Generation and Analysis of Gridded Visibility Data in the Arctic
With the accelerated warming of the arctic and the gradual opening of the Arctic passages, more and more attention has been paid to assessing the risk of the navigation environment in the Arctic. Due to the scarcity of visibility data in the Arctic, this study proposes a model for referring visibili...
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ftdoajarticles:oai:doaj.org/article:59147eddfb4b4ee081d034587ccb0d75 2023-05-15T14:33:28+02:00 Generation and Analysis of Gridded Visibility Data in the Arctic Yulong Shan Ren Zhang Ming Li Yangjun Wang Qiuhan Li Lifeng Li 2019-06-01T00:00:00Z https://doi.org/10.3390/atmos10060314 https://doaj.org/article/59147eddfb4b4ee081d034587ccb0d75 EN eng MDPI AG https://www.mdpi.com/2073-4433/10/6/314 https://doaj.org/toc/2073-4433 2073-4433 doi:10.3390/atmos10060314 https://doaj.org/article/59147eddfb4b4ee081d034587ccb0d75 Atmosphere, Vol 10, Iss 6, p 314 (2019) the Arctic passage back propagation neural network visibility spatial and temporal features Meteorology. Climatology QC851-999 article 2019 ftdoajarticles https://doi.org/10.3390/atmos10060314 2022-12-31T04:03:45Z With the accelerated warming of the arctic and the gradual opening of the Arctic passages, more and more attention has been paid to assessing the risk of the navigation environment in the Arctic. Due to the scarcity of visibility data in the Arctic, this study proposes a model for referring visibility based on a back propagation (BP) neural network. The reliability of the model is validated and the gridded atmospheric visibility data in the Arctic from 2009 to 2018 was obtained. At the same time, this study analyzed the spatial and temporal features of visibility in the Arctic. The results show that the mean relative error is less than 20% under the different sample forms and it is more accurate to infer the visibility in a specific month using the multiple-year data of that month as training samples. Furthermore, the amount of sample data has a positive effect on the accuracy of inferred visibility, but the effect decreases with data quantity increasing. Visibility changes quickly in the south of 80° N in August, but slowly in the north in that time. At the same time, visibility in July and August is lower than that in other months but higher in March and May. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Atmosphere 10 6 314 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
the Arctic passage back propagation neural network visibility spatial and temporal features Meteorology. Climatology QC851-999 |
spellingShingle |
the Arctic passage back propagation neural network visibility spatial and temporal features Meteorology. Climatology QC851-999 Yulong Shan Ren Zhang Ming Li Yangjun Wang Qiuhan Li Lifeng Li Generation and Analysis of Gridded Visibility Data in the Arctic |
topic_facet |
the Arctic passage back propagation neural network visibility spatial and temporal features Meteorology. Climatology QC851-999 |
description |
With the accelerated warming of the arctic and the gradual opening of the Arctic passages, more and more attention has been paid to assessing the risk of the navigation environment in the Arctic. Due to the scarcity of visibility data in the Arctic, this study proposes a model for referring visibility based on a back propagation (BP) neural network. The reliability of the model is validated and the gridded atmospheric visibility data in the Arctic from 2009 to 2018 was obtained. At the same time, this study analyzed the spatial and temporal features of visibility in the Arctic. The results show that the mean relative error is less than 20% under the different sample forms and it is more accurate to infer the visibility in a specific month using the multiple-year data of that month as training samples. Furthermore, the amount of sample data has a positive effect on the accuracy of inferred visibility, but the effect decreases with data quantity increasing. Visibility changes quickly in the south of 80° N in August, but slowly in the north in that time. At the same time, visibility in July and August is lower than that in other months but higher in March and May. |
format |
Article in Journal/Newspaper |
author |
Yulong Shan Ren Zhang Ming Li Yangjun Wang Qiuhan Li Lifeng Li |
author_facet |
Yulong Shan Ren Zhang Ming Li Yangjun Wang Qiuhan Li Lifeng Li |
author_sort |
Yulong Shan |
title |
Generation and Analysis of Gridded Visibility Data in the Arctic |
title_short |
Generation and Analysis of Gridded Visibility Data in the Arctic |
title_full |
Generation and Analysis of Gridded Visibility Data in the Arctic |
title_fullStr |
Generation and Analysis of Gridded Visibility Data in the Arctic |
title_full_unstemmed |
Generation and Analysis of Gridded Visibility Data in the Arctic |
title_sort |
generation and analysis of gridded visibility data in the arctic |
publisher |
MDPI AG |
publishDate |
2019 |
url |
https://doi.org/10.3390/atmos10060314 https://doaj.org/article/59147eddfb4b4ee081d034587ccb0d75 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Atmosphere, Vol 10, Iss 6, p 314 (2019) |
op_relation |
https://www.mdpi.com/2073-4433/10/6/314 https://doaj.org/toc/2073-4433 2073-4433 doi:10.3390/atmos10060314 https://doaj.org/article/59147eddfb4b4ee081d034587ccb0d75 |
op_doi |
https://doi.org/10.3390/atmos10060314 |
container_title |
Atmosphere |
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10 |
container_issue |
6 |
container_start_page |
314 |
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1766306713273630720 |