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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/17287
Ver los metadatos del registro completo
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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 |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.13397 |