Difference between revisions of "Measures2006"
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| − | < | + | <p>'''NASA MEaSUREs Ocean Color Product Evaluation Project'''<br> |
| + | ''Produce, evaluate & distribute advanced ocean color data products''<br></p> | ||
| + | <p><br></p> | ||
| + | <p><big><b>Beyond Chlorophyll: Management, Implementation and Distribution of Innovative Ocean Color Earth Science Data Records</b></big></p> | ||
| + | <p><br></p> | ||
| + | <p>PIs: [http://www.crseo.ucsb.edu/~stephane/StephaneHomePage.html Stéphane Maritorena], [http://www.icess.ucsb.edu/~davey/ Dave Siegel], [http://essw.bren.ucsb.edu/~frew/ Jim Frew], [http://www.icess.ucsb.edu/~norm/ Norm Nelson] (UCSB) and [http://www.science.oregonstate.edu/bpp/faculty/Behrenfeld/index.html Mike Behrenfeld] (OSU)</p> | ||
| + | <p><br></p> | ||
| + | <p>''Project Summary'':</p> | ||
| − | + | <p>Satellite ocean color data products are all too frequently relegated to a single, unique product, the chlorophyll concentration. However, ocean color signals (the normalized water-leaving radiance spectra, LwN(λ)) contain information describing the concentrations and type of suspended particulate and dissolved materials, the composition of the phytoplankton community and the productivity of the water column. Over the past decade many new satellite ocean color science data products have been introduced which are transforming our understanding of ocean biological and biogeochemical processes.</p> | |
| − | <p>< | + | <p>The implementation, distribution and management of these innovative ocean color data records are fraught with difficulties – at least by existing structures. First, there is a large suite of products that qualify as ocean color Earth Science Data Records (OC-ESDR’s). Existing data centers, such as the NASA Ocean Biology Processing Group (OBPG), need to be focused on the primary objective of providing the highest quality LwN(λ) and chlorophyll determinations from the suite of available satellite sensors. Second, existing data centers are not well suited to quickly handle the rapid rate of new innovative algorithms and products as is occurring today. The plethora of possibilities along with the large volume of data and the complex algorithms to implement is a huge load for a single group to handle (no matter how capable). Further, it is also necessary to constantly characterize the generated products and rapidly assess changes that may result from either versions of the input data stream (here LwN(λ)) or from updated OC-ESDR algorithms. These difficulties all act to limit the wide use of innovative OC-ESDR’s. Last, a decentralization of ocean color data product creation and dissemination is healthy as individual groups with different background and vision can make their unique contribution to the OC-ESDR’s available. </p> |
| + | <p> Here, we propose to implement a small scale ocean color data center (μDAAC) capable of processing and distributing a broad suite of OC-ESDR’s, some of them from merging of multiple sensors, while nimble enough to successfully manage scientific innovation. | ||
| + | <ul> | ||
| + | <li>Create and distribute a variety of established OC-ESDR’s ranging from ocean optical properties and phytoplankton functional groups to phytoplankton growth rates and carbon-based productivity, </li> | ||
| + | <li>Implement and distribute quality indices for these OC-ESDR’s so users know what they are getting and how it relates to previous versions of the products, similar satellite data products and in situ data sets, </li> | ||
| + | <li>Update the suite of OC-ESDR’s distributed in consultation with our advisory board and data users, and </li> | ||
| + | <li>Track and manage algorithm and data lineage throughout the process and implement methods for automatically informing users of updated products or analyses.</li></ul></p> | ||
| + | <p>Our proposed implementation of an OC-ESDR μDAAC builds on our experience in satellite data system research (ReASON; Frew, Siegel & Maritorena), in the development and implementation of novel satellite ocean color algorithms (Maritorena, Siegel & Behrenfeld) and in the acquisition and application of field-based calibration / validation data (Nelson, Maritorena, Siegel & Behrenfeld). The OC-ESDR μDAAC will be implemented in collaboration with the GSFC Ocean Biology Processing Group – providing added value to their efforts and to ours. It is our hope that the true value of scientific innovation possible with NASA Earth science data can be realized through the development of small, focused data centers cooperating with existing NASA data centers. </p> | ||
