Ines Bulatovic, Julien Savre, Caroline Leck, Michael Tjernström, Annica Ekman
This dataset presents the model output from the large-eddy simulation (LES) model. The LES was employed to simulate a two-layer boundary-layer cloud structure that was commonly present during the Arctic Ocean 2018 expedition, which was carried out during summer 2018 in the central Arctic Ocean.
The simulations are based on a twelve-hour long event from 18 August 12:00 UTC to 19 August 00:00 UTC. The model results are evaluated against observations and further used to explore how the cloud structure can be sustained.
The model output contains microphysical and dynamical properties of the simulated cloud structure for the selected region and period of 15 hours (first 3 hours are considered as a spin-up period).
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Citation
Ines Bulatovic, Julien Savre, Caroline Leck, Michael Tjernström, Annica Ekman (2022) Data from a modelling study of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/bulatovic-2022-cloud-structure-1
References
Bulatovic I, Savre J, Tjernström M, Leck C, Ekman AML (2022) Large-eddy simulation of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition. Manuscript in preparation.
Savre J, Ekman AML, Svensson G (2014) Technical note: Introduction to MIMICA, a large-eddy simulation solver for cloudy planetary boundary layers. J Adv Model Earth Syst 6: 630 – 649. https://doi.org/10.1002/2013MS000292
Linn Karlsson, Paul Zieger (2020) Aerosol particle number size distribution data collected during the Arctic Ocean 2018 expedition. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/oden-ao-2018-aerosol-dmps-1
John Prytherch (2021) Weather data from MISU weather station during the Arctic Ocean 2018 expedition. Dataset version 3. Bolin Centre Database. https://doi.org/10.17043/oden-ao-2018-misu-weather-3
John Prytherch, Michael Tjernström, Jutta Vuellers, Peggy Achtert, Ian Brooks, Grace Porter, Mike Adams (2019) Radiosonde data from the Arctic Ocean 2018 expedition. Dataset version 2. Bolin Centre Database. https://doi.org/10.17043/oden-ao-2018-radiosonde-2
Data description
Dataset represents the output from the LES model MIMICA (Savre et al. 2014) and contains cloud variables that are used in the Bulatovic et al. (2022) study. The variables that are used for plotting in the paper (together with their abbreviations in the files) are listed below:
- Potential temperature (PT)
- Relative humidity (RH)
- Relative humidity, over ice (RHi)
- Turbulent kinetic energy due to buoyancy (Buoy)
- Water vapour mixing fraction (Qv)
- Cloud droplet mixing fraction (Qc)
- Rain drops mixing fraction (Qr)
- Ice mixing fraction (Qi)
- Snow mixing fraction (Qs)
- Graupel mixing fraction (Qg)
- Cloud droplet number density (Nc)
- Rain drops number density (Nr)
- Ice number density (Ni)
- Snow number density (Ns)
- Graupel number density (Ng)
- Liquid water path (LWP)
- Ice water path (IWP)
- Showrtwave radiative flux (FRAD_sw)
- Longwave radiative flux (FRAD_lw)
Note: LWP and IWP variables are integrated from Qc+Qr and Qi+Qs+Qg variables, respectively.
The pressure, temperature and humidity profiles are initialized in the LES based on the radiosonde data from 18 August 12:00 UTC (Prytherch et al. 2019). Measurements from MISU weather station (Prytherch 2021) are used to set up surface variables in the model. For the initial aerosol size distribution, median values representative of the period 12:00 to 24:00 UTC on 18 August are used (Karlsson and Zieger 2020).
The dataset contains 14 files in HDF5 format (file extension nc).
Files are named as simulationname.nc.
File mocchadefault.nc corresponds to output of the control simulation. The rest of the files are model outputs from the sensitivity tests.
Comments
The computations performed using MIMICA and data handling were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC) partially funded by the Swedish Research Council through grant agreement no. 2018-05973.
Please, cite the study by Bulatovic et al. (2022) when using this dataset.