Climate sensitivity estimated from ensemble simulations of glacial climate
Climate sensitivity estimated from ensemble simulations of glacial climate
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根据冰川气候的集合模拟估算气候敏感性
DOI：
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发表时间：
2006
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通讯作者：
S. Rahmstorf
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作者：
Thomas Schneider von Deimling;H. Held;A. Ganopolski;S. Rahmstorf
大气中温室气体（GHG）浓度持续上升，因此估算气候系统对温室气体浓度变化的敏感性至关重要。气候敏感性的不确定性是未来气候变化预估中不确定性的主要来源。在这里，我们提出了一种新的方法，通过将末次极大期（LGM）的集合模拟与古数据相结合来限制这一关键的不确定性。为此，我们使用了一个中等复杂程度的气候模型，对(1)工业化前边界条件，(2)二氧化碳浓度加倍，以及(3)一整套冰川强迫（包括沙尘和植被变化）进行了大量的平衡运行。利用低纬度和高纬度地区LGM的代理数据，我们限制了一组现实的模式版本，从而限制了气候敏感性。我们表明，不考虑模式参数和反馈强度的不确定性，在我们的模式中，由于CO2加倍而模拟的变暖与LGM获得的冷却之间存在密切联系。我们的结果与最近的研究一致，即当前气候的年平均数据约束证明不能排除气候敏感性高于广泛假设的1.5-4.5°C的敏感性范围（Houghton等人，2001年）。基于我们推断的过去和未来温度演变之间的密切关系，我们的研究表明，古气候数据有助于减少未来气候预测的不确定性。我们在古数据约束下推断的气候敏感性不确定性范围为1.2-4.3°C，因此与IPCC的估计几乎相同。如果再考虑从其他模式推断出的潜在结构不确定性，上限将增加约1°C。
The concentration of greenhouse gases (GHGs) in the atmosphere continues to rise, hence estimating the climate system’s sensitivity to changes in GHG concentration is of vital importance. Uncertainty in climate sensitivity is a main source of uncertainty in projections of future climate change. Here we present a new approach for constraining this key uncertainty by combining ensemble simulations of the last glacial maximum (LGM) with paleo-data. For this purpose we used a climate model of intermediate complexity to perform a large set of equilibrium runs for (1) pre-industrial boundary conditions, (2) doubled CO2 concentrations, and (3) a complete set of glacial forcings (including dust and vegetation changes). Using proxy-data from the LGM at low and high latitudes we constrain the set of realistic model versions and thus climate sensitivity. We show that irrespective of uncertainties in model parameters and feedback strengths, in our model a close link exists between the simulated warming due to a doubling of CO2, and the cooling obtained for the LGM. Our results agree with recent studies that annual mean data-constraints from present day climate prove to not rule out climate sensitivities above the widely assumed sensitivity range of 1.5–4.5°C (Houghton et al. 2001). Based on our inferred close relationship between past and future temperature evolution, our study suggests that paleo-climatic data can help to reduce uncertainty in future climate projections. Our inferred uncertainty range for climate sensitivity, constrained by paleo-data, is 1.2–4.3°C and thus almost identical to the IPCC estimate. When additionally accounting for potential structural uncertainties inferred from other models the upper limit increases by about 1°C.