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Saeed Sharafi

Saeed Sharafi

Academic rank: Associate Professor
ORCID: https://orcid.org/0000-0003-2644-5924
Education: PhD.
ScopusId: 26640694100
HIndex:
Faculty: Agriculture and Environment
Address: Arak University
Phone:

Research

Title
Using linear regression method for predicting of UNESCO aridity index of Iran
Type
Presentation
Keywords
Climate Changes, Drought, Meteorology, Zonation
Year
2020
Researchers Saeed Sharafi ، mohammad javad Nahvinia ، Mehdi Mohammadi Ghaleni ، Farzaneh Zandieh ، Atefeh Rahmani

Abstract

The purpose of this paper is to discuss how prediction of UNESCO aridity index could be utilized to advance our understanding of climate change impact and of the potential for adaptation to climate change in the future of Iran. For this purpose, using linear regression method, we determined agricultural climatic indicators at 41 synoptic stations of the country under future climatic conditions under current conditions (2017) for 2025, 2050, 2075 and 2100. In linear regression method, the variables of precipitation, temperature (average, maximum and minimum), wind speed, relative humidity and solar radiation were evaluated. After investigating the slope trend of the mentioned variables for each station and then, classified using UNESCO aridity index. According to UNESCO aridity index, 85.36 percent of the stations were in the arid area in 2017 and 87.8 percent in the arid area since 2025 to 2100. According to these results, under future climatic conditions of the country, in terms of climatic indicators, the similarity between the stations will increase and the climatic diversity of the country will reduce compared to the current conditions.