Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the 90% percentile for 2036 - 2065 relative to 1976-2005, for the DJF season, under the RCP 4.5 pathway

Root Mean Square Difference for seasonal (DJF) mean near-surface (2m) temperature (°C) change from the 90% percentile projected for 2036-2065, relative to present (1976 - 2005), under the RCP 4.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily temperature averages, which are used to generate projections of seasonal change. The projections are generated using the medium to low (RCP4.5) pathway which associates CO2 concentrations of approximately 560ppm by the year 2100. The associated RMSD it calculated and shows the uncertainty range of the projected model simulated residual values, and gives a relative perspective of spatial areas associated with higher and lower projection uncertainties.本数据集针对南非地区RCP4.5排放情景下，以1976-2005年为基准期的2036-2065年季节（DJF，即12月-1月-2月）平均近地表（2米）气温（℃）变化的90%分位数预测值，计算其均方根差（Root Mean Square Difference）。为生成该可视化图像，研究采用罗斯比中心区域模式（RCA4）对9个粗分辨率大气环流模式（General Circulation Models, GCM）进行降尺度处理，将其空间分辨率提升至0.44°×0.44°，并以该模式作为侧边界强迫场。该模式模拟的日平均气温数据被用于生成季节尺度气候变化的预测结果。本预测基于中低排放情景（RCP4.5）构建，该情景预计到2100年大气二氧化碳浓度将达到约560ppm。此处计算得到的均方根差（RMSD）可反映模式模拟预测残差的不确定性范围，进而直观呈现不同空间区域的预测不确定性高低分布特征。