Constraining extreme precipitation projections using past precipitation variability
This study finds that projections of future extreme precipitation can be made more reliable using a constraint from observed present-day precipitation variability, which reduces projection uncertainty by 20–40% over the extra-tropics.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-34006-0 |
| _version_ | 1811233689810501632 |
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| author | Wenxia Zhang Kalli Furtado Tianjun Zhou Peili Wu Xiaolong Chen |
| author_facet | Wenxia Zhang Kalli Furtado Tianjun Zhou Peili Wu Xiaolong Chen |
| author_sort | Wenxia Zhang |
| collection | DOAJ |
| description | This study finds that projections of future extreme precipitation can be made more reliable using a constraint from observed present-day precipitation variability, which reduces projection uncertainty by 20–40% over the extra-tropics. |
| first_indexed | 2024-04-12T11:23:51Z |
| format | Article |
| id | doaj.art-f3177b1fa3734cd29fb129824df34a4c |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-12T11:23:51Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-f3177b1fa3734cd29fb129824df34a4c2022-12-22T03:35:17ZengNature PortfolioNature Communications2041-17232022-11-0113111110.1038/s41467-022-34006-0Constraining extreme precipitation projections using past precipitation variabilityWenxia Zhang0Kalli Furtado1Tianjun Zhou2Peili Wu3Xiaolong Chen4State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of SciencesMet OfficeState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of SciencesMet OfficeState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of SciencesThis study finds that projections of future extreme precipitation can be made more reliable using a constraint from observed present-day precipitation variability, which reduces projection uncertainty by 20–40% over the extra-tropics.https://doi.org/10.1038/s41467-022-34006-0 |
| spellingShingle | Wenxia Zhang Kalli Furtado Tianjun Zhou Peili Wu Xiaolong Chen Constraining extreme precipitation projections using past precipitation variability Nature Communications |
| title | Constraining extreme precipitation projections using past precipitation variability |
| title_full | Constraining extreme precipitation projections using past precipitation variability |
| title_fullStr | Constraining extreme precipitation projections using past precipitation variability |
| title_full_unstemmed | Constraining extreme precipitation projections using past precipitation variability |
| title_short | Constraining extreme precipitation projections using past precipitation variability |
| title_sort | constraining extreme precipitation projections using past precipitation variability |
| url | https://doi.org/10.1038/s41467-022-34006-0 |
| work_keys_str_mv | AT wenxiazhang constrainingextremeprecipitationprojectionsusingpastprecipitationvariability AT kallifurtado constrainingextremeprecipitationprojectionsusingpastprecipitationvariability AT tianjunzhou constrainingextremeprecipitationprojectionsusingpastprecipitationvariability AT peiliwu constrainingextremeprecipitationprojectionsusingpastprecipitationvariability AT xiaolongchen constrainingextremeprecipitationprojectionsusingpastprecipitationvariability |