Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.509 IF 5.509
  • IF 5-year value: 5.689 IF 5-year 5.689
  • CiteScore value: 5.44 CiteScore 5.44
  • SNIP value: 1.519 SNIP 1.519
  • SJR value: 3.032 SJR 3.032
  • IPP value: 5.37 IPP 5.37
  • h5-index value: 86 h5-index 86
  • Scimago H index value: 161 Scimago H index 161
Discussion papers
https://doi.org/10.5194/acp-2018-650
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2018-650
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Aug 2018

Research article | 21 Aug 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Quantifying uncertainty from aerosol and atmospheric parameters and their impact on climate sensitivity

Christopher G. Fletcher1, Ben Kravitz2, and Bakr Badawy1,a Christopher G. Fletcher et al.
  • 1Department of Geography and Environmental Management, University of Waterloo, Waterloo ON, Canada
  • 2Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
  • anow at: Environment and Climate Change Canada, Dorval, Québec, Canada

Abstract. Climate sensitivity in Earth System Models (ESMs) is an emergent property that is affected by structural (missing or inaccurate model physics) and parametric (variations in model parameters) uncertainty. This work provides the first quantitative assessment of the role of compensation between uncertainties in aerosol forcing and atmospheric parameters, and their impact on the climate sensitivity of the Community Atmosphere Model, Version 4 (CAM4). Running the model with prescribed ocean and ice conditions, we perturb four parameters related to sulfate and black carbon aerosol radiative forcing and distribution, as well as five atmospheric parameters related to clouds, convection, and radiative flux. The atmospheric parameters explain more than 85\% of the variance in climate sensitivity for the ranges of parameters explored here, with two parameters being the most important: one controlling low cloud amount, and one controlling the timescale for deep convection. Although the aerosol parameters strongly affect aerosol optical depth, the effects of these aerosol parameters on climate sensitivity are substantially weaker than the effects of the atmospheric parameters. Based on comparisons to inter-model spread of other ESMs, we conclude that structural uncertainties in this configuration of CAM4 likely contribute three times more to uncertainty in climate sensitivity than parametric uncertainty. We provide several parameter sets that could provide plausible (measured by a skill score) configurations of CAM4, but with different sulfate aerosol radiative forcing, black carbon radiative forcing, and climate sensitivity.

Christopher G. Fletcher et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Co-Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Christopher G. Fletcher et al.
Data sets

Data and scripts archive C. G. Fletcher https://doi.org/10.5281/zenodo.1400612

Christopher G. Fletcher et al.
Viewed  
Total article views: 399 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
305 88 6 399 3 6
  • HTML: 305
  • PDF: 88
  • XML: 6
  • Total: 399
  • BibTeX: 3
  • EndNote: 6
Views and downloads (calculated since 21 Aug 2018)
Cumulative views and downloads (calculated since 21 Aug 2018)
Viewed (geographical distribution)  
Total article views: 399 (including HTML, PDF, and XML) Thereof 396 with geography defined and 3 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 20 Nov 2018
Publications Copernicus
Special issue
Download
Short summary
The most important number in climate science is the climate sensitivity (CS), which tells us how much Earth will warm as carbon dioxide increases. We cannot know the true CS for the Earth, and the estimate of CS from climate models has a wide range. This study identifies the major factors that control this range in CS. We show that the assumptions and choice of methods used in creating a climate model are three times more important than fine-tuning the details of the model after it is created.
The most important number in climate science is the climate sensitivity (CS), which tells us how...
Citation
Share