Volume 9, Issue 3 (2021)                   ECOPERSIA 2021, 9(3): 179-189 | Back to browse issues page

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Jowkar L, Panahi F, Sadatinejad S, Shakiba A. The Spatio-Temporal Variability of Extreme Temperature Using Gridded AgMERRA Dataset over the Bakhtegan-Maharloo Basin, Iran. ECOPERSIA. 2021; 9 (3) :179-189
URL: http://ecopersia.modares.ac.ir/article-24-45017-en.html
1- Department of Desert Sciences Engineering, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran
2- Department of Desert Sciences Engineering, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran , alabd_fpanahi@yahoo.com
3- Department of Renewable Energy and the Environment, Faculty of New Sciences and Technologies, Tehran University, Tehran, Iran
4- ”Department of Remote Sensing and GIS, Faculty of Earth Science” and “Center for Remote Sensing & GIS Research”, Shahid Beheshti University, Tehran, Iran
Abstract:   (796 Views)
Aims: Trend analysis of climatic variables has got a great deal of notice from researchers recently. This study aimed to investigate the Spatio-temporal variability of extreme temperature indices based on the station data and gridded dataset analyses over the Bakhtegan-Maharloo basin in Iran from 1980 to 2010.
Materials & Methods: Climatic data related to the Bakhtegan-Maharloo basin was extracted from AgMERRA dataset for the study period (1980-2010) using R software. Daily temperature data were also extracted from the Meteorological Archive of meteorological stations located in the basin during the study period. Warm nights (TN90p), maximum monthly value of daily minimum temperature (TNx), cold nights (TN10p), and cold spell duration indicator (CSDI) indices had been chosen from the indices recommended by the Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI) and calculated by RClimDex software package.
Findings: The results of AgMERRA and stations data revealed an increasing trend in warm extremes including TN90p and TNx with the trend changes ranging from 0.135 to 0.721 and 0.061 to 0.139, respectively, but a declining trend in cold extremes including TN10p and CSDI with the trend changes ranging from -0.517 to -0.125 and -0.987 to -0.167, respectively.
Conclusion: The results of this study may contribute to a better understanding of regional temperature behavior in the study area. The results indicated that the frequency and intensity of cold extremes have declined, though warm extremes increased. Due to the intensive impacts of temperature extremes on human life, it is essential to speculate the effects of these extreme climatic events in future plannings in various sections.
Full-Text [PDF 860 kb]   (314 Downloads)    
Article Type: Original Research | Subject: Desert Ecosystems
Received: 2020/08/19 | Accepted: 2020/12/21 | Published: 2021/05/11
* Corresponding Author Address: Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran. Postal code: 8731753153

1. Zwiers FW, Zhang X. Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation. Geneva, Switzerland: World Meteorological Organization; 2009. [Link]
2. Gautam N, Arora M, Goel NK. Prediction of precipitation for considering climate change and gcm outputs: satluj river. Ecopersia. 2014;2(4):757-65. [Link]
3. Peterson T. Report on the activities of the working group on climate change detection and related rapporteurs. Geneva, Switzerland: World Meteorological Organization; 2001. pp. 1-143. [Link]
4. Hess JJ, Malilay JN, Parkinson AJ. Climate change: The importance of place. Am J Prev Med. 2008;35(5):468-78. [Link] [DOI:10.1016/j.amepre.2008.08.024]
5. Akbari M, Ownegh M, Asgari H, Sadoddin A, Khosravi H. Drought Monitoring Based on the SPI and RDI Indices under Climate Change Scenarios (Case Study: Semi-Arid Areas of West Golestan Province). ECOPERSIA. 2016;4(4):1585-602. [Link] [DOI:10.18869/modares.ecopersia.4.4.1585]
