Forecasting with Markovian max-stable fields in space and time: An application to wind gust speeds
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| Format: | Preprint |
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2024
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| _version_ | 1866910710409199616 |
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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 |
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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 |