شبیه‌سازی آماری فرین‌های دمای شهر زنجان براساس سناریوهای آب‌وهوایی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه جغرافیا، دانشکده علوم اجتماعی، دانشگاه زنجان، زنجان، ایران

2 گروه علوم محیط زیست، دانشکده علوم، دانشگاه زنجان، زنجان، ایران

چکیده

مقدمه: آب و هوا یکی از اساسی ترین عوامل در ساختار سیاره زمین است. تغییر اقلیم می­تواند بازخوردها و پیامدهای زیادی داشته باشد. با توجه به افزایش افراط‌های اقلیمی و مخاطرات طبیعی در ایران که با حساسیت اکولوژیکی مشخص می‌شود، این رویدادها تأثیر بسزایی بر وضعیت منابع آبی، کشاورزی، انرژی، گردشگری و شرایط زیست‌اقلیمی دارد. بنابراین مطالعه این رشته یک ضرورت اجتناب ناپذیر است. هدف اصلی پژوهش حاضر، بررسی شبیه‌سازی مقادیر میانگین و حداقل، حداکثر و میانگین دمای روزانه زنجان براساس سناریوهای اقلیمی و با استفاده از مدل SDSM است.
مواد و روش­ها: روش انجام پژوهش توصیفی- تحلیلی و روش گردآوری داده­ها کتابخانه­ای (اسنادی) است. مدل SDSM و سناریوهای آب و هوایی (RCP2.6، RCP4.5 و RCP8.5) برای شبیه­سازی متغیرهای دما استفاده شده است. داده های مورد استفاده شامل میانگین، حداقل و حداکثر دمای روزانه ثبت شده در ایستگاه حمید زنجان طی دوره زمانی 1961-2021 و داده­های مدل گردش عمومی جو برای شبیه­سازی متغیرهای اقلیمی در دوره­های آتی می­باشد. به منظور به دست آوردن مناسب­ترین متغیرهای جوی برای تخمین پروفیل­های دمایی سه گانه، رابطه بین متغیرهای وابسته (حداقل، متوسط و حداکثر دمای روزانه) با متغیرهای مستقل جوی (NCEP) برای انتخاب متغیرهای مستقل و کالیبراسیون مجدد مدل برای متغیرهای وابسته مورد بررسی قرار گرفت. همچنین از مدل زنجیره مارکوف برای بررسی احتمالات رخدادهای فرین استفاده شده است. به منظور کالیبراسیون مجدد مدل SDSM، داده­های مشاهده­ای ایستگاه زنجان و داده­های مرکز ملی پیش­بینی متغیرهای محیطی NCEP به دو دوره 1961-1990 و 1991-2005 تقسیم شدند. دوره اول برای کالیبراسیون مدل استفاده شد.
نتایج و بحث: نتایج شبیه­سازی سه متغیر دمایی مورد مطالعه نشان داد که در تمامی سناریوها در دوره زمانی 2100-2082 بیشترین افزایش را نسبت به مقادیر این متغیرها در دوره پایه (2021-1961) خواهند داشت. بررسی ماهانه داده­های شبیه­سازی شده و داده­های مشاهده شده متغیرهای مورد مطالعه نشان داد که براساس سناریوهای مورد مطالعه و مدل SDSM مشخص شد که از سال 2022 تا 2100 حداقل دما 2 درجه، حداکثر و متوسط دما افزایش می­یابد. 3 درجه میانگین حداقل و میانگین دما در دی و بهمن بیشترین افزایش و در مهرماه کمترین افزایش را خواهد داشت. در حالی که میانگین حداکثر دما در مرداد ماه و کمترین آن در فروردین ماه افزایش خواهد یافت.
نتیجه ­گیری: نتایج نشان می­دهد که تمام فصول سال به ویژه فصول سرد سال گرمتر خواهند شد. به عبارت دیگر، فصول سرد کوتاه­تر خواهد بود. تعداد فرکانس‌های شدید مشاهده‌ شده در هر سه پارامتر دمایی برای چارک‌های 25 و 75 کمتر از تعداد رویدادهای دمای شدید شبیه‌سازی ‌شده در هر سه سناریو است. بیشترین تعداد فرکانس­های بسیار پایین در ماه ژانویه و بیشترین تعداد فرکانس­های بسیار بالا در ماه جولای پیش­بینی می­شود.
ذیرش می‌سازد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Statistical simulation of extreme temperatures in Zanjan based on climate scenarios

