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Application of satellite remote sensing techniques for estimating air–sea CO2 fluxes in Hudson Bay, Canada during the ice-free season

Authors :
Else, Brent G.T.
Yackel, John J.
Papakyriakou, Tim N.
Source :
Remote Sensing of Environment. Sep2008, Vol. 112 Issue 9, p3550-3562. 13p.
Publication Year :
2008

Abstract

Abstract: The role of coastal seas as either a sink or a source of CO2 is subject to a great deal of uncertainty. This uncertainty largely arises from a lack of observations in the coastal zones. Remote sensing offers an avenue for expanding these observations by allowing for the extrapolation of relatively limited data sets of dissolved CO2 (pCO2sw). In this paper, predictive algorithms for pCO2sw that could be applied to remote sensing products were created from a field data set collected from September–October, 2005 in Hudson Bay, Canada. The field data showed that an effective pCO2sw interpolation algorithm could be created using sea surface temperature (SST) as a predictor, and that a slight improvement of the algorithm could be achieved if measurements of absorption due to coloured dissolved organic material (a CDOM) were included. Unfortunately, satellite retrievals of a CDOM did not match well with in situ observations, and so only SST (obtained from the MODIS Aqua sensor) was used to create monthly maps of pCO2sw for the period of August–October. To estimate fluxes of CO2, constructed surfaces of pCO2sw were combined with estimates of gas transfer velocity derived from QuikSCAT wind retrievals, and pCO2air based on field observations. The results of these calculations revealed that Hudson Bay acts as a source of CO2 during August and September, but reverts to a sink of CO2 in October as the water temperature decreases. Overall, a positive flux of 1.60 TgC was estimated for the region during the ice-free season. This result is in contrast to most Arctic or sub-Arctic continental shelf seas, where usually strong absorptions of CO2 are observed. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00344257
Volume :
112
Issue :
9
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
33529189
Full Text :
https://doi.org/10.1016/j.rse.2008.04.013