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Impacts of Climate Variability on Primary Productivity and Carbon Distributions in the Middle Atlantic Bight and Gulf of Maine (CliVEC)

Metadata Updated: February 21, 2025

Title: The Impacts of Climate Variability on Primary Productivity and Carbon Distributions in the Middle Atlantic Bight and Gulf of Maine (CliVEC)Research Team: Antonio Mannino (PI) - NASA GSFC Michael Novak - NASA GSFC Margaret Mulholland (co-PI) - Old Dominion University Peter Bernhardt - Old Dominion University CJ Staryk - Old Dominion University Kimberly Hyde (co-PI) - NOAA NEFSC Jon Hare (collaborator) - NOAA NEFSC David Lary (co-I) - University of Texas at DallasObservations from the MODIS and SeaWiFS time series (1997-2012) and measurements from an extensive field campaign are employed to examine how inter-annual and decadal-scale climate variability affects primary productivity and organic carbon distributions along the continental margin of the U.S. northeast coast. Estimates of daily primary productivity (PP) will be computed using the Ocean Productivity from Absorption of Light (OPAL) model. OPAL vertically resolves phytoplankton absorption of photosynthetically active radiation (PAR) and relates the chlorophyll-specific absorption coefficient to sea-surface temperature (SST), where SST is a proxy for seasonal changes in the phytoplankton community. OPAL will be validated with new field measurements of PP including dissolved organic carbon production.Field measurements of particulate (POC) and dissolved organic carbon (DOC) and the absorption coefficients of phytoplankton (aph) and colored dissolved organic matter (aCDOM) will allow us to extend the validation range (temporally and spatially) for our coastal algorithms and reduce the uncertainties in satellite-derived estimates of OPAL PP, POC, DOC, aph and aCDOM. Furthermore, we will apply our extensive field data to derive region-independent ocean color algorithms for PP, POC, DOC aCDOM and aph using machine learning approaches. We will rigorously validate and compare band-ratio and multivariate machine learning algorithms. Algorithms validated from this study will be applied to satellite observations to produce a time series of satellite data productsThe U.S. Middle Atlantic Bight (MAB), George's Bank (GB) and Gulf of Maine (GoM) stand at the crossroads between major ocean circulation features - the Gulf Stream and Labrador slope-sea and shelf currents - and are influenced by highly variable river discharge, summer upwelling, warm core rings, and intense seasonal stratification. Our work will focus on the impacts of variable river discharge, SST and large-scale climate indices on primary production, and POC and DOC distributions. These processes are not unique to the MAB and GoM. Consequently, the results from this activity can be applied to understanding how inter-annual and long-term variability in climate patterns can impact the carbon cycle of continental margins throughout the globe.

Access & Use Information

Public: This dataset is intended for public access and use. Non-Federal: This dataset is covered by different Terms of Use than Data.gov. License: No license information was provided.

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Dates

Metadata Created Date February 21, 2025
Metadata Updated Date February 21, 2025

Metadata Source

Harvested from nasa test json

Additional Metadata

Resource Type Dataset
Metadata Created Date February 21, 2025
Metadata Updated Date February 21, 2025
Publisher NASA/GSFC/SED/ESD/GCDC/OB.DAAC
Maintainer
Identifier C1633360191-OB_DAAC
Data First Published 2009-08-17
Language en-US
Data Last Modified 2025-02-19
Category geospatial
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 52208744-7d8a-4972-90e2-ec925f1d07e9
Harvest Source Id a73e0c30-4684-40ef-908e-d22e9e9e5f86
Harvest Source Title nasa test json
Homepage URL https://doi.org/10.5067/SeaBASS/CLIVEC/DATA001
Metadata Type geospatial
Old Spatial -180.0 -90.0 180.0 90.0
Program Code 026:001
Source Datajson Identifier True
Source Hash 9f274183f809657652e5bd30dc66175af53f704c1ffd38cdbec3fbb387b0377d
Source Schema Version 1.1
Spatial
Temporal 2009-08-17T00:00:02Z/2023-04-17T00:00:00Z

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