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Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia
Many studies have considered temperature trends at the global scale, but the literature is commonly associated with an overall increase in mean temperature in a defined past time period and hence lacking in in-depth analysis of the latent trends. For example, in addition to heterogeneity in mean and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9401128/ https://www.ncbi.nlm.nih.gov/pubmed/36001585 http://dx.doi.org/10.1371/journal.pone.0271457 |
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author | Duan, Qibin McGrory, Clare A. Brown, Glenn Mengersen, Kerrie Wang, You-Gan |
author_facet | Duan, Qibin McGrory, Clare A. Brown, Glenn Mengersen, Kerrie Wang, You-Gan |
author_sort | Duan, Qibin |
collection | PubMed |
description | Many studies have considered temperature trends at the global scale, but the literature is commonly associated with an overall increase in mean temperature in a defined past time period and hence lacking in in-depth analysis of the latent trends. For example, in addition to heterogeneity in mean and median values, daily temperature data often exhibit quasi-periodic heterogeneity in variance, which has largely been overlooked in climate research. To this end, we propose a joint model of quantile regression and variability. By accounting appropriately for the heterogeneity in these types of data, our analysis using Australian data reveals that daily maximum temperature is warming by ∼0.21°C per decade and daily minimum temperature by ∼0.13°C per decade. More interestingly, our modeling also shows nuanced patterns of change over space and time depending on location, season, and the percentiles of the temperature series. |
format | Online Article Text |
id | pubmed-9401128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94011282022-08-25 Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia Duan, Qibin McGrory, Clare A. Brown, Glenn Mengersen, Kerrie Wang, You-Gan PLoS One Research Article Many studies have considered temperature trends at the global scale, but the literature is commonly associated with an overall increase in mean temperature in a defined past time period and hence lacking in in-depth analysis of the latent trends. For example, in addition to heterogeneity in mean and median values, daily temperature data often exhibit quasi-periodic heterogeneity in variance, which has largely been overlooked in climate research. To this end, we propose a joint model of quantile regression and variability. By accounting appropriately for the heterogeneity in these types of data, our analysis using Australian data reveals that daily maximum temperature is warming by ∼0.21°C per decade and daily minimum temperature by ∼0.13°C per decade. More interestingly, our modeling also shows nuanced patterns of change over space and time depending on location, season, and the percentiles of the temperature series. Public Library of Science 2022-08-24 /pmc/articles/PMC9401128/ /pubmed/36001585 http://dx.doi.org/10.1371/journal.pone.0271457 Text en © 2022 Duan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Duan, Qibin McGrory, Clare A. Brown, Glenn Mengersen, Kerrie Wang, You-Gan Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia |
title | Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia |
title_full | Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia |
title_fullStr | Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia |
title_full_unstemmed | Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia |
title_short | Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia |
title_sort | spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: a study of long-term daily temperature in australia |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9401128/ https://www.ncbi.nlm.nih.gov/pubmed/36001585 http://dx.doi.org/10.1371/journal.pone.0271457 |
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