Probabilistic Forecasts of Arctic Sea Ice Thickness
Abstract In recent decades, warming temperatures have caused sharp reductions in the volume of sea ice in the Arctic Ocean. Predicting changes in Arctic sea ice thickness is vital in a changing Arctic for making decisions about shipping and resource management in the region. We propose a statistical...
Published in: | Journal of Agricultural, Biological and Environmental Statistics |
---|---|
Main Authors: | , , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Springer Science and Business Media LLC
2021
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1007/s13253-021-00480-0 https://link.springer.com/content/pdf/10.1007/s13253-021-00480-0.pdf https://link.springer.com/article/10.1007/s13253-021-00480-0/fulltext.html |
id |
crspringernat:10.1007/s13253-021-00480-0 |
---|---|
record_format |
openpolar |
spelling |
crspringernat:10.1007/s13253-021-00480-0 2023-05-15T14:39:37+02:00 Probabilistic Forecasts of Arctic Sea Ice Thickness Gao, Peter A. Director, Hannah M. Bitz, Cecilia M. Raftery, Adrian E. Climate Program Office 2021 http://dx.doi.org/10.1007/s13253-021-00480-0 https://link.springer.com/content/pdf/10.1007/s13253-021-00480-0.pdf https://link.springer.com/article/10.1007/s13253-021-00480-0/fulltext.html en eng Springer Science and Business Media LLC https://creativecommons.org/licenses/by/4.0 https://creativecommons.org/licenses/by/4.0 CC-BY Journal of Agricultural, Biological and Environmental Statistics ISSN 1085-7117 1537-2693 Applied Mathematics Statistics, Probability and Uncertainty General Agricultural and Biological Sciences Agricultural and Biological Sciences (miscellaneous) General Environmental Science Statistics and Probability journal-article 2021 crspringernat https://doi.org/10.1007/s13253-021-00480-0 2022-01-04T14:55:00Z Abstract In recent decades, warming temperatures have caused sharp reductions in the volume of sea ice in the Arctic Ocean. Predicting changes in Arctic sea ice thickness is vital in a changing Arctic for making decisions about shipping and resource management in the region. We propose a statistical spatio-temporal two-stage model for sea ice thickness and use it to generate probabilistic forecasts up to three months into the future. Our approach combines a contour model to predict the ice-covered region with a Gaussian random field to model ice thickness conditional on the ice-covered region. Using the most complete estimates of sea ice thickness currently available, we apply our method to forecast Arctic sea ice thickness. Point predictions and prediction intervals from our model offer comparable accuracy and improved calibration compared with existing forecasts. We show that existing forecasts produced by ensembles of deterministic dynamic models can have large errors and poor calibration. We also show that our statistical model can generate good forecasts of aggregate quantities such as overall and regional sea ice volume. Supplementary materials accompanying this paper appear on-line. Article in Journal/Newspaper Arctic Arctic Ocean Sea ice Springer Nature (via Crossref) Arctic Arctic Ocean Journal of Agricultural, Biological and Environmental Statistics 27 2 280 302 |
institution |
Open Polar |
collection |
Springer Nature (via Crossref) |
op_collection_id |
crspringernat |
language |
English |
topic |
Applied Mathematics Statistics, Probability and Uncertainty General Agricultural and Biological Sciences Agricultural and Biological Sciences (miscellaneous) General Environmental Science Statistics and Probability |
spellingShingle |
Applied Mathematics Statistics, Probability and Uncertainty General Agricultural and Biological Sciences Agricultural and Biological Sciences (miscellaneous) General Environmental Science Statistics and Probability Gao, Peter A. Director, Hannah M. Bitz, Cecilia M. Raftery, Adrian E. Probabilistic Forecasts of Arctic Sea Ice Thickness |
topic_facet |
Applied Mathematics Statistics, Probability and Uncertainty General Agricultural and Biological Sciences Agricultural and Biological Sciences (miscellaneous) General Environmental Science Statistics and Probability |
description |
Abstract In recent decades, warming temperatures have caused sharp reductions in the volume of sea ice in the Arctic Ocean. Predicting changes in Arctic sea ice thickness is vital in a changing Arctic for making decisions about shipping and resource management in the region. We propose a statistical spatio-temporal two-stage model for sea ice thickness and use it to generate probabilistic forecasts up to three months into the future. Our approach combines a contour model to predict the ice-covered region with a Gaussian random field to model ice thickness conditional on the ice-covered region. Using the most complete estimates of sea ice thickness currently available, we apply our method to forecast Arctic sea ice thickness. Point predictions and prediction intervals from our model offer comparable accuracy and improved calibration compared with existing forecasts. We show that existing forecasts produced by ensembles of deterministic dynamic models can have large errors and poor calibration. We also show that our statistical model can generate good forecasts of aggregate quantities such as overall and regional sea ice volume. Supplementary materials accompanying this paper appear on-line. |
author2 |
Climate Program Office |
format |
Article in Journal/Newspaper |
author |
Gao, Peter A. Director, Hannah M. Bitz, Cecilia M. Raftery, Adrian E. |
author_facet |
Gao, Peter A. Director, Hannah M. Bitz, Cecilia M. Raftery, Adrian E. |
author_sort |
Gao, Peter A. |
title |
Probabilistic Forecasts of Arctic Sea Ice Thickness |
title_short |
Probabilistic Forecasts of Arctic Sea Ice Thickness |
title_full |
Probabilistic Forecasts of Arctic Sea Ice Thickness |
title_fullStr |
Probabilistic Forecasts of Arctic Sea Ice Thickness |
title_full_unstemmed |
Probabilistic Forecasts of Arctic Sea Ice Thickness |
title_sort |
probabilistic forecasts of arctic sea ice thickness |
publisher |
Springer Science and Business Media LLC |
publishDate |
2021 |
url |
http://dx.doi.org/10.1007/s13253-021-00480-0 https://link.springer.com/content/pdf/10.1007/s13253-021-00480-0.pdf https://link.springer.com/article/10.1007/s13253-021-00480-0/fulltext.html |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Sea ice |
genre_facet |
Arctic Arctic Ocean Sea ice |
op_source |
Journal of Agricultural, Biological and Environmental Statistics ISSN 1085-7117 1537-2693 |
op_rights |
https://creativecommons.org/licenses/by/4.0 https://creativecommons.org/licenses/by/4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1007/s13253-021-00480-0 |
container_title |
Journal of Agricultural, Biological and Environmental Statistics |
container_volume |
27 |
container_issue |
2 |
container_start_page |
280 |
op_container_end_page |
302 |
_version_ |
1766311588225089536 |