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Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model
Arctic sea ice drift forecasts of 6 h–9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/ https://www.ncbi.nlm.nih.gov/pubmed/27818852 http://dx.doi.org/10.1002/2015JC011273 |
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author | Schweiger, Axel J. Zhang, Jinlun |
author_facet | Schweiger, Axel J. Zhang, Jinlun |
author_sort | Schweiger, Axel J. |
collection | PubMed |
description | Arctic sea ice drift forecasts of 6 h–9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys and other observational platforms. Forecast positions are compared with actual positions 24 h–8 days since forecast. Forecast results are further compared to those from the forecasts generated using an ice velocity climatology driven by multiyear integrations of the same model. The results are presented in the context of scheduling the acquisition of high‐resolution images that need to follow buoys or scientific research platforms. RMS errors for ice speed are on the order of 5 km/d for 24–48 h since forecast using the sea ice model compared with 9 km/d using climatology. Predicted buoy position RMS errors are 6.3 km for 24 h and 14 km for 72 h since forecast. Model biases in ice speed and direction can be reduced by adjusting the air drag coefficient and water turning angle, but the adjustments do not affect verification statistics. This suggests that improved atmospheric forecast forcing may further reduce the forecast errors. The model remains skillful for 8 days. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10 km × 10 km image from 60 to 95% for a 24 h forecast and from 27 to 73% for a 48 h forecast. |
format | Online Article Text |
id | pubmed-5070527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-50705272016-11-02 Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model Schweiger, Axel J. Zhang, Jinlun J Geophys Res Oceans Research Articles Arctic sea ice drift forecasts of 6 h–9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys and other observational platforms. Forecast positions are compared with actual positions 24 h–8 days since forecast. Forecast results are further compared to those from the forecasts generated using an ice velocity climatology driven by multiyear integrations of the same model. The results are presented in the context of scheduling the acquisition of high‐resolution images that need to follow buoys or scientific research platforms. RMS errors for ice speed are on the order of 5 km/d for 24–48 h since forecast using the sea ice model compared with 9 km/d using climatology. Predicted buoy position RMS errors are 6.3 km for 24 h and 14 km for 72 h since forecast. Model biases in ice speed and direction can be reduced by adjusting the air drag coefficient and water turning angle, but the adjustments do not affect verification statistics. This suggests that improved atmospheric forecast forcing may further reduce the forecast errors. The model remains skillful for 8 days. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10 km × 10 km image from 60 to 95% for a 24 h forecast and from 27 to 73% for a 48 h forecast. John Wiley and Sons Inc. 2015-12-12 2015-12 /pmc/articles/PMC5070527/ /pubmed/27818852 http://dx.doi.org/10.1002/2015JC011273 Text en © 2015. The Authors. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) 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 Articles Schweiger, Axel J. Zhang, Jinlun Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
title | Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
title_full | Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
title_fullStr | Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
title_full_unstemmed | Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
title_short | Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
title_sort | accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/ https://www.ncbi.nlm.nih.gov/pubmed/27818852 http://dx.doi.org/10.1002/2015JC011273 |
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