Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific

Autores
Hales, Burke; Strutton, Peter G.; Saraceno, Martin; Letelier, Ricardo; Takahashi, Taro; Feely, Richard; Sabine, Christopher; Chavez, Francisco
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Continental margin carbon cycling is complex, highly variable over a range of space and time scales, and forced by multiple physical and biogeochemical drivers. Predictions of globally significant air–sea CO2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO2 from remote-sensing data, based on self organizing maps (SOMs) and a nonlinear semi-empirical model of surface water carbonate chemistry. The model used simple empirical relationships between carbonate chemistry (total dissolved carbon dioxide (TCO2) and alkalinity (TAlk)) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO2 partial pressure (pCO2) was calculated from the empirically-predicted TCO2 and TAlk. This directly incorporated the inherent nonlinearities of the carbonate system, in a completely mechanistic manner. The model’s empirical coefficients were determined for a target study area of the central North American Pacific continental margin (22–50°N, within 370 km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO2 agreed with the highly variable observations with a root mean squared (RMS) deviation of <20 μatm, and with a correlation coefficient of >0.8 (r = 0.81; r2 = 0.66). This level of accuracy is a significant improvement relative to that of simpler models that did not resolve the biogeochemical sub-regions or that relied on linear dependences on input parameters. Air–sea fluxes based on these pCO2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14 Tg C yr−1 sink for atmospheric CO2 over the 1997–2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5 Tg C yr−1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area.
Fil: Hales, Burke. State University of Oregon; Estados Unidos
Fil: Strutton, Peter G.. University Of Tasmania; Australia
Fil: Saraceno, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina
Fil: Letelier, Ricardo. State University of Oregon; Estados Unidos
Fil: Takahashi, Taro. Lamont-Doherty Earth Observatory; Estados Unidos
Fil: Feely, Richard. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados Unidos
Fil: Sabine, Christopher. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados Unidos
Fil: Chavez, Francisco. Monterey Bay Aquarium Research Institute; Estados Unidos
Materia
EASTERN NORTH PACIFIC
SATELLITE
PCO2
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/17287

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network_name_str CONICET Digital (CONICET)
spelling Satellite-based prediction of pCO2 in coastal waters of the eastern North PacificHales, BurkeStrutton, Peter G.Saraceno, MartinLetelier, RicardoTakahashi, TaroFeely, RichardSabine, ChristopherChavez, FranciscoEASTERN NORTH PACIFICSATELLITEPCO2https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Continental margin carbon cycling is complex, highly variable over a range of space and time scales, and forced by multiple physical and biogeochemical drivers. Predictions of globally significant air–sea CO2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO2 from remote-sensing data, based on self organizing maps (SOMs) and a nonlinear semi-empirical model of surface water carbonate chemistry. The model used simple empirical relationships between carbonate chemistry (total dissolved carbon dioxide (TCO2) and alkalinity (TAlk)) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO2 partial pressure (pCO2) was calculated from the empirically-predicted TCO2 and TAlk. This directly incorporated the inherent nonlinearities of the carbonate system, in a completely mechanistic manner. The model’s empirical coefficients were determined for a target study area of the central North American Pacific continental margin (22–50°N, within 370 km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO2 agreed with the highly variable observations with a root mean squared (RMS) deviation of <20 μatm, and with a correlation coefficient of >0.8 (r = 0.81; r2 = 0.66). This level of accuracy is a significant improvement relative to that of simpler models that did not resolve the biogeochemical sub-regions or that relied on linear dependences on input parameters. Air–sea fluxes based on these pCO2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14 Tg C yr−1 sink for atmospheric CO2 over the 1997–2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5 Tg C yr−1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area.Fil: Hales, Burke. State University of Oregon; Estados UnidosFil: Strutton, Peter G.. University Of Tasmania; AustraliaFil: Saraceno, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; ArgentinaFil: Letelier, Ricardo. State University of Oregon; Estados UnidosFil: Takahashi, Taro. Lamont-Doherty Earth Observatory; Estados UnidosFil: Feely, Richard. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados UnidosFil: Sabine, Christopher. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados UnidosFil: Chavez, Francisco. Monterey Bay Aquarium Research Institute; Estados UnidosElsevier2012-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/17287Hales, Burke; Strutton, Peter G.; Saraceno, Martin; Letelier, Ricardo; Takahashi, Taro; et al.; Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific; Elsevier; Progress In Oceanography; 103; 9-2012; 1-150079-6611enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.pocean.2012.03.001info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0079661112000183info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:32Zoai:ri.conicet.gov.ar:11336/17287instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:32.723CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
title Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
spellingShingle Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
Hales, Burke
EASTERN NORTH PACIFIC
SATELLITE
PCO2
title_short Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
title_full Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
title_fullStr Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
title_full_unstemmed Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
title_sort Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific
dc.creator.none.fl_str_mv Hales, Burke
Strutton, Peter G.
