A new pre-operational model of circulation over the Texas-Louisiana continental shelf and slope, based on the Regional Ocean Modelling System (ROMS) is presented. The model is designed with a number of practical applications in mind: to predict oil spill trajectories, investigate the mechanisms controlling seasonal hypoxia, and to understand the origins of harmful algal blooms on the Texas-Louisiana continental shelf and slope. This model consists of two parts: the hindcast and pre-operational components. The hindcast model is forced with the observed freshwater fluxes from the nine major Texas and Louisiana rivers, surface winds, and heat and salt fluxes from North American Regional Reanalysis (NARR) dataset. The hindcast simulations are carried out over an eight-year period (February 2003June 2011). The pre-operational model, which provides nowcast and a five-day forecast, starts from July 2011 with a different surface momentum and heat flux forcing from the Global Forecast System (GFS). Both hindcast and forecast models are nested to the Gulf of Mexico HYCOM (Hybrid Coordinate Ocean Model) which provides an estimate of the circulation in the deep Gulf. Model performance is quantified based on the model skills calculated using measurements from the Texas Automated Buoy System (TABS), coastal water level stations and satellite altimetry data. The model is able to reproduce not only the seasonal pattern of sea surface height (SSH), temperature, and velocity fields, but also the strong sea-breezedriven near-inertial surface currents, which have been found dominant in this region during the summer months.
DATA/REPORT DETAILS
A high-resolution pre-operational forecast model of circulation on the Texas-Louisiana continental shelf and slope
- Published on:
- Science Area(s): Harmful Algal Bloom Detection and Forecasting, Stressor Impacts and Mitigation
- Region(s) of Study: Gulf of Mexico, Texas, U.S. States and Territories, Waterbodies
- Primary Contact(s): quay.dortch@noaa.gov
Citation:
Zhang, X., M. Marta-Almeida and R.D. Hetland
Zhang, X., M. Marta-Almeida and R.D. Hetland
Data/Report Type:
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