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Title: Predicting future uncertainty constraints on global warming projections

Abstract

Projections of global mean temperature changes (ΔT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by "current knowledge" of the ΔTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of ΔT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the ΔTs uncertainty in the 2040 s by 2029, and more than 60% of the ΔTs uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2°C (3°C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.

Authors:
 [1];  [2];  [1];  [1];  [3];  [4];  [1];  [5]
  1. National Institute for Environmental Studies, Ibaraki (Japan)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Tokyo Univ. of Science, Chiba (Japan)
  4. The Univ. of Tokyo, Tokyo (Japan)
  5. Univ. of Oxford, Oxford (United Kingdom)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1379028
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Attribution; Projection and prediction

Citation Formats

Shiogama, H., Stone, D., Emori, S., Takahashi, K., Mori, S., Maeda, A., Ishizaki, Y., and Allen, M. R. Predicting future uncertainty constraints on global warming projections. United States: N. p., 2016. Web. doi:10.1038/srep18903.
Shiogama, H., Stone, D., Emori, S., Takahashi, K., Mori, S., Maeda, A., Ishizaki, Y., & Allen, M. R. Predicting future uncertainty constraints on global warming projections. United States. doi:10.1038/srep18903.
Shiogama, H., Stone, D., Emori, S., Takahashi, K., Mori, S., Maeda, A., Ishizaki, Y., and Allen, M. R. Mon . "Predicting future uncertainty constraints on global warming projections". United States. doi:10.1038/srep18903. https://www.osti.gov/servlets/purl/1379028.
@article{osti_1379028,
title = {Predicting future uncertainty constraints on global warming projections},
author = {Shiogama, H. and Stone, D. and Emori, S. and Takahashi, K. and Mori, S. and Maeda, A. and Ishizaki, Y. and Allen, M. R.},
abstractNote = {Projections of global mean temperature changes (ΔT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by "current knowledge" of the ΔTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of ΔT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the ΔTs uncertainty in the 2040 s by 2029, and more than 60% of the ΔTs uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2°C (3°C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.},
doi = {10.1038/srep18903},
journal = {Scientific Reports},
number = 1,
volume = 6,
place = {United States},
year = {2016},
month = {1}
}

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