Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific

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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 CO 2 fluxes in these regions have been extrapolated based on very sparse data sets. We present...

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Autor principal:	Saraceno, Martin
Publicado:	2012
Materias:	Air sea flux Atmospheric CO Carbon cycling Carbonate system Coastal waters Continental margin Correlation coefficient Dissolved carbon dioxide Eastern north pacific Empirical coefficients Empirical relationships Historical observation Input parameter Linear dependence North American Root mean squared Satellite data Sea surface temperature (SST) Semiempirical models Space and time Sparse data sets Study areas Sub-regions Wind speed measurement Alkalinity Biogeochemistry Carbonation Chlorophyll Forecasting Remote sensing Satellites Self organizing maps Surface waters Uncertainty analysis Carbon dioxide air-sea interaction alkalinity biogeochemistry carbon cycle carbon dioxide coastal zone continental margin remote sensing satellite data sea surface temperature surface water timescale uncertainty analysis wind velocity Pacific Ocean Pacific Ocean (North)
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00796611_v103_n_p1_Hales http://hdl.handle.net/20.500.12110/paper_00796611_v103_n_p1_Hales
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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spelling	paper:paper_00796611_v103_n_p1_Hales2023-06-08T15:07:37Z Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific Saraceno, Martin Air sea flux Atmospheric CO Carbon cycling Carbonate system Coastal waters Continental margin Correlation coefficient Dissolved carbon dioxide Eastern north pacific Empirical coefficients Empirical relationships Historical observation Input parameter Linear dependence North American Root mean squared Satellite data Sea surface temperature (SST) Semiempirical models Space and time Sparse data sets Study areas Sub-regions Wind speed measurement Alkalinity Biogeochemistry Carbonation Chlorophyll Forecasting Remote sensing Satellites Self organizing maps Surface waters Uncertainty analysis Carbon dioxide air-sea interaction alkalinity biogeochemistry carbon cycle carbon dioxide coastal zone continental margin remote sensing satellite data sea surface temperature surface water timescale uncertainty analysis wind velocity Pacific Ocean Pacific Ocean (North) 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 CO 2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO 2 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 (T Alk )) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO 2 partial pressure (pCO 2 ) was calculated from the empirically-predicted TCO2 and T Alk . 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 370km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO 2 agreed with the highly variable observations with a root mean squared (RMS) deviation of <20μatm, and with a correlation coefficient of >0.8 (r=0.81; r 2 =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 pCO 2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14TgCyr -1 sink for atmospheric CO 2 over the 1997-2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5TgCyr -1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area. © 2012 Elsevier Ltd. Fil:Saraceno, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2012 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00796611_v103_n_p1_Hales http://hdl.handle.net/20.500.12110/paper_00796611_v103_n_p1_Hales
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Air sea flux Atmospheric CO Carbon cycling Carbonate system Coastal waters Continental margin Correlation coefficient Dissolved carbon dioxide Eastern north pacific Empirical coefficients Empirical relationships Historical observation Input parameter Linear dependence North American Root mean squared Satellite data Sea surface temperature (SST) Semiempirical models Space and time Sparse data sets Study areas Sub-regions Wind speed measurement Alkalinity Biogeochemistry Carbonation Chlorophyll Forecasting Remote sensing Satellites Self organizing maps Surface waters Uncertainty analysis Carbon dioxide air-sea interaction alkalinity biogeochemistry carbon cycle carbon dioxide coastal zone continental margin remote sensing satellite data sea surface temperature surface water timescale uncertainty analysis wind velocity Pacific Ocean Pacific Ocean (North)
spellingShingle	Air sea flux Atmospheric CO Carbon cycling Carbonate system Coastal waters Continental margin Correlation coefficient Dissolved carbon dioxide Eastern north pacific Empirical coefficients Empirical relationships Historical observation Input parameter Linear dependence North American Root mean squared Satellite data Sea surface temperature (SST) Semiempirical models Space and time Sparse data sets Study areas Sub-regions Wind speed measurement Alkalinity Biogeochemistry Carbonation Chlorophyll Forecasting Remote sensing Satellites Self organizing maps Surface waters Uncertainty analysis Carbon dioxide air-sea interaction alkalinity biogeochemistry carbon cycle carbon dioxide coastal zone continental margin remote sensing satellite data sea surface temperature surface water timescale uncertainty analysis wind velocity Pacific Ocean Pacific Ocean (North) Saraceno, Martin Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific
topic_facet	Air sea flux Atmospheric CO Carbon cycling Carbonate system Coastal waters Continental margin Correlation coefficient Dissolved carbon dioxide Eastern north pacific Empirical coefficients Empirical relationships Historical observation Input parameter Linear dependence North American Root mean squared Satellite data Sea surface temperature (SST) Semiempirical models Space and time Sparse data sets Study areas Sub-regions Wind speed measurement Alkalinity Biogeochemistry Carbonation Chlorophyll Forecasting Remote sensing Satellites Self organizing maps Surface waters Uncertainty analysis Carbon dioxide air-sea interaction alkalinity biogeochemistry carbon cycle carbon dioxide coastal zone continental margin remote sensing satellite data sea surface temperature surface water timescale uncertainty analysis wind velocity Pacific Ocean Pacific Ocean (North)
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 CO 2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO 2 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 (T Alk )) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO 2 partial pressure (pCO 2 ) was calculated from the empirically-predicted TCO2 and T Alk . 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 370km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO 2 agreed with the highly variable observations with a root mean squared (RMS) deviation of <20μatm, and with a correlation coefficient of >0.8 (r=0.81; r 2 =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 pCO 2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14TgCyr -1 sink for atmospheric CO 2 over the 1997-2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5TgCyr -1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area. © 2012 Elsevier Ltd.
author	Saraceno, Martin
author_facet	Saraceno, Martin
author_sort	Saraceno, Martin
title	Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific
title_short	Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific
title_full	Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific
title_fullStr	Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific
title_full_unstemmed	Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific
title_sort	satellite-based prediction of pco 2 in coastal waters of the eastern north pacific
publishDate	2012
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00796611_v103_n_p1_Hales http://hdl.handle.net/20.500.12110/paper_00796611_v103_n_p1_Hales
work_keys_str_mv	AT saracenomartin satellitebasedpredictionofpco2incoastalwatersoftheeasternnorthpacific
_version_	1768542405287477248

Satellite-based prediction of pCO 2 in coastal waters of the eastern North Pacific

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