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Title: A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contribution takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of themore » uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less
Authors:
 [1] ;  [1] ;  [2] ;  [1] ;  [1] ;  [1] ;  [1] ;  [3] ;  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of New South Wales, Sydney, NSW (Australia)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States)
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Weather and Climate Extremes
Additional Journal Information:
Journal Volume: 19; Journal Issue: C; Journal ID: ISSN 2212-0947
Publisher:
Elsevier
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org:
SC-23.1 USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; C20C+ D&A; CAM5.1; Extremes; Event attribution; Attributable warming
OSTI Identifier:
1425433

Stone, Dáithí A., Risser, Mark D., Angélil, Oliver M., Wehner, Michael F., Cholia, Shreyas, Keen, Noel, Krishnan, Harinarayan, O'Brien, Travis A., and Collins, William D.. A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree. United States: N. p., Web. doi:10.1016/j.wace.2017.12.003.
Stone, Dáithí A., Risser, Mark D., Angélil, Oliver M., Wehner, Michael F., Cholia, Shreyas, Keen, Noel, Krishnan, Harinarayan, O'Brien, Travis A., & Collins, William D.. A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree. United States. doi:10.1016/j.wace.2017.12.003.
Stone, Dáithí A., Risser, Mark D., Angélil, Oliver M., Wehner, Michael F., Cholia, Shreyas, Keen, Noel, Krishnan, Harinarayan, O'Brien, Travis A., and Collins, William D.. 2018. "A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree". United States. doi:10.1016/j.wace.2017.12.003. https://www.osti.gov/servlets/purl/1425433.
@article{osti_1425433,
title = {A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree},
author = {Stone, Dáithí A. and Risser, Mark D. and Angélil, Oliver M. and Wehner, Michael F. and Cholia, Shreyas and Keen, Noel and Krishnan, Harinarayan and O'Brien, Travis A. and Collins, William D.},
abstractNote = {This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contribution takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.},
doi = {10.1016/j.wace.2017.12.003},
journal = {Weather and Climate Extremes},
number = C,
volume = 19,
place = {United States},
year = {2018},
month = {3}
}