Using Bayesian statistics to detect trends in Alaskan precipitation
Abstract Air temperature has exhibited a clear positive trend over the past several decades throughout the arctic, including Alaska. Other variables, such as precipitation, have much more uncertain trends due to inhomogeneities in measurement and high internal variability. The use of linear regressi...
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crwiley:10.1002/joc.6946 2024-09-15T18:25:03+00:00 Using Bayesian statistics to detect trends in Alaskan precipitation White, James H.R. Walsh, John E. Thoman, Richard L. Climate Program Office 2020 http://dx.doi.org/10.1002/joc.6946 https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6946 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.6946 https://rmets.onlinelibrary.wiley.com/doi/am-pdf/10.1002/joc.6946 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6946 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#am http://onlinelibrary.wiley.com/termsAndConditions#vor International Journal of Climatology volume 41, issue 3, page 2045-2059 ISSN 0899-8418 1097-0088 journal-article 2020 crwiley https://doi.org/10.1002/joc.6946 2024-09-03T04:22:46Z Abstract Air temperature has exhibited a clear positive trend over the past several decades throughout the arctic, including Alaska. Other variables, such as precipitation, have much more uncertain trends due to inhomogeneities in measurement and high internal variability. The use of linear regression to analyse precipitation in Alaska has resulted in often contradictory results. This paper proposes the use of Bayesian models such as the R package Rbeast to allow for the more nuanced analysis. The examples given in this paper show how Bayesian analysis can be used to detect subtle changes and better constrain the disagreement between data sources. Applied to gridded data, Bayesian analysis shows how precipitation has changed overtime across Alaska. Change has accelerated over the past decade, but only precipitation increase on the North Slope can be assigned high confidence. Overall, this analysis highlights how Bayesian techniques may be uniquely useful to climate research in regions with heterogeneous data sources and substantial internal variability. Article in Journal/Newspaper north slope Alaska Wiley Online Library International Journal of Climatology 41 3 2045 2059 |
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Open Polar |
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Wiley Online Library |
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crwiley |
language |
English |
description |
Abstract Air temperature has exhibited a clear positive trend over the past several decades throughout the arctic, including Alaska. Other variables, such as precipitation, have much more uncertain trends due to inhomogeneities in measurement and high internal variability. The use of linear regression to analyse precipitation in Alaska has resulted in often contradictory results. This paper proposes the use of Bayesian models such as the R package Rbeast to allow for the more nuanced analysis. The examples given in this paper show how Bayesian analysis can be used to detect subtle changes and better constrain the disagreement between data sources. Applied to gridded data, Bayesian analysis shows how precipitation has changed overtime across Alaska. Change has accelerated over the past decade, but only precipitation increase on the North Slope can be assigned high confidence. Overall, this analysis highlights how Bayesian techniques may be uniquely useful to climate research in regions with heterogeneous data sources and substantial internal variability. |
author2 |
Climate Program Office |
format |
Article in Journal/Newspaper |
author |
White, James H.R. Walsh, John E. Thoman, Richard L. |
spellingShingle |
White, James H.R. Walsh, John E. Thoman, Richard L. Using Bayesian statistics to detect trends in Alaskan precipitation |
author_facet |
White, James H.R. Walsh, John E. Thoman, Richard L. |
author_sort |
White, James H.R. |
title |
Using Bayesian statistics to detect trends in Alaskan precipitation |
title_short |
Using Bayesian statistics to detect trends in Alaskan precipitation |
title_full |
Using Bayesian statistics to detect trends in Alaskan precipitation |
title_fullStr |
Using Bayesian statistics to detect trends in Alaskan precipitation |
title_full_unstemmed |
Using Bayesian statistics to detect trends in Alaskan precipitation |
title_sort |
using bayesian statistics to detect trends in alaskan precipitation |
publisher |
Wiley |
publishDate |
2020 |
url |
http://dx.doi.org/10.1002/joc.6946 https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6946 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.6946 https://rmets.onlinelibrary.wiley.com/doi/am-pdf/10.1002/joc.6946 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6946 |
genre |
north slope Alaska |
genre_facet |
north slope Alaska |
op_source |
International Journal of Climatology volume 41, issue 3, page 2045-2059 ISSN 0899-8418 1097-0088 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#am http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/joc.6946 |
container_title |
International Journal of Climatology |
container_volume |
41 |
container_issue |
3 |
container_start_page |
2045 |
op_container_end_page |
2059 |
_version_ |
1810465465586155520 |