Modeling and spatial analysis of future needs for cooling in Iran

Document Type : Full length article

Authors

1 Professor of climatology, Yazd University, Yazd, Iran

2 PhD candidate in climate hazards, Yazd University, Yazd, Iran

3 PhD candidate in urban climatology, Shahid Beheshti University, Faculty of Earth Science, Iran

Abstract

Introduction
Climate changes and global warming as important issues in environmental sciences have attracted the attention of many researchers.  In the study of the climate and atmospheric changes, it is essential to understand the temporal conditions of climate parameters, particularly degree day.  The temperature as one of the most critical climate parameter is effective in the global warming. Thus, a variety of indices and methods have been presented for the analysis of this parameter by many researchers. Degree day is one of the important indices. The studies about the climate change and energy requirements are necessary in Iran, in that, the increasing needs of the society due to the energy crisis of the world, fossil fuel resources, and increased temperature lead to a new state of energy in the near future of this country. In the present research, we have attempted to detect cooling degree days of the country using spatial statistics. 
 
Materials and methods
To examine the impacts of global warming on Cooling Degree Days (CDD), we have used the average of the daily temperature data derived from EH5OM database. The EH5OM is an Atmospheric Ocean Global Circulation Model (AOGCM) of the fifth general circulation models of atmosphere with spectral dynamic core. The model was presented by Max Plank physics institute. In this research, we have used the data in a period from 2015-2050 under scenario A1B. The reason we have selected this scenario is the ability to have equal use of fossil and non-fossil resources of the future. For a spatio-temporal exploration of the degree day, the balance of cooling need of Iran has been considered at 23.9° C threshold. The threshold was applied by the institute of US standard of science. We have employed three methods in ArcGIS10.3 for these analyses. We have also used Global Moran I to evaluate the spatial autocorrelation the cooling needs in the future decades, Anselin Local Morans I to draw the clusters and non-clusters, and Getis Ord Gi statistic to analyze the spatial patterns of the cooling needs. 
 
Results and discussion
The cooling degree day needs has a positive autocorrelation in the future (α=0.01). This has confirmed dependency of the cooling need for Iran. With the beginning of summer, the Global Moran I is reached 0.9. The changing patterns of the index in different months of the year have given distribution for all the country. In winter times the cooling need is reduced over the country. The parameter is at the peak in April, May, and June. The results have showed the spatial and temporal patterns of the needs for cooling in different regions of Iran. In the winter times, the need for cooling the buildings shows a proportional reduction in all the country. The cold climatic conditions in January and February reduced the need for cooling the house environment. The cooling needs in different areas of Lut, Zabol, and Turkmen regions have indicated the effects of elevation on the temperature. The southern coasts of Chabahar and Hormozgan also observed the temperature higher than average. In Marth and September the country can be categorized into three groups; the coastal plains, mountain areas, and internal arid plains. These regions have different patterns in different months. The southern coasts of Iran and coastal plains of north Iran will have the highest needs for cooling in the future decades. The mountainous areas have the lowest cooling needs in the country. In the mountain areas of Iran the need gradient is reduced towards the central low lands.
 
Conclusion
The results of spatial autocorrelation using local Moran model for Iran have indicated that the cooling need for the future decades follow a spatial pattern. The LISA has also indicated that the most needs for cooling is in the period from April to September. Thus, the southern areas of Iran and the mountainous areas have the highest and the lowest needs for cooling. The three regions of coastal plains, mountainous areas, and central arid plain will have different spatial patterns of cooling needs in different decades in the period of this study. The results of the study on the difference of cooling needs in two categories of flat and relief terrain areas are consistent with the results of Masoudian et al. (2011). In the future, the patterns may have changes in different latitudes. The highest need for cooling will be occurred in Chabahar and Hormozgan coasts.

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Main Subjects

References

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Physical Geography Research
Volume 49, Issue 2
July 2017
Pages 283-299

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History

  • Receive Date: 26 March 2016
  • Revise Date: 20 November 2016
  • Accept Date: 23 November 2016

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