Models of the Ocean Carbonate cycle and the Glacial-Interglacial CO2 Variations

海洋碳酸盐循环和冰期-间冰期二氧化碳变化模型

• 批准号: 1155295
• 负责人: Michael Follows
• 金额: $ 59.63万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1155295&HistoricalAwards=false
• 关键词: Models; Ocean; Carbonate; cycle; Glacial

The mechanisms underlying the glacial-interglacial CO2 variations constitute one of the major unsolved problems in the Earth Sciences. Ice-core measurements have shown that during cold glacial periods, CO2 levels are around 190 p.p.m., but reach 280 p.p.m. during warm interglacials. Though many mechanisms have been hypothesized, it still remains unclear why these large CO2 variations occur, and where the excess CO2 is stored during glacial periods. While it has generally been assumed that the ocean carbonate cycle is (approximately) at steady state, both during glacial and interglacial periods we propose to explore the possibility, and potential impact, of autonomous dynamical behavior of the carbonate cycle.A team of researchers at the Massachusetts Institute of Technology hypothesize the existence of a "biogeochemical oscillator" as a contributor to the glacial-interglacial CO2 variations, and in this project they will test that hypothesis. Their preliminary, highly-idealized model reveals the possibility of an internal oscillation of the ocean carbonate cycle which has several interesting features: (i) it produces oscillations in global ocean alkalinity (and thus atmospheric carbon dioxide) with the characteristic sawtooth shape observed in the ice-core record, (ii) the oscillations are due to ecological interactions between calcifying and noncalcifying primary producers, (iii) the period of the oscillations depends upon the chosen parameters but is in a range consistent with the observed glacial-interglacial variations, and (iv) the model predicts ?spikes? of enhanced calcifier productivity at the glacial-interglacial transitions, consistent with sedimentary records. Thus, the team will investigate the potential role of these mechanisms, employing a hierarchy of models of vastly different complexities, starting from a set of two ordinary differential equations and working up to a full general circulation model with explicit and detailed biogeochemical components including an explicit ecological model. The advantage of using such a hierarchical approach is that the idealized models can help to gain insight into the mechanisms behind and the robustness of the results from more realistic complex coupled simulations. They will test the model results against ice-core measurements of CO2, observations of glacial-interglacial variations in (carbonate) sediment accumulation, and observations of carbon isotope distributions in the oceans. Broader Impact : This work is obviously relevant for understanding historical climatic change, but should also be of significance in considering how the Earth system will respond to anthropogenically emitted CO2. The project is highly multidisciplinary, bringing together expertise in biogeochemical and ocean circulation models with advanced mathematical analysis and data from geological observations.

冰期-间冰期二氧化碳变化的机制是地球科学中未解决的主要问题之一。冰芯测量显示，在寒冷的冰川时期，二氧化碳浓度约为 190 p.p.m.，但最高可达 280 p.p.m.。在温暖的间冰期期间。尽管已经假设了许多机制，但仍然不清楚为什么会发生这些巨大的二氧化碳变化，以及冰河时期过量的二氧化碳储存在哪里。虽然人们普遍认为海洋碳酸盐循环（大约）处于稳定状态，但在冰期和间冰期期间，我们建议探索碳酸盐循环自主动态行为的可能性和潜在影响。麻省理工学院的一组研究人员假设存在“生物地球化学振荡器”作为冰期-间冰期二氧化碳的贡献者 变化，在这个项目中他们将测试这个假设。 他们初步的、高度理想化的模型揭示了海洋碳酸盐循环内部振荡的可能性，该循环具有几个有趣的特征：（i）它产生全球海洋碱度（以及大气二氧化碳）的振荡，并具有在冰芯记录中观察到的特征性锯齿形状，（ii）振荡是由于钙化和非钙化初级生产者之间的生态相互作用造成的，（iii） 振荡周期取决于所选参数，但在与观测到的冰期-间冰期变化一致的范围内，并且 (iv) 模型预测“尖峰”？冰期-间冰期过渡时期钙化剂生产力的提高，与沉积记录一致。因此，该团队将研究这些机制的潜在作用，采用复杂程度截然不同的模型层次结构，从一组两个常微分方程开始，逐步建立一个具有明确和详细的生物地球化学成分（包括明确的生态模型）的完整的大气环流模型。使用这种分层方法的优点是，理想化模型可以帮助深入了解背后的机制以及更现实的复杂耦合模拟结果的稳健性。他们将根据冰芯二氧化碳测量、冰期-间冰期（碳酸盐）沉积物积累变化的观测以及海洋中碳同位素分布的观测来测试模型结果。更广泛的影响：这项工作显然与理解历史气候变化相关，但在考虑地球系统如何应对人为排放的二氧化碳方面也应该具有重要意义。该项目是高度多学科的，将生物地球化学和海洋环流模型的专业知识与先进的数学分析和地质观测数据结合起来。