Correlation and Spatial Analysis of IRAN winter precipitation through outgoing long wave Radiation

Abstract

Precipitation is one of the most important and variable climatic elements that changes in time and place. Critical rainfall at various time scales, especially daily, causes severe damage to human communities in densely populated urban areas and natural ecosystems and affects many arid economies. Earth outgoing long-wave radiation is studied as a significant parameter to detect clouds and estimate this type of precipitation. The current study aims to examine the relationship and analysis of outgoing long-wave radiation variables and precipitation values in Arc GIS software environment for the four cold months 17 statistical years in Iran using AIRS sensor products of Aqua satellite and GPM satellite. Correlation and regression models and confidence interval estimation were used to measure the correlation of long-wave radiation output in predicting precipitation patterns and their changes. According to the results obtained in all months studied, In the whole country, except Caspian Sea basin in January, parts of the central and eastern plateau of eastern Iran, there is a negative correlation of 10 to 92%, Which indicates that the country's atmosphere is humid and prevents the release of outgoing long-wave radiation. In the western rainfall areas of the Zagros Mountains, negative correlations above 70% and outgoing long-wave radiation is less than 260 W⋅m−2 which is due to cloudy and humid atmosphere with precipitation.In December and February, the rainfall areas north of the Caspian Sea basin range have negative correlations of above 50% and OLR less than 235 W⋅m−2 of rainfall and the reason for the lower numerical value north of the Alborz mountain range to predict is the existence of high relative humidity in the region, which is the cause of less outgoing long-wave radiation output of the earth.

Keywords

• precipitation
• outgoing longwave radiation
• airs sensor
• satellite gpm
• iran