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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 21 Oct 2019

Submitted as: research article | 21 Oct 2019

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A revised version of this preprint is currently under review for the journal ACP.

Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with ICON

Montserrat Costa-Surós1, Odran Sourdeval2,3, Claudia Acquistapace1, Holger Baars4, Cintia Carbajal Henken5, Christa Genz2,4, Jonas Hesemann6, Cristofer Jimenez4, Marcel König4, Jan Kretzschmar2, Nils Madenach5, Catrin I. Meyer7, Roland Schrödner4, Patric Seifert4, Fabian Senf4, Matthias Brueck8, Guido Cioni8, Jan Frederik Engels9, Kerstin Fieg9, Ksenia Gorges9, Rieke Heinze8, Pavan Kumar Siligam9, Ulrike Burkhardt10, Susanne Crewell1, Corinna Hoose6, Axel Seifert11, Ina Tegen4, and Johannes Quaas2 Montserrat Costa-Surós et al.
  • 1Universität zu Köln
  • 2Universität Leipzig
  • 3Université de Lille, CNRS, UMR 8518 – Laboratoire D’Optique Atmospherique
  • 4Leibniz Institute for Tropospheric Research
  • 5Institute for Space Sciences, Freie Universität Berlin
  • 6Karlsruhe Institute of Technology
  • 7Jülich Supercomputing Centre, Forschungszentrum Jülich
  • 8Max Planck Institute for Meteorology
  • 9Deutsches Klimarechenzentrum
  • 10Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre
  • 11Deutscher Wetterdienst

Abstract. Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM, to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain, and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than five-fold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used aiming at a detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which over the selected domain of central Europe a large variety of cloud regimes was present.

It first is demonstrated, using satellite aerosol optical depth retrievals available for both 1985 and 2013, that the aerosol fields for the reference conditions and also for the perturbed ones, as well as the difference between the two, were consistent in the model and the satellite retrievals. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not.

Similarly, detection-and-attribution was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range.

For other cloud quantities, including cloud fraction, liquid water path, cloud-base altitude, and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection-attribution difficult for these quantities. An exception to this is the fact that at large liquid water path, the control simulation matches the observations, while the perturbed one shows too large LWP.

The model simulations allowed to quantify the radiative forcing due to aerosol-cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol-cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region, and aerosol perturbation −2.6 W m-2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m-2.

Montserrat Costa-Surós et al.

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Montserrat Costa-Surós et al.

Montserrat Costa-Surós et al.


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Publications Copernicus
Short summary
The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 in comparison to multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This...