L. Aixalà-Perelló, X. Barber, A. López-Quílez
Industries dependent on natural ecosystems, like marine aquaculture, are significantly impacted by environmental instability, potentially due to climate change. Sea surface temperature (SST) is an example of an unstable phenomenon with relevance to the fishing industry.
The peak over the threshold (POT) method analyzes extreme events by identifying and characterizing occurrences surpassing a predefined threshold, providing insights into their frequency, duration, and magnitude.
Hence, it is a valuable tool for studying SST instability, and climate change's potential effects, and aiding in the development of strategies to manage and adapt to evolving marine conditions.
Inference and predictions are conducted by implementing Bayesian hierarchical models, utilizing the R-INLA package within the R programming environment. The outcomes obtained yield estimations of the marine areas exhibiting the most stability, where fish or shellfish farming can prosper under optimal conditions.
Keywords: Extreme Events, spatio-temporal models, R-INLA
Scheduled
Posters II
November 9, 2023 11:40 AM
CC: coffee break Hall