Collaborative Research: Correcting sea surface temperature proxies for seasonal biases: combined data and model investigation

合作研究：修正海面温度代理的季节性偏差：结合数据和模型研究

• 批准号: 2202911
• 负责人: Samantha Bova
• 金额: $ 30.7万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2202911&HistoricalAwards=false
• 关键词: Collaborative; Research; Correcting; sea; surface

Warmer than present periods in Earth history can provide insight into how the climate system will respond to rising global temperatures. Knowledge of ocean conditions during past warm periods comes, in large part, from geochemical records (proxies) of past sea surface temperature. These proxies are generally interpreted to reflect the average yearly temperature. Many SST proxies suggest that prior to the industrial revolution, global temperatures had been cooling for 6000 years. This result is at odds with climate model simulations which show warming over that period in response to rising atmospheric greenhouse gas levels. This mismatch has cast doubts on model predictions of future climate change and the warming impact of greenhouse gases. However, a recent study suggested the mismatch arises from the interpretation of the proxies, not from problems with the climate models. That study suggested that proxies often record temperature during a particular season, rather than the yearly average. When the seasonality of the proxy was considered the models and proxies were consistent. This study will test and refine approaches for extracting the seasonal and mean annual temperature from proxies of past sea surface temperatures. In addition, new geochemical records of past temperature will be produced across three recent warm periods in Earth history. These new data will aid in ground-truthing model predictions of future climate change. The project will also provide training opportunities for early career scientists, including students from underrepresented groups in the sciences. Results from the project will be communicated via public lectures and a K-12 science outreach program.Accounting for seasonal biases in sea surface temperature (SST) proxies is critical for understanding the drivers of SST in response to internal and external forcings. The proposed work aims to provide a way forward to identify seasonal biases and remove them from proxy SST records to improve paleoceanographic reconstructions. The study will include a series of test of the seasonal to annual mean transformation method in fully coupled and idealized climate models to explore the impact of ice sheet forcing, greenhouse gases, nonlinearities in the climate system, and sampling errors on the efficacy of the method in different regions of the global ocean and during multiple interglacial periods. The study will produce new paired foraminifer-magnesium/calcium and alkenone derived SST records from seven locations. At each of these sites, data from the Holocene, last interglacial, and Marine isotope stage 9 will be used to explore the stability of biases and the drivers of seasonal and mean annual climate change during multiple examples of a warm interglacial.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.

地球历史上比现在更温暖的时期可以让我们深入了解气候系统将如何应对全球气温上升。对过去温暖时期海洋状况的了解在很大程度上来自过去海面温度的地球化学记录（代理）。这些代理通常被解释为反映年平均温度。许多海表温度指标表明，在工业革命之前，全球气温已经下降了 6000 年。这一结果与气候模型模拟不一致，气候模型模拟显示该时期大气温室气体水平上升导致气候变暖。这种不匹配使人们对未来气候变化和温室气体变暖影响的模型预测产生了怀疑。然而，最近的一项研究表明，这种不匹配源于对代理的解释，而不是气候模型的问题。该研究表明，代理通常记录特定季节的温度，而不是年平均值。当考虑代理的季节性时，模型和代理是一致的。这项研究将测试和完善从过去海面温度的代理中提取季节性和年平均温度的方法。此外，过去温度的新地球化学记录将在地球历史上最近的三个温暖时期产生。这些新数据将有助于对未来气候变化进行真实模型预测。该项目还将为早期职业科学家提供培训机会，包括来自科学领域代表性不足群体的学生。该项目的结果将通过公开讲座和 K-12 科学推广计划进行传达。考虑海面温度 (SST) 代理的季节性偏差对于理解海表温度响应内部和外部强迫的驱动因素至关重要。拟议的工作旨在提供一种识别季节性偏差并将其从代理海表温度记录中删除的方法，以改善古海洋学重建。该研究将包括在完全耦合和理想化气候模型中对季节平均转换方法进行一系列测试，以探索冰盖强迫、温室气体、气候系统非线性和采样误差对该方法有效性的影响在全球海洋的不同区域和多个间冰期。该研究将产生来自七个地点的新的成对有孔虫-镁/钙和烯酮衍生的海温记录。在每个地点，来自全新世、末次间冰期和海洋同位素第 9 阶段的数据将用于探索多个温暖间冰期实例中偏差的稳定性以及季节性和年平均气候变化的驱动因素。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，被认为值得支持。