A mechanistic semi-analytical method for remotely sensing sea surface pCO2 in river-dominated coastal oceans: A case study from the East China Sea

While satellite remote sensing has become a very useful tool contributing to assessments of sea surface partial pressure of carbon dioxide (pCO2) that subsequently allow quantification of air‐sea CO2 flux, the application of empirical approaches in coastal oceans has proven challenging owing to the...

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Bibliographic Details
Published in:Journal of geophysical research. Oceans 2015-03, Vol.120 (3), p.2331-2349
Main Authors: Bai, Yan, Cai, Wei-Jun, He, Xianqiang, Zhai, Weidong, Pan, Delu, Dai, Minhan, Yu, Peisong
Format: Article
Language:English
Subjects:
Algorithms
Alkalinity
aquatic pCO2
aquatic pCO2, satellite remote sensing, semi‐analytic algorithm, marine carbonate system
Biogeochemistry
Biological effects
Biology
Carbon dioxide
Carbon dioxide flux
Carbonates
Case studies
Chlorophyll
Chlorophyll a
Coastal environments
Coefficients
Components
Data processing
Dissolved inorganic carbon
Drawdown
East China Sea
Empirical analysis
Geophysics
Inorganic carbon
Integrals
marginal sea
Marine biology
marine carbonate system
Mathematical analysis
Mathematical models
Oceans
Partial pressure
Remote sensing
Rivers
Salinity
Salinity effects
Satellite data
Satellite observation
satellite remote sensing
Satellites
Sea surface
Sea surface temperature
semi-analytic algorithm
Sensitivity analysis
Temperature
Temperature effects
Thermodynamics
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Summary:While satellite remote sensing has become a very useful tool contributing to assessments of sea surface partial pressure of carbon dioxide (pCO2) that subsequently allow quantification of air‐sea CO2 flux, the application of empirical approaches in coastal oceans has proven challenging owing to the interaction of multiple controlling factors. We propose a “mechanistic semi‐analytic algorithm” (MeSAA) to estimate sea surface pCO2 in river‐dominated coastal oceans using satellite data. Observed pCO2 can be analytically expressed as the sum of individual components controlled by major factors such as thermodynamics (or temperature), mixing, and biology. With marine carbonate system calculations, temperature and mixing effects can be predicted using thermodynamic principles and by assuming conservative two end‐member mixing of total dissolved inorganic carbon and total alkalinity (e.g., the Changjiang River and Kuroshio water in the East China Sea, ECS). Next, an integral expression for pCO2 drawdown due to biological effects can be parameterized using the chlorophyll a concentration (chla). We demonstrate the validity and applicability of the algorithm in the ECS during summertime. Sensitivity analysis shows that errors in empirical coefficients and three input satellite parameters (salinity, SST, chla) have limited influence on the algorithm, and satellite‐derived pCO2 is consistent with underway data, even though no in situ pCO2 data from the ECS shelves was used to train the algorithm. Our algorithm has more physical and biogeochemical mechanistic meaning than empirical methods, and should be applicable to other similar systems. Key Points: A semi‐analytic algorithm for satellite‐derived pCO2 in the East China Sea Carbonate calculations with satellite‐derived salinity used as a mixing index Biological effect on pCO2 is parameterized by an integral expression of chla
ISSN:2169-9275
2169-9291
DOI:10.1002/2014JC010632