نویسندگان [English]

  • Leila Ahadi 1
  • Hossein Asakereh 1
  • Yunes Khosravi 2
1 Department of Geography, Faculty of Social Sciences, Zanjan University, Zanjan, Iran
2 Department of Environmental Sciences, Faculty of Science, Zanjan University, Zanjan, Iran
چکیده [English]

Introduction: Climate is one of the most fundamental factors in the structure of the planet Earth. Climate change can have many feedbacks and consequences. Due to the increase in climatic extremes and natural hazards in Iran, which is characterized by ecological sensitivity, these events have a significant impact on the state of water resources, agriculture, energy, tourism, and bio-climatic conditions; Therefore, studying this field is an inevitable necessity. The main goal of the current research is to investigate the simulation of average values and minimum, maximum and average daily temperatures of Zanjan based on climate scenarios and using the SDSM model.
Materials and methods: The method of carrying out descriptive-analytical research and the method of collecting data is library (documents). SDSM model and climate scenarios (RCP2.6, RCP4.5 and RCP8.5) have been used to simulate temperature variables. The data used includes the average, minimum and maximum daily temperature recorded at the Hamdid Zanjan station during the period of 1961-2021 and the data of the general atmospheric circulation model to simulate climate variables in future periods. In order to obtain the most suitable atmospheric variables for estimating triple temperature profiles, the relationship between dependent variables (minimum, average and maximum daily temperature) with independent atmospheric variables (NCEP) was examined to select independent variables and recalibrate the model for dependent variables. Also, the Markov chain model has been used to investigate the probabilities of Frein events. In order to recalibrate the SDSM model, the observational data of Zanjan station and the data of NCEP National Center for Prediction of Environmental Variables were divided into two periods: 1961-1990 and 1991-2005. The first period was used to calibrate the model.
Results and discussion: The simulation results of the three studied temperature variables showed that in all scenarios, they will increase the most in the period of 2082-2100 compared to the values of these variables in the base period (1961-2021). The monthly review of the simulated data and the observed data of the studied variables showed that based on the studied scenarios and the SDSM model, it was determined that from 2022-2100 the minimum temperature will increase by 2 degrees, the maximum and average temperature by 3 degrees. The average minimum and average temperature will increase the most in January and February and the least in October. While the average maximum temperature will increase the most in August and the least in April.
Conclusion: Result shows that all seasons of the year will become warmer, especially the cold seasons of the year. In other words, the cold seasons will be shorter. The number of extreme frequencies observed in all three temperature parameters for the 25th and 75th quartiles is less than the number of simulated extreme temperature events in all three scenarios. The highest number of extreme low frequencies is expected in January and the highest number of extreme high frequencies is expected in July.
 

کلیدواژه‌ها [English]

  • Zanjan
  • Climate scenarios
  • Simulation
  • Extreme temperature
  • SDSM

مراجع

منابع (References)
 
