Constraining Clouds and Convective Parameterizations in a Climate Model Using Paleoclimate Data
Constraining Clouds and Convective Parameterizations in a Climate Model Using Paleoclimate Data
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DOI：
10.1029/2021ms002893
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发表时间：
2022-07
影响因子：
6.8
通讯作者：
R. Ramos;A. Legrande;M. Griffiths;G. Elsaesser;D. Litchmore;J. Tierney;F. Pausata;J. Nusbaumer
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文献类型：
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作者：
R. Ramos;A. Legrande;M. Griffiths;G. Elsaesser;D. Litchmore;J. Tierney;F. Pausata;J. Nusbaumer
云和对流参数化强烈影响平衡气候敏感性的不确定性。我们提供了一个概念验证研究，通过使用多个卫星气候学评估当前运行中的模型偏差，并通过比较已知对参数化方案敏感的降水模拟δ18O（δ18Op），全球洞穴沉积物δ 18 O记录数据库涵盖末次冰期最大值（LGM）、全新世中期（MH）和工业化前（PI）时期。相对于现代年际变化，古气候模拟显示出更大的敏感性参数变化，允许在更广泛的气候强迫和识别的世界部分地区的参数敏感的模型的不确定性进行评估。某些模拟重现了所有时间段的δ 18 Op绝对值，沿着LGM和MH δ 18 Op相对于PI的异常，优于默认参数化。没有一组参数化在所有气候状态下都能很好地工作，这可能是由于云反馈在不同边界条件下的非平稳性。未来的工作，涉及不同的多个参数集，同时耦合海洋反馈可能会提供云和对流参数化的约束条件。
Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof‐of‐concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere‐only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present‐day runs using multiple satellite climatologies and by comparing simulated δ18O of precipitation (δ18Op), known to be sensitive to parameterization schemes, with a global database of speleothem δ18O records covering the Last Glacial Maximum (LGM), mid‐Holocene (MH) and pre‐industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ18Op values across all time periods, along with LGM and MH δ18Op anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non‐stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.