Future forecasting using the statistical downscaling model An applied study at Al- kut climate station

Abstract

Climate change and its impact on climatic phenomena and elements, as well as the imbalances in the ecosystem resulting from these changes, have become the talk of the world, which calls for studying and tracking the observed changes, and even the expectations and predictions in the events of the ecosystem on the globe. Therefore, the aim of the research is to predict the amounts of rainfall for the period (2020-2050), based on the amounts of rainfall observed at Al-Kut station for the baseline period for prediction (1985-2019) based on the radiative forcing scenarios (RCP) and climate models (CMIP5) published by the IPCC Working Group on Global Climate Change. This is done by employing the downscaling technique (statistical downscaling) SDSM, to obtain climate and environmental change forecasts. The results of the study showed that the amounts of rainfall at Al-Kut station increase significantly according to the change scenarios, and that the highest expected monthly amounts fall within the RCP4.5 scenario compared to the rest of the scenarios. In addition, the winter season recorded the highest amounts of expected rain for the period 2020-2050, compared to With a base period of 1985-2019