Modelling Afghanistan’s Average Monthly Temperature from 1901 to 2015

Abstract

The purpose of this investigation is to examine the variation of temperature in Afghanistan over the past 114 years. The historical dataset of the monthly average temperature from 1901 to 2015 were analyzed. The relationship between temperature and time during the four time intervals, i.e. (1901 -1930), (1931-1960), (1961-1990) and (1991-2015) is presented using a new analytical model based on the last –square method of estimation. We accurately fit a polynomial regression trend of degree 4 to the time series to describe the temperature variation. The results show the average difference of temperature between 2015 and 1901 increases about 1.03 °C. The average monthly difference between the maximum and minimum temperature was approximately 3.66 °C and the average monthly difference between the maximum and minimum temperature during these periods is approximately about 1.31 °C. This approach of modeling temperature using regression form significantly simplifies the data analysis. The information from data, namely the variation of the temperature, maybe be obtained from the extracted parameters such as slope, y-intercept, and the coefficients of polynomial function that are a function of time. More importantly, the parameters that describe the time variation temperature trends over 115 years obtained with a high R-squared do not vary significantly. This is in agreement with the Earth’s average temperature that has climbed to more 1 °C  The evaluation of Afghanistan’s past climate data can be extremely important for understanding how climate has varied along with their possible predictable outcomes that come with increasing drought risk due to gradual increase of temperature. These results may be useful for environmental policy makers in comprehension of climate change in Afghanistan. The results can help develop appropriate strategies for the environment, and regulate resource use or pollution reduction to promote human welfare and/or nature protection.