Discriminating water sources from space in the Arctic Ocean: A case study for the southern Beaufort Sea using MODIS ocean color and SMOS salinity data
A recent paper by Matsuoka et al. (2016), using SMOS ESA L2 SSS, found nice correlations between the interannual variability of SMOS SSS and ocean color CDOM (see fig 1 and 2 below) in the Mackenzie river mouth. Using this region as a case study, they derive an algorithm using this two sets of data for getting reasonable fractions of river water. As stated by the authors ‘Application of this algorithm may lead to the discrimination of water sources in the surface layer of the Arctic Ocean in various environments where seawater, ice melt water, and river water are intermingled,which might be useful to improve our understanding of physical and biogeochemical processes related to each water source’.
Fig.1 : Satellite images of CDOM absorption coefficient at 443 nm [aCDOM(443),m−1] using MODIS ocean color data in July to August 2010 to 2012 (from Matsuoka et al. (2016))
Fig. 2 : Same as Fig. 1 for SMOS SSS (from Matsuoka et al. (2016)).Atsushi Matsuoka, Marcel Babin, Emmanuel C. Devred, A new algorithm for discriminating water sources from space: A case study for the southern Beaufort Sea using MODIS ocean color and SMOS salinity data, Remote Sensing of Environment, Volume 184, October 2016, Pages 124-138, ISSN 0034-4257, http://dx.doi.org/10.1016/j.rse.2016.05.006. (//www.sciencedirect.com/science/article/pii/S0034425716301997)