Contribution of the Interdecadal Pacific Oscillation to twentieth-century global surface temperature trends
Contribution of the Interdecadal Pacific Oscillation to twentieth-century global surface temperature trends
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DOI：
10.1038/nclimate3107
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发表时间：
2016-11-01
影响因子：
30.7
通讯作者：
Xie, Shang-Ping
中科院分区：
文献类型：
--
作者：
Meehl, Gerald A.;Hu, Aixue;Xie, Shang-Ping
全球平均地表温度(GMST)的长期外部强迫趋势嵌入了内部产生的数十年变率的背景噪声中(1)。内部变化的一个关键模式是年代际太平洋涛动(IPO)，它导致了21世纪初GMST趋势的减少(1-3)。我们使用一种新颖的、基于物理现象的方法来量化内部产生的数十年变化的来源-IPO-对数十年GMST趋势的贡献。在这里，我们发现，在1910-1941年和1971-1995年的快速升温时期，IPO的贡献最大，分别对外部强迫趋势的中值与观察到的趋势的中值之差做出了71%和75%的贡献。20世纪90年代末IPO由正转负，造成了对GMST趋势强迫部分的模型中值估计与1995年至2013年观测趋势之间的差异的27%，另外的贡献可能是由于太平洋以外的内部变化(4)和小型火山喷发的外部强迫反应(5)。了解和量化内部产生的变异性的一个具体来源--首次公开发行--对全球最低气温趋势的贡献，对于提高十年气候预测技能是必要的。
Longer-term externally forced trends in global mean surface temperatures (GMSTs) are embedded in the background noise of internally generated multidecadal variability(1). A key mode of internal variability is the Interdecadal Pacific Oscillation (IPO), which contributed to a reduced GMST trend during the early 2000s(1-3). We use a novel, physical phenomenon-based approach to quantify the contribution from a source of internally generated multidecadal variability-the IPO-to multidecadal GMST trends. Here we show that the largest IPO contributions occurred in its positive phase during the rapidwarming periods from 1910-1941 and 1971-1995, with the IPO contributing 71% and 75%, respectively, to the difference between the median values of the externally forced trends and observed trends. The IPO transition from positive to negative in the late-1990s contributed 27% of the discrepancy between model median estimates of the forced part of the GMST trend and the observed trend from 1995 to 2013, with additional contributions that are probably due to internal variability outside of the Pacific(4) and an externally forced response from small volcanic eruptions(5). Understanding and quantifying the contribution of a specific source of internally generated variability-the IPO-to GMST trends is necessary to improve decadal climate prediction skill.