English

Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation

Data Analysis, Statistics and Probability 2021-12-16 v2 Statistical Mechanics Dynamical Systems Biological Physics Physics and Society

Abstract

An accurate forecast of the red tide respiratory irritation level would improve the lives of many people living in areas affected by algal blooms. Using a decades-long database of daily beach conditions, two conceptually different models to forecast the respiratory irritation risk level one day ahead of time are trained. One model is wind-based, using the current days' respiratory level and the predicted wind direction of the following day. The other model is a probabilistic self-exciting Hawkes process model. Both models are trained on beaches in Florida during 2011-2017 and applied to the red tide bloom during 2018-2019. For beaches where there is enough historical data to develop a model, the model which performs best depends on the beach. The wind-based model is the most accurate at half the beaches, correctly predicting the respiratory risk level on average about 84% of the time. The Hawkes model is the most accurate (81% accuracy) at nearly all of the remaining beaches.

Keywords

Cite

@article{arxiv.2105.11342,
  title  = {Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation},
  author = {Shane D. Ross and Jeremie Fish and Klaus Moeltner and Erik M. Bollt and Landon Bilyeu and Tracy Fanara},
  journal= {arXiv preprint arXiv:2105.11342},
  year   = {2021}
}

Comments

31 pages, 9 figures