A global monthly climatology of total alkalinity: a neural network approach
A global monthly climatology of total alkalinity: a neural network approach
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DOI：
10.5194/essd-11-1109-2019
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发表时间：
2019-07-31
影响因子：
11.4
通讯作者：
van Heuven, Steven M. A. C.
中科院分区：
文献类型：
--
作者：
Broullon, Daniel;Perez, Fiz F.;van Heuven, Steven M. A. C.
海水二氧化碳化学变量的全球气候学对于深入评估海洋碳循环是必要的。气候学应充分捕捉季节变化，以正确解决海洋酸化和与碳循环相关的类似问题。总碱度 (A(T)) 是涉及海洋酸化并经常测量的海水二氧化碳化学系统的变量之一。我们使用全球海洋数据分析项目 2.2019 版 (GLODAPv2) 来提取 A(T) 变异性和 A(T) 浓度驱动因素之间的关系，并使用神经网络 (NNGv2) 生成每月气候学。使用的 GLODAPv2 质量控制数据集由 NNGv2 建模，均方根误差 (RMSE) 为 5.3 mu mol kg(-1)。使用独立数据集的验证测试揭示了网络的良好泛化性。五个海洋时间序列站的数据显示可接受的 RMSE 范围为 3-6.2 mu mol kg(-1)。对时间序列中每月 A(T) 变化的成功建模表明 NNGv2 是生成每月气候学的良好候选者。 A(T) 的气候场是通过 NNGv2 2013 年世界海洋地图集 (WOA13) 的每月温度、盐度和氧气气候学以及通过神经网络计算的营养物气候学获得的。时空分辨率由 WOA13 设置：水平方向 1 度 x 1 度，垂直方向 102 个深度级别（0-5500 m）以及月度（0-1500 m）到年度（1550-5500 m）时间分辨率。该产品通过西班牙国家研究委员会的数据存储库分发（CSIC；https://doi.org/10.20350/digitalCSIC/8644，Broullon 等人，2019）。
Global climatologies of the seawater CO2 chemistry variables are necessary to assess the marine carbon cycle in depth. The climatologies should adequately capture seasonal variability to properly address ocean acidification and similar issues related to the carbon cycle. Total alkalinity (A(T)) is one variable of the seawater CO2 chemistry system involved in ocean acidification and frequently measured. We used the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2) to extract relationships among the drivers of the A(T) variability and A(T) concentration using a neural network (NNGv2) to generate a monthly climatology. The GLODAPv2 quality-controlled dataset used was modeled by the NNGv2 with a root-mean-squared error (RMSE) of 5.3 mu mol kg(-1). Validation tests with independent datasets revealed the good generalization of the network. Data from five ocean time-series stations showed an acceptable RMSE range of 3-6.2 mu mol kg(-1). Successful modeling of the monthly A(T) variability in the time series suggests that the NNGv2 is a good candidate to generate a monthly climatology. The climatological fields of A(T) were obtained passing through the NNGv2 the World Ocean Atlas 2013 (WOA13) monthly climatologies of temperature, salinity, and oxygen and the computed climatologies of nutrients from the previous ones with a neural network. The spatiotemporal resolution is set by WOA13: 1 degrees x 1 degrees in the horizontal, 102 depth levels (0-5500 m) in the vertical and monthly (0-1500 m) to annual (1550-5500 m) temporal resolution. The product is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/8644, Broullon et al., 2019).