Machine learning–based observation-constrained projections reveal elevated global socioeconomic risks from wildfire
A new study develops a machine learning framework to observationally constrain CMIP6-simulated fire carbon emissions, finding a weaker increase in 21st-century global fires but higher increase in their socioeconomic risks than previously thought.
Main Authors: | Yan Yu, Jiafu Mao, Stan D. Wullschleger, Anping Chen, Xiaoying Shi, Yaoping Wang, Forrest M. Hoffman, Yulong Zhang, Eric Pierce |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-03-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-022-28853-0 |
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