Testing ice sheet models and modelled estimates of Earth's climate sensitivity using Miocene palaeoclimate data

使用中新世古气候数据测试冰盖模型和地球气候敏感性的模型估计

• 批准号: NE/I006176/1
• 负责人: Gavin Foster
• 金额: $ 4.11万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI006176%2F1
• 关键词: Testing; ice; sheet; models; modelled

Climate models use computational techniques to mimic real physical and chemical processes in the climate system in order to predict future climate change. Such models have been used to quantify how sensitive Earth's climate is to atmospheric carbon dioxide levels. Knowing this 'climate sensitivity' is essential for politicians to set goals for future CO2 emissions that will keep Earth's climate within 'safe' limits. Until recently, the estimates for this climate sensitivity have been based on models that look only at the short-term (e.g., years-decades) effects of increasing CO2 and rising temperatures. They do not include other longer-term effects, such as melting ice sheets or changing global vegetation cover. An example of such a feedback is the melting of the Greenland ice-sheet, which in addition to causing rising sea levels will also cause further regional warming. The problem with ignoring such components of the climate system is that there are large uncertainties regarding the timescales on which they operate. Recently there have therefore been suggestions from the academic community that estimates of Earth's sensitivity to atmospheric CO2 levels should include all feedbacks within the climate system: both those that operate fast and those that operate more slowly. This more comprehensive view of the relationship between Earth's climate and pCO2 is termed 'Earth System Sensitivity'. The best way to estimate Earth System Sensitivity is to use intervals in the geological past when we know that CO2 and temperature were different to today. However, thus far this approach has led to very different estimates, largely due to uncertainties in the levels of atmospheric pCO2 reconstructed for these intervals. In the first part of the proposed work we will generate new pCO2 records using a relatively new method of estimating pCO2 (using the ratio of boron isotopes within marine planktonic microfossils) that has recently been refined. We will also use several methods for reconstructing temperatures from the same interval in the past, so that we can calculate Earth System Sensitivity. The second part of the proposed work is to use data to test a computational ice sheet model. Ice sheets are dynamically complex, and sophisticated models are required in order to predict their response to changing climate and therefore their effect on global sea level. The models need to be tested if we are to have confidence in their predictions. The long timescales involved with ice sheet dynamics means that we cannot test ice sheet models with real-time observational data. The best way to test ice sheet models is to use them to predict ice sheet changes for a period in the geological past where we have good records of Earth's temperature gradients, and compare the model results with well-constrained records of ice sheet growth for the same interval. In the proposed work we will use the Middle Miocene Climate Transition to test an ice sheet model. We know that CO2 decreased, climate cooled, and the Antarctic ice sheet expanded at this time (~14 million years ago). In this work we will obtain new, accurate records of pCO2 and temperature to drive our models. The models will then predict ice sheet changes, which we can compare to an existing record of ice sheet growth across the climate transition. If the model and the data are in good agreement then our confidence in the ice sheet model will be increased. If the model and the data are not in good agreement, then this work could lead to the identification of certain parameters within the model that may need to be adjusted. This may then lead to improved future predictions of ice sheet, and hence sea level change.

气候模型使用计算技术来模仿气候系统中的实际物理和化学过程，以预测未来的气候变化。此类模型已被用来量化地球气候对大气二氧化碳水平的敏感程度。知道这种“气候敏感性”对于政客来说，为将来的二氧化碳排放设定目标至关重要，这将使地球的气候保持在“安全”的范围内。直到最近，这种气候灵敏度的估计值一直基于模型，这些模型仅研究了二氧化碳增加和温度升高的短期（例如，十年）的影响。它们不包括其他长期效果，例如熔化的冰盖或改变全球植被覆盖。这种反馈的一个例子是格陵兰冰盖的融化，除了引起海平面上升外，还将导致进一步的区域变暖。忽略气候系统的此类组成部分的问题在于，在其操作的时间尺度上存在很大的不确定性。因此，学术界有一些建议，即估计地球对大气二氧化碳水平的敏感性应包括气候系统中的所有反馈：既快速运行的反馈，又有那些操作较慢的反馈。这种对地球气候与PCO2之间关系的更全面的看法称为“地球系统敏感性”。估计地球系统敏感性的最佳方法是在我们知道二氧化碳和温度与今天不同时使用地质过去的间隔。但是，到目前为止，这种方法导致了截然不同的估计，这在很大程度上是由于这些间隔重建大气PCO2水平的不确定性。在拟议的工作的第一部分中，我们将使用估计PCO2的新方法生成新的PCO2记录（使用最近已完善的Marine Planktonic微化石中的硼同位素比）。我们还将使用几种方法从过去的相同间隔中重建温度，以便我们可以计算地球系统敏感性。建议的工作的第二部分是使用数据测试计算冰盖模型。冰盖动态复杂，需要复杂的模型才能预测其对气候变化的反应，从而预测其对全球海平面的影响。如果我们对其预测有信心，则需要测试这些模型。与冰盖动力学有关的长时间尺度意味着我们无法测试具有实时观察数据的冰盖模型。测试冰盖模型的最佳方法是使用它们来预测地质过去一段时期的冰盖变化，在我们拥有良好的地球温度梯度的记录，并将模型结果与相同间隔的冰盖生长的良好约束记录进行比较。在拟议的工作中，我们将使用中新世中期气候过渡来测试冰盖模型。我们知道，二氧化碳降低，气候冷却，南极冰盖目前扩大（约1400万年前）。在这项工作中，我们将获得PCO2和温度的新的，准确的记录，以推动我们的模型。然后，这些模型将预测冰盖变化，我们可以将其与整个气候过渡过程中现有的冰盖生长记录进行比较。如果模型和数据非常同意，那么我们对冰盖模型的信心将会提高。如果模型和数据不符合良好的一致性，那么这项工作可能会导致识别模型中可能需要调整的某些参数。然后，这可能会改善对冰盖的未来预测，从而改善海平面变化。

项目成果

Neogene ice volume and ocean temperatures: Insights from infaunal foraminiferal Mg/Ca paleothermometry

• DOI: 10.1002/2015pa002833
• 发表时间: 2015-11
• 期刊: Paleoceanography
• 作者: C. Lear;H. Coxall;G. Foster;D. Lunt;E. Mawbey;Y. Rosenthal;S. Sosdian;E. Thomas;P. Wilson

A record of Neogene seawater d<sup>11</sup>B reconstructed from paired d<sup>11</sup>B analyses on benthic and planktic foraminifera

新近纪海水d记录

• DOI: 10.5194/cp-2015-177
• 发表时间: 2016
• 作者: Greenop R

Estimating the impact of the cryptic degassing of Large Igneous Provinces: A mid-Miocene case-study

• DOI: 10.1016/j.epsl.2014.06.040
• 发表时间: 2014-10-01
• 期刊: EARTH AND PLANETARY SCIENCE LETTERS
• 影响因子: 5.3
• 作者: Armstrong McKay, David I.;Tyrrell, Toby;Foster, Gavin L.
• 通讯作者: Foster, Gavin L.

The evolution of pCO2, ice volume and climate during the middle Miocene

• DOI: 10.1016/j.epsl.2012.06.007
• 发表时间: 2012-08-01
• 期刊: EARTH AND PLANETARY SCIENCE LETTERS
• 影响因子: 5.3
• 作者: Foster, Gavin L.;Lear, Caroline H.;Rae, James W. B.
• 通讯作者: Rae, James W. B.