Development, Operation, and Results From the Texas Automated Buoy System

Bender, Leslie; Guinasso, Norman L.; Walpert, John N.; Lee, Linwood L.; Martín, Robert D.; Hetland, Robert D.; Baum, Steven K.; Howard, Matthew K.

doi:10.18785/goms.2501.04

Cited by 13 publications

(6 citation statements)

References 18 publications

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“…Los datos y análisis sobre los impactos del cambio climático en los servicios públicos y las infraestructuras de la región eran esporádicos, aunque en general abundaban las investigaciones, los datos y las proyecciones sobre temperatura, precipitaciones y otros indicadores físicos del clima sobre la tierra. Además, aunque se disponía de datos sobre la costa y alta mar para el Golfo de México procedentes del Sistema de Observación Oceánica Costera del Golfo de México 267 y del Sistema Automatizado de Boyas de Texas 268 , estos sistemas de observación no se establecieron para monitorear las tendencias climáticas a largo plazo (p. ej., acidificación marina e intrusión de agua salada), y por lo tanto había una escasez de literatura sobre cómo estos sistemas de observación ayudaron en la toma de decisiones para el cambio climático.…”

Section: Principales Incertidumbres Y Brechas En La Investigaciónunclassified

Cap. 26: Grandes Llanuras del Sur. En: La Quinta Evaluación del Clima

2023

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Section: Principales Incertidumbres Y Brechas En La Investigaciónunclassified

Cap. 26: Grandes Llanuras del Sur. En: La Quinta Evaluación del Clima

2023

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“…SCOOP also demonstrated that the relationship between basic research and applications can and must be bidirectional. Research by operational projects must assess and demonstrate scientific model skill to support operational needs, while simultaneously conducting critical assessments to improve current operational models such as the sea, lake, and overland surges from hurricanes (SLOSH) model [11].…”

Section: Scoop: a Launch Pad For Testbed Developmentmentioning

confidence: 99%

“…A SCOOP Education Virtual Appliance developed by the University of Florida enhanced the ability of scientists and non-scientists to understand the primary factors influencing coastal and estuarine processes. SCOOP partnered with the Gulf of Mexico Coastal Ocean Observing System and this interaction was critical in transferring research results to benefit those running GNOME (General NOAA Operational Modeling Environment), a modeling tool used by NOAA's Office of Response and Restoration [11].…”

Section: Community Engagementmentioning

confidence: 99%

The Evolution and Outcomes of a Collaborative Testbed for Predicting Coastal Threats

Nichols¹,

Wright

2020

JMSE

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Beginning in 2003, the Southeastern Universities Research Association (SURA) enabled an open-access network of distributed sensors and linked computer models through the SURA Coastal Ocean Observing and Predicting (SCOOP) program. The goal was to support collaborations among universities, government, and industry to advance integrated observation and modeling systems. SCOOP improved the path to operational real-time data-guided predictions and forecasts of coastal ocean processes. This was critical to the maritime infrastructure of the U.S. and to the well-being of coastal communities. SCOOP integrated and expanded observations from the Gulf of Mexico, the South Atlantic Bight, the Middle Atlantic Bight, and the Chesapeake Bay. From these successes, a Coastal and Ocean Modeling Testbed (COMT) evolved with National Oceanic and Atmospheric Administration (NOAA) funding via the Integrated Ocean Observing System (IOOS) to facilitate the transition of key models from research to operations. Since 2010, COMT has been a conduit between the research community and the federal government for sharing and improving models and software tools. SCOOP and COMT have been based on strong partnerships among universities and U.S. agencies that have missions in ocean and coastal environmental prediction. During SURA’s COMT project, which ended September 2018, significant progress was made in evaluating the performance of models that are progressively becoming operational. COMT successes are ongoing.

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“…National Buoy Data Center (NDBC; https://www.ndbc.noaa.gov/) and Texas Automated Buoys System (TABS; http://tabs.gerg.tamu.edu) both maintain an array of buoys in the Gulf of Mexico which record bulk meteorological and oceanographic parameters that are made publically available in near real time. TABS is funded by the Texas General Land Office and managed and operated by the Geochemical Environmental Research Group at Texas A&M University (Bender et al, ). The data are collected for the primary purpose of aiding oil spill response.…”

Section: Datamentioning

confidence: 99%

Tropical Cyclone Heat Potential and the Rapid Intensification of Hurricane Harvey in the Texas Bight

2019

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Harvey entered the Gulf of Mexico as a tropical depression on 23 August 2017; two days later it had strengthened to a category 1 hurricane. Over the following 30 hr Harvey rapidly intensified, reaching the Texas Bight as a category 3 storm. This intensification continued while Harvey crossed the shelf, making landfall as a category 4 storm 60 km east of Corpus Christi, TX on 26 August. A hydrographic survey two weeks prior to landfall shows that the tropical cyclone heat potential across the Texas Bight was approximately 35 kJ/cm2, which is 55 kJ/cm2 less than the amount of upper ocean heat normally associated with intensification. Combined with buoy, float, and satellite data, we use hydrographic surveys to study the conditions of the Texas Bight that contributed to Harvey's rapid intensification. We find that, at the time of landfall, the Texas Bight was well mixed with very warm water extending from the surface to bottom. As a consequence, mixing induced by Harvey had a small impact on surface temperatures which remained high and supported continued intensification. The results show that tropical cyclone heat potential is not an effective metric for hurricane intensity prediction in shallow water, and illustrate the need for continuous subsurface monitoring in order to improve hurricane forecasts.

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Development, Operation, and Results From the Texas Automated Buoy System

Cited by 13 publications

References 18 publications

Cap. 26: Grandes Llanuras del Sur. En: La Quinta Evaluación del Clima

Cap. 26: Grandes Llanuras del Sur. En: La Quinta Evaluación del Clima

The Evolution and Outcomes of a Collaborative Testbed for Predicting Coastal Threats

Tropical Cyclone Heat Potential and the Rapid Intensification of Hurricane Harvey in the Texas Bight

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