Dataset: Global cell abundance of picoeukaryotic phytoplankton, predicted by neural network models using average temperatures and nitrate from the World Ocean Atlas 2005

Name: Global cell abundance of picoeukaryotic phytoplankton, predicted by neural network models using average temperatures and nitrate from the World Ocean Atlas 2005
Published: 2019-12-04
Keywords: oceans

Final no updates expectedDOI: 10.1575/1912/bco-dmo.783537.1Version 1 (2019-12-04)Dataset Type:model results

Principal Investigator: Adam Martiny (University of California-Irvine)

Co-Principal Investigator: Pedro Flombaum (Universidad de Buenos Aires)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: Convergence: RAISE: Linking the adaptive dynamics of plankton with emergent global ocean biogeochemistry (Ocean Stoichiometry)

Abstract

Global cell abundance of picoeukaryotic phytoplankton, predicted by our neural network models using average temperatures and nitrate from the World Ocean Atlas 2005 (1°x1° resolution), and 8 d average PAR and K490 values derived from satellite data (SeaWiFS 0.083°x0.083°) and obtained as an output cells/ml for each set of conditions in a 1°x1° resolution.

Cite Dataset

Spatial Extent: N:90.00 E:180.00 S:-90.00 W:-180.00
Temporal Extent: -

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Each cell corresponds to a 1x1 cell grid
Files 90 to -90
Columns 1 to 360
Cell concentration: cells/ml
Land mask NAN

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