2002-2019 Global Ocean pH Grid Data Products

Dataset Overview

Global ocean pH data product based on step forward feedback neural network algorithm Based on the K-fold cross validation method and the continuous observation data of several marine fixed-point observation stations,the validation of pH data was completed. The average interpolation error of the global ocean pH is less than 0.02,and the average error between the model and the observation data of each fixed point station is 0.007-0.012,indicating that the model can reproduce the change rule of the global ocean pH in the past 30 years.

Dataset Details

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Spatial Resolution: 1度

Time Resolution: 月平均

Product Number: 2017YFA0603200_013

Create Institution: Oceanographic Data Center,Chinese Academy of Sciences (CASODC)

Created By: Zhong Guorong

Creation Date: 2022-10-17T02:54:02.953Z

File Size: 3

Data Format: NetCDF

Type Of Data: 栅格

Data Label:

pH

Global oceans

Marine chemistry

Marine biogeochemistry

global change

Paper Citation

Zhong, G., Li, X., Song, J., Qu, B., Wang, F., Wang, Y., Zhang, B., Sun, X., Zhang, W., Wang, Z., Ma, J., Yuan, H., and Duan, L.: Reconstruction of global surface ocean pCO2 using region-specific predictors based on a stepwise FFNN regression algorithm, Biogeosciences, 19, 845–859, https://doi.org/10.5194/bg-19-845-2022, 2022.

Data Citation

Zhong Guorong. 2002-2019 Global Ocean pH Gridded Data Product

Data Licence Agreement

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Funded Projects

National Key Research and Development Program "Global Change and Response" Key Project "Development of Data Processing Methods and Products for Observing Key Parameters of Marine Environmental Change (2017YFA0603200)"；Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19060000).