6. Goodarzi E, Dastorani M, Massah Bavani A, Talebi A. Evaluation of the change-factor and lars-wg methods of downscaling for simulation of climatic variables in the future (case study: Herat Azam Watershed, Yazd - Iran). ECOPERSIA. 2015;3(1):833-46. [Link]
7. Ghazanfari MM, Alizadeh A, Mosavi BS, Faridhosseini A, Bannayan AM. Comparison the PERSIANN model with the interpolation method to estimate daily precipitation (a case study: North Khorasan). Iran J Water Soil. 2011;25(1):207-15. [Link]
8. Sadras VO. Influence of size of rainfall events on water-driven processes. I. Water budget of wheat crops in south-eastern Australia. Crop Pasture Sci. 2003;54(4):341-51. [Link] [DOI:10.1071/AR02112]
9. Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Thorburn P, et al. The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies. Agric For Meteorol. 2013;170:166-82. [Link] [DOI:10.1016/j.agrformet.2012.09.011]
10. Ruane AC, Goldberg R, Chryssanthacopoulos J. Climate forcing datasets for agricultural modeling: Merged products for gap-filling and historical climate series estimation. Agric For Meteorol. 2015;200:233-48. [Link] [DOI:10.1016/j.agrformet.2014.09.016]
11. Luo F, Wilcox L, Dong B, Su Q, Chen W, Dunstone N, et al. Projected near-term changes of temperature extremes in Europe and China under different aerosol emissions. Environ Res Lett. 2020;15(3):034013. [Link] [DOI:10.1088/1748-9326/ab6b34]
12. Niu Z, Wang L, Fang L, Li J, Yao R. Analysis of spatiotemporal variability in temperature extremes in the Yellow and Yangtze River basins during 1961-2014 based on high‐density gauge observations. Int J Climatol. 2020;40(1):1-21. [Link] [DOI:10.1002/joc.6188]
13. Tavakol A, Rahmani V, Harrington Jr J. Evaluation of hot temperature extremes and heat waves in the Mississippi River Basin. Atmos Res. 2020;239:104907. [Link] [DOI:10.1016/j.atmosres.2020.104907]
14. Parak F, Roshani A, Jamali JB. Trends and anomalies in daily climate extremes over Iran during 1961-2010. J Environ Agric Sci. 2015;2(11):1-17. [Link]
15. Rahimzadeh F, Asgari A, Fattahi E. Variability of extreme temperature and precipitation in Iran during recent decades. Int J Climatol. 2009;29(3):329-43. [Link] [DOI:10.1002/joc.1739]
16. Abolverdi J, Ferdosifar G, Khalili D, Kamgar-Haghighi AA, Haghighi MA. Recent trends in regional air temperature and precipitation and links to global climate change in the Maharlo watershed, Southwestern Iran. Meteorol Atmos Phys. 2014;126(3-4):177-92. [Link] [DOI:10.1007/s00703-014-0341-5]
17. Ghiami-Shamami F, Sabziparvar AA, Shinoda S. Long-term comparison of the climate extremes variability in different climate types located in coastal and inland regions of Iran. Theoretic Appl Climatol. 2019;136(3-4):875-97. [Link] [DOI:10.1007/s00704-018-2523-4]
18. Alizadeh-Choobari O, Najafi M. Extreme weather events in Iran under a changing climate. Clim Dyn. 2018;50(1-2):249-60. [Link] [DOI:10.1007/s00382-017-3602-4]
19. Zampieri M, Ceglar A, Dentener F, Toreti A. Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales. Environ Res Lett. 2017;12(6):064008. [Link] [DOI:10.1088/1748-9326/aa723b]
20. Joseph JE, Akinrotimi OO, Rao KP, Ramaraj A, Traore PS, Sujatha P, et al. The usefulness of gridded climate data products in characterizing climate variability and assessing crop production. 2020. [Link]
21. Razavi A, Mahallati M, Koocheki A, Beheshti A. Applicability of AgMERRA for gap-filling of Afghanistan in-situ temperature and precipitation data. J Water Soil. 2018;32(3):601-11. [Link]
22. Tesfaye K, Aggarwal PK, Mequanint F, Shirsath PB, Stirling CM, Khatri-Chhetri A, et al. Climate variability and change in Bihar, India: Challenges and opportunities for sustainable crop production. Sustainability. 2017;9(11):1998. [Link] [DOI:10.3390/su9111998]
23. Salehnia N, Alizadeh A, Sanaeinejad H, Bannayan M, Zarrin A, Hoogenboom G. Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data. J Arid L. 2017;9(6):797-809. [Link] [DOI:10.1007/s40333-017-0070-y]
