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--- start [2021/09/24 12:57] – [High Performance Computing (HPC)] neggers
+++ start [2024/01/23 14:13] (current) – [High Performance Computing (HPC)] kiszler
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 ==== High-resolution simulation ====
-{{:snapshot_lwc-iwc_pascal-exp003-highfreq_v2.mp4?&600|Paraview visualization of mixed-phase cloud evolution in a DALES simulation of Arctic conditions observed during the PASCAL field campaign north of Svalbard in June 2017. The cloud condensate is visualized using volume rendering, with the liquid condensate (lwc) shaded grey and the ice condensate (iwc) shaded in color. The white box represents the simulation domain, with sizes 2.56 x 2.56 x 1.28 km at a resolution of 20 x 20 x 10m.}}
+{{:movie_joyce_tsi_dales_20140724-hr014_rs256_20s.mp4?&500|Time lapse movie of simulated cumulus clouds on 24 July 2014 at the JOYCE site. The ray tracing renderings are generated using the open source Blender tool. A hemispheric projection is used, allowing comparison to Total Sky Imager (TSI) data.}}
-To achieve its science goals the InScAPE group makes use of a hierarchy of atmospheric models. These can be run on platforms ranging from simple workstations to supercomputers. One of the main "working horse" models is the Large-Eddy Simulation (LES) model, which simulates the atmospheric flow in a limited domain (~10km) at high resolutions (~25m). These resolutions are fine enough to resolve atmospheric phenomena such as turbulence and convection, including the associated clouds like cumulus and stratocumulus. Processes at smaller scales are still parameterized, including small-scale turbulence and cloud microphysics. LES has emerged as an important research tool in the last decades, as it can provide virtual information on four dimensional fields (in time and space) of many relevant atmospheric variables. In practice these are still hard to measure by instrumentation, so that the LES can act as a "virtual laboratory" for investigating a phenomenon of interest. Such information is essential for the effective evaluation and improvement of parameterizations for large-scale models.
+To achieve its science goals the InScAPE group makes use of a hierarchy of atmospheric models. These can be run on platforms ranging from simple workstations to supercomputers. One of the main "working horse" models is the Large-Eddy Simulation (LES) model, which simulates the atmospheric flow in a limited domain (~10km) at high resolutions (~25m). These resolutions are high enough to resolve atmospheric phenomena such as turbulence and convection, including the associated clouds like cumulus and stratocumulus. Processes at smaller scales are still parameterized, including small-scale turbulence and cloud microphysics. LES has emerged as an important research tool in the last decades, as it can provide virtual information on four dimensional fields (in time and space) of many relevant atmospheric variables. In practice these are still hard to measure by instrumentation, so that the LES can act as a "virtual laboratory" for investigating a phenomenon of interest. Such information is essential for the effective evaluation and improvement of parameterizations for large-scale models.
-In the InScAPE working group various LES codes are operational. Our LES codes include the Dutch Atmospheric Large-Eddy Simulation (DALES) model and LES version of the Icosahedral Non-hydrostatic model (ICON) as developed by DWD and MPI-M. Both codes have been thoroughly tested for a range of prototype situations, and have participated in various model intercomparison studies.
+At InScAPE various LES codes are used, including the Dutch Atmospheric Large-Eddy Simulation model ([[https://github.com/dalesteam/dales|DALES]]) and LES version of the Icosahedral Non-hydrostatic model ([[https://code.mpimet.mpg.de/projects/iconpublic|ICON]]) as developed by DWD and MPI-M. Both codes have been thoroughly tested for a range of prototype situations, and have participated in various model intercomparison studies. A key ingredient of working with LES to study convective clouds is its evaluation against observational data. Despite its awesome possibilities, LES is still a model and needs to be validated. We explore new ways to achieve this, for example by applying ray tracing techniques in the volume rendering of simulated cloud populations (see the movie above).
 More details of our LES codes can be found in the [[models|overview of models]].
 ==== Testbeds ====
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 **[[sizedistribution|Cloud geometry]]**
-Gaining insight into the morphology of cumulus cloud populations is essential for understanding cloud climate feedbacks and for improving their representation in ESMs. This concerns an incredibly broad range of scales, from single-cloud geometry via mesoscale cloud patterns to large-scale synoptic cloud structures. At InScAPE we explore new pathways to investigate and detect cloud field morphology and to capture this in conceptual models.
+Gaining insight into the morphology of cumulus cloud populations is essential for understanding cloud climate feedbacks and for improving their representation in ESMs. This concerns an incredibly broad range of scales, from single-cloud geometry via mesoscale cloud patterns to large-scale synoptic cloud structures. At InScAPE we explore new pathways to investigate and detect cloud field morphology and to capture this in conceptual models. An exciting new effort is to use the Blender ray tracing tool for scientific renderings of simulated clouds fields.
 **[[edmf|EDMF]]**
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 ==== High Performance Computing (HPC) ====
-To perform the various model simulations we make use of HPC facilities. Thesse include the CHEOPS cluster at the Regional Computing Center of the university of Cologne ([[http://rrzk.uni-koeln.de/rrzk.html?&L=1|RRZK]]), the JUWELS cluster at the Jülich Supercomputing Centre ([[http://www.fz-juelich.de/ias/jsc/EN/Home/home_node.html|JSC]]), and the MISTRAL cluster at the Deutsches Klima Rechenzentrum ([[https://www.dkrz.de/Nutzerportal-en/doku/mistral|DKRZ]]).
+To perform the various model simulations we make use of HPC facilities. Thesse include the CHEOPS cluster at the Regional Computing Center of the university of Cologne ([[http://rrzk.uni-koeln.de/rrzk.html?&L=1|RRZK]]), the JUWELS cluster at the Jülich Supercomputing Centre ([[http://www.fz-juelich.de/ias/jsc/EN/Home/home_node.html|JSC]]), and the LEVANTE cluster at the Deutsches Klima Rechenzentrum ([[https://www.dkrz.de/Nutzerportal-en/doku/mistral|DKRZ]]).