Temperature variability has substantial socioeconomic impacts through its association with the frequency and severity of heat extremes. Under anthropogenic influence, climate models project seasonally-dependent amplifications of near-surface temperature variability over some sectors of the Southern Hemisphere, and robust positive trends have already been observed in recent decades. Here we show that the amplification of subweekly temperature variability simulated by the multi-model ensemble mean of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) over South Africa, Australia, and South America is often substantially smaller than in reanalyses in recent decades, reaching a similar amplification only at the end of the 21st century due to a weaker amplification of subweekly variance generation efficiency. Analysis of a large model ensemble indicates that this discrepancy may be due to internal climatic variability suggesting that the recent rapid amplification seen in reanalyses may slow down or even temporarily reverse in the near future.

温度变化通过与极端高温的频率和严重程度相关联，具有重大的社会经济影响。在人为影响下，气候模型预测了南半球某些地区近地表温度变化的季节性依赖性放大，近几十年来已经观察到强劲的积极趋势。在这里，我们表明，耦合模式比较计划（CMIP6）第六阶段的多模式集合均值模拟的南非、澳大利亚和南美洲的次周温度变率的放大通常比近几十年来的再分析要小得多，只有在 21 世纪末才达到类似的放大，因为次周方差生成效率的放大较弱。对大型模型集合的分析表明，这种差异可能是由于内部气候变率造成的，这表明最近在再分析中看到的快速放大可能会在不久的将来减慢甚至暂时逆转。