Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China
ABSTRACT Precipitation in Xinjiang, China, was modelled with covariates, such as time and climate indices, using quantile regressions. Compared to a frequentist quantile regression, a Bayesian quantile regression tended to generate smoother and narrower band confidence intervals of quantile regressi...
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crwiley:10.1002/joc.4794 2024-06-23T07:50:39+00:00 Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China Tan, Xuezhi Shao, Dongguo University of Alberta National Natural Science Foundation of China 2016 http://dx.doi.org/10.1002/joc.4794 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.4794 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.4794 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor International Journal of Climatology volume 37, issue 3, page 1510-1525 ISSN 0899-8418 1097-0088 journal-article 2016 crwiley https://doi.org/10.1002/joc.4794 2024-06-04T06:41:43Z ABSTRACT Precipitation in Xinjiang, China, was modelled with covariates, such as time and climate indices, using quantile regressions. Compared to a frequentist quantile regression, a Bayesian quantile regression tended to generate smoother and narrower band confidence intervals of quantile regression coefficients, especially at extremely high and low quantile levels. A full picture of temporal trends at quantile levels from 0.01 to 0.99 indicates that the wet season (May to August) precipitation in Northern Xinjiang and the western regions of Southern Xinjiang showed statistically significant increases with different magnitudes over all quantile levels. However, the wet season precipitation in South‐eastern Xinjiang decreased at some quantile levels. The Eastern Atlantic/Western Russia ( EAWR ) pattern was the most significant large‐scale climate pattern that influenced wet season precipitation when compared to other studied patterns, i.e. the El Niño–Southern Oscillation ( ENSO ), the Atlantic Multidecadal Oscillation ( AMO ), the Pacific Decadal Oscillation ( PDO ), the Northern Oscillation ( NO ), the Arctic Oscillation ( AO ) and the North Atlantic Oscillation ( NAO ). The quantile regression coefficients associated with the EAWR index positively increased from low to high quantile levels. The ENSO significantly affected the extremely high wet season precipitation in Xinjiang. El Niño increased and La Niña decreased wet season precipitation in Northern Xinjiang, with different magnitudes at different quantile levels. Other climate patterns, i.e. the AMO , PDO , NO , NAO and AO , did not evidently affect the wet season precipitation conditional on the ENSO and EAWR . These findings suggest that the predictability of seasonal precipitation over Xinjiang can be improved by incorporating indices associated with the ENSO and EAWR as model predictors. Article in Journal/Newspaper Arctic North Atlantic North Atlantic oscillation Wiley Online Library Arctic Pacific International Journal of Climatology 37 3 1510 1525 |
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Wiley Online Library |
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crwiley |
language |
English |
description |
ABSTRACT Precipitation in Xinjiang, China, was modelled with covariates, such as time and climate indices, using quantile regressions. Compared to a frequentist quantile regression, a Bayesian quantile regression tended to generate smoother and narrower band confidence intervals of quantile regression coefficients, especially at extremely high and low quantile levels. A full picture of temporal trends at quantile levels from 0.01 to 0.99 indicates that the wet season (May to August) precipitation in Northern Xinjiang and the western regions of Southern Xinjiang showed statistically significant increases with different magnitudes over all quantile levels. However, the wet season precipitation in South‐eastern Xinjiang decreased at some quantile levels. The Eastern Atlantic/Western Russia ( EAWR ) pattern was the most significant large‐scale climate pattern that influenced wet season precipitation when compared to other studied patterns, i.e. the El Niño–Southern Oscillation ( ENSO ), the Atlantic Multidecadal Oscillation ( AMO ), the Pacific Decadal Oscillation ( PDO ), the Northern Oscillation ( NO ), the Arctic Oscillation ( AO ) and the North Atlantic Oscillation ( NAO ). The quantile regression coefficients associated with the EAWR index positively increased from low to high quantile levels. The ENSO significantly affected the extremely high wet season precipitation in Xinjiang. El Niño increased and La Niña decreased wet season precipitation in Northern Xinjiang, with different magnitudes at different quantile levels. Other climate patterns, i.e. the AMO , PDO , NO , NAO and AO , did not evidently affect the wet season precipitation conditional on the ENSO and EAWR . These findings suggest that the predictability of seasonal precipitation over Xinjiang can be improved by incorporating indices associated with the ENSO and EAWR as model predictors. |
author2 |
University of Alberta National Natural Science Foundation of China |
format |
Article in Journal/Newspaper |
author |
Tan, Xuezhi Shao, Dongguo |
spellingShingle |
Tan, Xuezhi Shao, Dongguo Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China |
author_facet |
Tan, Xuezhi Shao, Dongguo |
author_sort |
Tan, Xuezhi |
title |
Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China |
title_short |
Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China |
title_full |
Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China |
title_fullStr |
Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China |
title_full_unstemmed |
Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China |
title_sort |
precipitation trends and teleconnections identified using quantile regressions over xinjiang, china |
publisher |
Wiley |
publishDate |
2016 |
url |
http://dx.doi.org/10.1002/joc.4794 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.4794 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.4794 |
geographic |
Arctic Pacific |
geographic_facet |
Arctic Pacific |
genre |
Arctic North Atlantic North Atlantic oscillation |
genre_facet |
Arctic North Atlantic North Atlantic oscillation |
op_source |
International Journal of Climatology volume 37, issue 3, page 1510-1525 ISSN 0899-8418 1097-0088 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/joc.4794 |
container_title |
International Journal of Climatology |
container_volume |
37 |
container_issue |
3 |
container_start_page |
1510 |
op_container_end_page |
1525 |
_version_ |
1802641565440540672 |