Random and systematic uncertainty in ship-based seawater carbonate chemistry observations

IF 3.8 1区 地球科学 Q1 LIMNOLOGY Limnology and Oceanography Pub Date : 2024-09-08 DOI:10.1002/lno.12674
Brendan R. Carter, Jonathan D. Sharp, Maribel I. García-Ibáñez, Ryan J. Woosley, Michael B. Fong, Marta Álvarez, Leticia Barbero, Simon L. Clegg, Regina Easley, Andrea J. Fassbender, Xinyu Li, Katelyn M. Schockman, Zhaohui Aleck Wang
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Abstract

Seawater carbonate chemistry observations are increasingly necessary to study a broad array of oceanographic challenges such as ocean acidification, carbon inventory tracking, and assessment of marine carbon dioxide removal strategies. The uncertainty in a seawater carbonate chemistry observation comes from unknown random variations and systematic offsets. Here, we estimate the magnitudes of these random and systematic components of uncertainty for the discrete open-ocean carbonate chemistry measurements in the Global Ocean Data Analysis Project 2022 update (GLODAPv2.2022). We use both an uncertainty propagation approach and a carbonate chemistry measurement “inter-consistency” approach that quantifies the disagreement between measured carbonate chemistry variables and calculations of the same variables from other carbonate chemistry measurements. Our inter-consistency analysis reveals that the seawater carbonate chemistry measurement community has collected and released data with a random uncertainty that averages about 1.7 times the uncertainty estimated by propagating the desired “climate-quality” random uncertainties. However, we obtain differing random uncertainty estimates for subsets of the available data, with some subsets seemingly meeting the climate-quality criteria. We find that seawater pH measurements on the total scale do not meet the climate-quality criteria, though the inter-consistency of these measurements improves (by 38%) when limited to the subset of measurements made using purified indicator dyes. We show that GLODAPv2 adjustments improve inter-consistency for some subsets of the measurements while worsening it for others. Finally, we provide general guidance for quantifying the random uncertainty that applies for common combinations of measured and calculated values.

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船基海水碳酸盐化学观测的随机和系统不确定性
海水碳酸盐化学观测对研究海洋酸化、碳库存跟踪和海洋二氧化碳清除战略评估等一系列海洋学挑战越来越有必要。海水碳酸盐化学观测的不确定性来自未知的随机变化和系统偏移。在此,我们估算了全球海洋数据分析项目 2022 更新版(GLODAPv2.2022)中离散公海碳酸盐化学测量的随机和系统不确定性的大小。我们同时使用了不确定性传播方法和碳酸盐化学测量 "相互一致性 "方法,该方法量化了碳酸盐化学测量变量与其他碳酸盐化学测量计算出的相同变量之间的差异。我们的一致性分析表明,海水碳酸盐化学测量界收集和发布的数据,其随机不确定性平均约为传播所需的 "气候质量 "随机不确定性估计值的 1.7 倍。不过,我们对现有数据子集的随机不确定性估计值有所不同,有些子集似乎符合气候质量标准。我们发现,总尺度上的海水 pH 测量值不符合气候质量标准,不过,如果仅限于使用纯化指示剂染料进行测量的子集,这些测量值之间的一致性会有所改善(38%)。我们表明,GLODAPv2 的调整改善了某些测量子集的相互一致性,同时也恶化了其他子集的相互一致性。最后,我们提供了量化随机不确定性的一般指导,适用于测量值和计算值的常见组合。
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来源期刊
Limnology and Oceanography
Limnology and Oceanography 地学-海洋学
CiteScore
8.80
自引率
6.70%
发文量
254
审稿时长
3 months
期刊介绍: Limnology and Oceanography (L&O; print ISSN 0024-3590, online ISSN 1939-5590) publishes original articles, including scholarly reviews, about all aspects of limnology and oceanography. The journal''s unifying theme is the understanding of aquatic systems. Submissions are judged on the originality of their data, interpretations, and ideas, and on the degree to which they can be generalized beyond the particular aquatic system examined. Laboratory and modeling studies must demonstrate relevance to field environments; typically this means that they are bolstered by substantial "real-world" data. Few purely theoretical or purely empirical papers are accepted for review.
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