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...

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Published in:Journal of Geophysical Research: Oceans
Main Authors: Schweiger, Axel J., Zhang, Jinlun
Format: Text
Language:English
Published: John Wiley and Sons Inc. 2015
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/
https://doi.org/10.1002/2015JC011273
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spelling ftpubmed:oai:www.ncbi.nlm.nih.gov/pmc:5070527 2023-05-15T15:11:02+02:00 Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model Schweiger, Axel J. Zhang, Jinlun 2015-12-12 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/ https://doi.org/10.1002/2015JC011273 en eng John Wiley and Sons Inc. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/ http://dx.doi.org/10.1002/2015JC011273 © 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. CC-BY-NC-ND Research Articles Text 2015 ftpubmed https://doi.org/10.1002/2015JC011273 2016-11-06T01:23:25Z 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. Text Arctic Sea ice PubMed Central (PMC) Arctic Journal of Geophysical Research: Oceans 120 12 7827 7841
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Research Articles
spellingShingle Research Articles
Schweiger, Axel J.
Zhang, Jinlun
Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model
topic_facet Research Articles
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 Text
author Schweiger, Axel J.
Zhang, Jinlun
author_facet Schweiger, Axel J.
Zhang, Jinlun
author_sort Schweiger, Axel J.
title 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_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_sort accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model
publisher John Wiley and Sons Inc.
publishDate 2015
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/
https://doi.org/10.1002/2015JC011273
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070527/
http://dx.doi.org/10.1002/2015JC011273
op_rights © 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.
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container_title Journal of Geophysical Research: Oceans
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