Neural networks and the seawater CO2 system. From the global ocean to the Ría de Vigo

This doctoral dissertation is structured in six chapters and two appendices. From this point the reader is warned about the independent numbering in each chapter, both for sections and subsections as well as for figures and tables, that is, the numbering restarts at the beginning of each chapter. Chapter I is divided into two parts. On the one hand, the topic of the doctoral dissertation is introduced in a general way to put in context the different research studies that are part of it. This introduction presents the key concepts on climate change and ocean acidification necessary to approach the reading of the following chapters. On the other hand, the main and secondary objectives that are addressed in the next chapters are detailed. Chapter II develops the construction of a global and seasonal climatology of total alkalinity. The chapter details for the first time in the thesis the use of neural networks. This methodology is used throughout the manuscript, highlighting the peculiarities associated with each study in each of the chapters where it is applied. This chapter has been published in Earth System Science Data: https://doi.org/10.5194/essd-11-1109-2019 Chapter III describes the development of a total dissolved inorganic carbon climatology. In general terms, a methodology similar to that of chapter II is used, although with certain relevant nuances such as the inclusion of a new database. In this chapter, a pCO2 climatology is also generated in a secondary way to evaluate the consistency between the two climatologies previously generated in this thesis. This chapter has been published in Earth System Science Data: https://doi.org/10.5194/essd-12-1725-2020.


Chapter IV completely changes the scale of the previous two chapters and focuses on the study of sweater CO2 chemistry system on a regional scale. Specifically, neural networks are used to generate time series of total alkalinity and pH at various locations in the Ría de Vigo. From the time series, the magnitude of seasonal variability and interannual trends for these variables are analyzed. This chapter has been published in Biogeosciences Discussions: https://doi.org/10.5194/bg-2021-33, 2021 Chapter V contains an analysis of the variability of the hydrogen ion concentration and the aragonite saturation state in the Ría de Vigo. This analysis is carried out from the time series of these variables that are constructed thanks to the study developed in chapter IV. Chapters II to V are structured in the same way as a typical scientific article, thus containing an introduction, methodology, results, discussion and conclusions about each study. Finally, chapter VI summarizes the main conclusions derived from the complete work shown through this doctoral thesis. It is worth noting the inclusion of two appendices in the final part of the thesis. Appendix I details the meaning of each of the acronyms, abbreviations and symbols used throughout the manuscript. Appendix II contains a summary of the doctoral dissertation in Spanish

Broullón D., 2022. Neural networks and the seawater CO2 system. From the global ocean to the Ría de Vigo. PhD thesis, Universidad de Vigo, 279 p. Thesis.

0 Responses to “Neural networks and the seawater CO2 system. From the global ocean to the Ría de Vigo”



  1. Leave a Comment

Leave a Reply




  • Reset

Subscribe

OA-ICC Highlights


%d bloggers like this: