Improve the projection of East China summer precipitation with emergent constraints

Under global warming, summer precipitation over East China was projected to increase by current state-of-the-art climate models, but a large inter-model spread exists. Here we try to reduce the projection uncertainty by imposing constraints. Our procedure consists of first decomposing the projected future precipitation into inter-model principal components. The two leading modes (region-wide uniform monopole and north-south dipole, accounting for 55% of variability), by emergent constraints, are then linked to the simulation of historical precipitation in the northwest Pacific and the tropical Pacific (constraining areas). This allows us to reduce the uncertainties by 23% and obtain a smaller increase of projected precipitation in East China, relative to previous multi-model ensemble projections. Quasi-uniform increases, although weak, are obtained for the first mode, while the second mode shows a contrast pattern with a decrease in the south and an increase in the north, which both contribute to the spatial structure of constrainted projection. It is also shown that the emergent relations of both modes are physically consistent, with an enhancement of future zonal land-sea thermal contrast and a La Niña-like pattern, respectively. The use of emergent constraints inspires more confidence in the future regional precipitation projection and helps policymakers and stakeholders adjust their management policies.

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Publication Details

Journal
npj Climate and Atmospheric Science
Published
2024-12-04
DOI
https://doi.org/10.1038/s41612-024-00863-3
Citations
9
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
2.54

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article

Improve the projection of East China summer precipitation with emergent constraints

Huanhuan Zhu, Sheng Jiang, Wei Li, Laurent Li et al.
9 citations
npj Climate and Atmospheric Science
Climate variability and models
2.54
article

Improve the projection of East China summer precipitation with emergent constraints

Huanhuan Zhu, Sheng Jiang, Wei Li, Laurent Li, Zhihong Jiang
article en
9 citations

Abstract

Under global warming, summer precipitation over East China was projected to increase by current state-of-the-art climate models, but a large inter-model spread exists. Here we try to reduce the projection uncertainty by imposing constraints. Our procedure consists of first decomposing the projected future precipitation into inter-model principal components. The two leading modes (region-wide uniform monopole and north-south dipole, accounting for 55% of variability), by emergent constraints, are then linked to the simulation of historical precipitation in the northwest Pacific and the tropical Pacific (constraining areas). This allows us to reduce the uncertainties by 23% and obtain a smaller increase of projected precipitation in East China, relative to previous multi-model ensemble projections. Quasi-uniform increases, although weak, are obtained for the first mode, while the second mode shows a contrast pattern with a decrease in the south and an increase in the north, which both contribute to the spatial structure of constrainted projection. It is also shown that the emergent relations of both modes are physically consistent, with an enhancement of future zonal land-sea thermal contrast and a La Niña-like pattern, respectively. The use of emergent constraints inspires more confidence in the future regional precipitation projection and helps policymakers and stakeholders adjust their management policies.

npj Climate and Atmospheric ScienceVol. 7(1)
Centre National de la Recherche Scientifique (FR), China Meteorological Administration (CN), École Polytechnique (FR), Nanjing University of Information Science and Technology (CN), Sorbonne Université (FR), Laboratoire de Météorologie Dynamique (FR)
National Natural Science Foundation of China, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province, Nanjing University of Information Science and Technology, Key Laboratory of Meteorological Disaster
Climate action
Openalex Percentile: Top 10%
Climate variability and models
2.54
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