EGU21-13307, updated on 10 Jan 2023
EGU General Assembly 2021
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Exploring microphysical properties of marine boundary layer clouds through network analysis

Lucile Ricard1, Athanasios Nenes1,2, Jakob Runge3, and Paraskevi Georgakaki1
Lucile Ricard et al.
  • 1Laboratory of Atmospheric Processes and their Impacts (LAPI), School of Architecture, Civil & Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland (,
  • 2Institute of Chemical Engineering Sciences, Foundation for Research & Technology-Hellas, Patras 26504, Greece (
  • 3German Aerospace Center, Institute of Data Science, Jena 07745, Germany (

Aerosol-cloud interactions remain the largest uncertainty in assessments of anthropogenic climate forcing, while the complexity of these interactions require methods that enable abstractions and simplifications that allow their improved treatment in climate models. Marine boundary layer clouds are an important component of the climate system as their large albedo and spatial coverage strongly affect the planetary radiative balance. High resolution simulations of clouds provide an unprecedented understanding of the structure and behavior of these clouds in the marine atmosphere, but the amount of data is often too large and complex to be useful in climate simulations. Data reduction and inference methods provide a way that to reduce the complexity and dimensionality of datasets generated from high-resolution Large Eddy Simulations.

In this study we use network analysis, (the δ-Maps method) to study the complex interaction between liquid water, droplet number and vertical velocity in Large Eddy Simulations of Marine Boundary Layer clouds. δ-Maps identifies domains that are spatially contiguous and possibly overlapping and characterizes their connections and temporal interactions. The objective is to better understand microphysical properties of marine boundary layer clouds, and how they are impacted by the variability in aerosols. Here we will capture the dynamical structure of the cloud fields predicted by the MIMICA Large Eddy Simulation (LES) model. The networks inferred from the different simulation fields are compared between them (intra-comparisons) using perturbations in initial conditions and aerosol, using a set of four metrics. The networks are then evaluated for their differences, quantifying how much variability is inherent in the LES simulations versus the robust changes induced by the aerosol fields. 

How to cite: Ricard, L., Nenes, A., Runge, J., and Georgakaki, P.: Exploring microphysical properties of marine boundary layer clouds through network analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13307,, 2021.


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