Pulse Brain · Growing Health Evidence Index
Peer-reviewed

A global monthly climatology of total alkalinity: a neural network approach

Daniel Broullón, Fı́z F. Pérez, A. Velo, Mario Hoppema, Are Olsen, Taro Takahashi, Robert M. Key, Toste Tanhua, Melchor González‐Dávila, Emil Jeansson, Alex Kozyr, Steven van Heuven

Earth system science data · 2019

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Summary

Abstract. 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 (AT) 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 AT variability and AT 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 µmol kg−1. Validation tests with independent d

Source type
Peer-reviewed study
DOI
10.5194/essd-11-1109-2019
Catalogue ID
BFmoakvhu2-42o72a
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