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Hindi Research Article
A Study of Impacts of Temperature Components on Precipitation in Iran Using SEM-PLS-GIS
| Javari M* | |
| College of Social Science, PayameNoor University, Iran | |
| Corresponding Author : | Javari M Assistant Prof. of Climatology College of Social Science PayameNoor University, Iran Tel: +98 (21) 2244 2042 E-mail: majid_javari@yahoo.com |
| Received April 25, 2015; Accepted May 18, 2015; Published May 28, 2015 | |
| Citation: Javari M (2015) A Study of Impacts of Temperature Components on Precipitation in Iran Using SEM-PLS-GIS. J Earth Sci Climat Change S3:004. doi: 10.4172/2157-7617.S3-004 | |
| Copyright: © 2015 Javari M. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
Abstract
Structural equation modeling (SEM) is a quantitative technique for evaluating the causal relations between and among a number of variables using a combination of statistical methods and assumptions. Although there have been recent developments in expanding SEM to include climatic changes, most applications have been restricted to the simulation of causal processes; this is especially true for the modelling of environmental changes. However, when SEM is applied as an exploratory technique in climate studies, the proposed model can illustrate and examine the relationships among several climatic elements in the environment. To investigate the relationship between temperature and precipitation, a combination of SEM, partial least squares (PLS) and GIS methods were employed in this study. A measurement model, a structural model and a spatial model for examining the relationships between temperature and precipitation were proposed. A SEM-PLS-GIS model consisting of three measurement sub-models was created on the basis of the concentration values of 14 climatic elements; the data were the monthly and seasonal values for the period between 1975 and 2012, and were obtained from 140 stations. The results of the new SEM-PLS-GIS model showed that seven temperature factors affected, directly or indirectly, the precipitation with minimum temperatures were being the most effective of all. It can be concluded that employing SEM-PLS-GIS model for the purpose of describing causal patterns of climate variations especially the variations of precipitation can be of great value.
