Development of Upper-Ocean Aggregation Models Useful for Interpreting and Predicting Carbon Fluxes

开发有助于解释和预测碳通量的上层海洋聚集模型

• 批准号: 9726077
• 负责人: George Jackson
• 金额: $ 34.13万
• 依托单位: Texas A&M Research Foundation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-01-01 至 2001-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9726077&HistoricalAwards=false
• 关键词: Development; Upper; Ocean; Aggregation; Models

ABSTRACT Understanding the mechanisms and rates of carbon removal from surface waters remains an important goal of the Joint Global Oceanographic Flux Study (JGOFS). Particle formation and sinking is an important process for such removal. Much of the particulate fraction in surface waters is in the form of small cells having slow sinking rates. For these cells to sink more rapidly, they need to be packaged into larger particles. Fecal pellet production by animals provides one way of doing this; aggregate formation another. Because aggregates are the dominant form of sedimenting particles, understanding the processes that form and destroy aggregates is crucial for JGOS to achieve its goal. This proposal will develop models to increase our understanding of the processes affecting organic matter export from the surface mixed layer. To this end, the models will combine particle aggregation models with plankton food web models. Data sets from the JGOFS process and time-series studies will be used to determine and refine the ability of the models to predict carbon export. Data collected during the JGOFS field programs will be used to refine the models. Combining the simulation results with JGOFS field data will increase our understanding of the processes affecting vertical export fluxes and improve the accuracy of flux predictions made using the models. The results of this work will increase significantly our ability to accurately describe the movement of organic material from the surface to the deeper parts of the ocean.

摘要了解表层水中碳的去除机制和速率仍然是全球海洋通量联合研究(JGOFS)的重要目标。颗粒的形成和下沉是这种去除的一个重要过程。地表水中的大部分颗粒物以小细胞的形式存在，下沉速度很慢。为了让这些细胞更快地下沉，它们需要被包装成更大的颗粒。动物产生粪便颗粒提供了一种方式；聚集体形成另一种方式。由于团聚体是沉降颗粒的主要形式，了解形成和破坏团聚体的过程对JGOS实现其目标至关重要。这项提议将开发模式，以增加我们对影响表层混合层有机物输出的过程的理解。为此，这些模型将结合颗粒聚集模型和浮游生物食物网模型。来自JGOFS进程和时间序列研究的数据集将用于确定和改进模型预测碳出口的能力。在联合全球海洋观测系统实地方案期间收集的数据将用于改进模型。将模拟结果与JGOFS现场资料相结合，将加深我们对影响垂直出口通量的过程的理解，并提高利用该模式进行通量预报的精度。这项工作的结果将大大提高我们准确描述有机物质从海洋表面向更深部移动的能力。