Southern Benguela shelf and open ocean seasonal mean nanophytoplankton proportion time series, 1997 to 2018 ...

Reconstructed seasonal mean nanophytoplankton proportion for SeaWiFS and MODIS-Aqua in the Southern Benguela (29-34.3°S;12-18.5°E) shelf and open ocean regions during austral summer, autumn, winter, and spring. Shelf and open ocean regions have been separated using the GEBCO 1000m isobath. ... : A p...

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Bibliographic Details
Main Authors: Tarron Lamont, R.G. Barlow, R.J.W. Brewin
Format: Dataset
Language:English
Published: Department of Forestry, Fisheries and the Environment 2019
Subjects:
historicalArchive
license
oceans
Bio-optical Investigation of Phytoplankton
SOUTH ATLANTIC OCEAN
remote sensing
bio-optics
phytoplankton biomass
BCLME
ASCLME
Benguela Current Large Marine Ecosystem
Agulhas and Somali Current Large Marine Ecosystems
nanophytoplankton
Southern Benguela
WGS 84
textTable
South Atlantic Ocean
Online Access:https://dx.doi.org/10.15493/dea.mims.10000008
https://api.odp.saeon.ac.za/catalog/MIMS/go/10.15493/DEA.MIMS.10000008
Description
Summary:Reconstructed seasonal mean nanophytoplankton proportion for SeaWiFS and MODIS-Aqua in the Southern Benguela (29-34.3°S;12-18.5°E) shelf and open ocean regions during austral summer, autumn, winter, and spring. Shelf and open ocean regions have been separated using the GEBCO 1000m isobath. ... : A phytoplankton size-class model (Lamont et al. 2018, RSE 204, 617-631) was applied to standard monthly-averaged SeaWiFS and MODIS-Aqua Chlorophyll a concentrations, with a spatial resolution of 9km, to compute fractional contributions of nanophytoplankton to the total chlorophyll a in Southern Benguela shelf and open ocean regions. The shelf and open ocean regions were separated using the 1000m GEBCO isobath. Seasonal means were computed by averaging data over a three-month period for each season, defined as austral summer (December, January, February), autumn (March, April, May), winter (June, July, August), and spring (September, October, November). Using the MODIS-Aqua data as the reference dataset, the SeaWiFS values were reconstructed (predicted) within the framework of a Generalized Linear Model, in order to remove the systematic bias between SeaWiFS and MODIS-Aqua values. This data has been processed and published as Lamont et al. (2019) JGR Oceans, 124, 1170-1195 ...

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