Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-5103-2020
https://doi.org/10.5194/gmd-13-5103-2020
Model description paper
 | 
27 Oct 2020
Model description paper |  | 27 Oct 2020

Retrieving monthly and interannual total-scale pH (pHT) on the East China Sea shelf using an artificial neural network: ANN-pHT-v1

Xiaoshuang Li, Richard Garth James Bellerby, Jianzhong Ge, Philip Wallhead, Jing Liu, and Anqiang Yang

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Short summary
We have developed an ANN model to predict pH using 11 cruise datasets from 2013 to 2017, demonstrated its reliability using three cruise datasets during 2018 and applied it to retrieve monthly pH for the period 2000 to 2016 on the East China Sea shelf using the ANN model in combination with input variables from the Changjiang biology Finite-Volume Coastal Ocean Model. This approach may be a valuable tool for understanding the seasonal variation of pH in poorly observed regions.