Application of remote sensing products to identification of critical regions resulted from monthly extreme temperatures

Subject Areas : Climatology

Mohammad Rezaei ¹ ( دانشجوی دکترا اقلیم شناسی ماهواره ای دانشگاه تربیت مدرس،تهران،ایران )
Elham Ghasemifar ² ( دانشجوی دکترا اقلیم شناسی ماهواره ای دانشگاه تربیت مدرس ،تهران،ایران )
Yousef Ghavidel Rahimi ³ ( استادیار گروه جغرافیا دانشکده علوم انسانی دانشگاه تربیت مدرس، تهران، ایران )

Received: 2015-07-15 Accepted : 2015-11-09 Published : 2016-03-17

Keywords: Iran, extreme temperatures, regionalization of temperature, remote sensing products, extreme events,

Abstract :

In the past, during extreme temperature events in Iran, precise determination of very hot and cold regions has been difficult due to absence and not a proper distribution of synoptic stations. But, nowadays the satellite data with appropriate spatial resolution provides an opportunity for improving the previous research. The main purpose of this paper is determination of these regions in above mentioned conditions. Standardized Monthly mean temperature of 81 synoptic stations in Iran showed that during 1986 to 2014, in January 2008 and July 2010 most stations have been an extreme temperatures anomaly. For this, we used land surface temperatures from MODIS data product (level2) onboared on Terra satellite. To classification of regions, we used cluster analysis. When we cutting the dendrogram in the first step, separated 13 regions for July 2010 and 6 region for January 2008. In July 2010, Lut desert determined as the hottest area and in January 2008 northwest of Iran was the coldest and costal sea in south east was the pleasant in term of temperatures. Therefore, due to the lack synoptic station in Lut desert and also not distinct of this region as a separate region in previous study, capability of remote sensing product was obvious.Also result showed that unlike of synoptic station data, the MODIS remote sensing product very well indicate role of mountain in variability of temperature. However, by existing of satellite data, temperature map must have ability to showing the role of roughness.

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