Model data from a study on the influence of biomass burning aerosol plumes on low-level clouds over the Southeastern Atlantic

Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, Annica M. L. Ekman

This dataset contains the output from the MISU-MIT Cloud and Aerosol (MIMICA) large eddy simulation (LES) Savre et al. (2014). The model simulations were performed to explore and disentangle the individual impacts of aerosols and moisture on the underlying stratocumulus clouds, the marine boundary layer evolution and the stratocumulus to cumulus transition for three different meteorological situations over the Southeast Atlantic during August 2017.

Citation

Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, Annica M. L. Ekman (2023) Model data from a study on the influence of biomass burning aerosol plumes on low-level clouds over the Southeastern Atlantic. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/baro-perez-2023-biomass-burning-1

References

Baró-Pérez A., Diamond, M.S. , Bender, F. A-M., Devasthale, A., Schwarz, M., Savre, J., Tonttila, J., Kokkola, H., Lee, H., Painemal, D., and Ekman, A. M.L. (2023). Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions. Manuscript in preparation.

Savre, J., Ekman, A. M. L., & Svensson, G. (2014). Technical note: Introduction to MIMICA, a large-eddy simulation solver for cloudy planetary boundary layers. Journal of Advances in Modeling Earth Systems, 6(3), 630–649. Portico. https://doi.org/10.1002/2013ms000292

Data description

The dataset contains output from MIMICA (Savre et al., 2014).

The data are provided as NetCDF files. The file names are composed by the following labels (e.g. AUG03_CTRL_prof.nc):

• Simulation day, referring to August 2017
  • AUG03
  • AUG16
  • AUG31
• Experiment name
  • CTRL control simulation
  • AER-rad-off aerosol-radiation interaction turned off
  • DRY water vapor mixing ratio reduced
  • N100 aerosol number concentration reduced to 100 mg⁻¹
• Output type
  • prof profile data with dimensions Z and time, which are average profiles of the same variables in the model domain
  • surf surface data with dimensions X, Y and time

From the described files we used the following variables in the manuscript:

• From the prof files:
  • Water vapor mixing ratio [kg/kg] Qv
  • Aerosol number concentration [1/kg] N_AERO1
  • Resolved turbulent kinetic energy [m²/s²] TKE
  • SGS turbulent kinetic energy [m²/s²] TKE_sgs
  • Long wave radiative heating [K/s] DT_LW
  • Cloud area fraction in atmospheric layer [-] ClF_layer
• From the surf files:
  • Liquid water path [kg/m²] LWP
  • Accumulated surface precipitation [mm] R_cumul

We additionally used the following variables from MIMICA outputs with dimensions X, Y, Z and time:

• Cloud droplet number density [kg⁻¹] Nc
• Cloud droplet mean size [mm] Dc

Due to their large size, these outputs are not included in this dataset. The files will be temporally available at Stockholm University (contact Annica Ekman).