A global monthly field of seawater pH over 3 decades: a machine learning approach

The continuous uptake of anthropogenic CO2 by the ocean leads to ocean acidification, which is an ongoing threat to the marine ecosystem. The ocean acidification rate was globally documented in the surface ocean but limited below the surface. Here, we present a monthly four-dimensional 1°×1° gridded product of global seawater pH, derived from a machine learning algorithm trained on pH observations at total scale and in-situ temperature from the Global Ocean Data Analysis Project (GLODAP). The constructed pH product covers the years 1992–2020 and depths from the surface to 2 km on 41 levels. Three types of machine learning algorithms were used in the pH product construction, including self-organizing map neural networks for region dividing, a stepwise algorithm for predictor selection, and feed-forward neural networks (FFNN) for non-linear relationship regression. The performance of the machine learning algorithm was validated using real observations by a cross validation method, where four repeating iterations were carried out with 25 % varied observations for each evaluation and 75 % for training. The constructed pH product is evaluated through comparisons to time series observations and the GLODAP pH climatology. The overall root mean square error between the FFNN constructed pH and the GLODAP measurements is 0.028, ranging from 0.044 in the surface to 0.013 at 2000 m. The pH product is distributed through the data repository of the Marine Science Data Center of the Chinese Academy of Sciences at http://dx.doi.org/10.12157/IOCAS.20230720.001 (Zhong et al., 2023)

Carbon Chemistry in the Mainstream of Kuroshio Current in Eastern Taiwan and Its Transport of Carbon into the East China Sea Shelf

Comprehensive carbon chemistry data were measured from the mainstream of Kuroshio, off eastern Taiwan, in May 2014. Results indicated that variations of pH@25 °C, POC, ΩCa, DIC, pCO2 and RF were closely related to the characteristics of various water types. Phytoplankton photosynthesis played important roles in DIC variation in Kuroshio Surface Water (KSW), whereas the DIC variation in Kuroshio Subsurface Water (KSSW) was probably influenced by the external transport of DIC-enriched water from the South China Sea. Vertical profiles of hydrological parameters and carbonate species indicated that the Kuroshio Current off eastern Taiwan could intrude into the ECS shelf as far as 27.9° E, 125.5° N in spring. What is more, the KSW, KSSW and Kuroshio Intermediate Water (KIW) could convey DIC into the East China Sea (ECS) with flux of 285, 305 and 112 Tg C/half year (1 Tg = 1012 g), respectively. The relevant flux of POC was 0.16, 2.93 and 0.04 Tg C/half year, respectively. Consequently, the intrusion of Kuroshio could probably exert a counteracting influence on the potential of CO2 uptake in the ECS, which needs further study

Variations in isoprenoid tetraether lipids through the water column of the Western Pacific Ocean: Implications for sedimentary TEX86 records

The TetraEther indeX of 86 carbon atoms (TEX86) is widely used as a proxy to reconstruct past sea surface temperatures. Most current applications of TEX86 are primarily based on analyzing the composition of isoprenoid glycerol dialkyl glycerol tetraethers (isoGDGTs) that comprise TEX86 in sediments, with the assumption that the sedimentary isoGDGTs are mainly derived from the surface mixed layer. Here we report on the variations in the isoGDGT distribution, archaeal abundance and community through the water column of the Western Pacific Ocean, directly testing the export depth of isoGDGTs and constraining the temperature records of TEX86. Our data show that maximum isoGDGT concentrations occurred in subsurface waters (150–200 m) with maximum archaeal abundances. The ratio between isoGDGTs bearing 2 vs. 3 cyclopentane moieties, i.e. [2/3] ratio, increased with depth, which is likely related to the shift of the archaeal community from Ca. Nitrosopelagicus-dominance to norank_f__Nitrosopumilaceae-dominance. Models based on the [2/3] ratios in the water column predicted an average export depth of isoGDGTs to sediments of around 150–200 m, consistent with the robust relationship between the compiled sedimentary TEX86 and the annual mean subsurface temperature. Taken together, our findings support that TEX86 records subsurface rather than surface temperatures in the open ocean

Reconstruction of global surface ocean pCO(2) using region-specific predictors based on a stepwise FFNN regression algorithm

Various machine learning methods were attempted in the global mapping of surface ocean partial pressure of CO2 (pCO(2)) to reduce the uncertainty of the global ocean CO2 sink estimate due to undersampling of pCO(2). In previous research, the predictors of pCO(2) were usually selected empirically based on theoretic drivers of surface ocean pCO(2), and the same combination of predictors was applied in all areas except where there was a lack of coverage. However, the differences between the drivers of surface ocean pCO(2) in different regions were not considered. In this work, we combined the stepwise regression algorithm and a feed-forward neural network (FFNN) to select predictors of pCO(2) based on the mean absolute error in each of the 11 biogeochemical provinces defined by the self-organizing map (SOM) method. Based on the predictors selected, a monthly global 1 circle x 1 circle surface ocean pCO(2) product from January 1992 to August 2019 was constructed. Validation of different combinations of predictors based on the Surface Ocean CO2 Atlas (SOCAT) dataset version 2020 and independent observations from time series stations was carried out. The prediction of pCO(2) based on region-specific predictors selected by the stepwise FFNN algorithm was more precise than that based on predictors from previous research. Applying the FFNN size-improving algorithm in each province decreased the mean absolute error (MAE) of the global estimate to 11.32 mu atm and the root mean square error (RMSE) to 17.99 mu atm. The script file of the stepwise FFNN algorithm and pCO(2) product are distributed through the Institute of Oceanology of the Chinese Academy of Sciences Marine Science Data Center (IOCAS, , Zhong, 2021

Table_1_The increasing big gap of carbon sink between the western and eastern Pacific in the last three decades.docx

The Pacific Ocean is one of the important carbon sink regions, and there is a significant west-east difference in sea-air CO2 flux. However, the influence of the long-standing greater CO2 uptakes in the western Pacific than in the east and the dynamic change of this west-east difference remain unclear. In this paper, using the gridded surface ocean pCO2 product constructed by the stepwise FFNN algorithm, we reported an increasing west-east CO2 flux difference from 0.41 PgC yr-1 in 1992 to 0.73 PgC yr-1 in 2020. This increase was mainly attributed to the strengthening western Pacific carbon sink and relatively stable eastern Pacific carbon source. During El Nino events, the west-east CO2 flux difference decreased significantly in a few years, and it then rose back rapidly when El Nino events ended. In addition, the increasing west-east difference in CO2 uptakes during the last three decades did not lead to a higher acidification speed in the western surface temperate Pacific than the east. The greater CO2 absorbed in the west was mainly transported to the deeper waters and caused a more significant carbon inventory change at 200-600 m than the eastern Pacific.</p