Richard P Signell, Ph.D. (Former Employee)
Science and Products
Filter Total Items: 90
IOOS modeling subsystem: vision and implementation strategy IOOS modeling subsystem: vision and implementation strategy
Numerical modeling is vital to achieving the U.S. IOOS® goals of predicting, understanding and adapting to change in the ocean and Great Lakes. In the next decade IOOS should cultivate a holistic approach to coastal ocean prediction, and encourage more balanced investment among the observing, modeling and information management subsystems. We believe the vision of a prediction framework
Authors
Leslie Rosenfeld, Yi Chao, Richard P. Signell
Priorities for IOOS® Data Management and Communications (DMAC) Priorities for IOOS® Data Management and Communications (DMAC)
Dramatic increases in the volume of online data and rapid advances in information technology have transformed many aspects of our society. In the coastal ocean, the amount of data is also growing dramatically due to new sensor and modeling technologies. Lagging behind this deluge of ocean data, however, is an effective framework of standards, protocols, tools and culture needed to...
Authors
Corrine Alexander, Joan Thomas, K. Benedict, W. Johnson, R. Morrison, J. Andrechik, E. Stabenau, M. Gierach, K. Casey, Richard P. Signell, H. Norris, R. Proctor, K. Kirby, D. Snowden, J. de La Beaujardière, E. Howlett, S. Uczekaj, K. Narasimhan, E. Key, M. Trice, J. Fredericks
Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database
The U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database contains estimates of bottom stress and sediment mobility for the U.S. continental shelf. This U.S. Geological Survey database provides information that is needed to characterize sea floor ecosystems and evaluate areas for human use. The estimates contained in the database are designed to spatially and seasonally...
Authors
P. Soupy Dalyander, Bradford Butman, Christopher R. Sherwood, Richard P. Signell
Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023 Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023
Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that grew out of the 2007 Science Strategy, “Facing Tomorrow’s Challenges: U.S. Geological Survey Science in the Decade 2007–2017.” This report describes the vision for this USGS mission and outlines a strategy for Core Science Systems to facilitate integrated characterization and understanding of the complex...
Authors
R. Sky Bristol, Ned H. Euliss, Nathaniel L. Booth, Nina Burkardt, Jay E. Diffendorfer, Dean B. Gesch, Brian E. McCallum, David M. Miller, Suzette A. Morman, Barbara S. Poore, Richard P. Signell, Roland J. Viger
Building transparent data access for ocean observatories: Coordination of U.S. IOOS DMAC with NSF's OOI Cyberinfrastructure Building transparent data access for ocean observatories: Coordination of U.S. IOOS DMAC with NSF's OOI Cyberinfrastructure
The NOAA-led U.S. Integrated Ocean Observing System (IOOS) and the National Science Foundation's Ocean Observatories Initiative (OOI) have been collaborating since 2007 on advanced tools and technologies that ensure open access to ocean observations and models. Initial collaboration focused on serving ocean data via cloud computing-a key component of the OOI cyberinfrastructure (CI)...
Authors
M. Arrott, Corrine Alexander, J. Graybeal, C. Mueller, R. Signell, J. de La Beaujardière, A. Taylor, J. Wilkin, B. Powell, J. Orcutt
Serving ocean model data on the cloud Serving ocean model data on the cloud
The NOAA-led Integrated Ocean Observing System (IOOS) and the NSF-funded Ocean Observatories Initiative Cyberinfrastructure Project (OOI-CI) are collaborating on a prototype data delivery system for numerical model output and other gridded data using cloud computing. The strategy is to take an existing distributed system for delivering gridded data and redeploy on the cloud, making...
Authors
Michael Meisinger, Claudiu Farcas, Emilia Farcas, Charles Alexander, Matthew Arrott, Jeff de La Beaujardiere, Paul Hubbard, Roy Mendelssohn, Richard P. Signell
Science and Products
Filter Total Items: 90
IOOS modeling subsystem: vision and implementation strategy IOOS modeling subsystem: vision and implementation strategy
Numerical modeling is vital to achieving the U.S. IOOS® goals of predicting, understanding and adapting to change in the ocean and Great Lakes. In the next decade IOOS should cultivate a holistic approach to coastal ocean prediction, and encourage more balanced investment among the observing, modeling and information management subsystems. We believe the vision of a prediction framework
Authors
Leslie Rosenfeld, Yi Chao, Richard P. Signell
Priorities for IOOS® Data Management and Communications (DMAC) Priorities for IOOS® Data Management and Communications (DMAC)
Dramatic increases in the volume of online data and rapid advances in information technology have transformed many aspects of our society. In the coastal ocean, the amount of data is also growing dramatically due to new sensor and modeling technologies. Lagging behind this deluge of ocean data, however, is an effective framework of standards, protocols, tools and culture needed to...
Authors
Corrine Alexander, Joan Thomas, K. Benedict, W. Johnson, R. Morrison, J. Andrechik, E. Stabenau, M. Gierach, K. Casey, Richard P. Signell, H. Norris, R. Proctor, K. Kirby, D. Snowden, J. de La Beaujardière, E. Howlett, S. Uczekaj, K. Narasimhan, E. Key, M. Trice, J. Fredericks
Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database
The U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database contains estimates of bottom stress and sediment mobility for the U.S. continental shelf. This U.S. Geological Survey database provides information that is needed to characterize sea floor ecosystems and evaluate areas for human use. The estimates contained in the database are designed to spatially and seasonally...
Authors
P. Soupy Dalyander, Bradford Butman, Christopher R. Sherwood, Richard P. Signell
Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023 Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023
Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that grew out of the 2007 Science Strategy, “Facing Tomorrow’s Challenges: U.S. Geological Survey Science in the Decade 2007–2017.” This report describes the vision for this USGS mission and outlines a strategy for Core Science Systems to facilitate integrated characterization and understanding of the complex...
Authors
R. Sky Bristol, Ned H. Euliss, Nathaniel L. Booth, Nina Burkardt, Jay E. Diffendorfer, Dean B. Gesch, Brian E. McCallum, David M. Miller, Suzette A. Morman, Barbara S. Poore, Richard P. Signell, Roland J. Viger
Building transparent data access for ocean observatories: Coordination of U.S. IOOS DMAC with NSF's OOI Cyberinfrastructure Building transparent data access for ocean observatories: Coordination of U.S. IOOS DMAC with NSF's OOI Cyberinfrastructure
The NOAA-led U.S. Integrated Ocean Observing System (IOOS) and the National Science Foundation's Ocean Observatories Initiative (OOI) have been collaborating since 2007 on advanced tools and technologies that ensure open access to ocean observations and models. Initial collaboration focused on serving ocean data via cloud computing-a key component of the OOI cyberinfrastructure (CI)...
Authors
M. Arrott, Corrine Alexander, J. Graybeal, C. Mueller, R. Signell, J. de La Beaujardière, A. Taylor, J. Wilkin, B. Powell, J. Orcutt
Serving ocean model data on the cloud Serving ocean model data on the cloud
The NOAA-led Integrated Ocean Observing System (IOOS) and the NSF-funded Ocean Observatories Initiative Cyberinfrastructure Project (OOI-CI) are collaborating on a prototype data delivery system for numerical model output and other gridded data using cloud computing. The strategy is to take an existing distributed system for delivering gridded data and redeploy on the cloud, making...
Authors
Michael Meisinger, Claudiu Farcas, Emilia Farcas, Charles Alexander, Matthew Arrott, Jeff de La Beaujardiere, Paul Hubbard, Roy Mendelssohn, Richard P. Signell