Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate
Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate
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DOI：
10.1038/nature08769
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发表时间：
2010-01-28
期刊：
影响因子：
64.8
通讯作者：
Joos, Fortunat
中科院分区：
文献类型：
--
作者：
Frank, David C.;Esper, Jan;Joos, Fortunat
控制大气、海洋和陆地生物圈的碳通量和碳储存的过程对温度敏感(1-4)，并可能提供正反馈，导致放大的人为变暖(3)。由于这种反馈，在从年际到地球轨道变化20-100 KYR周期(1，5-7)的时间尺度上，气候系统变暖导致向大气中净释放二氧化碳；这反过来又放大了变暖。但是，全球碳循环(称为伽马)的气候敏感性以及其正反馈强度的大小仍在争论中，这给全球变暖预测带来了很大的不确定性(8，9)。在这里，我们将伽马的中位数量化为每摄氏度的每摄氏度下午7.7对二氧化碳，可能的范围是每摄氏度下午1.7-21.4对二氧化碳。敏感性实验排除了工业化前土地利用变化对这些估计的显著影响。我们的结果基于概率方法与基于代理的温度重建和来自三个冰芯的工业化前二氧化碳数据的集合的耦合，为伽马在与政策相关的数十年到百年时间尺度上提供了强有力的约束。通过使用200,000名成员的集合，不仅改进了伽马的量化，而且还可以分配可能性，从而为未来的模型模拟提供了基准。尽管目前不确定因素不允许排除从十个碳-气候耦合模型中的任何一个计算出的伽马，但我们发现伽马落在范围最低的四分之一的可能性大约是最高四分之一的两倍。我们的结果比最近工业化前的经验估计值低得不相容(P<；0.05)，后者类似于每摄氏度下午40分对二氧化碳的影响(参考文献6，7)，相应地表明，持续的全球变暖的潜在放大作用类似于80%。
The processes controlling the carbon flux and carbon storage of the atmosphere, ocean and terrestrial biosphere are temperature sensitive(1-4) and are likely to provide a positive feedback leading to amplified anthropogenic warming(3). Owing to this feedback, at time-scales ranging from interannual to the 20-100-kyr cycles of Earth's orbital variations(1,5-7), warming of the climate system causes a net release of CO2 into the atmosphere; this in turn amplifies warming. But the magnitude of the climate sensitivity of the global carbon cycle (termed gamma), and thus of its positive feedback strength, is under debate, giving rise to large uncertainties in global warming projections(8,9). Here we quantify the median gamma as 7.7 p. p. m. v. CO2 per degrees C warming, with a likely range of 1.7-21.4 p. p. m. v. CO2 per degrees C. Sensitivity experiments exclude significant influence of pre-industrial land-use change on these estimates. Our results, based on the coupling of a probabilistic approach with an ensemble of proxy-based temperature reconstructions and pre-industrial CO2 data from three ice cores, provide robust constraints for gamma on the policy-relevant multi-decadal to centennial timescales. By using an ensemble of >200,000 members, quantification of gamma is not only improved, but also likelihoods can be assigned, thereby providing a benchmark for future model simulations. Although uncertainties do not at present allow exclusion of gamma calculated from any of ten coupled carbon-climate models, we find that gamma is about twice as likely to fall in the lowermost than in the uppermost quartile of their range. Our results are incompatibly lower (P < 0.05) than recent pre-industrial empirical estimates of similar to 40 p. p. m. v. CO2 per degrees C (refs 6, 7), and correspondingly suggest similar to 80% less potential amplification of ongoing global warming.