Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers
In this article, we investigate the dependence of extreme surges on the North Atlantic weather regime variability across different timescales using the North Atlantic Oscillation (NAO) and Scandinavian blocking (SCAND) indices. The analysis was done using time series of surges along the North French...
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MDPI AG
2022
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ftdoajarticles:oai:doaj.org/article:5c3781c499cf49e8ae4cc82ef696939d 2023-05-15T17:32:05+02:00 Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers Lisa Baulon Emma Imen Turki Nicolas Massei Gaël André Yann Ferret Nicolas Pouvreau 2022-05-01T00:00:00Z https://doi.org/10.3390/atmos13050850 https://doaj.org/article/5c3781c499cf49e8ae4cc82ef696939d EN eng MDPI AG https://www.mdpi.com/2073-4433/13/5/850 https://doaj.org/toc/2073-4433 doi:10.3390/atmos13050850 2073-4433 https://doaj.org/article/5c3781c499cf49e8ae4cc82ef696939d Atmosphere, Vol 13, Iss 850, p 850 (2022) long-term extreme surges variability climate drivers non-stationary GEV analysis Meteorology. Climatology QC851-999 article 2022 ftdoajarticles https://doi.org/10.3390/atmos13050850 2022-12-30T21:47:40Z In this article, we investigate the dependence of extreme surges on the North Atlantic weather regime variability across different timescales using the North Atlantic Oscillation (NAO) and Scandinavian blocking (SCAND) indices. The analysis was done using time series of surges along the North French Coast, covering long time periods (43 to 172 years of data). Time series that exhibited gaps were filled using linear interpolation to allow spectral analyses to be conducted. First, a continuous wavelet analysis on monthly maxima surges in the North French Coast was conducted to identify the multi-timescale variability. Second, a wavelet coherence analysis and maximum overlap discrete wavelet transform (MODWT) were used to study the timescale-dependent relationships between maxima surges and NAO or SCAND. Finally, NAO and SCAND were tested as physical covariates for a nonstationary generalized extreme value (GEV) distribution to fit monthly maxima surge series. Specific low-frequency variabilities characterizing these indices (extracted using MODWT) were also used as covariates to determine whether such specific variabilities would allow for even better GEV fitting. The results reveal common multi-annual timescales of variability between monthly maxima surge time series along the North French coasts: ~2–3 years, ~5–7 years, and ~12–17 years. These modes of variability were found to be mainly induced by the NAO and the SCAND. We identified a greater influence of the NAO on the monthly maxima surges of the westernmost stations (Brest, Cherbourg, Le Havre), while the SCAND showed a greater influence on the northernmost station (Dunkirk). This shows that the physical climate effects at multi-annual scales are manifested differently between the Atlantic/English Channel and the North Sea regions influenced by NAO and SCAND, respectively. Finally, the introduction of these two climate indices was found to clearly enhance GEV models as well as a few timescales of these indices. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Directory of Open Access Journals: DOAJ Articles Havre ENVELOPE(-71.417,-71.417,-69.333,-69.333) Le Havre ENVELOPE(-71.417,-71.417,-69.333,-69.333) Atmosphere 13 5 850 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
long-term extreme surges variability climate drivers non-stationary GEV analysis Meteorology. Climatology QC851-999 |
spellingShingle |
long-term extreme surges variability climate drivers non-stationary GEV analysis Meteorology. Climatology QC851-999 Lisa Baulon Emma Imen Turki Nicolas Massei Gaël André Yann Ferret Nicolas Pouvreau Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers |
topic_facet |
long-term extreme surges variability climate drivers non-stationary GEV analysis Meteorology. Climatology QC851-999 |
description |
In this article, we investigate the dependence of extreme surges on the North Atlantic weather regime variability across different timescales using the North Atlantic Oscillation (NAO) and Scandinavian blocking (SCAND) indices. The analysis was done using time series of surges along the North French Coast, covering long time periods (43 to 172 years of data). Time series that exhibited gaps were filled using linear interpolation to allow spectral analyses to be conducted. First, a continuous wavelet analysis on monthly maxima surges in the North French Coast was conducted to identify the multi-timescale variability. Second, a wavelet coherence analysis and maximum overlap discrete wavelet transform (MODWT) were used to study the timescale-dependent relationships between maxima surges and NAO or SCAND. Finally, NAO and SCAND were tested as physical covariates for a nonstationary generalized extreme value (GEV) distribution to fit monthly maxima surge series. Specific low-frequency variabilities characterizing these indices (extracted using MODWT) were also used as covariates to determine whether such specific variabilities would allow for even better GEV fitting. The results reveal common multi-annual timescales of variability between monthly maxima surge time series along the North French coasts: ~2–3 years, ~5–7 years, and ~12–17 years. These modes of variability were found to be mainly induced by the NAO and the SCAND. We identified a greater influence of the NAO on the monthly maxima surges of the westernmost stations (Brest, Cherbourg, Le Havre), while the SCAND showed a greater influence on the northernmost station (Dunkirk). This shows that the physical climate effects at multi-annual scales are manifested differently between the Atlantic/English Channel and the North Sea regions influenced by NAO and SCAND, respectively. Finally, the introduction of these two climate indices was found to clearly enhance GEV models as well as a few timescales of these indices. |
format |
Article in Journal/Newspaper |
author |
Lisa Baulon Emma Imen Turki Nicolas Massei Gaël André Yann Ferret Nicolas Pouvreau |
author_facet |
Lisa Baulon Emma Imen Turki Nicolas Massei Gaël André Yann Ferret Nicolas Pouvreau |
author_sort |
Lisa Baulon |
title |
Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers |
title_short |
Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers |
title_full |
Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers |
title_fullStr |
Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers |
title_full_unstemmed |
Versatile Modelling of Extreme Surges in Connection with Large-Scale Circulation Drivers |
title_sort |
versatile modelling of extreme surges in connection with large-scale circulation drivers |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/atmos13050850 https://doaj.org/article/5c3781c499cf49e8ae4cc82ef696939d |
long_lat |
ENVELOPE(-71.417,-71.417,-69.333,-69.333) ENVELOPE(-71.417,-71.417,-69.333,-69.333) |
geographic |
Havre Le Havre |
geographic_facet |
Havre Le Havre |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Atmosphere, Vol 13, Iss 850, p 850 (2022) |
op_relation |
https://www.mdpi.com/2073-4433/13/5/850 https://doaj.org/toc/2073-4433 doi:10.3390/atmos13050850 2073-4433 https://doaj.org/article/5c3781c499cf49e8ae4cc82ef696939d |
op_doi |
https://doi.org/10.3390/atmos13050850 |
container_title |
Atmosphere |
container_volume |
13 |
container_issue |
5 |
container_start_page |
850 |
_version_ |
1766130034037227520 |