-Afrosheh, R., Rasouli, A.A., Mokhtari, D. and Jalali, T., 1400. Analysis of the behavior of the distribution sequence and the frequency of extreme events in selected stations in the west of Iran. Scientific Quarterly of Geographical Space, 21st year, v. 74, p. 73-88 (in Persian).
-Ansari Mahabadi, S., Dehban, H., Zareian, M.J. and Farrokhnia, A., 1401. Studying the trend of temperature and precipitation changes in Iran's watersheds in the next 20 years based on the output of CMIP6 models, Iranian Water Research Journal, v. 16(1(44)), p. 11-24 (in Persian).
-Argueso, D., Evans, Jason, P., Fita, L. and Bormann, K.J., 2014. Temperature response to future urbanization and climate change, Climate Dynamics, v. 42, p. 2183-2199.
-Asakereh, H. and Kayani, H., 2017. evaluation of the efficiency of SDSM model in simulating the average temperature of Kermanshah city, Scientific-Research Quarterly of Geographical Information, v. 27(105), p. 49-62 (in Persian).
-Asakereh, H. and Akbarzadeh, Y., 2016. Simulation of temperature and precipitation changes of Tabriz synoptic station during the period (2010-2100) using Statistical Exponential Microscale (SDSM) and CanESM2 model output, Journal of Geography and Environmental Hazards, v. 6(1(21)), p. 153-174 (in Persian).
-Asakereh, H. and Mazini, F., 2009. investigating the probability of dry days in Golestan province using the Markov chain model, Geography and Development, v. 17, p. 29-44 (in Persian).
-Asakereh, H., Shahbai Kotnai, A. and Farumdi, M., 2018. evaluation of changes and prediction of minimum temperature in the west of Mazandaran province using SDSM statistical microscale model, Water and Soil Sciences - Agricultural Sciences and Techniques and Natural Resources, v. 23(1), p. 101-119 (in Persian).
-Ashrafzadeh, A., Salehpour, J., Sharifi, A. and Nasab Pour Molaei, M., 2018. The effect of climate change on temperature and precipitation and the assessment of the uncertainty of atmospheric general circulation models and climate scenarios (case study: Jiroft city, Miande supplementary synoptic station), Human and Environment Journal, published online from May 2 (in Persian).
-Chen, Y., Moufouma-Okia, W., Masson-Delmotte, V., Zhai, P.,
and Pirani, A., 2018. Annual Review of Environment and Resources: Recent Progress and Emerging Topics on Weather and Climate Extremes Since the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, v. 43, p. 17.1-17.25, 10.1146/annurev-environ-102017-030052
-Darand, M. and Hamidi, S., 1400. simulation of Iran Earth temperature changes based on different RCP scenarios, Journal of Environmental Hazards, v. 10(28(2)), p. 85-106 (in Persian).
-Darand, M., Dolatyari, Z., Aslani Slammers, F. and Azizi, Y., 2013. Investigating the behavior of precipitation and temperature variables in Kermanshah with the help of statistical tests, Geospatial Journal, v. 14(46), p. 213-233 (in Persian).
-Dasht bozorgi, A., Alijani, B., Jafarpour, Z.A. and Shakiba, A., 2014. simulation of extreme temperature indices of Khuzestan province based on RCP scenarios, geography and environmental risk, v. 16, p. 105-123 (in Persian).
-Dibike, Y.B. and Coulibaly, P., 2005. Hydrologic impact of climate change in the Saguenay watershed: comparison of ownscaling methods and hydrologic models. Journal of Hydrology, v. 307(1-4), p. 145-163.
-Dookie, N., T.Chadee, X. and M. Clarke, R., 2018. Trends in extreme temperature and precipitation indices for the Caribbean small islands: Trinidad and Tobago, Theoretical and Applied Climatology, v. 136, p. 31-44.
-Etemadi, H., Sharifi Kia, M., Samadi, S.Z., Ismaili Sari, A. and Dane Kar, A., 2014. Simulating future climate changes in Jask region and its effect on mangrove forests, Geography and Development, v. 41, p. 87-104 (in Persian).
-Erfanian, M., Ansari, H., Alizadeh, A. and Banayan Aval, M., 2016. Estimation of frequency-continuity-return period relationships of extreme climate profiles in different parts of Razavi Khorasan Province, Geographical Research Quarterly, 32nd Year, v. 1(124), p. 37-50 (in Persian).
-Fatemi, M. and Narangi Fard, M., 2018. Investigating the relationship between altitude and temperature and precipitation profiles in Hamdid stations of Fars province. Scientific-Research Quarterly of Geographical Thought, Year 11, v. 22, p. 23-39 (in Persian).
