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

Autor:	Ross, Shane D., Fish, Jeremie, Moeltner, Klaus, Bollt, Erik M., Bilyeu, Landon, Fanara, Tracy
Rok vydání:	2021
Předmět:	Physics - Data Analysis Statistics and Probability Condensed Matter - Statistical Mechanics Mathematics - Dynamical Systems Physics - Biological Physics Physics - Physics and Society
Zdroj:	Harmful Algae 111:102149 (2022)
Druh dokumentu:	Working Paper
DOI:	10.1016/j.hal.2021.102149
Popis:	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. Comment: 31 pages, 9 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.11342 Zobrazit plný text záznamu View this record from Arxiv