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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...

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Detalles Bibliográficos
Autores principales: Duan, Qibin, McGrory, Clare A., Brown, Glenn, Mengersen, Kerrie, Wang, You-Gan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
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.
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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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