-Fakhimi, P., Shirdeli, A. and Masoudi, M., 2014. water and climate change: investigation of monthly, seasonal and annual air temperature changes in Zanjan province, conference: Iran National Irrigation and Drainage Congress, Mashhad (in Persian).
-Falahi Khoshji, M. and Akbari, M., 2018. simulation of temperature changes in western Iran, 6th regional climate change conference (in Persian).
-Hejazizadeh, Z., Hosseini, S.M. and Karbalai Dorthi, A., 2014. simulation of climatic variables of Semnan province with scenarios of general atmospheric circulation model (Hadcm3), Geography and Environmental Hazards, v. 15, p. 1-24 (in Persian).
-Haites, E., 2018. Carbon taxes and greenhouse gas emissions trading systems: what have we learned? Climate Policy, v. 18(8), p. 955-966.
-Hu, Y., Maskey, Sh. and Uhlenbrook, S., 2012. Trends in temperature and rainfall extremes in the Yellow River source region, China, Climate Change, v. 110, p. 403-429.
-Jarvie, J., Sutarto, R., Syam, D. and Jeffery, P., 2015. Lessons for Africa from urban climate change resilience building in Indonesia, Current Opinion in Environmental Sustainability, v. 13, p. 19-24.
-Jafarzadeh, A., Khashei, A. and Shahidi, A., 2016. evaluation of two statistical exponential microscale methods, LARS-WG and SDSM, in estimating changes in climatic parameters (case study: Birjand Plain), Water and Soil Conservation Research, v. 23(4), p. 309-322 (in Persian).
-Khademi, M., Fazl Oli, R. and Emadi, A., 2016. Investigating the capabilities of the artificial neural network model in simulating the rainfall-runoff process under climate change conditions (case study: Pashakola dam area of Babol), watershed management research paper, v. 16, p. 53-64 (in Persian).
-Kazemi Rad, L. ans Mohammadi, H., 2014. evaluation of the appropriate general circulation model of the atmosphere for predicting climate changes in Gilan province, Geography and Environmental Hazards, v. 16, p. 55-73 (in Persian).
-Keggenhoff, I., Elizbarashvili, M., Amiri-Farahani, A. and King, L., 2014. Trends in daily temperature and precipitation extremes over Georgia, 1971–2010, Weather and Climate Extremes, v. 4, p. 75-85.
-Kenward, A. and Raja, U., 2014. Blackout: Extreme weather, climate change and power outages, Clim Cent, p. 1-23.
-Kobuliev, M., Liu, T., Kobuliev, Z., Chen, X., Gulakhmadov. and Bao, A., 2021. Effect of future climate change on the water footprint of major crops in southern Tajikistan, Regional Sustainability, v 2(1), p. 60-72.
-Maduako, I.D., Yun, Z. and Patrick, B., 2016. Simulation and Prediction of Land Surface Temperature (LST) Dynamics within Ikom City in Nigeria Using Artificial Neural Network (ANN). J Remote Sensing & GIS 5:158. doi:10.4172/2469-4134.1000158
-Mahmood, R. and Babel, M.S., 2014. Future changes in extreme temperature events using the statistical downscaling model (SDSM) in the trans-boundary region of the Jhelum river basin, Weather and Climate Extremes, v. 5-6, p. 56-66.
-Malalgoda, C., Amaratunga, R.D.G. and Pathirage, C.P., 2010. Exploring disaster risk reduction in the built environment. School of The Built Environment, University of Salford, uk.
-Nik, V.M. and Moazami, A., 2021. Using collective intelligence to enhance demand flexibility and climate resilience in urban areas, Applied Energy, v. 281, doi.org/10.1016/j.apenergy.2020.116106.
-Oji, R., 2017. Comparison of single-station and multi-station temperature and precipitation microinversion (case study: southern shores of the Caspian Sea), Journal of Earth and Space Physics, v. 44(2), p. 410-397 (in Persian).
-Parhizkari, A. and Mozafari, M.M., 2015., Assessment of the effects of greenhouse gas emissions and climate change on the supply and demand of irrigation water and agricultural production in the watersheds of Qazvin province, watershed management research journal, 7th year, v. 14, p. 141-151 (in Persian).
-Panahi, H. and Ismail Darjani, N., 2019. investigating the effect of global warming and climate changes on economic growth (case study: Iranian provinces during the period 2010-2015). Environmental Science and Technology, v. 22(1), p. 80-82 (in Persian).
-Pal, J.S. and Eltahir, E.A.B., 2015. Future temperature in southwest Asia projected to exceed a threshold for human adaptability, Nature Climate Change, v. 6, p. 197-200.
