Experimental Real-Time
Intra-Americas Sea Ocean Nowcast/Forecast System


      An experimental real-time Ocean Nowcast/Forecast System has been developed for the Intra-Americas Sea (IASNFS). The area of coverage includes the Caribbean Sea, the Gulf of Mexico and the Straits of Florida. The system produces nowcast and up to 72 hours forecast the sea level variation, 3D ocean current, temperature and salinity fields.

      IASNFS consists an 1/24 degree (~6 km), 41-level sigma-z data-assimilating ocean model based on NCOM. The model topography is from NRL DBDB2. For daily nowcast/forecast the model is restarted from previous nowcast. Once model is restarted it continuously assimilates the synthetic temperature/salinity profiles generated by a data analysis model called MODAS to produce nowcast. Real-time data come from satellite altimeter (GFO, Jason-1, ERS-2) sea surface height (global) anomaly and AVHRR sea surface temperature (global). Three hourly surface heat fluxes, including solar radiation, wind stresses and sea level air pressure from NOGAPS/FNMOC are applied for surface forcing. Forecasts are produced with available NOGAPS forecasts. Once the nowcast/forecast are produced they are distributed through the internet via the updated web pages.

      The open boundary conditions including sea surface elevation, transport, temperature, salinity and currents are provided by the NRL 1/8 degree Global NCOM which is operated daily. An one way coupling scheme is used to ingest those boundary conditions into the IAS model. There are 140 rivers with monthly discharges included in the IASNFS.

      IASNFS is a fully automated end-to-end ocean prediction system operated at NRL Oceanography Division with founding provided by NASA. See IASNFS System Components.

      IASNFS predictions have been evaluated against observations including coastal sea level measurements. See "evaluations".

AMS 2003 Proceedings: B/W | Color
Ko, Dong S., Ruth H. Preller, and Paul J. Martin, 2003: An Experimental Real-Time Intra Americas Sea Ocean Nowcast/Forecast System for Coastal Prediction, Proceedings, AMS 5th Conference on Coastal Atmospheric & Oceanic Prediction & Processes, 97-100, 2003.
Other IASNFS related Publications
Allee, R.J., J.C. Kurtz, R.W. Gould, D.S. Ko, K.L. Goodin, and M. Finkbeiner 2014: Application of the coastal and marine ecological classification standard using satellite-derived and modeled data products for pelagic habitats in the northern Gulf of Mexico, Ocean and Coastal Management, 88, 13-20, http://dx.doi.org/10.1016/j.ocecoaman.2013.10.02.

Chaichitehrani, N., E.J. D'Sa, D.S. Ko, N. Walker, C.L. Osburn, and R.F. Chen, 2014: Colored dissolved organic matter dynamics in the northern Gulf of Mexico from ocean color and numerical model results, J. Coast. Res., 30, 800-814, doi: 10.2112/JCOASTRES-D-13-00036.1.

Lehrter, J., D.S. Ko, M. Murrell, G. Richard, H. James, S. Blake, R.W. Gould, and B. Penta, 2013: Nutrient transports and source/sink dynamics on the inner Louisiana continental shelf, J. Geophys. Res., 118, 4822-4838, doi:10.1002/jgrc.20362.

D'Sa, E., M. Korobkin, and D.S. Ko, 2011: Effects of Hurricane Ike on the Louisiana-Texas coast from satellite and model data, Remote Sensing Lett., 2, 11-19, doi: 10.1080/01431161.2010.489057.

Arnone, R.A., B. Casey, S. Ladner, D.S. Ko, and R.W. Gould, 2010: Forecasting the Coastal Optical Properties using Satellite Ocean Color, Oceanography from Space, eds. V. Barale et al., Springer Science+Business Media B. V., 335-348, doi:10.1007/978-90-481-8681-5_19.

Mendoza, W.G., R.G. Zika, J.E. Corredor, D.S. Ko, and C.N.K. Mooers, 2009: Developmental strategy for effective sampling to detect possible nutrient fluxes in oligotrophic coastal reef waters in the Caribbean, J. Operational Oceanogr., 2, 35-47.

D'Sa, E.J., and D.S. Ko, 2008: Short-term influences on suspended particulate matter distribution in the northern Gulf of Mexico: Satellite and model observations, Sensors, 8, 4249-4264, doi:10.3390/s8074249.

Green, R.E., R.W. Gould, and D.S. Ko, 2008: Statistical models for sediment/detritus and dissolved absorption coefficients in coastal waters of the northern Gulf of Mexico, Cont. Shelf Res., 28, 1273-1285.

Ko, D.S., P.J. Martin, C.D. Rowley, and R.H. Preller, 2008: A real-time coastal ocean prediction experiment for MREA04, J. Mar. Syst., 69, 17-28, doi:10.1016/j.jmarsys.2007.02.022.

Arnone, R.A., B. Casey, D. Ko, P. Flynn, L. Carrolo, and S. Ladner, 2007: Forecasting coastal optical properties using ocean color and coastal circulation models, Proc. SPIE, 6680, doi:10.1117/12.737201.

Haltrin, V.I., R.A. Arnone, P. Flynn, B. Casey, A.D. Weidemann, and D.S. Ko, 2007: Restoring number of suspended particles in ocean using satellite optical images and forecasting particle fields, Proc. SPIE, 6615, doi: 10.1117/12.740435.

Chassignet, E.P., H.E. Hurlburt, O.M. Smedstad, C.N. Barron, D.S. Ko, R.C. Rhodes, J.F. Shriver, A.J. Wallcraft, and R.A. Arnone, 2005: Assessment of Data Assimilative Ocean Models in the Gulf of Mexico Using Ocean Color, Geophysical Monography 161 - Circulation in the Gulf of Mexico: Observations and Models, eds. W. Sturgers and A. Lugo-Fernandes, AGU, Washington D.C., 87-100.

Grid | Topography | Rivers

Nowcast/Forecast | Movie ( GOM | Windward Pass | LC | Trasport/Trajectory)

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