May common model biases reduce CMIP5's ability to simulate the recent Pacific La Nina-like cooling?
May common model biases reduce CMIP5's ability to simulate the recent Pacific La Nina-like cooling?
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DOI：
10.1007/s00382-017-3688-8
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发表时间：
2018-02-01
期刊：
影响因子：
4.6
通讯作者：
Dommenget, Dietmar
中科院分区：
文献类型：
--
作者：
Luo, Jing-Jia;Wang, Gang;Dommenget, Dietmar
近三十年来，东赤道太平洋的海表温度（SST）有所下降，这有助于减缓全球变暖的速度。然而，大多数具有历史辐射强迫的CMIP5模式模拟并没有重现这种类似太平洋拉尼娜的冷却。基于“完美”模式的假设，以往的研究表明，模拟内部气候变化和/或外部辐射强迫的误差可能导致多模式模拟与观测之间的差异。但确切原因尚不清楚。最近的研究表明，在过去几十年里观测到的另外两个海洋盆地的海温变暖，以及太平洋响应辐射强迫增加的恒温机制，也可能在驱动这种类似拉尼娜的变冷中发挥重要作用。在此，我们研究了另一种假设，即当前最先进的气候模型的共同偏差可能会降低模型的能力，并可能导致这种多模式模拟-观测差异。我们的研究结果表明，低估了三个热带海洋的盆地间变暖对比，高估了赤道太平洋的地表净热通量和低估了当地海温云负反馈，可能有利于模式中出现类似厄尔尼诺的变暖偏差。三种常见模式偏差的影响并不相互抵消，它们共同解释了观测值与单个模式总体平均模拟太平洋海温趋势之间差异的总方差的50%左右。减少共同模式偏差的进一步努力可以帮助改进对外部强迫气候趋势和多年代际气候波动的模拟。
Over the recent three decades sea surface temperate (SST) in the eastern equatorial Pacific has decreased, which helps reduce the rate of global warming. However, most CMIP5 model simulations with historical radiative forcing do not reproduce this Pacific La Nia-like cooling. Based on the assumption of "perfect" models, previous studies have suggested that errors in simulated internal climate variations and/or external radiative forcing may cause the discrepancy between the multi-model simulations and the observation. But the exact causes remain unclear. Recent studies have suggested that observed SST warming in the other two ocean basins in past decades and the thermostat mechanism in the Pacific in response to increased radiative forcing may also play an important role in driving this La Nia-like cooling. Here, we investigate an alternative hypothesis that common biases of current state-of-the-art climate models may deteriorate the models' ability and can also contribute to this multi-model simulations-observation discrepancy. Our results suggest that underestimated inter-basin warming contrast across the three tropical oceans, overestimated surface net heat flux and underestimated local SST-cloud negative feedback in the equatorial Pacific may favor an El Nio-like warming bias in the models. Effects of the three common model biases do not cancel one another and jointly explain similar to 50% of the total variance of the discrepancies between the observation and individual models' ensemble mean simulations of the Pacific SST trend. Further efforts on reducing common model biases could help improve simulations of the externally forced climate trends and the multi-decadal climate fluctuations.