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

基本信息

批准号：
NE/I006427/1
负责人：
Caroline Lear
金额：
$ 34.54万
依托单位：
CARDIFF UNIVERSITY
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%2FI006427%2F1
关键词：
Testing ice sheet models modelled

项目摘要

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拟气候系统中真实的物理和化学过程，以预测未来的气候变化。此类模型已用于量化地球气候对大气二氧化碳水平的敏感程度。了解这种“气候敏感性”对于政治家制定未来二氧化碳排放目标至关重要，从而使地球气候保持在“安全”范围内。直到最近，对这种气候敏感性的估计仍然基于仅考虑二氧化碳增加和气温上升的短期（例如，几年到几十年）影响的模型。它们不包括其他长期影响，例如冰盖融化或全球植被覆盖变化。这种反馈的一个例子是格陵兰冰盖的融化，这除了导致海平面上升之外，还将导致进一步的区域变暖。忽略气候系统的这些组成部分的问题在于，它们运行的时间尺度存在很大的不确定性。因此，最近学术界建议，估计地球对大气二氧化碳水平的敏感性应包括气候系统内的所有反馈：包括运行速度快的反馈和运行速度较慢的反馈。这种对地球气候与 pCO2 之间关系的更全面的看法被称为“地球系统敏感性”。估计地球系统敏感性的最佳方法是使用地质过去的时间间隔，当时我们知道二氧化碳和温度与今天不同。然而，到目前为止，这种方法导致了截然不同的估计，这主要是由于这些时间间隔重建的大气 pCO2 水平的不确定性。在拟议工作的第一部分中，我们将使用最近经过改进的相对较新的 pCO2 估计方法（使用海洋浮游微化石中硼同位素的比率）来生成新的 pCO2 记录。我们还将使用多种方法来重建过去同一区间的温度，以便我们可以计算地球系统敏感性。拟议工作的第二部分是使用数据来测试计算冰盖模型。冰盖动态复杂，需要复杂的模型来预测它们对气候变化的反应，从而预测它们对全球海平面的影响。如果我们要对模型的预测有信心，就需要对模型进行测试。冰盖动力学涉及的长时间尺度意味着我们无法用实时观测数据测试冰盖模型。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内的冰盖变化，在该时期我们对地球温度梯度有良好的记录，并将模型结果与冰盖生长的良好约束记录进行比较。相同的间隔。在拟议的工作中，我们将利用中中新世气候转变来测试冰盖模型。我们知道此时（约 1400 万年前）二氧化碳减少，气候变冷，南极冰盖扩张。在这项工作中，我们将获得新的、准确的 pCO2 和温度记录来驱动我们的模型。然后，这些模型将预测冰盖的变化，我们可以将其与气候转型期间冰盖增长的现有记录进行比较。如果模型和数据非常吻合，那么我们对冰盖模型的信心就会增加。如果模型和数据不一致，那么这项工作可能会导致模型中某些可能需要调整的参数的识别。这可能会导致未来对冰盖以及海平面变化的预测得到改善。