Gaussian process regression as a powerful tool for analysing time series in environmental geochemistry DOI Creative Commons
Teba Gil-Díaz,

Michael Trumm

Ecological Informatics, Journal Year: 2024, Volume and Issue: 84, P. 102877 - 102877

Published: Nov. 8, 2024

Language: Английский

Ocean data assimilation focusing on integral quantities characterizing observation profiles DOI Creative Commons
Nozomi Sugiura, Shinya Kouketsu, Satoshi Osafune

et al.

Frontiers in Marine Science, Journal Year: 2024, Volume and Issue: 11

Published: Sept. 30, 2024

An observation operator in data assimilation was formalized based on the signatures extracted from integral quantities contained within observed vertical profiles ocean. A four-dimensional variational global ocean system, founded this operator, developed and utilized to conduct preliminary experiments over a ten-year window, comparing proposed method, namely profile-by-profile matching, with traditional point-by-point matching. The method not only demonstrated skill comparable but also provided superior analysis fields terms of profile shapes temperature-salinity plane. This is an indication well-balanced field, contrast which can produce extremely poor relative errors for certain metrics. Additionally, were shown successfully represent properties water column, such as steric height, serve effective new diagnostic tool. top-down, or macro–micro, viewpoint fundamental extent that it offer alternative view how we comprehend observations, holding significant implications advancement assimilation.

Language: Английский

Citations

1

Gaussian process regression as a powerful tool for analysing time series in environmental geochemistry DOI Creative Commons
Teba Gil-Díaz,

Michael Trumm

Ecological Informatics, Journal Year: 2024, Volume and Issue: 84, P. 102877 - 102877

Published: Nov. 8, 2024

Language: Английский

Citations

1