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Red Tide Prediction and Tracking on the West Florida Shelf
Upper Water Column, Tampa Bay Region
This product is based on the West Florida Coastal Ocean Model (WFCOM). A higher resolution Tampa Bay Circulation Model (TBCOM) focuses on this region, and its red tide forecast product provides more detailed information for the estuaries and inlets. Check out the latest information on the TBCOM-Based Red Tide Tracking for the Tampa Bay Region.
The College of Marine Science, University of South Florida (CMS-USF) provides seasonal predictions of major red tide events and short-term tracking of red tide once an event occurs. Seasonal prediction follows from the recognition that Karenia brevis red tide, of offshore origin, thrives under the low nutrient conditions generally found in the middle of the west Florida continental shelf (WFS). Conditions in successive years are generally not alike. When deeper ocean currents influence the WFS in certain ways, nutrients may be upwelled onto the WFS and carried toward the shore. If this occurs in spring to summer months, when K. brevis blooms tend to form offshore, other faster growing microscopic plants can prevail over the slower growing K. brevis, thereby suppressing red tide bloom development. By keeping track of Gulf of Mexico currents, we can account for the occurrence or lack of major red tide blooms for 20 out of 25 years in which concurrent ocean currents and red tide data are available. As examples, 2010 experienced no red tide, 2012 was severe, whereas 2013 was only nominal. All subsequent years experienced major blooms, although 2016 provided an outlier, a year when we thought that there would not be a major bloom when one indeed occurred.
Once a bloom occurs, the Florida Wildlife Research Institute (FWRI) conducts K. brevis sampling and provides cell count observations to the CMS-USF team. The USF team then inputs these into an ocean circulation model to forecast where these cells may go over the next 4.5 days. With the cell counts a day old when received, the forecast consists of a 1-day hindcast followed by a 3.5-day forecast using our daily, automated West Florida Coastal Ocean Model (WFCOM). The "X" represents the starting point where each sample was collected. The lines show the 3.5 day trajectory for each sample. The color represents the red tide concentration for each sample. Black lines are not indicative of red tide; instead, they show where the current would take a simulated buoyant particle. These may be useful for search and rescue, or for tracking hazardous spills. The short-term red tide trajectory forecast products (uppper and lower water columns) are updated daily in early morning.
Weisberg, R.H., Liu, Y., Lembke, C., Hu, C., Hubbard, K., Garrett, M. (2019), The coastal ocean circulation influence on the 2018 West Florida Shelf K. brevis red tide bloom, J. Geophys. Res. Oceans, 124, 2501-2512, https://doi.org/10.1029/2018JC014887.
Liu, Y., R.H. Weisberg, J.M. Lenes, L. Zheng, K. Hubbard, and J.J. Walsh (2016), Offshore forcing on the "pressure point" of the West Florida Shelf: Anomalous upwelling and its influence on harmful algal blooms, J. Geophys. Res. Oceans, 121, 5501-5515, http://dx.doi.org/10.1002/2016JC011938.
Weisberg, R.H., L. Zheng, Y. Liu, A.A. Corcoran, C. Lembke, C. Hu, J.M. Lenes, and J.J. Walsh (2016), Karenia brevis blooms on the West Florida Shelf: A comparative study of the robust 2012 bloom and the nearly null 2013 event, Cont. Shelf Res., 120, 106-121, http://dx.doi.org/10.1016/j.csr.2016.03.011.
Weisberg, R.H., L. Zheng, Y. Liu, C. Lembke, J.M. Lenes, and J.J. Walsh (2014), Why no red tide was observed on the west Florida continental shelf in 2010, Harmful Algae, 38, 119-136, doi:10.1016/j.hal.2014.04.010.
Zheng, L.Y., and R.H. Weisberg (2012), Modeling the west Florida coastal ocean by downscaling from the deep ocean, across the continental shelf and into the estuaries, Ocean Modell., 48, 10-29, doi:10.1016/j.ocemod.2012.02.002.
The FVCOM HAB tracking tool has benefited from several sources of funding beginning with the FWC and USF. Additional resources from ONR, NOAA and NASA have helped advance the modeling effort over the years.