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Dataset
Open Access
Creative Commons Attribution 4.0 International License
UCLA-LES shallow cumulus dataset with 3D cloud output data
Fabian Jakub1 and Philipp Gregor1
1Ludwig-Maximilians-Universität München
First published:
Nov. 17, 2022
DOI: 10.57970/5d0k9-q2n86
Keywords:
Meteorology
Large-Eddy-Simulation
Atmosphere
Clouds
UCLA-LES
high-res
shallow-cumulus
convection

Jakub, F. and Gregor, P. (2022): UCLA-LES shallow cumulus dataset with 3D cloud output data. LMU Munich, Faculty of Physics. (Dataset). DOI: 10.57970/5d0k9-q2n86

wget and curl are the two standard tools that are available on most Linux and macOS computers. wget contains a feature for downloading a list of files:
wget -x -nH -i 'https://opendata.physik.lmu.de/5d0k9-q2n86/?list'
curl is missing a feature like that, but the same functionality can be created by combining curl and xargs:
curl 'https://opendata.physik.lmu.de/5d0k9-q2n86/?list' | xargs -I URL -n1 bash -c 'curl --create-dirs -o ${1:31} ${1}' -- URL
Abstract
The dataset features 6 hours of single layer shallow cumulus clouds with an ever increasing cloud deck. I.e. domain average cloud fraction ranges from 0% in the beginning to 100% towards the end of the simulation. A key feature of the dataset is its very high temporal resolution of 3D output fields (every 10 seconds). The vision is that the high temporal frequency and spatial resolution of cloud and wind variables will allow for a wide range of offline benchmarks. Applications that come to our mind are offline benchmark for 1D and 3D radiative heating rate computations, 3D radiative transfer effects on retrievals as well as cloud motion tracking algorithms.
README.md

UCLA-LES shallow cumulus dataset with 3D cloud output data

Authors: Fabian Jakub and Philipp Gregor (LMU - MIM)

Contact: Fabian.Jakub@physik.uni-muenchen.de, Philipp.Gregor@physik.uni-muenchen.de

The dataset features 6 hours of single layer shallow cumulus clouds with an ever increasing cloud deck. I.e. domain average cloud fraction ranges from 0% in the beginning to 100% towards the end of the simulation. A key feature of the dataset is its very high temporal resolution of 3D output fields (every 10 seconds). The vision is that the high temporal frequency and spatial resolution of cloud and wind variables will allow for a wide range of offline benchmarks. Applications that come to our mind are offline benchmark for 1D and 3D radiative heating rate computations, 3D radiative transfer effects on retrievals as well as cloud motion tracking algorithms.


The dataset is comprised of the following files:

  • shallow_convection_25m_10s_ts.nc - Timeseries
  • shallow_convection_25m_10s_ps.nc - Vertical profiles
  • shallow_convection_25m_10s_3d.nc - 3D fields
  • gl_images/ - virtual camera to get a feel for the cloud structure
  • inputs/ - UCLA-LES input files
  • plots/ - timeseries plots for quick views

Look at cloud fraction e.g. with:

ncdump shallow_convection_25m_10s_ts.nc -f c -v cfrac

Cloud Fraction over time Cloud extent over time


Notable Variables in the 3D file:

varname dim description units
time 2161 time steps dt 10 sec.
z 120 vertical layers (stretched) 25m at the surface
x 256 horizontal grid dx 25m
y 256 horizontal grid dy 25m
l time, y, x, z Liquid water mixing ratio kg/kg
p time, y, x, z Pressure Pa
q time, y, x, z Total water mixing ratio kg/kg
r time, y, x, z Rain-water mixing ratio kg/kg
n time, y, x, z Rain-drop number mixing ratio #/kg
t time, y, x, z Liquid Water Potential temperature K
u time, y, x, z Horiz. wind velocity m/s
v time, y, x, z Horiz. wind velocity m/s
w time, y, x, z Vertical wind velocity m/s

The folder gl_images contains images generated every 60s with an artificial All-Sky Imager (ASI) at ground position at the origin. Images are generated using an OpenGL implementation of ray marching through a field of precomputed twostream irradiances. Only cloud liquid water is considered for rendering, rain is neglected. A standard US atmosphere profile was assumed. For more details about ASI geometry and the rendering contact philipp.gregor@lmu.de

Download_movie

Cloud field at 2.5 hrs
Cloud field at 2.5 hrs
Cloud field at 4 hrs
Cloud field at 4 hrs

Files