سناریوی A2 شرایط به مراتب نامطلوبتری را برای استان گلستان تصویر نمود و بر اساس نتایج حاصله،  اقلیم نیمه­خشک گرم که تاکنون در استان وجود نداشته است در دوره اقلیمی آینده دور، این اقلیم در سناریوی  A2برای 5 درصد مساحت استان پیش‌بینی می‌شود.  

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Oct, p: 636-646 . (In Farsi) The effects of climate change on DeMartone climatic classification in Golestan province

نویسندگان [English]

  • Khalil Ghorbani 1
  • Mehrnaz Bazrafshan Daryasary 2
  • Mehdi Meftah Halaghi 3
  • Nozar Ghahreman 4
1 Faculty member
چکیده [English]

Increasing trend of greenhouse gasses in recent decades has affected weather and climatic zones across the globe. The aim of this study is to investigate the effect of climate change on climatic classes of Golestan province, Iran based on the extended de-Martone index. Rainfall data of 60 rain gauges and daily minimum/ maximum temperature data of 22 weather stations during period of 1982-2010 were used as baseline observations. Besides, HadCM3 model outputs were statistically downscaled using LARS-WG model under A1B ,A2 وB1scenarios to project rainfall and temperature data for three periods of 2011-2040,2041-2070 and 2071 to 2100.Generated time series of mean annual rainfall, mean temperature and minimum temperature of coldest month of the year were interpolated using Kriging method. Based on extended de-Martonne index, climatic zones were worked out and drawn using GIS tools. Results indicated that Kriging method interpolated rainfall data with less error comparing to other methods. According to the results both temperature and rainfall in the region would increase but the increase magnitude may vary in different periods, such that in near future (2011-20140) the rate of rainfall increase would be more than temperature which lead to more humid climates. This will be reverse during 2071-2100 in which drier years are expected. Among the chose scenarios, the A2 projects the worse conditions for the study region. Taking into account the temperature gradient, the Geographically Weighted Regression method is suitable for regionalization of temperature. Comparative examination of climatic zones of province under climate change scenarios showed that warm semi-arid climatic class which does not exist at present, would cover about 5 % of the province. in the last study period.i.e.2071-2100 under A2 scenario.

کلیدواژه‌ها [English]

