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Title: Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations

Abstract

Model estimates of aerosol impacts on climate frequently exceed observational estimates. Conventional evaluation procedures generally neglect sampling and retrieval differences that confound interpretation of discrepancies. Here we show that satellite simulators can reconcile differences between modeled and retrieved estimates of aerosol climate impacts. A-­train satellite simulators overflying the model atmosphere matching satellite retrieval procedures moderately underestimate the model’s total aerosol direct radiative effect and significantly underestimate anthropogenic aerosol indirect effects (by a factor of 3). Model cloud droplet size and precipitation probability retrieved from simulators indicate significantly less sensitivity to aerosols than the real model sensitivity, exhibiting much better agreement with satellite estimates. While climate models are still likely to have substantial deficiencies in representing aerosol­climate interactions, inconsistent comparisons between modeled and observed estimates can lead to inappropriate model calibration, development, and interpretation. Simulators are a necessary tool for comparing models and satellite estimates of aerosol climate effects.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [1]
+ Show Author Affiliations
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Sorbonne Univ., Paris (France); Ecole Polytechnique, Palaiseau (France)
  3. NASA Langley Research Center, Hampton, VA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1463346
Alternate Identifier(s):
OSTI ID: 1513205
Report Number(s):
PNNL-SA-118058
Journal ID: ISSN 2041-1723; PII: 5028
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Ma, Po -Lun, Rasch, Philip J., Chepfer, Helene, Winker, David M., and Ghan, Steven J. Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations. United States: N. p., 2018. Web. doi:10.1038/S41467-018-05028-4.
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Ma, Po -Lun, Rasch, Philip J., Chepfer, Helene, Winker, David M., & Ghan, Steven J. Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations. United States. https://doi.org/10.1038/S41467-018-05028-4
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Ma, Po -Lun, Rasch, Philip J., Chepfer, Helene, Winker, David M., and Ghan, Steven J. Fri . "Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations". United States. https://doi.org/10.1038/S41467-018-05028-4. https://www.osti.gov/servlets/purl/1463346.
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@article{osti_1463346,
title = {Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations},
author = {Ma, Po -Lun and Rasch, Philip J. and Chepfer, Helene and Winker, David M. and Ghan, Steven J.},
abstractNote = {Model estimates of aerosol impacts on climate frequently exceed observational estimates. Conventional evaluation procedures generally neglect sampling and retrieval differences that confound interpretation of discrepancies. Here we show that satellite simulators can reconcile differences between modeled and retrieved estimates of aerosol climate impacts. A-­train satellite simulators overflying the model atmosphere matching satellite retrieval procedures moderately underestimate the model’s total aerosol direct radiative effect and significantly underestimate anthropogenic aerosol indirect effects (by a factor of 3). Model cloud droplet size and precipitation probability retrieved from simulators indicate significantly less sensitivity to aerosols than the real model sensitivity, exhibiting much better agreement with satellite estimates. While climate models are still likely to have substantial deficiencies in representing aerosol­climate interactions, inconsistent comparisons between modeled and observed estimates can lead to inappropriate model calibration, development, and interpretation. Simulators are a necessary tool for comparing models and satellite estimates of aerosol climate effects.},
doi = {10.1038/S41467-018-05028-4},
journal = {Nature Communications},
number = 1,
volume = 9,
place = {United States},
year = {Fri Jul 06 00:00:00 EDT 2018},
month = {Fri Jul 06 00:00:00 EDT 2018}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1038/S41467-018-05028-4
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Cited by: 29 works
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Figures / Tables:

Fig. 1 Fig. 1 : Global mean susceptibility of cloud droplet size, susceptibility of precipitation probability, and effective radiative forcing due to aerosol-cloud interactions. Estimates of SRe = −∂ln(Re)/∂ln(CCN)18, SPOP=−∂ln(POP)/ ∂ln(CCN)6, and the inferred ERFaci are derived from satellite retrievals and CAM5 model simulation when accounting for sampling and retrieval limitations. Observationalmore » estimates are derived from satellite-retrieved data products at the 20 km footprints of the Cloud and Earth’s Radiant Energy System (CERES) from CERES-CALIPSO-CloudSat-MODIS (C3M) 70, 71. Model estimates are derived from conventional sampling of model fields (CAM5_clim) and incrementally accounting for orbital sampling (CAM5_orb), cloud clearing (CAM5_cld), aerosol detection threshold (CAM5_det), aerosol extinction retrieval (CAM5_aer), and cloud retrieval uncertainties using CALIPSO, CloudSat, and MODIS cloud simulators (CAM5_sim). Vertical and horizontal bars represent the range of SRe and SPOP for a range of LWP from 20 to 200 gm−2. Blue shaded background represents ERFaci estimates as a function of SRe and SPOP derived from a series of CAM5 sensitivity simulations6. See Methods for details« less
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Unveiling aerosol–cloud interactions – Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate
journal, January 2017

  • Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.
  • Atmospheric Chemistry and Physics, Vol. 17, Issue 21
  • DOI: 10.5194/acp-17-13151-2017

Satellite estimates of precipitation susceptibility in low‐level marine stratiform clouds
journal, September 2015

  • Terai, C. R.; Wood, R.; Kubar, T. L.
  • Journal of Geophysical Research: Atmospheres, Vol. 120, Issue 17
  • DOI: 10.1002/2015JD023319

Lidar signal simulation for the evaluation of aerosols in chemistry transport models
journal, January 2012

  • Stromatas, S.; Turquety, S.; Menut, L.
  • Geoscientific Model Development, Vol. 5, Issue 6
  • DOI: 10.5194/gmd-5-1543-2012

Evaluation of tropical cloud and precipitation statistics of Community Atmosphere Model version 3 using CloudSat and CALIPSO data
journal, January 2010

  • Zhang, Y.; Klein, S. A.; Boyle, J.
  • Journal of Geophysical Research, Vol. 115, Issue D12
  • DOI: 10.1029/2009JD012006

MISR Level 3 Component Global Aerosol product covering a month HDF-EOS File - Version 4
dataset, January 2009

Global observations of aerosol impacts on precipitation occurrence in warm maritime clouds
journal, January 2009

  • L'Ecuyer, Tristan S.; Berg, Wesley; Haynes, John
  • Journal of Geophysical Research, Vol. 114, Issue D9
  • DOI: 10.1029/2008JD011273
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    • Atmospheric Chemistry and Physics, Vol. 19, Issue 22
    • DOI: 10.5194/acp-19-13989-2019
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