Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping
The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to support such navigation are often flawed. To address this challenge, this study advances a statistical i...
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Multidisciplinary Digital Publishing Institute
2023
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Online Access: | https://doi.org/10.3390/app13074374 |
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ftmdpi:oai:mdpi.com:/2076-3417/13/7/4374/ 2023-08-20T04:03:53+02:00 Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping Da Wu Wuliu Tian Xiao Lang Wengang Mao Jinfen Zhang agris 2023-03-30 application/pdf https://doi.org/10.3390/app13074374 EN eng Multidisciplinary Digital Publishing Institute Transportation and Future Mobility https://dx.doi.org/10.3390/app13074374 https://creativecommons.org/licenses/by/4.0/ Applied Sciences; Volume 13; Issue 7; Pages: 4374 sea ice concentration Arctic shipping transit navigation windows ARIMA model time series analysis Text 2023 ftmdpi https://doi.org/10.3390/app13074374 2023-08-01T09:29:56Z The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to support such navigation are often flawed. To address this challenge, this study advances a statistical interpolation method aimed at reducing errors arising from traditional interpolation approaches. Additionally, this study introduces an autoregressive integrated moving average model, derived from ERA5 reanalysis data, for short-term sea ice concentration forecasts along the Northern Sea Route. The validity of the model has been confirmed through comparison with ensemble experiments from the Coupling Model Intercomparison Project Phase 5, yielding reliable outcomes. The route availability is assessed on the basis of the sea ice concentration forecasts, indicating that the route will be available in the upcoming years. The proposed statistical models are also shown the capacity to facilitate effective management of Arctic shipping along the Northern Sea Route. Text Arctic Northern Sea Route Sea ice MDPI Open Access Publishing Arctic Applied Sciences 13 7 4374 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
sea ice concentration Arctic shipping transit navigation windows ARIMA model time series analysis |
spellingShingle |
sea ice concentration Arctic shipping transit navigation windows ARIMA model time series analysis Da Wu Wuliu Tian Xiao Lang Wengang Mao Jinfen Zhang Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping |
topic_facet |
sea ice concentration Arctic shipping transit navigation windows ARIMA model time series analysis |
description |
The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to support such navigation are often flawed. To address this challenge, this study advances a statistical interpolation method aimed at reducing errors arising from traditional interpolation approaches. Additionally, this study introduces an autoregressive integrated moving average model, derived from ERA5 reanalysis data, for short-term sea ice concentration forecasts along the Northern Sea Route. The validity of the model has been confirmed through comparison with ensemble experiments from the Coupling Model Intercomparison Project Phase 5, yielding reliable outcomes. The route availability is assessed on the basis of the sea ice concentration forecasts, indicating that the route will be available in the upcoming years. The proposed statistical models are also shown the capacity to facilitate effective management of Arctic shipping along the Northern Sea Route. |
format |
Text |
author |
Da Wu Wuliu Tian Xiao Lang Wengang Mao Jinfen Zhang |
author_facet |
Da Wu Wuliu Tian Xiao Lang Wengang Mao Jinfen Zhang |
author_sort |
Da Wu |
title |
Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping |
title_short |
Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping |
title_full |
Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping |
title_fullStr |
Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping |
title_full_unstemmed |
Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping |
title_sort |
statistical modeling of arctic sea ice concentrations for northern sea route shipping |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/app13074374 |
op_coverage |
agris |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Northern Sea Route Sea ice |
genre_facet |
Arctic Northern Sea Route Sea ice |
op_source |
Applied Sciences; Volume 13; Issue 7; Pages: 4374 |
op_relation |
Transportation and Future Mobility https://dx.doi.org/10.3390/app13074374 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/app13074374 |
container_title |
Applied Sciences |
container_volume |
13 |
container_issue |
7 |
container_start_page |
4374 |
_version_ |
1774714308645617664 |