A real-time coastal ocean prediction experiment for MREA04

Ko, Dong S.; Martin, Paul J.; Rowley, Clark; Preller, Ruth H.

doi:10.1016/j.jmarsys.2007.02.022

Cited by 82 publications

(54 citation statements)

References 19 publications

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“…Six such numerical ocean circulation models were available from different institutions: (1) the West Florida Shelf (WFS) model [Barth et al, 2008], (2) the Global Hybrid Coordinate Ocean Model (Global HYCOM [Chassignet et al, 2007]), (3) the Gulf of Mexico HYCOM (http:// www .hycom .org), (4) the South Atlantic Bight-Gulf of Mexico model (SABGOM [Hyun and He, 2010]), (5) the Real Time Ocean Forecast System for the North Atlantic Ocean (RTOFS [Mehra and Rivin, 2010]), and (6) the Intra-Americas Sea Nowcast/ Forecast System (IASNFS [Ko et al, 2008]). All but the RTOFS, which is an operational model of the U.S. National Oceanic and Atmospheric Administration (NOAA), include academic research partnerships (see the online supplement to this Eos issue (http:// www .agu .org/ eos _elec/)).…”

Section: Ensemble Models and Their Initializationmentioning

confidence: 99%

Tracking the Deepwater Horizon Oil Spill: A Modeling Perspective

et al. 2011

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The Deepwater Horizon oil spill was caused by a drilling rig explosion on 20 April 2010 that killed 11 people. It was the largest oil spill in U.S. history and presented an unprecedented threat to Gulf of Mexico marine resources. Although oil gushing to the surface diminished after the well was capped, on 15 July 2010, much remains to be known about the oil and the dispersants beneath the surface, including their trajectories and effects on marine life. A system for tracking the oil, both at the surface and at depth, was needed for mitigation efforts and ship survey guidance. Such a system was implemented immediately after the spill by marshaling numerical model and satellite remote sensing resources available from existing coastal ocean observing activities [e.g., Weisberg et al., 2009]. Analyzing this system's various strengths and weaknesses can help further improve similar systems designed for other emergency responses.

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Section: Ensemble Models and Their Initializationmentioning

confidence: 99%

Tracking the Deepwater Horizon Oil Spill: A Modeling Perspective

et al. 2011

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“…Near-real-time SSH maps were available during T-PARC/TCS-08 to monitor mesoscale ocean front and eddy activity, provided courtesy of the NRLStennis Space Center (Ko et al 2008). Shown in T-PARC/TCS-08 utilized the near-real-time OHC product in selecting locations to place aircraft-deployed airborne expendable bathythermograph (AXBT, probes that measure temperature from the surface down to 1,000 m) and floats/buoys with multiple sensors at depth to map mesoscale ocean features and to capture critical regions of air-sea interaction during TC conditions.…”

Section: Real-time Mission Planning Nowcasting and Forecast Supportmentioning

confidence: 99%

Supporting Meteorological Field Experiment Missions and Postmission Analysis with Satellite Digital Data and Products

Hawkins¹,

Velden²

2011

Bulletin of the American Meteorological Society

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“…The ocean circulation model used in this study is an application of the US Naval Research Laboratory's Ocean Nowcast/Forecast System [15] on the Louisiana Continental Shelf. The NRL Ocean Nowcast/Forecast System is an integration of a data-assimilating, dynamical ocean model, a statistical data-analysis model, and various data streams for ocean bathymetry, climatological data, surface forcing, open boundary forcing, and observations for data assimilation.…”

Section: Ocean Model Configurationmentioning

confidence: 99%

Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf

Gould

Penta

et al. 2016

Remote Sensing

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Abstract:We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability was missed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the Louisiana shelf, an important management metric, was substantially improved in comparison to observed hypoxic area by including the satellite data.

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A real-time coastal ocean prediction experiment for MREA04

Cited by 82 publications

References 19 publications

Tracking the Deepwater Horizon Oil Spill: A Modeling Perspective

Tracking the Deepwater Horizon Oil Spill: A Modeling Perspective

Supporting Meteorological Field Experiment Missions and Postmission Analysis with Satellite Digital Data and Products

Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf

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