Inferring the anthropogenic contribution to local temperature extremes

Stone, Dáithí A.; Paciorek, Christopher J.; Prabhat, .; Pall, Pardeep; Wehner, Michael

doi:10.1073/pnas.1221461110

Title: Inferring the anthropogenic contribution to local temperature extremes

Abstract

Here, in PNAS, Hansen et al. document an observed planet-wide increase in the frequency of extremely hot months and a decrease in the frequency of extremely cold months, consistent with earlier studies. This analysis is achieved through aggregation of gridded monthly temperature measurements from all over the planet. Such aggregation is advantageous in achieving statistical sampling power; however, it sacrifices regional specificity. Lastly, in that light, we find the conclusion of Hansen et al. that “the extreme summer climate anomalies in Texas in 2011, in Moscow in 2010, and in France in 2003 almost certainly would not have occurred in the absence of global warming” to be unsubstantiated by their analysis.

Authors:

Stone, Dáithí A. ^[1]; Paciorek, Christopher J. ^[2]; Prabhat, . ^[1]; Pall, Pardeep ^[1]; Wehner, Michael ^[1]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
Univ. of California, Berkeley, CA (United States). Department of Statistics

Publication Date:: Tue Mar 19 00:00:00 EDT 2013

Research Org.:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

OSTI Identifier:: 1407185

Grant/Contract Number:: AC02-05CH11231

Resource Type:: Accepted Manuscript

Journal Name:: Proceedings of the National Academy of Sciences of the United States of America

Additional Journal Information:: Journal Volume: 110; Journal Issue: 17; Journal ID: ISSN 0027-8424

Publisher:: National Academy of Sciences, Washington, DC (United States)

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING

Citation Formats


                    Stone, Dáithí A., Paciorek, Christopher J., Prabhat, ., Pall, Pardeep, and Wehner, Michael. Inferring the anthropogenic contribution to local temperature extremes.  United States: N. p., 2013. 
Web.  doi:10.1073/pnas.1221461110.

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                    Stone, Dáithí A., Paciorek, Christopher J., Prabhat, ., Pall, Pardeep, & Wehner, Michael. Inferring the anthropogenic contribution to local temperature extremes.  United States.  https://doi.org/10.1073/pnas.1221461110

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                    Stone, Dáithí A., Paciorek, Christopher J., Prabhat, ., Pall, Pardeep, and Wehner, Michael. Tue .  
"Inferring the anthropogenic contribution to local temperature extremes".  United States.  https://doi.org/10.1073/pnas.1221461110.  https://www.osti.gov/servlets/purl/1407185.

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@article{osti_1407185,

  title        = {Inferring the anthropogenic contribution to local temperature extremes},

  author       = {Stone, Dáithí A. and Paciorek, Christopher J. and Prabhat, . and Pall, Pardeep and Wehner, Michael},

  abstractNote = {Here, in PNAS, Hansen et al. document an observed planet-wide increase in the frequency of extremely hot months and a decrease in the frequency of extremely cold months, consistent with earlier studies. This analysis is achieved through aggregation of gridded monthly temperature measurements from all over the planet. Such aggregation is advantageous in achieving statistical sampling power; however, it sacrifices regional specificity. Lastly, in that light, we find the conclusion of Hansen et al. that “the extreme summer climate anomalies in Texas in 2011, in Moscow in 2010, and in France in 2003 almost certainly would not have occurred in the absence of global warming” to be unsubstantiated by their analysis.},

  doi          = {10.1073/pnas.1221461110},

  journal      = {Proceedings of the National Academy of Sciences of the United States of America},

  number       = 17,

  volume       = 110,

  place        = {United States},

  year         = {Tue Mar 19 00:00:00 EDT 2013},

  month        = {Tue Mar 19 00:00:00 EDT 2013}

}

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https://doi.org/10.1073/pnas.1221461110

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Works referenced in this record:

Perception of climate change
journal, August 2012

Hansen, J.; Sato, M.; Ruedy, R.
Proceedings of the National Academy of Sciences, Vol. 109, Issue 37
DOI: 10.1073/pnas.1205276109

Changes in Climate Extremes and their Impacts on the Natural Physical Environment
book, May 2012

Seneviratne, Sonia I.; Nicholls, Neville; Easterling, David
Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation
DOI: 10.1017/CBO9781139177245.006

Works referencing / citing this record:

Quantile-based bias correction and uncertainty quantification of extreme event attribution statements
text, January 2016

Jeon, Soyoung; Paciorek, Christopher J.; Wehner, Michael F.
arXiv
DOI: 10.48550/arxiv.1602.04139

Quantifying statistical uncertainty in the attribution of human influence on severe weather
preprint, January 2017

Paciorek, Christopher J.; Stone, Dáithí A.; Wehner, Michael F.
arXiv
DOI: 10.48550/arxiv.1706.03388

Quantifying the influence of global warming on unprecedented extreme climate events
journal, April 2017

Diffenbaugh, Noah S.; Singh, Deepti; Mankin, Justin S.
Proceedings of the National Academy of Sciences, Vol. 114, Issue 19
DOI: 10.1073/pnas.1618082114

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Title: Inferring the anthropogenic contribution to local temperature extremes

Abstract

Citation Formats

Perception of climate change journal, August 2012

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Quantile-based bias correction and uncertainty quantification of extreme event attribution statements text, January 2016

Quantifying statistical uncertainty in the attribution of human influence on severe weather preprint, January 2017

Quantifying the influence of global warming on unprecedented extreme climate events journal, April 2017

Perception of climate change
journal, August 2012

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book, May 2012

Quantile-based bias correction and uncertainty quantification of extreme event attribution statements
text, January 2016

Quantifying statistical uncertainty in the attribution of human influence on severe weather
preprint, January 2017

Quantifying the influence of global warming on unprecedented extreme climate events
journal, April 2017