dc.contributor.author
Juhls, Bennet
dc.contributor.author
Overduin, Pier Paul
dc.contributor.author
Hölemann, Jens
dc.contributor.author
Hieronymi, Martin
dc.contributor.author
Matsuoka, Atsushi
dc.contributor.author
Heim, Birgit
dc.contributor.author
Fischer, Jürgen
dc.date.accessioned
2019-08-01T08:45:01Z
dc.date.available
2019-08-01T08:45:01Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/25186
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-3891
dc.description.abstract
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 aCDOM(λ) samples from 11 expeditions to river, coastal and offshore waters and present a new DOC–aCDOM(λ) model for the fluvial–marine transition zone in the Laptev Sea. The aCDOM(λ) characteristics revealed that the dissolved organic matter (DOM) in samples of this dataset are primarily of terrigenous origin. Observed changes in aCDOM(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 (aCDOM(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 aCDOM(λ)sat. The OLCI (Sentinel-3 Ocean and Land Colour Instrument) neural network swarm (ONNS) algorithm showed the best performance compared to in situ aCDOM(440) (r2=0.72). Additionally, we found ONNS-derived aCDOM(440), in contrast to other algorithms, to be partly independent of sediment concentration, making ONNS the most suitable aCDOM(λ)sat algorithm for the Laptev Sea region. The DOC–aCDOM(λ) model was applied to ONNS-derived aCDOM(440), and retrieved DOC concentration maps showed moderate agreement to in situ data (r2=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) satellite data demonstrate rapid removal of DOC within short time periods in coastal waters of the Laptev Sea, which is likely caused by physical mixing and different types of degradation processes. Using samples from all occurring water types leads to a more robust DOC–aCDOM(λ) model for the retrievals of DOC in Arctic shelf and river waters.
en
dc.format.extent
21 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
ocean colour remote sensing
en
dc.subject
dissolved organic matter
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie::550 Geowissenschaften
dc.title
Dissolved organic matter at the fluvial–marine transition in the Laptev Sea using in situ data and ocean colour remote sensing
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.5194/bg-16-2693-2019
dcterms.bibliographicCitation.journaltitle
Biogeosciences
dcterms.bibliographicCitation.pagestart
2693
dcterms.bibliographicCitation.pageend
2713
dcterms.bibliographicCitation.volume
16
dcterms.bibliographicCitation.url
https://doi.org/10.5194/bg-16-2693-2019
refubium.affiliation
Geowissenschaften
refubium.affiliation.other
Institut für Weltraumwissenschaften
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin und der DFG gefördert.
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
1726-4170
dcterms.isPartOf.eissn
1726-4189
refubium.resourceType.provider
WoS-Alert