English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/131416
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

A remote sensing algorithm for planktonic dimethylsulfoniopropionate (DMSP) and an analysis of global patterns

AutorGalí, Martí ; Devred, Emmanuel; Levasseur, Maurice; Royer, S.-J. ; Babin, Marcel
Palabras claveDimethylsulfoniopropionate
Sulfur cycle
Particulate inorganic carbon
Fecha de publicacióndic-2015
CitaciónRemote Sensing of Environment 171: 171-184 (2015)
ResumenDimethylsulfoniopropionate (DMSP) is a ubiquitous phytoplankton metabolite and the main precursor of the climate-active gas dimethylsulfide (DMS) in the oceans' surface. Here we use total DMSP (DMSPt) and ancillary measurements from a global database to develop a remote sensing algorithm for DMSPt in the upper mixed layer (UML). Over 55% of total DMSPt variability (log scale) is explained by in situ chlorophyll a (Chl) after dividing the database into two subsets, according to >stratified> and >mixed> water column criteria, based on the ratio between euphotic layer depth (Z) and mixed layer depth (MLD). Up to 70% of the variability is explained when adding sea surface temperature (SST) and log(Z/MLD) as predictors for the stratified and mixed subsets, respectively. Independent validation on satellite Chl match-ups indicates that the algorithm predicts DMSPt across three orders of magnitude with a root-mean-squared error spanning from 0.20 to 0.26 (log space) and mean absolute error typically around 45% (linear space). An additional submodel based on remotely sensed particulate inorganic carbon (PIC) is used to predict DMSPt in coccolithophore blooms if satellite Chl is not available. We use the algorithm to produce a monthly global DMSPt climatology, and estimate that DMSP synthesis amounts to 5-9% of oceanic phytoplankton gross carbon production. Our algorithm provides a new remote sensing tool for resolving temporal and spatial variations in DMSPt concentration, and represents a step forward toward improved diagnosis of contemporary DMS emission based on satellite Earth observation
Descripción14 pages, 9 figures, 2 tables, supplementary data http://dx.doi.org/10.1016/j.rse.2015.10.012
Versión del editorhttp://dx.doi.org/10.1016/j.rse.2015.10.012
Identificadoresdoi: 10.1016/j.rse.2015.10.012
issn: 0034-4257
e-issn: 1879-0704
Aparece en las colecciones: (ICM) Artículos
Ficheros en este ítem:
No hay ficheros asociados a este ítem.
Mostrar el registro completo

Artículos relacionados:

NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.