New models for deriving and partitioning absorption coefficients of
colored dissolved organic matter in the global ocean
P. Shanmugam
Department of Ocean Engineering, Indian Institute of Technology Madras,
Chennai – 600036
Summary
Colored dissolved organic matter (CDOM) is a strong absorber of ultraviolet and blue light and a
key factor in the light-induced biogeochemical cycling of many components in surface waters.
Despite the importance of CDOM to such upper ocean processes and optics, our current
understanding of its spatial and temporal distributions and the factors controlling these
distributions is very limited. This eventually prevents our understanding of its relationship to the
pool of dissolved organic carbon in coastal and open oceans. Here we present new models for
deriving absorption coefficients of CDOM (aCDOM) and portioning its terrestrial and marine pools
in the global waters. The robustness of this new model was evaluated on the in-situ bio-optical
data sets collected in a variety of waters and also tested on the SeaWiFS images acquired over the
Northwest Pacific and global ocean waters. The accuracy of the estimates of absorption
coefficients of CDOM is generally excellent (Fig.1), although it deviates from the detrital
absorption coefficients (CDOM+detrital) generally retrieved by the standard algorithm applied to
SeaWiFS images. Applying the model to SeaWiFS images reveals the highest surface abundances
of CDOM within the subpolar gyres and along the continental shelves (Fig.2) dominated by
terrestrial inputs of colored dissolved materials and the lowest surface abundances of CDOM in
the central subtropical gyres and the open waters presumably regulated by photobleaching
phenomenon, biological activity and local oceanic processes. Large interseasonal changes in
CDOM absorption/distribution are also apparently consistent with recent satellite-based
assessments at global scale and significant interannual seasonal changes in (terrestrially-derived)
CDOM distribution closely correspond with increase of the global mean runoff and river
discharge induced by climate change/warming scenarios (Fig.3).
Fig. 1. Comparison between modeled and in-situ values of aCDOM (412) and relative error
distribution (right panels) for the IOCCG data set (N=656).
Fig.2. The aCDOM patterns in the North Atlantic inferred from the SeaWiFS images for the
winter (December-February), spring (March-May), summer (June-August) and autumn
(September-November) 1998.
Global cover
6
8.00x10
6
6.00x10
6
2
1.20x107
1.20x10
8
1.12x10
7
1.00x108
1.04x10
2
3 -1
Global
coverage area
River discharge
) )
(m s(km
Spring
Summer
Autumn
Summer
Summer
Autumn
Autumn
Summer
Summer
Period
Period
Autumn
Autumn
Summer
Autumn
Period
8
1.28x107
1.40x10
2
Global
Global
coverage
coverage
area (km
area)(km )
4.00x10
Winter
8
6
7
8.00x10
9.60x10
7
6
8.80x10
6.00x10
7
8.00x106
4.00x10
Winter
Winter
Spring
Spring
Period
Period
4
3.0x108
1.28x10
4
2.7x108
1.20x10
4
2.4x108
1.12x10
4
2.1x108
1.04x10
4
1.8x107
9.60x10
4
1.5x107
8.80x10
4
1.2x107
8.00x10
Winter
Winter
Spring
Spring
4
3
-1
River discharge (m s )
3.0x10
Fig. 3. Seasonal patterns of
the global coverage area with CDOM terrestrially transported
into the coastal seas via rivers4 and runoff from land and the observed seasonal river
2.7x10
discharge records.
4
2.4x10
4
2.1x10
4
1.8x10
4
1.5x10
4
1.2x10
Winter
Spring
Period