Large-eddy simulation of droplet and aerosol microphysics role in radiation fog from FAIRARI campaign, Po Valley, February 2022

Hao Ding, Almuth Neuberger, Rahul Ranjan, Fredrik Mattsson, Liine Heikkinen, Karam Mansour, Stefano Decesari, Claudia Mohr, Alejandro Baró Pérez, Nazario Mastroianni, Paul Zieger, Ilona Riipinen, Annica M. L. Ekman

This dataset contains horizontally averaged two-dimensional outputs from large-eddy simulations (LES) performed with the MISU-MIT Cloud and Aerosol (MIMICA) model for radiation fog (Events 7–9, 18–19 February 2022) during the FAIRARI campaign in the Po Valley, Italy.

The simulations investigate how fog microphysical properties, near-surface visibility, and fog lifecycle respond to variations in aerosol number concentration, size distribution, and chemical composition, as well as to prescribed droplet size distributions.

In addition, the dataset also includes sensitivity tests addressing on surface forcing and key in-fog microphysical processes, including aerosol hygroscopic growth, droplet collision–coalescence, and sedimentation.

AtmosphereAerosolsFogFAIRARILESMicrophysicsMIMICA

Name

Version

Citation

References

Ding H, Neuberger A, Ranjan R, Mattsson F, Heikkinen L, Mansour K, Decesari S, Mohr C, Pérez AB, Mastroianni N, Zieger P, Riipinen I, Ekman AML (2026) The Importance of Aerosol and Droplet Microphysics for the Properties and Life Cycle of Radiation Fog in the Po Valley. https://doi.org/10.5194/egusphere-2025-6435

Neuberger A, Mattsson F, Zieger P (2024) Aerosol particle number size distribution measured during the FAIRARI campaign, Po valley, Italy, February – April 2022. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/fairari-2021-2022-aerosol-dmps1-1

Data description

The dataset is provided in NetCDF format (63 files, 63.85 GB).

All variables and their corresponding metadata are documented within the NetCDF files, including meteorological fields, radiation, turbulence characteristics, as well as aerosol and droplet microphysical properties.

The data are organised into five directories:

fairari-2021-2022-LES2-REF-TEST

This directory contains the reference simulations for fog events 7-9, along with sensitivity experiments on key microphysical processes and advection.

Files

• REF.nc Reference Simulation
• ADV_OFF.nc Same as REF but with advection disabled
• HYG_OFF.nc Same as REF but with aerosol hygroscopic growth disabled
• COL_ON.nc Same as REF but with droplet collision-coalescence enabled
• SED_OFF.nc Same as REF but with droplet sedimentation disabled

fairari-2021-2022-LES2-SFC-TEST

This directory includes sensitivity experiments related to surface forcing.

Example Files

• SSM_[*].nc Nighttime surface skin moisture set to [*] times that in REF
• SST_m[*]k.nc Surface skin temperature decreased by [*]K relative to REF

fairari-2021-2022-LES2-AERO_PHYS

This directory includes sensitivity experiments on aerosol physics.

Example Files

• AERO_NA[*].nc Initial aerosol number concentration set to [*]cm⁻³
• AERO_RGm[*]p.nc Geometric mean radius of aerosols decreased by [*]% relative to REF
• AERO_RGp[*]p.nc Geometric mean radius of aerosols increased by [*]% relative to REF
• AERO_SIGm[*]p.nc Geometric standard deviation decreased by [*]% relative to REF
• AERO_SIGp[*]p.nc Geometric standard deviation increased by [*]% relative to REF

fairari-2021-2022-LES2-AERO_CHEM

This directory contains sensitivity experiments on aerosol chemistry.

Example Files

• AERO_NA[*]KCbase.nc Baseline aerosol hygroscopicity scenario under clean conditions with aerosol concentration of [*] cm⁻³
• AERO_NA[*]KCm10p.nc Hygroscopicity decreased by 10% relative to baseline under clean conditions with aerosol concentration of [*] cm⁻³
• AERO_NA[*]KCp10p.nc Hygroscopicity increased by 10% relative to baseline under clean conditions with aerosol concentration of [*] cm⁻³
• AERO_NA[*]KPbase.nc Baseline aerosol hygroscopicity scenario under polluted conditions with aerosol concentration of [*] cm⁻³
• AERO_NA[*]KPm10p.nc Hygroscopicity decreased by 10% relative to baseline under polluted conditions with aerosol concentration of [*] cm⁻³
• AERO_NA[*]KPp10p.nc Hygroscopicity increased by 10% relative to baseline under polluted conditions with aerosol concentration of [*] cm⁻³

fairari-2021-2022-LES2-DROP-MICR

This directory includes sensitivity experiments on prescribed droplet size distribution.

Example Files

• DROP_A[*]N[*].nc Settings for the shape parameter α[*] and ν[*] in the Gamma distribution describing droplet size spectrum

Comments

This dataset contains the results of the large-eddy simulations presented in Ding et al. (2026), where the initial model setup and the simulation results are discussed in detail.

Observational aerosol data used for model initialisation can be accessed from Neuberger et al. (2024).

Project

This project was supported from the European Union’s Horizon 2020 research and innovation programme (Project FORCeS under Grant Agreement 821205), European Research Council (Consolidator Grant INTEGRATE 865799), Horizon Europe programme (Project CERTAINTY under Grant Agreement 101137680), the Knut and Alice Wallenberg Foundation (Grant. 2015.0162, 2021.0169, 2021.0298 and 2022.0104), Goran Gustafssons stiftelse and the Swedish Research Council (No. 2020–04158). The computations and data handling in MIMICA were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS), partially funded by the Swedish Research Council (No. 2022-06725).

Publisher

Bolin Centre Database

License

Open Data Commons Attribution License (ODC-By) v1.0

First name

Hao

Last name or organisation

Ding

Email address

hao.ding@misu.su.se

Address

Department of Meteorology; Stockholm University

Postal code

SE-106 91

City

Stockholm

Country

Sweden

GCMD science keyword

Earth science services > Models > Weather research/forecast models

GCMD location

Continent > Europe > Southern Europe > Italy

Dataset language

English

DOI

Time