University of Engineering and Technology, Taxila, Pakistan.
COMSATS University Islamabad, Wah Campus, Wah Cantt, Pakistan.
Environ Monit Assess. 2023 Jun 7;195(7):810. doi: 10.1007/s10661-023-11419-y.
This study investigates the projections of precipitation and temperature at the local scale in the Upper Indus Basin (UIB) in Pakistan using six Regional Climate Models (RCMs) from CORDEX under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). For twenty-four stations spread across the study area, the Long Ashton Research Station Weather Generator, version six (LARS-WG6), was used to downscale the daily data from the six different RCMs for maximum temperature (T), minimum temperature (T), and precipitation (pr) at a spatial resolution of 0.44°. Investigations were made to predict changes in mean annual values of T, T, and precipitation during two future periods, i.e., the mid-century (2041-2070) and end-century (2071-2100). The model results from statistical and graphical comparison validated that the LARS-WG6 can simulate the temperature and the precipitation in the UIB. Each of the six RCMs and their ensemble revealed a continuously increased temperature projection in the basin; nevertheless, there is variation in projected magnitude across RCMs and between RCPs. The rise in average T and T was more significant under RCP 8.5 than RCP 4.5, possibly due to unmitigated greenhouse gas emissions (GHGs). The precipitation projections follow the non-uniform trend, i.e., not all RCMs agree on whether the precipitation will increase or decrease in the basin, and no orderly variations were detected during any future periods under any RCP. However, an overall increase in precipitation is projected by the ensemble of RCMs.
本研究使用 CORDEX 下的六个区域气候模式(RCM)在巴基斯坦上印度河流域(UIB)进行了当地尺度的降水和温度预测。对于分布在研究区域的 24 个站,使用 Long Ashton Research Station Weather Generator,版本六(LARS-WG6)将六个不同 RCM 的日数据下推到 0.44°的空间分辨率,以预测最大温度(T)、最小温度(T)和降水(pr)的年平均值变化。调查了在两个未来时期(即本世纪中叶(2041-2070 年)和本世纪末(2071-2100 年))的平均年值变化。统计和图形比较的模型结果验证了 LARS-WG6 可以模拟 UIB 的温度和降水。六个 RCM 中的每一个及其集合都显示出流域内温度预测的持续上升;然而,RCM 之间和 RCP 之间的预测幅度存在差异。在 RCP 8.5 下,平均 T 和 T 的上升幅度比 RCP 4.5 更为显著,这可能是由于温室气体(GHG)未得到缓解。降水预测呈现出非均匀趋势,即并非所有 RCM 都同意流域内降水是增加还是减少,在任何 RCP 下的任何未来时期都没有检测到有序变化。然而,RCM 集合预测降水总体上会增加。