Forecasting seasonal to interannual variability in extreme sea levels
<qd> Menendez, M., Mendez, F. J., and Losada, I. J. 2009. Forecasting seasonal to interannual variability in extreme sea levels. – ICES Journal of Marine Science, 66: 000–000. </qd>A statistical model to predict the probability of certain extreme sea levels occurring is presented. The mo...
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fthighwire:oai:open-archive.highwire.org:icesjms:fsp095v1 2023-05-15T17:33:44+02:00 Forecasting seasonal to interannual variability in extreme sea levels Menendez, Melisa Mendez, Fernando J. Losada, Inigo J. 2009-04-16 09:26:13.0 text/html http://icesjms.oxfordjournals.org/cgi/content/short/fsp095v1 https://doi.org/10.1093/icesjms/fsp095 en eng Oxford University Press http://icesjms.oxfordjournals.org/cgi/content/short/fsp095v1 http://dx.doi.org/10.1093/icesjms/fsp095 Copyright (C) 2009, International Council for the Exploration of the Sea/Conseil International pour l'Exploration de la Mer Effects of Climate Change on the World's Oceans TEXT 2009 fthighwire https://doi.org/10.1093/icesjms/fsp095 2013-05-26T22:26:07Z <qd> Menendez, M., Mendez, F. J., and Losada, I. J. 2009. Forecasting seasonal to interannual variability in extreme sea levels. – ICES Journal of Marine Science, 66: 000–000. </qd>A statistical model to predict the probability of certain extreme sea levels occurring is presented. The model uses a time-dependent generalized extreme-value (GEV) distribution to fit monthly maxima series, and it is applied for a particular time-series record for the Atlantic Ocean (Newlyn, UK). The model permits the effects of seasonality, interannual variability, and secular trends to be identified and estimated in the probability distribution of extreme sea levels. These factors are parameterized as temporal functions (linear, quadratic, exponential, and periodic functions) or covariates (for instance, the North Atlantic Oscillation index), which automatically yield the best-fit model for the variability present in the data. A clear pattern of within-year variability and significant effects resulting from astronomical modulations (the nodal cycle and perigean tides) are detected. Modelling different time-scales helps to gain a better understanding of recent secular trends regarding extreme climate events, and it allows predictions to be made (for example, up to 2020) about the probability of the future occurrence of a particular sea level. Text North Atlantic North Atlantic oscillation HighWire Press (Stanford University) ICES Journal of Marine Science 66 7 1490 1496 |
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Open Polar |
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HighWire Press (Stanford University) |
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fthighwire |
language |
English |
topic |
Effects of Climate Change on the World's Oceans |
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Effects of Climate Change on the World's Oceans Menendez, Melisa Mendez, Fernando J. Losada, Inigo J. Forecasting seasonal to interannual variability in extreme sea levels |
topic_facet |
Effects of Climate Change on the World's Oceans |
description |
<qd> Menendez, M., Mendez, F. J., and Losada, I. J. 2009. Forecasting seasonal to interannual variability in extreme sea levels. – ICES Journal of Marine Science, 66: 000–000. </qd>A statistical model to predict the probability of certain extreme sea levels occurring is presented. The model uses a time-dependent generalized extreme-value (GEV) distribution to fit monthly maxima series, and it is applied for a particular time-series record for the Atlantic Ocean (Newlyn, UK). The model permits the effects of seasonality, interannual variability, and secular trends to be identified and estimated in the probability distribution of extreme sea levels. These factors are parameterized as temporal functions (linear, quadratic, exponential, and periodic functions) or covariates (for instance, the North Atlantic Oscillation index), which automatically yield the best-fit model for the variability present in the data. A clear pattern of within-year variability and significant effects resulting from astronomical modulations (the nodal cycle and perigean tides) are detected. Modelling different time-scales helps to gain a better understanding of recent secular trends regarding extreme climate events, and it allows predictions to be made (for example, up to 2020) about the probability of the future occurrence of a particular sea level. |
format |
Text |
author |
Menendez, Melisa Mendez, Fernando J. Losada, Inigo J. |
author_facet |
Menendez, Melisa Mendez, Fernando J. Losada, Inigo J. |
author_sort |
Menendez, Melisa |
title |
Forecasting seasonal to interannual variability in extreme sea levels |
title_short |
Forecasting seasonal to interannual variability in extreme sea levels |
title_full |
Forecasting seasonal to interannual variability in extreme sea levels |
title_fullStr |
Forecasting seasonal to interannual variability in extreme sea levels |
title_full_unstemmed |
Forecasting seasonal to interannual variability in extreme sea levels |
title_sort |
forecasting seasonal to interannual variability in extreme sea levels |
publisher |
Oxford University Press |
publishDate |
2009 |
url |
http://icesjms.oxfordjournals.org/cgi/content/short/fsp095v1 https://doi.org/10.1093/icesjms/fsp095 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
http://icesjms.oxfordjournals.org/cgi/content/short/fsp095v1 http://dx.doi.org/10.1093/icesjms/fsp095 |
op_rights |
Copyright (C) 2009, International Council for the Exploration of the Sea/Conseil International pour l'Exploration de la Mer |
op_doi |
https://doi.org/10.1093/icesjms/fsp095 |
container_title |
ICES Journal of Marine Science |
container_volume |
66 |
container_issue |
7 |
container_start_page |
1490 |
op_container_end_page |
1496 |
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1766132333885259776 |