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气候敏感性估计来自于最后一个冰川最大时期的温度重建
Andreas Schmittner1, Nathan M Urban, Jeremy D Shakun
1College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331-5503, USA. aschmitt@coas.oregonstate.edu
概括
这项研究修订了平衡气候灵敏度,发现了2.3K的较低中位数. 这表明碳排放迫在眉的极端气候变化的可能性有所降低.
科学领域:
- 气候科学 气候科学
- 古气候学 古气候学
- 气候建模气候模型
背景情况:
- 对二氧化碳翻倍的平衡气候敏感性 (ECS) 的不确定性阻碍了气候变化影响评估.
- 以前的ECS估计表明中位数为3K,66%的概率范围为2-4.5K,包括高影响场景的小机会.
- 高的ECS值意味着严重,不可避免的气候变化的风险.
研究的目的:
- 通过将古气候数据与气候模型相结合,完善均衡气候灵敏度 (ECS) 的估计.
- 减少围绕未来人为碳排放的潜在影响的不确定性.
- 重新评估极端气候变化事件的可能性.
主要方法:
- 从最后的冰川最大期开始,海面和陆地表面温度的综合重建.
- 利用气候模型模拟,结合古气候数据.
- 分析温度数据以限制ECS估计.
主要成果:
- 估计较低的ECS中位数为2.3K.
- 确定了ECS为1.7至2.6K的66%的减少概率范围.
- 证明了古气候约束,当通过模型应用于未来的预测时,表明快速,极端气候变化的可能性较低.
结论:
- 与之前的评估相比,精确的ECS估计表明即将发生的严重气候变化的概率下降.
- 古气候数据集成为气候敏感性提供了更受限制的观点.
- 未来的气候变化影响可能比以往更高的ECS概率所表明的要少极端.
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