Optimizing observational arrays for biogeochemistry in the tropical Pacific by estimating correlation lengths

IF 2.1 3区 地球科学 Q2 LIMNOLOGY
Winnie U. Chu, Matthew R. Mazloff, Ariane Verdy, Sarah G. Purkey, Bruce D. Cornuelle
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引用次数: 0

Abstract

Global climate change has impacted ocean biogeochemistry and physical dynamics, causing increases in acidity and temperature, among other phenomena. These changes can lead to deleterious effects on marine ecosystems and communities that rely on these ecosystems for their livelihoods. To better quantify these changes, an array of floats fitted with biogeochemical sensors (BGC‐Argo) is being deployed throughout the ocean. This paper presents an algorithm for deriving a deployment strategy that maximizes the information captured by each float. The process involves using a model solution as a proxy for the true ocean state and carrying out an iterative process to identify optimal float deployment locations for constraining the model variance. As an example, we use the algorithm to optimize the array for observing ocean surface dissolved carbon dioxide concentrations (pCO2) in a region of strong air–sea gas exchange currently being targeted for BGC‐Argo float deployment. We conclude that 54% of the pCO2 variability in the analysis region could be sampled by an array of 50 Argo floats deployed in specified locations. This implies a relatively coarse average spacing, though we find the optimal spacing is nonuniform, with a denser sampling being required in the eastern equatorial Pacific. We also show that this method could be applied to determine the optimal float deployment along ship tracks, matching the logistics of real float deployment. We envision this software package to be a helpful resource in ocean observational design anywhere in the global oceans.
通过估算相关长度优化热带太平洋生物地球化学观测阵列
全球气候变化影响了海洋生物地球化学和物理动力学,导致酸度和温度上升等现象。这些变化会对海洋生态系统和依赖这些生态系统为生的社区造成有害影响。为了更好地量化这些变化,目前正在整个海洋部署一个装有生物地球化学传感器的浮筒阵列(BGC-Argo)。本文介绍了一种算法,用于推导出一种部署策略,使每个浮标捕获的信息量最大化。这一过程包括使用模型解作为真实海洋状态的代理,并通过迭代过程来确定浮标的最佳布放位置,以限制模型方差。例如,我们使用该算法对阵列进行了优化,以便在目前作为 BGC-Argo 浮筒部署目标的海气强烈交换区域观测海洋表面溶解二氧化碳浓度(pCO2)。我们得出的结论是,在指定地点布放 50 个 Argo 浮漂阵列,可以对分析区域内 54% 的 pCO2 变化进行采样。这意味着平均间距相对较小,但我们发现最佳间距是不均匀的,在东赤道太平洋需要更密集的采样。我们还表明,这种方法可用于确定沿船轨的最佳浮标部署,与实际浮标部署的后勤工作相匹配。我们设想该软件包将成为全球任何地方海洋观测设计的有用资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.80
自引率
3.70%
发文量
56
审稿时长
3 months
期刊介绍: Limnology and Oceanography: Methods (ISSN 1541-5856) is a companion to ASLO''s top-rated journal Limnology and Oceanography, and articles are held to the same high standards. In order to provide the most rapid publication consistent with high standards, Limnology and Oceanography: Methods appears in electronic format only, and the entire submission and review system is online. Articles are posted as soon as they are accepted and formatted for publication. Limnology and Oceanography: Methods will consider manuscripts whose primary focus is methodological, and that deal with problems in the aquatic sciences. Manuscripts may present new measurement equipment, techniques for analyzing observations or samples, methods for understanding and interpreting information, analyses of metadata to examine the effectiveness of approaches, invited and contributed reviews and syntheses, and techniques for communicating and teaching in the aquatic sciences.
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