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Volume 17, issue 21 | Copyright
Atmos. Chem. Phys., 17, 13165-13185, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 07 Nov 2017

Research article | 07 Nov 2017

Unveiling aerosol–cloud interactions – Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

David Neubauer1, Matthew W. Christensen2,3, Caroline A. Poulsen2, and Ulrike Lohmann1 David Neubauer et al.
  • 1Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland
  • 2RAL Space, STFC Rutherford Appleton Lab, Harwell, OX11 0QX, UK
  • 3Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, OX1 3PU, UK

Abstract. Aerosol–cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud–Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS–CERES (Moderate Resolution Imaging Spectroradiometer – Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes.

The aerosol–liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR–CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR–CAPA or MODIS–CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities.

We further find that the statistical relationships inferred from different satellite sensors (AATSR–CAPA vs. MODIS–CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS–CERES but positive for AATSR–CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well constrained by satellite observations.

In addition to aerosol swelling, wet scavenging and aerosol processing have an impact on liquid water path, cloud albedo and cloud droplet number susceptibilities. Aerosol processing leads to negative liquid water path susceptibilities to changes in aerosol index (AI) in ECHAM6-HAM2, likely due to aerosol-size changes by aerosol processing.

Our results indicate that for statistical analysis of aerosol–cloud interactions the unwanted effects of aerosol swelling, wet scavenging and aerosol processing need to be minimised when computing susceptibilities of cloud variables to changes in aerosol.

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Short summary
When aerosol particles take up water their number may seem to be increased optically. However if aerosol particles are removed by precipitation (formation) their numbers will decrease. We applied methods to account for such effects in model and satellite data to analyse the change in cloud properties by changes in aerosol particle number. The agreement of model and satellite data improves when these effects are accounted for.
When aerosol particles take up water their number may seem to be increased optically. However if...