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Dataset
Open Access
Creative Commons Attribution 4.0 International License
PALM-LES dataset for evaluating the impact of radiative transfer solvers on shallow cumulus cloud development
Richard Maier1 , Fabian Jakub1 , and Bernhard Mayer1
1Ludwig-Maximilians-Universität München
First published:
March 11, 2026
DOI: 10.57970/np5r3-t5x93
Keywords:
meteorology
large-eddy simulation
atmosphere
clouds
convection
PALM-LES
shallow cumulus
radiative transfer
cloud-radiation interaction
delta-Eddington
TenStream
dynamic TenStream

Maier, R., Jakub, F., and Mayer, B. (2026): PALM-LES dataset for evaluating the impact of radiative transfer solvers on shallow cumulus cloud development. LMU Munich, Faculty of Physics. (Dataset). DOI: 10.57970/np5r3-t5x93

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/iZQmjWF7qmddk9k/?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/iZQmjWF7qmddk9k/?list' | xargs -I URL -n1 bash -c 'curl --create-dirs -o ${1:31} ${1}' -- URL
Abstract
This dataset contains output from large-eddy simulations of shallow cumulus clouds, each driven by one of three different radiative transfer solvers. The simulations were performed with the PALM model on a grid with 100 m horizontal and 50 m vertical resolution. After an 11-hour spin-up period, they cover almost one full diurnal cycle, including both daytime and nighttime conditions, with output provided at a temporal resolution of 60 s. The three radiative transfer schemes applied are a conventional 1D delta-Eddington approximation, the fully 3D TenStream solver, and the dynamic TenStream solver, which accelerates 3D radiative transfer calculations by using incomplete solves. Because the simulations are identical except for the radiative transfer method applied, the dataset enables an analysis of how cloud development differs depending on whether 1D or 3D radiative transfer is used, and an assessment of how well the dynamic TenStream solver reproduces key 3D radiative effects.
README.md

README


This dataset contains output from large-eddy simulations of shallow cumulus clouds, each driven by one of three different radiative transfer solvers. The simulations were performed with the PALM model on a grid with 100 m horizontal and 50 m vertical resolution. After an 11-hour spin-up period, they cover almost one full diurnal cycle, including both daytime and nighttime conditions, with output provided at a temporal resolution of 60 s. The three radiative transfer schemes applied are a conventional 1D δ-Eddington approximation, the fully 3D TenStream solver, and the dynamic TenStream solver, which accelerates 3D radiative transfer calculations by using incomplete solves. Because the simulations are identical except for the radiative transfer method applied, the dataset enables an analysis of how cloud development differs depending on whether 1D or 3D radiative transfer is used, and an assessment of how well the dynamic TenStream solver reproduces key 3D radiative effects.

General dataset structure


Each simulation is stored in its own folder, with

  • INPUT containing the full set of input files.
  • OUTPUT containing all the model output files.
  • RESTART containing the restart files associated with the simulation.

Initial simulations


The folders initial_main and initial_control contain the data from the two statistically independent but otherwise identical initial simulations. Both were driven by a classical 1D δ-Eddington solver. They were started on 14 June 2023 at 22:00 UTC and ran for 29 hours until 16 June 2023 at 03:00 UTC.

Because both of these simulations were restarted every 30 minutes, each OUTPUT folder contains 58 output files of each file type. In addition, the corresponding RESTART folders contain 58 restart files, allowing users to continue the simulations from any of the available restart timestamps, for example with modified runtime parameters.

Restart simulations


After an 11-hour spin-up period, starting on 15 June 2023 at 09:00 UTC, three different restart simulations were launched from each of the two initial runs. These simulations differ only in the radiative transfer solver applied and are stored in the following folders:

  • delta_eddington_main
  • delta_eddington_control
  • dynamic_tenstream_main
  • dynamic_tenstream_control
  • tenstream_main
  • tenstream_control

The specific restart file used to initialize each of these simulations can be found in the RESTART directory of the corresponding simulation. In contrast to the initial simulations, these restart runs were conducted without intermediate restarts. Hence, the OUTPUT folders contain only one file of each type. The detailed solver configurations for each of these runs can be found in the ..._ts_options files in the INPUT directory of each simulation.

Reproducing the simulations


To rerun a simulation, copy the folder

<Simulation Name>/INPUT

into

<PALMPATH>/build/JOBS

of your PALM installation.

For the six restart runs, also copy

<Simulation Name>/RESTART

into

<PALMPATH>/build/tmp

From the build directory of your PALM installation, the initial runs can then be started, for example, using:

bin/palmrun -k -v -r initial_main -c default -a "d3# restart" -X 64 -T 64 -q cluster -b -m 2000 -t 170000

This launches initial_main as a batch job on 64 cores with 2 GB of memory per core and a wallclock limit of 47.2 hours.

Restart runs require a slightly different argument string and can be started, for example, using:

bin/palmrun -k -v -r tenstream_main -c default -a "d3r restart" -X 64 -T 64 -q cluster -b -m 2000 -t 600000

For further details on palmrun options and input files, please refer to the official PALM documentation.

Output files


Each simulation produces four main types of output files:

  • *_3d — full 3D model fields
  • *_pr — vertical profiles
  • *_ts — domain-averaged time series
  • *_xy — 2D horizontal fields (e.g., surface temperature, liquid water path)

Below, some general remarks on these files as well as lists of notable variables are given.

