Predicting future uncertainty constraints on global warming projections.
Predicting future uncertainty constraints on global warming projections.
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DOI：
10.1038/srep18903
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发表时间：
2016-01-11
影响因子：
4.6
通讯作者：
Allen MR
中科院分区：
文献类型：
--
作者：
Shiogama H;Stone D;Emori S;Takahashi K;Mori S;Maeda A;Ishizaki Y;Allen MR
对未来全球平均温度变化（ΔT）的预测与内在的不确定性有关。许多气候政策讨论都以ΔTs不确定性的“现有知识”为指导，忽视了未来不确定性可能的减少，因为缺乏预测这些减少的机制。通过使用耦合模式相互比较项目第5阶段集合的全球气候模式模拟作为伪过去和未来观测，我们估计了当维持当前地面气温观测网络时，ΔT的不确定性下降的速度和方式。至少在代表性浓度路径（RCP）下的伪观测世界中，到2029年，我们可以大幅减少2040年代的ΔTs不确定性的50%以上，到2049年，到2090年代的ΔTs不确定性的60%以上。在RCP最高强迫情景下，我们可以提前20（30）年预测超过2 °C（3 °C）变暖阈值的真实时间，误差小于10年。这些结果表明，潜在的顺序决策战略，以利用未来的进展，在人为气候变化的理解。
Projections of global mean temperature changes (ΔT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by “current knowledge” of the ΔTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of ΔT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the ΔTs uncertainty in the 2040 s by 2029, and more than 60% of the ΔTs uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2 °C (3 °C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.