Future Changes in Maximum Temperature Events Using the Statistical Downscaling Model (SDSM) in Kufra Area–Libya (Journal of Basic and Applied Sciences, 2021)
All the IPCC's five reports between 1990 and 2013 concluded that we cannot expect stable climate in the future and we should prepare scenarios and strategies for the survival of humankind under the conditions of forthcoming global change. The study describes the application of statistical downscaling method (SDSM) to downscale maximum temperature data. In order to explore the SDSM method, the Kufra station in Libya has been selected as a study site to test the methodology for maximum temperature. The study included calibration and validate with large-scale atmospheric variables encompassing NCEP reanalysis data, the future estimation due to a climate scenario, which are HadCM3 A2 and HadCM3 B2. Results of downscaling show that during the calibration and validation stage, the SDSM model can be well acceptable regard its performance in the downscaling of daily maximum temperature. Trend analysis in the study area showed an increase in average annual and monthly maximum temperature, compared to the baseline period for both HadCM3A2a and HadCM3B2a scenarios in both the dry and wet seasons. The average annual maximum temperature in Kufra area is predicted to increase by 1.3°C and 1.4°C by the 2020s (2011-2040) under the A2 and B2 scenarios respectively. By the 2050s (2041-2070) the increase is predicted to be 1.4°C, 1.7°C under the both A2 and B2 scenarios. By the 2080s, (2071-2099) the average annual maximum temperature is predicted to increase by 1.9 °C and 1.4°C under A2 and B2.However, there is likely to be a significant warming in local surface temperature, which is enough for a significant change on the energy balance and is likely to affect water availability.
Keywords: Climate Change; Statistical Downscaling SDSM; Emission Scenarios; Kufra Area