  • LARS-WG
  • Hadcm3
  • extended de-Martone
  • climate change
  • climatic zones
Abassi, F. Malbusi, S. Babaeian, I. Asmari, M and Borhani, R. (2010). Climate change prediction of South Khorasan Province during 2010-2039 by using statistical downscaling of ECHO-G data. Journal of Water and Soil. 24(2), 218-233. (In Farsi)
Aghdasi, F. (2004). Study of some geostatistical methods for mapping of daily and annual precipitation (case study: Borkhar Plain), MSc. Thesis, University of Tehran. 112 p. (In Farsi)
Asakereh, H. (2008). Application of Kriging interpolation of rainfall, Case Study: interpolation of precipitation 1998/3/17 in Iran. Journal of Geography and Development, 12, 25-42. (In Farsi)
Babaeian, I. and Najafi Nick, Z. (2007). Climate change assessment in Khorasan-e Razavi Province from 2010 to 2039 using statistical downscaling of GCM Output. Development of Geography and Regional Magazine, 15,1-19. (In Farsi)
Babaeian, I. Najafi Nick, Z. Nokhandan Habibi, M., Zabul Abbasi, F., Adab, H. and Malboci, Sh. (2007). Modeling the climate of Iran in the period 2010-2039 using a statistical overview of the output of small-scale model ECHO-G. Technical Workshop on the Climate Change Impacts on Water Resources Management. (In Farsi)
Bahri, M., Dastorany, M. and Goudarzi, M. (2013). Assessment of the effects of climate change on precipitation and temperature 2011-2030 period using LARS-WG (case study: Watershed Eskandari, Isfahan). The 9th National Congress of Watershed Management Science and Engineering, Nov. 8-9, 2013, University of Yazd, Yazd, Iran. (In Farsi)
Bazrafshan, J. 2009. Agricultural drought risk assessment and searching a sufficient method for estimating its quantitative impact on crops yield of wheat and barley. Ph.D. Dissertation, University of Tehran. 253p.
Ebrahimpour, M. Ghahreman, N. and Orang, M. (2014). Assessment of climate change impacts on reference evapotranspiration and simulation of daily weather data using SIMETAW. Journal of Irrigation and Drainage Engineering. 140(2): 04013012[u1] . (In Farsi)
Farahmand, A. Golkar, F. and Farahmand, F. (2010). Estimating the spatial distribution of rainfall in the Dorudzan Dam Basin using GIS. Geomatics Conference, May.[u2]  (In Farsi)
Fotheringham, A.S., Brunsdon, C. and Charlton, M. (2002). Geographically weighted regression. John Wiley & Sons Inc.
Ghamghami, M. and Ghahreman, N. (2013). Downscaling of climatic change using a non-parametric statistical approach in Karkheh Basin. Iranian Journal of Geophysics. 7(2): 142-157. (In Farsi)
Ghamghami, M., Ghahreman, N. and Hejabi, S. (2014). Detection of climate change effects on meteorological droughts in northwest of Iran. Journal of Earth and Space Physics. 40(1): 167-184. (In Farsi)
Gharekhani, A. and Ghahreman, N. (2010). Seasonal and annual trend of relative humidity and dew point temperature in several climatic regions of Iran. Journal of Water and Soil. 24(4): 636-646. (In Farsi)
Ghorbani, Kh. (2014). Evaluation data mining models in downscaling of precipitation based on NCEP general circulation model output (case study: Kermanshah synoptic station). Iranian Water Research Journal. 8(15), 177-186. (In Farsi)
Ghorbani, Kh. and Agha Shariatmadari, Z. (2014). The effect of local gradients on increasing of climatic data interpolation accuracy by geographically weighted regression (case study: air temperature and relative humidity). Journal of Watershed Management Research. 5(10),132-143. (In Farsi)
Goovaerts, P. (2000). Geostatistical approach for incorporating elevation into spatial interpolation of rainfall. Journal of Hydrology. 228 (2), 113-129.
Gruza, G., Rankova, E., Razuvaev, V. and Bulygina, O. (1999). Indicators of climate change for the Russian Federation. Climatic Change. 42, 219–242.
Gundogdu, I. and Esen, O. (2010). The importance of secondary variables for mapping of meteorological data. The 3rd International Conference on Cartography and GIS. Jun. 15-20, 2010, Nessebar, Bulgaria.
Hadley Center. (2006). Effect of climate change in the developing countries. The UK Meteorological Office.
Hess, T.M., Stephens, W. and Maryah, U.M. (1995). Rainfall trends in the north east arid zone of Nigeria 1961–1990. Agricultural and Forest Meteorology. 74: 87–97.
IPCC. (2007). Climate change: The physical science basis. Contribution of Working Group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. 996 p.
Kakavand, R. and Najaf Abadi, M. (2008). Qazvin climatic maps using GIS. Conference on Geographic Information System. Azad University of Qazvin. (In Farsi)
Karamooz, M. and Araghinejad, Sh. (2006). Advanced hydrology, Amir Kabir University Press, 464 p. (In Farsi)
Khalili, A. (1973). The scientific understanding of climate and weather. IRIMO publication. (In Farsi)
Khorshid Doust, M.A. and Ghavidel Rahimi, Y. (2006). The simulation of atmospheric carbon dioxide doubling impacts on climatic changes in Tabriz using Geophysical Fluid Dynamics Laboratory (GFDL) General Circulation Model. Journal of Environmental Studies. 32(39), 1-10. (In Farsi)
Lashany Zand, M., Shah Hosseini, M. and Beyranvand Zade, M. (2010). Climate zoning of Gilan using classical methods. Conference on Applications of Natural Geography in Environmental Planning. Jun. 5-6, 2010, Islamic Azad University of Khorramabad, Khorramabad, Iran. (In Farsi)
Massah Bavani, A.R. and Morid, S. (2006). Impact of climate change on the water resources of Zayandeh Rud Basin. JWSS - Isfahan University of Technology. 9(4), 17-28. (In Farsi)
Mennis, J. 2006. Mapping the results of geographically weighted regression. The Cartographic Journal, 43(2), 171-179.
Meshkatee, A., Kordjazi, M. and Babaeian, I. (2010). Evaluation of the simulation model LARS during the 1993-2007. Journal of Geographical Sciences and Applied Research, 16(19): ??????. [u3] (In Farsi)
Mohammadi, Gh.H. and Husseini Sadr, A. (2010). District of West Azerbaijan Province from the perspective of agricultural climatology using GIS. The 3rd National Conference on Geography and Scientific Approach to Sustainable Development. Nov. 11-12, 2010, Pyranshahr, West Azarbaijan, Iran. (In Farsi)
Plummer, N., Salinger, M.J., Nicholls, 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. Climatic Change. 42, 183–202.
Racsko, P. and Szeidl, L. (1991). A serial approach to local stochastic weather models. Ecological Modelling. 57, 27-41.
Rahimi, J., Ebrahimpour, M. and Khalili, A. (2013). Spatial changes of Extended De Martonne climatic zones affected by climate change in Iran. Theoretical and Applied Climatology. 112(3), 409-418. (In Farsi)
Sabohi, R. and Soltani, S. (2009). Trend analysis of climatic factors in great cities of Iran. JWSS - Isfahan University of Technology. 12(46), 303-321. (In Farsi)
Semenov, M.A., Brooks, R.J., Barrow, E.M. and Richardson, C.W. (1998). Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research. 10, 95-107.
Suppiah, R. and Hennessy, K. (1998). Trends in total rainfall, heavy rain events and number of dry days in Australia, 1910–1990. International Journal of Climatology. 10, 1141–1164.
Turke¸ S.M. (1996). Spatial and temporal analysis of annual rainfall variations in Turkey. Internatonal Journal of Climatology. 16, 1057–1076.
Varshavian, V., Khalili, A., Ghahreman, N. and Hajjam, S. (2011). Trend analysis of minimum, maximum, and mean daily temperature extremes in several climatic regions of Iran. Journal of the Earth and Space Physics. 37(1), 169-179.
Viglizzo, E.F., Roberto, Z.E., Filippin, M.C. and Pordomingo, A.J. (1995). Climate variability and agroecological change in the central Pampas of Argentina. Agricultural Ecosystem and Environment. 55, 7–16.
Xu, C.Y. (1999). From GCMs to river flow: a review of downscaling methods and hydrologic modeling approaches. Progress in Physical Geography. 23(2), 229-249
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.