Dissolved organic matter at the fluvial–marine transition in the Laptev Sea using in situ data and ocean colour remote sensing

River water is the main source of dissolved organic carbon (DOC) in the Arctic Ocean. DOC plays an important role in the Arctic carbon cycle, and its export from land to sea is expected to increase as ongoing climate change accelerates permafrost thaw. However, transport pathways and transformation...

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Bibliographic Details
Published in:Biogeosciences
Main Authors: B. Juhls, P. P. Overduin, J. Hölemann, M. Hieronymi, A. Matsuoka, B. Heim, J. Fischer
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2019
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Online Access:https://doi.org/10.5194/bg-16-2693-2019
https://doaj.org/article/562030fe14934088960090a044cbb119
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Summary:River water is the main source of dissolved organic carbon (DOC) in the Arctic Ocean. DOC plays an important role in the Arctic carbon cycle, and its export from land to sea is expected to increase as ongoing climate change accelerates permafrost thaw. However, transport pathways and transformation of DOC in the land-to-ocean transition are mostly unknown. We collected DOC and a CDOM ( λ ) samples from 11 expeditions to river, coastal and offshore waters and present a new DOC– a CDOM ( λ ) model for the fluvial–marine transition zone in the Laptev Sea. The a CDOM ( λ ) characteristics revealed that the dissolved organic matter (DOM) in samples of this dataset are primarily of terrigenous origin. Observed changes in a CDOM (443) and its spectral slopes indicate that DOM is modified by microbial and photo-degradation. Ocean colour remote sensing (OCRS) provides the absorption coefficient of coloured dissolved organic matter ( a CDOM ( λ ) sat ) at λ =440 or 443 nm, which can be used to estimate DOC concentration at high temporal and spatial resolution over large regions. We tested the statistical performance of five OCRS algorithms and evaluated the plausibility of the spatial distribution of derived a CDOM ( λ ) sat . The OLCI (Sentinel-3 Ocean and Land Colour Instrument) neural network swarm (ONNS) algorithm showed the best performance compared to in situ a CDOM (440) ( r 2 =0.72 ). Additionally, we found ONNS-derived a CDOM (440), in contrast to other algorithms, to be partly independent of sediment concentration, making ONNS the most suitable a CDOM ( λ ) sat algorithm for the Laptev Sea region. The DOC– a CDOM ( λ ) model was applied to ONNS-derived a CDOM (440), and retrieved DOC concentration maps showed moderate agreement to in situ data ( r 2 =0.53 ). The in situ and satellite-retrieved data were offset by up to several days, which may partly explain the weak correlation for this dynamic region. Satellite-derived surface water DOC concentration maps from Medium Resolution Imaging Spectrometer (MERIS) ...