Dr. Ali Bayat, Mr. Saeed Mashhadizadeh Maleki,
Volume 19, Issue 53 (6-2019)
Abstract
Precipitable Water Vapor (PWV) is one of the most important quantities in meteorology and climate studies. PWV in Earth's atmosphere can be measured by Sun-photometer, the Atmospheric Infrared Sounder (AIRS), and radiosonde from surface, atmosphere and space-based systems, respectively. In this paper, we use PWV measured by Sun-photometer located in Institute for Advanced Studies in Basic Sciences (IASBS), AIRS and 29 Iranian synoptic stations data include temperature, dew-point temperature, pressure and relative humidity. For validation of AIRS data, the correlation coefficient between AIRS and Sun-photometer data calculated. The correlation is 90%. Average of PWV measured with sun-photometer and AIRS are 9.8 and 10.8 mm, respectively. Pearson's correlation coefficients between PWV of AIRS data set and temperature, dew-point temperature, pressure and relative humidity for synoptic stations are calculated. Correlation between PWV and temperature, dew-point temperature, pressure, and humidity are 73%, 74%, -40% and -30%, respectively. PWV and temperature correlation coefficient map shows a positive trend between latitude and correlation coefficient. Rising a degree in latitude lead to increasing 2.8 percent in the correlation coefficient.
Dr Gholamabbas Fallah Ghalhari, Fahimeh Shakeri,
Volume 22, Issue 67 (12-2022)
Abstract
In this Research, the maximum temperature of selected stations in Khuzestan province and the numerical values of 8 extreme climatic indicators belonging to the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) were used in the statistical period of 1987-2017. To analyze the trend of extreme climatic indices, the Man-Kendall test was used and to estimate the slope of the trend line, the Sen’s estimator was used. In this study, given the importance of global warming that severely affected all aspects of life, the authors explore the relationship between climatic factors and maximum temperature in Khuzestan province until to rely on it, and ones can predict and forecast air temperature at this region. For this purpose, the temperature of selected stations in Khuzestan province and numerical values of 8 climate indicators in the period 1987-2014 have been used. To understand the relationship between climate indicators and maximum temperature at 1 to 12 months of delays, Pearson’s correlation coefficient was used. The results showed that most of the extreme climatic indicators in the study period had a significant trend. The TX10 and TN10 indices have had negative trend in most stations and the TX90, TN90, TXx, TXn, TNx and TNn indices have had positive trend. According to the results of correlation coefficients can be concluded that all studied signals have a significant effect on the province's maximum temperature. The correlation between maximum temperature and indices PNA, TSA, WHWP, WP and NAO, was more than the other climate indicators. Results also showed that the entire indices except NAO have significant positive correlation with maximum temperature of the province. PNA index with a delay of 10 months has the highest positive correlation with maximum temperature of study area.
