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Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect
As China makes every effort to control air pollution, India emerges as the world’s most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636995/ https://www.ncbi.nlm.nih.gov/pubmed/31328156 http://dx.doi.org/10.1126/sciadv.aav4157 |
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author | Gao, Meng Sherman, Peter Song, Shaojie Yu, Yueyue Wu, Zhiwei McElroy, Michael B. |
author_facet | Gao, Meng Sherman, Peter Song, Shaojie Yu, Yueyue Wu, Zhiwei McElroy, Michael B. |
author_sort | Gao, Meng |
collection | PubMed |
description | As China makes every effort to control air pollution, India emerges as the world’s most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulated mainly by a combination of El Niño and the Antarctic Oscillation (AAO). Both El Niño sea surface temperature (SST) anomalies and AAO-induced Indian Ocean Meridional Dipole SST anomalies can persist from autumn to winter, offering prospects for a prewinter forecast of wintertime aerosol pollution over northern India. We constructed a multivariable regression model incorporating El Niño and AAO indices for autumn to predict wintertime AOD. The prediction exhibits a high degree of consistency with observation, with a correlation coefficient of 0.78 (P < 0.01). This statistical model could allow the Indian government to forecast aerosol pollution conditions in winter and accordingly improve plans for pollution control. |
format | Online Article Text |
id | pubmed-6636995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66369952019-07-19 Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect Gao, Meng Sherman, Peter Song, Shaojie Yu, Yueyue Wu, Zhiwei McElroy, Michael B. Sci Adv Research Articles As China makes every effort to control air pollution, India emerges as the world’s most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulated mainly by a combination of El Niño and the Antarctic Oscillation (AAO). Both El Niño sea surface temperature (SST) anomalies and AAO-induced Indian Ocean Meridional Dipole SST anomalies can persist from autumn to winter, offering prospects for a prewinter forecast of wintertime aerosol pollution over northern India. We constructed a multivariable regression model incorporating El Niño and AAO indices for autumn to predict wintertime AOD. The prediction exhibits a high degree of consistency with observation, with a correlation coefficient of 0.78 (P < 0.01). This statistical model could allow the Indian government to forecast aerosol pollution conditions in winter and accordingly improve plans for pollution control. American Association for the Advancement of Science 2019-07-17 /pmc/articles/PMC6636995/ /pubmed/31328156 http://dx.doi.org/10.1126/sciadv.aav4157 Text en Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Gao, Meng Sherman, Peter Song, Shaojie Yu, Yueyue Wu, Zhiwei McElroy, Michael B. Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect |
title | Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect |
title_full | Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect |
title_fullStr | Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect |
title_full_unstemmed | Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect |
title_short | Seasonal prediction of Indian wintertime aerosol pollution using the ocean memory effect |
title_sort | seasonal prediction of indian wintertime aerosol pollution using the ocean memory effect |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636995/ https://www.ncbi.nlm.nih.gov/pubmed/31328156 http://dx.doi.org/10.1126/sciadv.aav4157 |
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