Suggesting a Method to Estimate the Cooling Time of Iranand its Simulation in the Future

Document Type : Research Paper

Authors

Abstract

One of the criteria for estimating the amount of energy used for cooling and heating is the degree hour. The aim of this study was to select the most appropriate method to calculate the cooling degree hour and simulate these parameters in the coming decades. Firstly, by using EH5OM model data from Max Planck Institute in Germany, the hourly temperature data at a time interval of 3 hours (8 data per day) in Iran territory during the period of 2025-2060 under A1B scenario of the International Committee of Climate Changes and resolution 1.75×1.75 of longitude and latitude degree were simulated.Then the hourly temperature data separetely with 0.27×0.27 of geographical altitude and latitude degree which covers an area with dimensions of approximately 30 x 30 km of  Iran was downscaled by the fourth edition of the regional climatic model. By using temperature threshold 23.9° C degree, the required hours of cooling per hour in each day and their monthly calculation were extracted in a matrix of size 2138 × 3456. In this matrix, the rows indicate the total of monthly degree hours and the columns indicate the cells. Then the hours of 09, 12 and 15 Zulu were selected from the existing hours and the  total monthly average of degree hours  of 6 warm months of the  year (April to September) were calculated on a matrix of size 2140×12 and its maps were drawn in Surfer software. The trend amount of the said degree hours was calculated in MATLAB software and through the Mann-Kendall test on 2140×12 matrix and their monthly process maps were drawn. The results showed that spring season sepecially April and May months will have  the greatest hour cooling need and the lowest one will be in summer, especially in August and September. Maximum cooling needs in the hours of 09 and 12 Zulu in April and May in Khuzestan plain and 900-1000 hour degree in the southern coast hinterlanda and the lowest one at 15 o'clock  zulu, On the hills of Azerbaijan, Zagros, Alborz and Khorasan in June, July, August and September will be zero hour degree. The positive trend of cooling need is in the West and southern banks at every three hours of the  under study in the months of April, May and June and July which  indicate the  warmer temperatures in the first half year. Central belt and across the eastern and northern half of the country except in  June has no trend in the rest months of the year.

