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Prediction of Sea of Japan (East Sea) acidification over the past 40 years using a multiparameter regression model

机译:使用多参数回归模型预测日本海(东海)过去40年的酸化

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A multiparameter linear regression model (MLR) of aragonite saturation state (_(ARG)) as a function of temperature, pressure and O_2 concentration in the upper 1,000 m of the Sea of Japan (East Sea) was derived with an uncertainty of 0.020 (1). The _(ARG) data (n = 1,482) used to derive the basin-wide _(ARG) prediction model were collected during a field survey in 1999 and were corrected for anthropogenic CO_2. Some biases were resolved by addition of a pressure and O_2 concentration interaction term to the proposed model. Correlation between the two predictor terms, caused by addition of this term, was minimized by centering the data for the three variables (thus subtracting the mean from each individual data point). Validation of the model against data sets obtained in 1992 and 2007 yielded correlation coefficients of 0.995 0.013 for 1992 (n = 64, p $ll$ 0.001) and 0.995 0.009 for 2007 (n = 137, p $ll$ 0.001) and root mean square errors of 0.064 for 1992 and 0.050 for 2007. The strong correlation between measurements and predictions suggests that the model can be used to estimate the distribution of _(ARG) in the Sea of Japan (East Sea) (including dynamic coastal waters) on varying time scales when basic hydrographic data on temperature, pressure and O_2 concentration are available. Application of the model to past measurements for the Sea of Japan (East Sea) indicated that interdecadal variability (2 from the mean) in _(ARG) corrected for anthropogenic CO_2 was generally high (0.1-0.7) in the upper water layer (<200 m depth), and decreased (0.05-0.2) with depth for waters deeper than 500 m. The interdecadal variability is largely controlled by variations in the degree of water column ventilation. Superimposed on this natural variability, the input of CO_2 derived from fossil fuels has markedly acidified the upper water layers during the anthropocene and thereby moved the aragonite saturation horizon upward by 50-250 m. The impact of CO_2 derived from fossil fuels on upper ocean acidification will increase in the future. The present study indicates that, in combination with other easily measurable parameters, a multifunctional model can be a powerful tool for predicting the temporal evolution of _(ARG) in the ocean, including coastal waters that are highly likely to be susceptible to ocean acidification in the future.
机译:推导了日本海(东海)上1,000 m处文石饱和状态(_(ARG))作为温度,压力和O_2浓度的函数的多参数线性回归模型(MLR),不确定度为0.020( 1)。在1999年的一次实地调查中收集了用于推导出整个流域范围的_(ARG)预测模型的_(ARG)数据(n = 1,482),并对人为的CO_2进行了校正。通过将压力和O_2浓度相互作用项添加到建议的模型中,可以解决一些偏差。通过将三个变量的数据居中(从而从每个单独的数据点减去平均值),可以最小化由该术语相加引起的两个预测项之间的相关性。针对1992年和2007年获得的数据集对该模型进行验证,得出1992年的相关系数为0.995 0.013(n = 64,p $ ll $ 0.001),2007年的相关系数为0.995 0.009(n = 137,p $ ll $ 0.001), 1992年的均方根误差为0.064,2007年的均方根误差为0.050。测量值与预测值之间的强相关性表明,该模型可用于估算日本海(东海)(包括动态沿海水域)中_(ARG)的分布),只要有关于温度,压力和O_2浓度的基本水文数据就可以在不同的时间尺度上进行。该模型在日本海(东海)过去的测量中的应用表明,针对人为CO_2校正的_(ARG)的年代际变化(平均值为2)在上层水层中普遍较高(0.1-0.7)(< 200 m深度),对于深度超过500 m的水域,深度会降低(0.05-0.2)。年代际变化主要由水柱通风程度的变化控制。在这种自然变化的基础上,源自化石燃料的CO_2输入在人类世期间显着酸化了上层水层,从而使文石饱和层向上移动了50-250 m。将来,来自化石燃料的CO_2对高位海洋酸化的影响将会增加。本研究表明,与其他易于测量的参数结合使用时,多功能模型可以成为预测海洋中_(ARG)随时间变化的强大工具,其中包括极有可能在海洋酸化的沿海水域。未来。

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