Saraceno, Martin
Letelier, Ricardo
Takahashi, Taro
Feely, Richard
Sabine, Christopher
Chavez, Francisco
author Hales, Burke
author_facet Hales, Burke
Strutton, Peter G.
Saraceno, Martin
Letelier, Ricardo
Takahashi, Taro
Feely, Richard
Sabine, Christopher
Chavez, Francisco
author_role author
author2 Strutton, Peter G.
Saraceno, Martin
Letelier, Ricardo
Takahashi, Taro
Feely, Richard
Sabine, Christopher
Chavez, Francisco
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv EASTERN NORTH PACIFIC
SATELLITE
PCO2
topic EASTERN NORTH PACIFIC
SATELLITE
PCO2
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Continental margin carbon cycling is complex, highly variable over a range of space and time scales, and forced by multiple physical and biogeochemical drivers. Predictions of globally significant air–sea CO2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO2 from remote-sensing data, based on self organizing maps (SOMs) and a nonlinear semi-empirical model of surface water carbonate chemistry. The model used simple empirical relationships between carbonate chemistry (total dissolved carbon dioxide (TCO2) and alkalinity (TAlk)) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO2 partial pressure (pCO2) was calculated from the empirically-predicted TCO2 and TAlk. This directly incorporated the inherent nonlinearities of the carbonate system, in a completely mechanistic manner. The model’s empirical coefficients were determined for a target study area of the central North American Pacific continental margin (22–50°N, within 370 km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO2 agreed with the highly variable observations with a root mean squared (RMS) deviation of <20 μatm, and with a correlation coefficient of >0.8 (r = 0.81; r2 = 0.66). This level of accuracy is a significant improvement relative to that of simpler models that did not resolve the biogeochemical sub-regions or that relied on linear dependences on input parameters. Air–sea fluxes based on these pCO2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14 Tg C yr−1 sink for atmospheric CO2 over the 1997–2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5 Tg C yr−1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area.
Fil: Hales, Burke. State University of Oregon; Estados Unidos
Fil: Strutton, Peter G.. University Of Tasmania; Australia
Fil: Saraceno, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina
Fil: Letelier, Ricardo. State University of Oregon; Estados Unidos
Fil: Takahashi, Taro. Lamont-Doherty Earth Observatory; Estados Unidos
Fil: Feely, Richard. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados Unidos
Fil: Sabine, Christopher. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados Unidos
Fil: Chavez, Francisco. Monterey Bay Aquarium Research Institute; Estados Unidos
description Continental margin carbon cycling is complex, highly variable over a range of space and time scales, and forced by multiple physical and biogeochemical drivers. Predictions of globally significant air–sea CO2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO2 from remote-sensing data, based on self organizing maps (SOMs) and a nonlinear semi-empirical model of surface water carbonate chemistry. The model used simple empirical relationships between carbonate chemistry (total dissolved carbon dioxide (TCO2) and alkalinity (TAlk)) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO2 partial pressure (pCO2) was calculated from the empirically-predicted TCO2 and TAlk. This directly incorporated the inherent nonlinearities of the carbonate system, in a completely mechanistic manner. The model’s empirical coefficients were determined for a target study area of the central North American Pacific continental margin (22–50°N, within 370 km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO2 agreed with the highly variable observations with a root mean squared (RMS) deviation of <20 μatm, and with a correlation coefficient of >0.8 (r = 0.81; r2 = 0.66). This level of accuracy is a significant improvement relative to that of simpler models that did not resolve the biogeochemical sub-regions or that relied on linear dependences on input parameters. Air–sea fluxes based on these pCO2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14 Tg C yr−1 sink for atmospheric CO2 over the 1997–2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5 Tg C yr−1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area.
publishDate 2012
dc.date.none.fl_str_mv 2012-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/17287
Hales, Burke; Strutton, Peter G.; Saraceno, Martin; Letelier, Ricardo; Takahashi, Taro; et al.; Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific; Elsevier; Progress In Oceanography; 103; 9-2012; 1-15
0079-6611
url http://hdl.handle.net/11336/17287
identifier_str_mv Hales, Burke; Strutton, Peter G.; Saraceno, Martin; Letelier, Ricardo; Takahashi, Taro; et al.; Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific; Elsevier; Progress In Oceanography; 103; 9-2012; 1-15
0079-6611
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.pocean.2012.03.001
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0079661112000183
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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