| + | |||
| + | |||
| + | |||
| + | <p>This project is part of the '''M'''aking '''E'''arth '''S'''cience Data Records for '''U'''se in '''R'''esearch '''E'''nvironments ([http://measures-projects.gsfc.nasa.gov/ MEaSUREs]) initiative of NASA. | ||
| + | </p> | ||
Revision as of 15:58, 21 May 2009
NASA MEaSUREs Ocean Color Product Evaluation Project
Produce, evaluate & distribute advanced ocean color data products
Beyond Chlorophyll: Management, Implementation and Distribution of Innovative Ocean Color Earth Science Data Records
PIs: Stéphane Maritorena, Dave Siegel, Jim Frew, Norm Nelson (UCSB) and Mike Behrenfeld (OSU)
Project Summary:
Satellite ocean color data products are all too frequently relegated to a single, unique product, the chlorophyll concentration. However, ocean color signals (the normalized water-leaving radiance spectra, LwN(λ)) contain information describing the concentrations and type of suspended particulate and dissolved materials, the composition of the phytoplankton community and the productivity of the water column. Over the past decade many new satellite ocean color science data products have been introduced which are transforming our understanding of ocean biological and biogeochemical processes.
The implementation, distribution and management of these innovative ocean color data records are fraught with difficulties – at least by existing structures. First, there is a large suite of products that qualify as ocean color Earth Science Data Records (OC-ESDR’s). Existing data centers, such as the NASA Ocean Biology Processing Group (OBPG), need to be focused on the primary objective of providing the highest quality LwN(λ) and chlorophyll determinations from the suite of available satellite sensors. Second, existing data centers are not well suited to quickly handle the rapid rate of new innovative algorithms and products as is occurring today. The plethora of possibilities along with the large volume of data and the complex algorithms to implement is a huge load for a single group to handle (no matter how capable). Further, it is also necessary to constantly characterize the generated products and rapidly assess changes that may result from either versions of the input data stream (here LwN(λ)) or from updated OC-ESDR algorithms. These difficulties all act to limit the wide use of innovative OC-ESDR’s. Last, a decentralization of ocean color data product creation and dissemination is healthy as individual groups with different background and vision can make their unique contribution to the OC-ESDR’s available.
Here, we propose to implement a small scale ocean color data center (μDAAC) capable of processing and distributing a broad suite of OC-ESDR’s, some of them from merging of multiple sensors, while nimble enough to successfully manage scientific innovation.
- Create and distribute a variety of established OC-ESDR’s ranging from ocean optical properties and phytoplankton functional groups to phytoplankton growth rates and carbon-based productivity,
- Implement and distribute quality indices for these OC-ESDR’s so users know what they are getting and how it relates to previous versions of the products, similar satellite data products and in situ data sets,
- Update the suite of OC-ESDR’s distributed in consultation with our advisory board and data users, and
- Track and manage algorithm and data lineage throughout the process and implement methods for automatically informing users of updated products or analyses.
Our proposed implementation of an OC-ESDR μDAAC builds on our experience in satellite data system research (ReASON; Frew, Siegel & Maritorena), in the development and implementation of novel satellite ocean color algorithms (Maritorena, Siegel & Behrenfeld) and in the acquisition and application of field-based calibration / validation data (Nelson, Maritorena, Siegel & Behrenfeld). The OC-ESDR μDAAC will be implemented in collaboration with the GSFC Ocean Biology Processing Group – providing added value to their efforts and to ours. It is our hope that the true value of scientific innovation possible with NASA Earth science data can be realized through the development of small, focused data centers cooperating with existing NASA data centers.
This project is part of the Making Earth Science Data Records for Use in Research Environments (MEaSUREs) initiative of NASA.
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