Keywords

References

بابائیان، ایمان؛ عاطفه عرفانی؛ مریم کریمیان؛ راحله مدیریان(1392). شبیه‌سازی اثر تغییر اقلیم بر مصرف برق کشور در دوره‌ی 2020-2010 با استفاده از ریز مقیاس نمایی برونداد مدل گردش عمومی جو، دهمین همایش بین‌المللی انرژی.
شاهکویی، اسماعیل؛ غلامرضا روشن(1391).تغییرات زمانی درجه- روز مورد نیاز گیاه سویا بر مبنای دگرگونی‌های اقلیمی دهه‌های آینده مطالعه موردی: شهرستان گرگان فصلنامه تحقیقات جغرافیایی. سال 27. شماره اول. بهار 1391. شماره پیاپی 104. صفحات 65-51.
کریمیان، مریم؛ ایمان بابائیان؛ راحله مدیریان (1386). بررسی و توانمندی مدل RegCM در مدل‌سازی بارش و دمای استان خراسان، فصلنامه علمی- پژوهشی دانشگاه گلستان. مجله آمایش جغرافیایی فضا. سال سوم. شماره مسلسل هفتم. بهار 1392. صفحات 186-167.
مسعودیان، سیدابوالفضل؛ رضا ابراهیمی؛ الهام یاراحمدی (1393). واکاوی مکانی- زمانی میزان روند ماهانه درجه روز گرمایش در قلمرو ایران‌ زمین، مجله جغرافیا و توسعه ناحیه‌ای. سال 12. شماره 1393. صفحات 128-111.
Borah Pallavi, Manoj Kumar Singh & Sadhan Mahapatra (2015). Estimation of degree - days for different climatic zones of North-EastIndia. Sustainable Cities and Society 14,  PP: 70–81.
Ceppi Paulo, Yen-Ting Hwang, Dargan M. W. Frierson, & Dennis L. Hartmann (2012). Southern Hemisphere jet latitude biases in CMIP5 models linked to shortwave cloud forcing Geophysical Research Letters, Vol. 39, L19708,doi:10.1029/2012 PP:1-5.
Cesaraccio, Carla. Donatella, Spano. Pierpaolo Duce Richard L (2001). Snyder model for determining degree-days values from daily temperature data An improved. Biometeorol 45, PP:161-169.
Elizabeth M., & Federico C (2013). Variability and trends of heating degree-days in Argentina, International Journal of Climatology, Vol. 33, Issue 10, August 2013, PP: 2352–2361.
Fung, F., A. L. Lopez & M. New (2011). Modeling the impact of climate change on water resources.Wiley -Blackwell, N,(187), PP:43 -62.
Fengqing .Jiang, Xuemei. Li., Binggan. Wei., &  Ruji Hu .Zhen (2010). Observed trends of heating and cooling degree-days in Xinjiang Province, China. Theor Appl Climatol: 97,
PP: 349–360.
Fang, X, Wang, A, Fong, S.K, Lin, W & Liu, J (2008).Changes  of reanalysis-derived Northern  Hemisphere summer warm extreme indices during 1948–2006 and links with climate variability”, Global and planetary change, Vol. 63, PP: 67-78.
Frank, T (2005). Climate change impacts onbuilding heating and cooling energy demand in Switzerland. Energy and Buildings 37 (2005),  PP:1175-1185.
Ginn, E.W.L., Lee, T.C. & Chan, K.Y (2010). Past and Future Changes in the Climate of Hong Kong. Accepted for publication in Acta Meteorologica Sinica..140-164.
J. David Neelin (2010). Climate Change and Climate Modeling, Cambridge University Press the Edinburgh Building, Cambridge CB2 8RU, UK.1-272.
K. P. Moustris و P. T. Nastos و A. Bartzokas و I. K. Larissi, P. T. Zacharia., & A. G. Paliatso(2015).Energy consumption based on heating/ cooling degree days within the urban environment of Athens, Greece, Theor Appl Climatol DOI 10.1007/s00704-014-1308-7, PP:1-13.
Papakostas, K. T., Michopoulos, A. K., & Kyriakis, N.A(2004). Equivalent full-load hours for estimating heating & cooling energy requirements in buildings: Greece casestudy. Applied Energy,86(5),PP:757-761.
Roeckner E, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kornblueh L, Manzini E, & Schlese U Schulzweida U (2003). Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model''. J Clim 19, PP: 3771–3791.
Reichard T, & Kim J (2008). How well do coupled models simulate today’s climate'' Bull Am Meteorol Soc 89, PP:303–311.
Roshan, Gh. R., Grab, & S.W (2012). Regional Climate Change Scenarios and Their Impacts on Water - Requirements for Wheat Production in Iran, International Journal of Plant Production, Vol. 2, PP:239-265.
Randall DA (2007). Climate models and their evaluation. In: Solomon S, Qin D, Manning M Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Cambridge University Press, Cambridge, PP:1-15.
Roeckner E, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kornblueh L, Manzini E, Schlese U Schulzweida U (2006) .Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model. J Clim 19, PP:3771–3791. 
Roshan,G.R.,& Grab, S. W (2012). Regional climate change scenarios and their impacts on water requirements for wheat production in Iran. Int J Plant Prod, 6(2), 239-266.
Van, T & N Van (2005). Downscaling methods for evaluating the impact of climate change and variability on hydrological regime at basin scale role of water sciences in Trans boundary river basin management. Thailand, PP:1-8.
Wang, H. & Chen, Q (2014). Impact of climate change heating and cooling energy use in buildings in the United States,” Energy and Buildings, 82,  PP: 428–436.
Wilby, R. L . & W.C. Dawson (2007). SDSM 4.2-Adecision support tool for the assessment of regional climate change impacts, SDSM manual version 4.2, Environment Agency of England & Wales, PP:1-94.
Geography and Development
Volume 15, Issue 48
September 2017
Pages 19-38

Files

History

  • Receive Date: 12 September 2017
  • Accept Date: 12 September 2017

Share

How to cite

Statistics