Isolating the anthropogenic component of Arctic warming
Structural equation modeling is used in statistical applications as both confirmatory and exploratory modeling to test models and to suggest the most plausible explanation for a relationship between the independent and the dependent variables. Although structural analysis cannot prove causation, it...
| Published in: | Geophysical Research Letters |
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| Main Authors: | , , , , , , |
| Language: | unknown |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://www.osti.gov/servlets/purl/1291212 https://www.osti.gov/biblio/1291212 https://doi.org/10.1002/2014GL060184 |
| Summary: | Structural equation modeling is used in statistical applications as both confirmatory and exploratory modeling to test models and to suggest the most plausible explanation for a relationship between the independent and the dependent variables. Although structural analysis cannot prove causation, it can suggest the most plausible set of factors that influence the observed variable. Here, we apply structural model analysis to the annual mean Arctic surface air temperature from 1900 to 2012 to find the most effective set of predictors and to isolate the anthropogenic component of the recent Arctic warming by subtracting the effects of natural forcing and variability from the observed temperature. We also find that anthropogenic greenhouse gases and aerosols radiative forcing and the Atlantic Multidecadal Oscillation internal mode dominate Arctic temperature variability. Finally, our structural model analysis of observational data suggests that about half of the recent Arctic warming of 0.64 K/decade may have anthropogenic causes. |
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