Modeling Trends in Rainfall Rates at Shahat Meteorological Station (1961 - 2050) Using Statistical Techniques

Abstract

 This research paper aims to identify the Statistical Downscaling Model (SDSM) technique and the methods used to predict future climate. It relies on rainfall data from the Shahat meteorological station for the period from 1961 to 2020, and predict its increase or decrease in the future (2021-2050) using SDSM based on climate change scenarios (A2a) and (B2a), which are scenarios adopted by the IPCC climate change team in the SRES report in 2000 to make climate and environmental forecasts based on greenhouse gases. In addition, it will rely on statistical analysis methods used in climate studies by SPSS to detect variations in the means of annual and seasonal rainfall rates for the three periods: (1961-1990), (1991-2020), (2021-2050), using one-way ANOVA analysis. The results showed trends of decreasing annual rainfall rates compared to the first period, with seasonal variations and statistical significance level below 0.05. The cumulative difference curves also confirmed a trend of decreasing rainfall rates at the study station during the three periods, except for the autumn period from 2023-2039 and the summer season, which experienced higher than average rainfall compared to the first two periods.