Isolating the anthropogenic component of Arctic warming
Abstract
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.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Dalhousie Univ., Halifax, NS (Canada)
- Par Associates, Las Cruces New Mexico USA
- Univ. of Oslo (Norway)
- Univ. of Colorado, Boulder, CO (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1291212
- Report Number(s):
- LA-UR-14-22377
Journal ID: ISSN 0094-8276
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Geophysical Research Letters
- Additional Journal Information:
- Journal Volume: 41; Journal Issue: 10; Journal ID: ISSN 0094-8276
- Publisher:
- American Geophysical Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Earth Sciences
Citation Formats
Chylek, Petr, Hengartner, Nicholas, Lesins, Glen, Klett, James D., Humlum, Ole, Wyatt, Marcia, and Dubey, Manvendra K. Isolating the anthropogenic component of Arctic warming. United States: N. p., 2014.
Web. doi:10.1002/2014GL060184.
Chylek, Petr, Hengartner, Nicholas, Lesins, Glen, Klett, James D., Humlum, Ole, Wyatt, Marcia, & Dubey, Manvendra K. Isolating the anthropogenic component of Arctic warming. United States. https://doi.org/10.1002/2014GL060184
Chylek, Petr, Hengartner, Nicholas, Lesins, Glen, Klett, James D., Humlum, Ole, Wyatt, Marcia, and Dubey, Manvendra K. Wed .
"Isolating the anthropogenic component of Arctic warming". United States. https://doi.org/10.1002/2014GL060184. https://www.osti.gov/servlets/purl/1291212.
@article{osti_1291212,
title = {Isolating the anthropogenic component of Arctic warming},
author = {Chylek, Petr and Hengartner, Nicholas and Lesins, Glen and Klett, James D. and Humlum, Ole and Wyatt, Marcia and Dubey, Manvendra K.},
abstractNote = {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.},
doi = {10.1002/2014GL060184},
journal = {Geophysical Research Letters},
number = 10,
volume = 41,
place = {United States},
year = {Wed May 28 00:00:00 EDT 2014},
month = {Wed May 28 00:00:00 EDT 2014}
}
Web of Science
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