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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 3 | Copyright
Atmos. Chem. Phys., 18, 2035-2047, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 13 Feb 2018

Research article | 13 Feb 2018

Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data

Daniel T. McCoy1, Frida A.-M. Bender2, Daniel P. Grosvenor1,5, Johannes K. Mohrmann3, Dennis L. Hartmann3, Robert Wood3, and Paul R. Field1,4 Daniel T. McCoy et al.
  • 1School of Earth and Environment, Institute of Climate and Atmospheric Science, University of Leeds, Leeds, LS2 9JT, UK
  • 2Department of Meteorology and Bolin Centre for Climate Research, Stockholm University, Stockholm, 106 91, Sweden
  • 3Department of Atmospheric Sciences, University of Washington, Seattle, 98195, USA
  • 4MetOffice, Exeter, EX1 3PB, UK
  • 5National Centre for Atmospheric Science (NCAS), University of Leeds, Leeds, LS2 9JT, UK

Abstract. Cloud droplet number concentration (CDNC) is the key state variable that moderates the relationship between aerosol and the radiative forcing arising from aerosol–cloud interactions. Uncertainty related to the effect of anthropogenic aerosol on cloud properties represents the largest uncertainty in total anthropogenic radiative forcing. Here we show that regionally averaged time series of the Moderate-Resolution Imaging Spectroradiometer (MODIS) observed CDNC of low, liquid-topped clouds is well predicted by the MERRA2 reanalysis near-surface sulfate mass concentration over decadal timescales. A multiple linear regression between MERRA2 reanalyses masses of sulfate (SO4), black carbon (BC), organic carbon (OC), sea salt (SS), and dust (DU) shows that CDNC across many different regimes can be reproduced by a simple power-law fit to near-surface SO4, with smaller contributions from BC, OC, SS, and DU. This confirms previous work using a less sophisticated retrieval of CDNC on monthly timescales. The analysis is supported by an examination of remotely sensed sulfur dioxide (SO2) over maritime volcanoes and the east coasts of North America and Asia, revealing that maritime CDNC responds to changes in SO2 as observed by the ozone monitoring instrument (OMI). This investigation of aerosol reanalysis and top-down remote-sensing observations reveals that emission controls in Asia and North America have decreased CDNC in their maritime outflow on a decadal timescale.

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The interaction between clouds and aerosols represents the largest source of uncertainty in the anthropogenic radiative forcing. Cloud droplet number concentration (CDNC) is the state variable that moderates the interaction between aerosol and clouds. Here we show that CDNC decreases off the coasts of East Asia and North America due to controls on emissions. We support this analysis through an examination of volcanism in Hawaii and Vanuatu.
The interaction between clouds and aerosols represents the largest source of uncertainty in the...