Collaborative Research: Quantifying the sea-surface temperature pattern effect for Last Glacial Maximum and Pliocene constraints on climate sensitivity

合作研究：量化末次盛冰期和上新世气候敏感性限制的海面温度模式效应

• 批准号: 2002385
• 负责人: Cristian Proistosescu
• 金额: $ 8.19万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2002385&HistoricalAwards=false
• 关键词: Collaborative; Research; Quantifying; sea; surface

Predictions of future climate change are based in part on changes seen in geological records of times with different climates. Such times include the Last Glacial Maximum (LGM) 21 thousand years ago (a colder time with lower atmospheric carbon dioxide levels) and the Pliocene Epoch 5.3 to 2.6 million years ago (a warmer time with higher carbon dioxide). These periods can be used to estimate the sensitivity of climate to changes in greenhouse gases such as carbon dioxide. Those sensitivity estimates help predict the amount of global warming we should expect to see in response to future greenhouse gas emissions. However, recent work has shown that the climate’s sensitivity to greenhouse gases depends not only on the average surface temperature change but also on the geographic pattern of that change. Thus, use of geological paleoclimate records to estimate future warming must account for how the spatial pattern of temperature changes in the past differs from that expected in the future. This project will combine information from paleoclimate data and climate models to evaluate the spatial pattern of surface temperature changes during the LGM and Pliocene. It will then develop methods to account for temperature pattern differences when using data from these past periods to help estimate future global warming.Earth’s equilibrium climate sensitivity (ECS) is the change in average surface temperature associated with a doubling of the atmospheric carbon dioxide concentration (CO2) relative to the pre-industrial atmosphere. The ECS is set by the radiative feedbacks that link surface warming to changes in the amount of radiation leaving Earth’s atmosphere. Recent studies have shown that global radiative feedbacks depend on the spatial pattern of sea-surface temperature (SST). Estimates of ECS based on the proxy record of past climate changes – such as those during the Last Glacial Maximum (LGM) and Pliocene – have traditionally been based on global mean energy budget constraints and thus do not account for how SST patterns in those states may be different from those in the future. This research will use recently developed data assimilation techniques, combining information from climate models and proxies, to reconstruct gridded SST fields for the LGM and Pliocene that are dynamically consistent with available proxy data. These SST fields will then be compared against those projected by global climate models under CO2 forcing. The sensitivity of radiative feedbacks to differences between LGM / Pliocene and CO2-forced SST patterns will then be quantified using a suite of atmospheric general circulation models and Green’s functions that link warming patterns to radiative feedbacks. By producing estimates of LGM and Pliocene surface temperature patterns and quantifying the impact of temperature pattern differences on radiative feedbacks, this research will improve our understanding of ECS derived from those past climate states. This work will further facilitate researchers’ participation in activities aimed at introducing high school students to climate science, through Current Climate Science workshops for high school teachers facilitated by the University of Washington’s Program on Climate Change and through George Mason University’s Aspiring Scientists Summer Internship Program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

对未来气候变化的预测部分基于不同气候时期的地质记录中的变化，这些时期包括21000年前的末次盛冰期（LGM）（大气二氧化碳水平较低的较冷时期）和上新世。 5.3 至 260 万年前（二氧化碳含量较高的温暖时期）可用于估计气候对二氧化碳等温室气体变化的敏感性。然而，最近的研究表明，气候对温室气体的敏感性不仅取决于平均地表温度的变化，还取决于这种变化的地理格局。利用地质古气候记录来估计未来变暖必须考虑到过去温度变化的空间模式与未来预期的变化有何不同。该项目将结合古气候数据和气候模型的信息来评估未来变暖的地表温度变化的空间模式。末次盛会和然后，它将开发方法来解释使用过去时期的数据来帮助估计未来全球变暖的温度模式差异。地球的平衡气候敏感性（ECS）是与大气二氧化碳加倍相关的平均表面温度的变化。相对于工业化前大气的二氧化碳浓度 (ECS) 由辐射反馈决定，该辐射反馈将地表变暖与离开地球大气的辐射量的变化联系起来。海面温度（SST）的空间格局基于过去气候变化的代理记录——例如末次盛冰期（LGM）和上新世——传统上是基于全球平均能源预算约束，因此不考虑这些州的海温模式可能与未来的海温模式有何不同。这项研究将使用最近开发的数据同化技术，结合来自气候模型和代理的信息，重建末次盛冰期和上新世的网格海温场。然后将这些海表温度场与二氧化碳强迫下的全球气候模型预测的数据进行比较，然后使用套件对末次盛宴/上新世和二氧化碳迫使的海表温度模式之间的差异的敏感性进行量化。通过对末次盛夏和上新世表面温度模式进行估计并量化温度模式差异对辐射反馈的影响，这项研究将改进大气环流模型和将变暖模式与辐射反馈联系起来的格林函数。这项工作将进一步促进研究人员参与旨在向高中生介绍气候科学的活动，通过华盛顿大学气候变化项目为高中教师举办的当前气候科学研讨会。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，认为值得支持。