-Powell, E.J. and Keim, B.D., 2015. Trends in Daily Temperature and Precipitation Extremes for the Southeastern United States: 1948–2012, Journal of Climate, v. 28(4), p. 1592-1612.
-Rashid, M.M., Beecham, S. and Chowdhury, R.K., 2015. Statistical downscaling of CMIP5 outputs for projecting future changes in rainfall in the Onkaparinga catchment, Science of The Total Environment, v. 530-531, p. 171-182.
-Razmi, R. and Sotoudeh, F., 2016. zoning the probability of droughts and droughts in the northwest of Iran, Andisheh Geography, 9th year, 16th issue, p. 68-95 (in Persian).
-Rezaei, M., Nahtani, M., Moghadamnia, A., Abkar, A. and Rezaei, M., 2016. Long-term forecasting of precipitation using statistical microscale exponential model, Danesh Water and Soil Science, v. 26(1/2), p. 115-127 (in Persian).
-Saddique, N., Khaliq, A. and Bernhofer, Ch., 2020. Trends in temperature and precipitation extremes in historical (1961–1990) and projected (2061–2090) periods in a data scarce mountain basin, northern Pakistan, Stochastic Environmental Research and Risk Assessment v. 34, p. 1441-1455.
-Souvignet, M., Gaese, H., Ribbe, L., Kretschmer, N. and Oyarzún, R., 2010. Statistical downscaleing of precipitation and temperature in north-central Chile: an assessment of possible climate change impacts in an arid Andean watershed, Hydrological Sciences Journal– Journal des Sciences Hydrologiques, v. 55, p. 41-57.
-Sobhani, B., Eslahi, M. and Babaian, A., 2014. The effectiveness of SDSM and LARS-WG statistical microscale models in simulating meteorological variables in the Urmia Lake catchment, Natural Geography Research, v. 47(4(4)), p. 499-516 (in Persian).
-Selajegheh, A., Rafii Sardoi, A., Moghadamnia, A., Malekian, A., Iraqinejad, Sh., Khalighi Sigarodi, Sh. and Salehpour Jam, A.P., 2016. investigating the effectiveness of LARS-WG and SDSM statistical micro-scale models in simulating temperature and precipitation, Iran Water and Soil Research, v. 48(2), p. 253-262 (in Persian).
-Sayari, N., Alizadeh, A., Banayan Aval, M., Farid Hasani, A. and Hesami Kermani, M.R., 2017. Comparison of two atmospheric general circulation models (HadCM3, CGCM2) in predicting climatic parameters and water requirements of plants under climate change, case study: Kashf Roud Basin, Water and Soil Journal (Agricultural Sciences and Industries), v. 25(4), p. 912-925 (in Persian).
-Sheikh Rabiei, M.R., Peyrovan, H.R., Daneshkar Arasteh, P., Akbari, M. and Motamed Waziri, B., 1400. Comparison of the efficiency of SDSM and CCT models in climate change studies (case studies of Karganrood watershed), Journal of Meteorology and Atmospheric Sciences, v. 4(2), p. 128-146 (in Persian).
-Shidayan, M., Zia Tabar Ahmadi, M.Kh. and Fazl Ola, R., 2013. the effect of climate change on the net irrigation requirement and rice yield (case study: Tajan Plain), Water and Soil Journal (Agricultural Sciences and Industries), v. 28(6), p. 1284-1297 (in Persian).
-Taghilo, M., Alijani, B. and Asakereh, H., 2018. the study of the efficiency of the regional climate model (RegCM) in simulating the temperature and precipitation of some selected cities of Iran (case study: 2010-2015 period), Geographical Space Scientific Quarterly, 19th year, v. 68, p. 95-110 (in Persian).
-Tai Semiromi, S., Moradi, H.R. and Khodaqoli, M., 2013. simulation and prediction of some climate variables by SDSM multiple linear model and atmospheric general circulation models (case study: Bar Neyshabur watershed), Human and Environment Quarterly, v. 28, p. 1-16 (in Persian).
-Vahidi, A.A. ans Mataji, A., 2012. The amount of carbon sequestration distribution of oak trunks in relation to physiographic factors of natural forests in northern Iran. Scientific-research quarterly of Iranian forest and poplar research, v. 21(4), p. 716-717 (in Persian).
-Wilby, R.L., Dawson, C.W. and Barrow, E.M., 2002. SDSM—a decision support tool for the assessment of regional climate change impacts. Environmental Modelling & Software, v. 17, (2), p. 145-157.
-Yazdan Panah, H.A. and Alizadeh, T., 1390. estimating the probability of occurrence of heat waves with different periods of continuity in Kerman province using the Markov chain, Journal of Geographical Research, v. 102(3) (in Persian).
 
 
 

فایل ها

هم رسانی

ارجاع به این مقاله

آمار