24. Bannayan M, Lashkari A, Zare H, Asadi S, Salehnia N, editors. Applicability of AgMERRA forcing dataset to fill the gaps in historical in-situ meteorological data, case study: Iran. AGU Fall Meeting San Francisco. San Francisco: American Geophysical :union:; 2015. [Link]
25. Yaghoubi F, Bannayan Aval M, Asadi GA. Evaluation of grided AgMERRA weather data for simulation of water requirement and yield of rainfed wheat in Khorasan Razavi Province. J Water Soil. 2018;32(2):415-31. [Link]
26. Lashkari A, Bannayan M, KoochekiI A, Alizadeh A, Choi Y, Park S. Applicability of AgMERRA forcing dataset forgap-filling of in-situ meteorological observation, Case Study: Mashhad Plain. J Water Soil. 2015;29(6):1749-58. [Link]
27. Yaghoubi F, Bannayan M, Asadi G-A. Performance of predicted evapotranspiration and yield of rainfed wheat in the northeast Iran using gridded AgMERRA weather data. Int J Biometeorol. 2020;64:1519-37. [Link] [DOI:10.1007/s00484-020-01931-y]
28. Tabari H, Talaee PH. Analysis of trends in temperature data in arid and semi-arid regions of Iran. Glob Planet Chang. 2011;79(1-2):1-10. [Link] [DOI:10.1016/j.gloplacha.2011.07.008]
29. Tan ML, Samat N, Chan NW, Lee AJ, Li C. Analysis of precipitation and temperature extremes over the Muda River Basin, Malaysia. Water. 2019;11(2):283. [Link] [DOI:10.3390/w11020283]
30. Tong S, Li X, Zhang J, Bao Y, Bao Y, Na L, et al. Spatial and temporal variability in extreme temperature and precipitation events in Inner Mongolia (China) during 1960-2017. Sci Total Environ. 2019;649:75-89. [Link] [DOI:10.1016/j.scitotenv.2018.08.262]
31. Worku G, Teferi E, Bantider A, Dile YT. Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia. Theor Appl Climatol. 2019;135(3-4):839-54. [Link] [DOI:10.1007/s00704-018-2412-x]
32. Zhang M, Chen Y, Shen Y, Li B. Tracking climate change in Central Asia through temperature and precipitation extremes. J Geogr Sci. 2019;29(1):3-28. [Link] [DOI:10.1007/s11442-019-1581-6]
33. DehghanSh KS, Eslamian S, Gandomkar A, Marani-Barzani M, Amoushahi-Khouzani M, Singh V, et al. Changes in temperature and precipitation with the analysis of geomorphic basin Chaos in Shiraz, Iran. Int J Constr Res Civ Eng. 2017;3(2):50-7. [Link] [DOI:10.20431/2454-8693.0302004]
34. Choubin B, Khalighi-Sigaroodi S, Malekian A, Ahmad S, Attarod P. Drought forecasting in a semi-arid watershed using climate signals: A neuro-fuzzy modeling approach. J Mt Sci. 2014;11(6):1593-605. [Link] [DOI:10.1007/s11629-014-3020-6]
35. Abbasi H, Delavar M, Bigdeli NR. Evaluation of the Effects of Climate Change on Water Resource Sustainability in Basins Using Water Footprint Scarcity Indicators. Iran Water Resour Res. 2020;15(4):259-72. [Persian] [Link]
36. Tabouzadeh S, Zarei H, Bazrafshan O. Analysis of severity, duration, frequency and zoning map of meteorological drought of Bakhtegan river basin. Irri Sci Engin. 2016;38(4):109-23. [Persian] [Link]
37. Choubin B, Malekian A, Golshan M. Application of several data-driven techniques to predict a standardized precipitation index. Atmósfera. 2016;29(2):121-8. [Link] [DOI:10.20937/ATM.2016.29.02.02]
38. Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank A, et al. Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res Atmos. 2006;111(D5). [Link] [DOI:10.1029/2005JD006290]
39. Zhang X, Yang F. RClimDex (1.0) user manual. Canada: Climate Research Branch Environment Canada; 2004. [Link]
40. Zhang X, Aguilar E, Sensoy S, Melkonyan H, Tagiyeva U, Ahmed N, et al. Trends in Middle East climate extreme indices from 1950 to 2003. J Geophys Res Atmos. 2005;110(D22). [Link] [DOI:10.1029/2005JD006181]
41. Williams MA, Balling Jr RC. Interactions of desertification and climate: Edward Arnold. London: Hodder Headline; 1996. P. 270. [Link]
42. Darand M. Assessment and detection of climate change in Iran during recent decades. Iran J Watershed Manag Scie Engin. 2015;9(30):1-14. [Persian] [Link]

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