Comparing regional precipitation and temperature extremes in climate model and reanalysis products
Abstract
A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.
- Authors:
- Publication Date:
- 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:
- 1345437
- Alternate Identifier(s):
- OSTI ID: 1377441
- Grant/Contract Number:
- AC02- 05CH11231; GA01101; AC02-05CH11231
- Resource Type:
- Published Article
- Journal Name:
- Weather and Climate Extremes
- Additional Journal Information:
- Journal Name: Weather and Climate Extremes Journal Volume: 13 Journal Issue: C; Journal ID: ISSN 2212-0947
- Publisher:
- Elsevier
- Country of Publication:
- Netherlands
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Extremes; Evaluation; Event attribution; CAM5.1; MIROC5; HadGEM3-A-N216
Citation Formats
Angélil, Oliver, Perkins-Kirkpatrick, Sarah, Alexander, Lisa V., Stone, Dáithí, Donat, Markus G., Wehner, Michael, Shiogama, Hideo, Ciavarella, Andrew, and Christidis, Nikolaos. Comparing regional precipitation and temperature extremes in climate model and reanalysis products. Netherlands: N. p., 2016.
Web. doi:10.1016/j.wace.2016.07.001.
Angélil, Oliver, Perkins-Kirkpatrick, Sarah, Alexander, Lisa V., Stone, Dáithí, Donat, Markus G., Wehner, Michael, Shiogama, Hideo, Ciavarella, Andrew, & Christidis, Nikolaos. Comparing regional precipitation and temperature extremes in climate model and reanalysis products. Netherlands. https://doi.org/10.1016/j.wace.2016.07.001
Angélil, Oliver, Perkins-Kirkpatrick, Sarah, Alexander, Lisa V., Stone, Dáithí, Donat, Markus G., Wehner, Michael, Shiogama, Hideo, Ciavarella, Andrew, and Christidis, Nikolaos. Thu .
"Comparing regional precipitation and temperature extremes in climate model and reanalysis products". Netherlands. https://doi.org/10.1016/j.wace.2016.07.001.
@article{osti_1345437,
title = {Comparing regional precipitation and temperature extremes in climate model and reanalysis products},
author = {Angélil, Oliver and Perkins-Kirkpatrick, Sarah and Alexander, Lisa V. and Stone, Dáithí and Donat, Markus G. and Wehner, Michael and Shiogama, Hideo and Ciavarella, Andrew and Christidis, Nikolaos},
abstractNote = {A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.},
doi = {10.1016/j.wace.2016.07.001},
journal = {Weather and Climate Extremes},
number = C,
volume = 13,
place = {Netherlands},
year = {Thu Sep 01 00:00:00 EDT 2016},
month = {Thu Sep 01 00:00:00 EDT 2016}
}
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https://doi.org/10.1016/j.wace.2016.07.001
https://doi.org/10.1016/j.wace.2016.07.001
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Works referencing / citing this record:
Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe
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- Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew
- Climate Dynamics, Vol. 52, Issue 1-2
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journal, June 2018
- Risser, Mark D.; Paciorek, Christopher J.; Stone, Dáithí A.
- Journal of the American Statistical Association, Vol. 114, Issue 525
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- Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew
- Climate Dynamics, Vol. 52, Issue 1-2
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- Risser, Mark D.; Paciorek, Christopher J.; Stone, Dáithí A.
- Journal of the American Statistical Association, Vol. 114, Issue 525
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- Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah
- Climate Dynamics, Vol. 50, Issue 7-8
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- Crimp, Steven; Jin, Huidong; Kokic, Philip
- Climate Dynamics, Vol. 52, Issue 1-2
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journal, January 2020
- Zhao, Siyao; Zhou, Tianjun; Chen, Xiaolong
- Climate Dynamics, Vol. 54, Issue 3-4
A hierarchical collection of political/economic regions for analysis of climate extremes
journal, June 2019
- Stone, Dáithí A.
- Climatic Change, Vol. 155, Issue 4
Calibrating Climate Model Ensembles for Assessing Extremes in a Changing Climate
journal, June 2018
- Herger, Nadja; Angélil, Oliver; Abramowitz, Gab
- Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 11
Toward Calibrated Language for Effectively Communicating the Results of Extreme Event Attribution Studies
journal, September 2019
- Lewis, Sophie C.; King, Andrew D.; Perkins‐Kirkpatrick, Sarah E.
- Earth's Future, Vol. 7, Issue 9
Towards reliable extreme weather and climate event attribution
journal, April 2019
- Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco
- Nature Communications, Vol. 10, Issue 1
Emissions and emergence: a new index comparing relative contributions to climate change with relative climatic consequences
journal, July 2019
- Frame, David J.; Harrington, Luke J.; Fuglestvedt, Jan S.
- Environmental Research Letters, Vol. 14, Issue 8
Forecasted attribution of the human influence on Hurricane Florence
journal, January 2020
- Reed, K. A.; Stansfield, A. M.; Wehner, M. F.
- Science Advances, Vol. 6, Issue 1
Brief communication: Drought likelihood for East Africa
journal, January 2018
- Yang, Hui; Huntingford, Chris
- Natural Hazards and Earth System Sciences, Vol. 18, Issue 2