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Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?

Seasonal-to-decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would re...

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Detalles Bibliográficos
Autores principales: Eade, Rosie, Smith, Doug, Scaife, Adam, Wallace, Emily, Dunstone, Nick, Hermanson, Leon, Robinson, Niall
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4373130/
https://www.ncbi.nlm.nih.gov/pubmed/25821271
http://dx.doi.org/10.1002/2014GL061146
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author Eade, Rosie
Smith, Doug
Scaife, Adam
Wallace, Emily
Dunstone, Nick
Hermanson, Leon
Robinson, Niall
author_facet Eade, Rosie
Smith, Doug
Scaife, Adam
Wallace, Emily
Dunstone, Nick
Hermanson, Leon
Robinson, Niall
author_sort Eade, Rosie
collection PubMed
description Seasonal-to-decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here.
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spelling pubmed-43731302015-03-27 Do seasonal-to-decadal climate predictions underestimate the predictability of the real world? Eade, Rosie Smith, Doug Scaife, Adam Wallace, Emily Dunstone, Nick Hermanson, Leon Robinson, Niall Geophys Res Lett Research Letters Seasonal-to-decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here. BlackWell Publishing Ltd 2014-08-16 2014-08-08 /pmc/articles/PMC4373130/ /pubmed/25821271 http://dx.doi.org/10.1002/2014GL061146 Text en ©2014. The Authors. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Research Letters
Eade, Rosie
Smith, Doug
Scaife, Adam
Wallace, Emily
Dunstone, Nick
Hermanson, Leon
Robinson, Niall
Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
title Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
title_full Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
title_fullStr Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
title_full_unstemmed Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
title_short Do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
title_sort do seasonal-to-decadal climate predictions underestimate the predictability of the real world?
topic Research Letters
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4373130/
https://www.ncbi.nlm.nih.gov/pubmed/25821271
http://dx.doi.org/10.1002/2014GL061146
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