Forecasting with Markovian max-stable fields in space and time: An application to wind gust speeds

Fuente: arXiv
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Main Authors: Cotsakis, Ryan, Koch, Erwan, Robert, Christian-Yann
Format: Preprint
Published: 2024
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author Cotsakis, Ryan
Koch, Erwan
Robert, Christian-Yann
author_facet Cotsakis, Ryan
Koch, Erwan
Robert, Christian-Yann
contents Hourly maxima of 3-second wind gust speeds are prominent indicators of the severity of wind storms, and accurately forecasting them is thus essential for populations, civil authorities and insurance companies. Space-time max-stable models appear as natural candidates for this, but those explored so far are not suited for forecasting and, more generally, the forecasting literature for max-stable fields is limited. To fill this gap, we consider a specific space-time max-stable model, more precisely a max-autoregressive model with advection, that is well-adapted to model and forecast atmospheric variables. We apply it, as well as our related forecasting strategy, to reanalysis 3-second wind gust data for France in 1999, and show good performance compared to a competitor model. On top of demonstrating the practical relevance of our model, we meticulously study its theoretical properties and show the consistency and asymptotic normality of the space-time pairwise likelihood estimator which is used to calibrate the model.
format Preprint
id arxiv_https___arxiv_org_abs_2411_15511
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Forecasting with Markovian max-stable fields in space and time: An application to wind gust speeds
Cotsakis, Ryan
Koch, Erwan
Robert, Christian-Yann
Methodology
Applications
62P12
Hourly maxima of 3-second wind gust speeds are prominent indicators of the severity of wind storms, and accurately forecasting them is thus essential for populations, civil authorities and insurance companies. Space-time max-stable models appear as natural candidates for this, but those explored so far are not suited for forecasting and, more generally, the forecasting literature for max-stable fields is limited. To fill this gap, we consider a specific space-time max-stable model, more precisely a max-autoregressive model with advection, that is well-adapted to model and forecast atmospheric variables. We apply it, as well as our related forecasting strategy, to reanalysis 3-second wind gust data for France in 1999, and show good performance compared to a competitor model. On top of demonstrating the practical relevance of our model, we meticulously study its theoretical properties and show the consistency and asymptotic normality of the space-time pairwise likelihood estimator which is used to calibrate the model.
title Forecasting with Markovian max-stable fields in space and time: An application to wind gust speeds
topic Methodology
Applications
62P12
url https://arxiv.org/abs/2411.15511