Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness

<p>Interest in seasonal predictions of Arctic sea ice has been increasing in recent years owing, primarily, to the sharp reduction in Arctic sea-ice cover observed over the last few decades, a decline that is projected to continue. The prospect of increased human industrial activity in the...

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Main Authors: E. W. Blockley, K. A. Peterson
Format: Article
Language:English
Published: Copernicus Publications 2018-10-01
Series:The Cryosphere
Online Access:https://www.the-cryosphere.net/12/3419/2018/tc-12-3419-2018.pdf
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author E. W. Blockley
K. A. Peterson
author_facet E. W. Blockley
K. A. Peterson
author_sort E. W. Blockley
collection DOAJ
description <p>Interest in seasonal predictions of Arctic sea ice has been increasing in recent years owing, primarily, to the sharp reduction in Arctic sea-ice cover observed over the last few decades, a decline that is projected to continue. The prospect of increased human industrial activity in the region, as well as scientific interest in the predictability of sea ice, provides important motivation for understanding, and improving, the skill of Arctic predictions. Several operational forecasting centres now routinely produce seasonal predictions of sea-ice cover using coupled atmosphere–ocean–sea-ice models. Although assimilation of sea-ice concentration into these systems is commonplace, sea-ice thickness observations, being much less mature, are typically not assimilated. However, many studies suggest that initialization of winter sea-ice thickness could lead to improved prediction of Arctic summer sea ice. Here, for the first time, we directly assess the impact of winter sea-ice thickness initialization on the skill of summer seasonal predictions by assimilating CryoSat-2 thickness data into the Met Office's coupled seasonal prediction system (GloSea). We show a significant improvement in predictive skill of Arctic sea-ice extent and ice-edge location for forecasts of September Arctic sea ice made from the beginning of the melt season. The improvements in sea-ice cover lead to further improvement of near-surface air temperature and pressure fields across the region. A clear relationship between modelled winter thickness biases and summer extent errors is identified which supports the theory that Arctic winter thickness provides some predictive capability for summer ice extent, and further highlights the importance that modelled winter thickness biases can have on the evolution of forecast errors through the melt season.</p>
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spelling doaj.art-8c02202e7bd540b1903e846de21127b22022-12-21T19:14:12ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242018-10-01123419343810.5194/tc-12-3419-2018Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thicknessE. W. Blockley0K. A. Peterson1Met Office, FitzRoy Road, Exeter, EX1 3PB, UKMet Office, FitzRoy Road, Exeter, EX1 3PB, UK<p>Interest in seasonal predictions of Arctic sea ice has been increasing in recent years owing, primarily, to the sharp reduction in Arctic sea-ice cover observed over the last few decades, a decline that is projected to continue. The prospect of increased human industrial activity in the region, as well as scientific interest in the predictability of sea ice, provides important motivation for understanding, and improving, the skill of Arctic predictions. Several operational forecasting centres now routinely produce seasonal predictions of sea-ice cover using coupled atmosphere–ocean–sea-ice models. Although assimilation of sea-ice concentration into these systems is commonplace, sea-ice thickness observations, being much less mature, are typically not assimilated. However, many studies suggest that initialization of winter sea-ice thickness could lead to improved prediction of Arctic summer sea ice. Here, for the first time, we directly assess the impact of winter sea-ice thickness initialization on the skill of summer seasonal predictions by assimilating CryoSat-2 thickness data into the Met Office's coupled seasonal prediction system (GloSea). We show a significant improvement in predictive skill of Arctic sea-ice extent and ice-edge location for forecasts of September Arctic sea ice made from the beginning of the melt season. The improvements in sea-ice cover lead to further improvement of near-surface air temperature and pressure fields across the region. A clear relationship between modelled winter thickness biases and summer extent errors is identified which supports the theory that Arctic winter thickness provides some predictive capability for summer ice extent, and further highlights the importance that modelled winter thickness biases can have on the evolution of forecast errors through the melt season.</p>https://www.the-cryosphere.net/12/3419/2018/tc-12-3419-2018.pdf
spellingShingle E. W. Blockley
K. A. Peterson
Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
The Cryosphere
title Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
title_full Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
title_fullStr Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
title_full_unstemmed Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
title_short Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
title_sort improving met office seasonal predictions of arctic sea ice using assimilation of cryosat 2 thickness
url https://www.the-cryosphere.net/12/3419/2018/tc-12-3419-2018.pdf
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