Thomas P. Huff, Rusty A. Feagin, and Jens Figlus, 2020. “Enhanced tide model: Improving tidal predictions with integration of wind data”, Shore & Beach 88(2), 40-45.
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http://doi.org/10.34237/1008824
Enhanced tide model: Improving tidal predictions with integration of wind data
Thomas P. Huff (1), Rusty A. Feagin (1), and Jens Figlus (2)
1) Texas A&M University, Department of Ecology and Conservation Biology
2138 TAMU College Station, Texas 77843
thomas2013@tamu.edu
2) Texas A&M University-Galveston Campus, Department of Ocean Engineering
200 Seawolf Pkwy., Galveston, TX, 77553
Publicly available tidal predictions for coastlines are predominantly based on astronomical predictions. In shallow water basins, however, water levels can deviate from these predictions by a factor of two or more due to wind-induced fluctuations from non-regional storms. To model and correct these wind-induced tidal deviations, a two-stage empirical model was created: the Enhanced Tidal Model (ETM). For any given NOAA tide gauge location, this model first measured the wind-induced deviation based on a compiled dataset, and then adjusted the astronomical predictions into the future to create a 144-hour forecast. The ETM, when incorporating wind data, had only 76% of the error of NOAA astronomical tidal predictions (e.g. if NOAA had 1.0 ft. of error, ETM had only 0.76 ft. error from the observed water level). Certain ETM locations had approximately half (49%) as much prediction error as NOAA. With the improvement in tidal accuracy prediction, the ETM has the ability to significantly aid in navigation along with coastal flood prediction. We envision the ETM as a resource for industry and the public to make informed decisions that impact their livelihood.