General remarks

Output quantities are provided either at grid-box centers or at grid-box interfaces. To this end, two different types of spatial coordinates are used:

  • Cell-center coordinates such as x, y, zu, or zu_3d represent cell-centered quantities. Using these coordinates, values are assigned to the centers of the corresponding grid boxes.
  • Cell-interface coordinates such as xu, yv, zw, or zw_3d, on the other hand, represent values located at grid-box boundaries. For example, the zonal wind u is stored on x-interfaces and therefore uses the staggered coordinate xu. Likewise, radiative fluxes such as downwelling longwave radiation rad_lw_in are stored on vertical interfaces and use zw_3d.

In addition, especially the *_pr files often contain multiple variable-specific vertical coordinates (e.g., zq, zql, zhyp, zrho). In this dataset, however, these are typically identical in values to the main vertical coordinates (zu or zw).

Notable variables

With these conventions in mind, the following tables now list some of the variables that can be used to analyze the dataset, together with their dimensions and units. Note that in all file types, the global attribute origin_time can be used to convert time (seconds) into absolute timestamps.

Notable variables in the *_3d files

Variable Dimensions Units Description
time 30 (initial runs) or 1080 (restart runs) seconds time coordinate
zu_3d 82 meters cell-center vertical coordinate for 3D fields
zw_3d 82 meters cell-interface vertical coordinate for 3D fields
x 256 meters cell-center x-coordinate
xu 256 meters cell-interface x-coordinate (used by u)
y 256 meters cell-center y-coordinate
yv 256 meters cell-interface y-coordinate (used by v)
zs_3d 8 meters soil vertical coordinate (for soil fields)
--- --- --- ---
u (time, zu_3d, y, xu) m/s zonal wind component
v (time, zu_3d, yv, x) m/s meridional wind component
w (time, zw_3d, y, x) m/s vertical wind component
q (time, zu_3d, y, x) kg/kg total water mixing ratio
ql (time, zu_3d, y, x) kg/kg liquid water mixing ratio
qc (time, zu_3d, y, x) kg/kg cloud water mixing ratio
qv (time, zu_3d, y, x) kg/kg water vapor mixing ratio
ta (time, zu_3d, y, x) °C air temperature
theta (time, zu_3d, y, x) K potential temperature
m_soil (time, zs_3d, y, x) m3/m3 volumetric soil moisture
t_soil (time, zs_3d, y, x) K soil temperature
rad_sw_in (time, zw_3d, y, x) W/m2 incoming shortwave radiative flux
rad_sw_out (time, zw_3d, y, x) W/m2 outgoing shortwave radiative flux
rad_lw_in (time, zw_3d, y, x) W/m2 incoming longwave radiative flux
rad_lw_out (time, zw_3d, y, x) W/m2 outgoing longwave radiative flux
rad_sw_hr (time, zu_3d, y, x) K/h shortwave heating rate
rad_lw_hr (time, zu_3d, y, x) K/h longwave heating rate


Notable variables in the *_pr files

Variable Dimensions Units Description
time 30 (initial runs) or 1080 (restart runs) seconds time coordinate
zu 82 meters layer-centered vertical coordinate for u
zv 82 meters layer-centered vertical coordinate for v
zw 82 meters level (interface) vertical coordinate for w
zq 82 meters layer-centered vertical coordinate for q
zql 82 meters layer-centered vertical coordinate for ql
zqc 82 meters layer-centered vertical coordinate for qc
zqv 82 meters layer-centered vertical coordinate for qv
zrh 82 meters layer-centered vertical coordinate for rh
zrho 82 meters layer-centered vertical coordinate for rho
zhyp 82 meters layer-centered vertical coordinate for hyp
--- --- --- ---
u (time, zu) m/s zonal wind component
v (time, zv) m/s meridional wind component
w (time, zw) m/s vertical wind component
q (time, zq) kg/kg total water mixing ratio
ql (time, zql) kg/kg liquid water mixing ratio
qc (time, zqc) kg/kg cloud water mixing ratio
qv (time, zqv) kg/kg water vapor mixing ratio
rh (time, zrh) % relative humidity
rho (time, zrho) kg/m3 air density
hyp (time, zhyp) hPa hydrostatic pressure


Notable variables in the *_xy files

Variable Dimensions Units Description
time 30 (initial runs) or 1080 (restart runs) seconds time coordinate
x 256 meters cell-center x-coordinate
y 256 meters cell-center y-coordinate
zu1_xy 1 meters single-layer “surface plane” vertical coordinate
--- --- --- ---
lwp*_xy (time, zu1_xy, y, x) kg/m2 liquid water path
shf*_xy (time, zu1_xy, y, x) W/m2 surface sensible heat flux
qsws*_xy (time, zu1_xy, y, x) W/m2 surface latent heat flux
ta_2m*_xy (time, zu1_xy, y, x) °C 2-m air temperature


A complete description of all of the output parameters in the files is provided in the official PALM documentation: https://palm.muk.uni-hannover.de/trac/wiki/doc/app/runtime_parameters#data_output

Quick look at the data


For a quick visual inspection of the output files, you may use ncview, a visual browser for netCDF files. For example, you can execute

ncview tenstream_main/OUTPUT/tenstream_main_3d.022.nc

This provides an easy way to browse through the 3D fields and check the content of the dataset without having to load it into a post-processing environment.

Example plot


To give a first glimpse at the data, the following plot shows the temporal evolution of the liquid water path (LWP) in the delta_eddington_main (left), dynamic_tenstream_main (middle), and tenstream_main (right) simulations for five selected time steps between 09:01 and 21:00 UTC. Note that, to enhance the contrast of the plots, the maximum LWP value for the colorbar was set to 50 g m⁻² instead of the global maximum value of 363 g m⁻².

Temporal evolution of the liquid water path in the PALM simulations driven by the 1D δ-Eddington approximation (left), the dynamic TenStream solver (middle), and the original TenStream model (right), shown for five time steps between 09:01 and 21:00 UTC.

Files