Understanding Diverse Model Projections of Future Extreme El Niño
Understanding Diverse Model Projections of Future Extreme El Niño
复制标题
了解未来极端厄尔尼诺现象的多种模型预测
DOI：
10.1175/jcli-d-19-0969.1
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发表时间：
2021
影响因子：
4.9
通讯作者：
B. Otto‐Bliesner
中科院分区：
文献类型：
--
作者：
S. Stevenson;A. Wittenberg;J. Fasullo;S. Coats;B. Otto‐Bliesner
耦合模式相互比较项目的大多数未来预测显示，厄尔尼诺期间赤道东太平洋降雨量更频繁地超过5毫米一天的−1降雨量阈值，以前在文献中被描述为“极端厄尔尼诺事件”的增加；然而，这些超出频率在不同模型之间差别很大，在一些预测中实际上是减少的。在这里，我们将单模式大型集合模拟与耦合模式比较项目(CMIP5)的第五阶段相结合，以诊断这些差异的机制。在CMIP类模式中，降水对局地海温异常的敏感性持续增加，倾向于放大极端厄尔尼诺现象的发生；然而，与ENSO有关的海温变率大小的变化可以极大地影响结果，这表明理解海温变率的变化仍然是当务之急。未来厄尔尼诺降水在以下模式中加剧最大：1)赤道中部太平洋历史上较大的冷SST偏差，这抑制了未来局部对流云阴影的增加，使当地变暖；2)远东赤道太平洋历史上较小的暖SST偏差，这加强了未来层云的减少，使局部变暖。这些相互竞争的机制使确定CMIP5模型是否低估或高估了气候变化对厄尔尼诺降水及其全球影响的未来影响的努力复杂化。然而，未来预测和历史偏差之间的关系表明，可以使用可观测的度量作为对未来极端厄尔尼诺的“紧急约束”，并给出了利用SSTA方差、降水对SST的敏感性和区域SST趋势的概念验证。
The majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day−1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. These competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.