Biased Estimates of Changes in Climate Extremes From Prescribed SST Simulations
Biased Estimates of Changes in Climate Extremes From Prescribed SST Simulations
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DOI：
10.1029/2018gl079176
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发表时间：
2018-08
影响因子：
5.2
通讯作者：
E. Fischer;U. Beyerle;C. Schleussner;A. King;R. Knutti
中科院分区：
文献类型：
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作者：
E. Fischer;U. Beyerle;C. Schleussner;A. King;R. Knutti
大型气候模型组合被广泛用于量化极端气候的变化。在这里，我们证明，如果使用规定的海洋表面温度(SSTs)而不是使用完全耦合的气候模式来量化，则基于模型的对全球变暖1.5℃极端温度概率的估计在区域上是不同的。基于两个实验装置中使用的相同气候模式，我们证明，特别是在热带和澳大利亚，使用规定的SST而不是完全耦合的模式配置，对年极端温度变化的估计可以高出5到10倍以上。这两个实验设计暗示了对框架投影的不同视角。如果以规定的观测到的SST为条件的实验被解释为无条件的真实世界预测，它们就会在极端情况下投射出变化，这些变化具有系统性的高度偏见和过度自信。我们的结果说明了在解释极值投影时仔细考虑实验设计的重要性。
Large climate model ensembles are widely used to quantify changes in climate extremes. Here we demonstrate that model‐based estimates of changes in the probability of temperature extremes at 1.5 °C global warming regionally differ if quantified using prescribed sea surface temperatures (SSTs) instead of using a fully coupled climate model. Based on the identical climate model used in two experimental setups, we demonstrate that particularly over the tropics and Australia estimates of the changes in the odds of annual temperature extremes can be up to more than a factor of 5 to 10 larger using prescribed SSTs rather than a fully coupled model configuration. The two experimental designs imply a different perspective on framing projections. If experiments conditional on prescribed observed SSTs are interpreted as unconditional real‐world projections, they project changes in extremes that are systematically biased high and overconfident. Our results illustrate the importance of carefully considering experimental design when interpreting projections of extremes.