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Dataset: GMx_CDOM
Deployment: PE07-32

Absorption spectra and DOC concentrations
Principal Investigator: 
Chris Osburn (North Carolina State University - Marine, Earth and Atmospheric Sciences, NCSU MEAS)
BCO-DMO Data Manager: 
Cynthia L. Chandler (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Project: 
Current State: 
Final with updates expected
Version: 
26 August 2010
Version Date: 
2010-08-26
Description

Geospatial Synthesis of Chromophoric (color-absorbing) Dissolved Organic Matter (CDOM) Distribution in the Gulf of Mexico

PI: Christopher Osburn, Dept. Marine, Earth, and Atmospheric Sciences, NC State University

Co-PIs: Thomas Bianchi, Texas A&M University, Bob Chen, University of Massachusetts-Boston; Paula Coble, University of South Florida; Eurico D'Sa, Louisiana State University

This dataset is affiliated with the North American Carbon Program (NACP). For additional information, please see the entry at the NACP site.

This data set will be a synthesis of bio-optical data on chromophoric or color-absorbing dissolved organic matter (CDOM) in the coastal regions the Gulf of Mexico - an immediate goal of the NACP and OCB programs. Absorption spectra and DOC concentrations from the Organic Matter Cycli project will be reported. In addition to in situ absorption spectra and DOC concentrations some study locations may also report fluorescence (estimate of chlorophyll a concentration), plus CTD and dissolved oxygen measurements

CDOM affects on water quality and water clarity are part of a high priority issue identified by the Gulf of Mexico Alliance (GOMA). Each of the PI's listed has historical CDOM data from coastal regions of the Gulf of Mexico, ranging from the Texas coast to West Florida Shelf.

The historic CDOM synthesis data set will provide a resource for validating remote sensing algorithms that predict water clarity properties in the coastal areas of the Gulf of Mexico. Each dataset to be shared by a PI is linked to specific research cruises. Thus the database has temporal and spatial coverage and associated metadata. In Years 1-2 of the project, data will be collated from each PI and transformed into a format amenable to data rescue by BCO-DMO. The structure of the resulting database will provide a mechanism by which future data sets may be integrated by members of the scientific community, through the project. In Year 2, as data comes online, it will be used to validate a coastal CDOM remote sensing algorithm for the Gulf of Mexico. Co-PI D'Sa has a decision support science website (http://gulf-coast.lsu.edu/index.html) that will provide water clarity data products based on CDOM algorithms.

The goal of the project is to have a functional database of CDOM information for two objectives. One objective is to provide coastal oceanographers with a clearinghouse for CDOM data that can be accessed and to which future cruise-related data acquisitions can be added. The second objective is to provide a resource for decision makers who require water clarity data on spatial and time scales for which satellite imagery may be used. For the second goal to be met, we have as an objective the validation of CDOM algorithms using the proposed database. Once the algorithm is validated, water clarity data products can be generated by users using the GCIS website, which will link to the CDOM database hosted by BCO-DMO.

The CDOM database will also provide pilot data for research proposals to NSF from our team. Part of our evolving project is to produce geospatial models of CDOM distributions in the Gulf of Mexico from the inflows of multiple rivers as well as the Loop Current. Functional models of CDOM distributions will further aid in remote sensing algorithm development and validation and in the general understanding of terrestrial C flux to the Gulf of Mexico.

Modification History:
September 2010: added processed Atchafalaya data from Chris Osburn
December 2010: raw/unprocessed Mississippi Plume absorption coefficients were added but then quickly removed
June 2011: added processed Mississippi Plume data from Bob Chen; a_lambda units corrected to "per meter" (had been incorrectly specified as "per nanometer" in earlier version)

More information about this dataset deployment