Seasonal variations in the aragonite saturation state in the upper open-ocean waters of the North Pacific Ocean

Tae Wook Kim; Geun Ha Park; Dongseon Kim; Kitack Lee; Richard A. Feely; Frank J. Millero

doi:10.1002/2015GL063602

Seasonal variations in the aragonite saturation state in the upper open-ocean waters of the North Pacific Ocean

Tae Wook Kim, Geun Ha Park, Dongseon Kim, Kitack Lee, Richard A. Feely, Frank J. Millero

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

Seasonal variability of the aragonite saturation state (Ω_AR) in the upper (50 m and 100 m depths) North Pacific Ocean (NPO) was investigated using multiple linear regression (MLR). The MLR algorithm derived from a high-quality carbon data set accurately predicted the Ω_AR of evaluation data sets (three time series stations and P02 section) with acceptable uncertainty (<0.1 Ω_AR). The algorithm was combined with seasonal climatology data, and the estimated Ω_AR varied in the range of 0.4-0.6 in the midlatitude western NPO, with the largest variation found for the tropical eastern NPO. These marked variations were largely controlled by seasonal changes in vertical mixing and thermocline depth, both of which determine the degree of entrainment of CO₂-rich corrosive waters from deeper depths. Our MLR-based subsurface Ω_AR climatology is complementary to surface climatology based on pCO₂ measurements.

Original language	English
Pages (from-to)	4498-4506
Number of pages	9
Journal	Geophysical Research Letters
Volume	42
Issue number	11
DOIs	https://doi.org/10.1002/2015GL063602
Publication status	Published - 2015 Jun 16

Bibliographical note

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©2015. American Geophysical Union. All Rights Reserved.

Keywords

North Pacific Ocean
aragonite saturation state
fossil fuel CO2
mutiple linear regression
ocean acidification

ASJC Scopus subject areas

Geophysics
General Earth and Planetary Sciences

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/2015GL063602

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title = "Seasonal variations in the aragonite saturation state in the upper open-ocean waters of the North Pacific Ocean",

abstract = "Seasonal variability of the aragonite saturation state (ΩAR) in the upper (50 m and 100 m depths) North Pacific Ocean (NPO) was investigated using multiple linear regression (MLR). The MLR algorithm derived from a high-quality carbon data set accurately predicted the ΩAR of evaluation data sets (three time series stations and P02 section) with acceptable uncertainty (<0.1 ΩAR). The algorithm was combined with seasonal climatology data, and the estimated ΩAR varied in the range of 0.4-0.6 in the midlatitude western NPO, with the largest variation found for the tropical eastern NPO. These marked variations were largely controlled by seasonal changes in vertical mixing and thermocline depth, both of which determine the degree of entrainment of CO2-rich corrosive waters from deeper depths. Our MLR-based subsurface ΩAR climatology is complementary to surface climatology based on pCO2 measurements.",

keywords = "North Pacific Ocean, aragonite saturation state, fossil fuel CO2, mutiple linear regression, ocean acidification",

author = "Kim, {Tae Wook} and Park, {Geun Ha} and Dongseon Kim and Kitack Lee and Feely, {Richard A.} and Millero, {Frank J.}",

year = "2015",

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AU - Kim, Tae Wook

AU - Park, Geun Ha

AU - Kim, Dongseon

AU - Lee, Kitack

AU - Feely, Richard A.

AU - Millero, Frank J.

PY - 2015/6/16

Y1 - 2015/6/16

N2 - Seasonal variability of the aragonite saturation state (ΩAR) in the upper (50 m and 100 m depths) North Pacific Ocean (NPO) was investigated using multiple linear regression (MLR). The MLR algorithm derived from a high-quality carbon data set accurately predicted the ΩAR of evaluation data sets (three time series stations and P02 section) with acceptable uncertainty (<0.1 ΩAR). The algorithm was combined with seasonal climatology data, and the estimated ΩAR varied in the range of 0.4-0.6 in the midlatitude western NPO, with the largest variation found for the tropical eastern NPO. These marked variations were largely controlled by seasonal changes in vertical mixing and thermocline depth, both of which determine the degree of entrainment of CO2-rich corrosive waters from deeper depths. Our MLR-based subsurface ΩAR climatology is complementary to surface climatology based on pCO2 measurements.

AB - Seasonal variability of the aragonite saturation state (ΩAR) in the upper (50 m and 100 m depths) North Pacific Ocean (NPO) was investigated using multiple linear regression (MLR). The MLR algorithm derived from a high-quality carbon data set accurately predicted the ΩAR of evaluation data sets (three time series stations and P02 section) with acceptable uncertainty (<0.1 ΩAR). The algorithm was combined with seasonal climatology data, and the estimated ΩAR varied in the range of 0.4-0.6 in the midlatitude western NPO, with the largest variation found for the tropical eastern NPO. These marked variations were largely controlled by seasonal changes in vertical mixing and thermocline depth, both of which determine the degree of entrainment of CO2-rich corrosive waters from deeper depths. Our MLR-based subsurface ΩAR climatology is complementary to surface climatology based on pCO2 measurements.

KW - North Pacific Ocean

KW - aragonite saturation state

KW - fossil fuel CO2

KW - mutiple linear regression

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ER -

Seasonal variations in the aragonite saturation state in the upper open-ocean waters of the North Pacific Ocean

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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