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start [2021/09/24 12:42] – [Selected Research Highlights] neggersstart [2024/01/23 14:13] (current) – [High Performance Computing (HPC)] kiszler
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 ==== High-resolution simulation ==== ==== 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 renderingwith the liquid condensate (lwcshaded 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 usedallowing comparison to Total Sky Imager (TSIdata.}}
  
-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]]. More details of our LES codes can be found in the [[models|overview of models]].
 +
  
 ==== Testbeds ==== ==== Testbeds ====
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 **[[arcticclouds|Arctic clouds]]** **[[arcticclouds|Arctic clouds]]**
-Clouds in the Arctic appear in many forms. Much is still not understood about their behavior, which is for a large part due to the difficulty in sampling such clouds at high latitudes. At InScAPE we use dedicated large-eddy simulation based on available measurements to study such clouds in a virtual laboratory setting. Among others, we use data from recent field campaigns, including the year-long MOSAiC drift in 2019-2020.+Clouds in the Arctic appear in many forms. Much is still not understood about their behavior, which is for a large part due to the difficulty in sampling such clouds at high latitudes. At InScAPE we use dedicated large-eddy simulation based on available measurements to study such clouds in a virtual laboratory setting. Among others, we use data from recent field campaigns, including two recent cruises by the Polarstern Research Vessel (RV). The first is the PASCAL campaign north of Svalbard in 2017, and the other is the year-long MOSAiC drift in 2019-2020. Aircraft campaigns include ACLOUD in 2017 and the upcoming HALO-AC3 campaign in March/April 2022.
  
 **[[sizedistribution|Cloud geometry]]** **[[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]]** **[[edmf|EDMF]]**
-We are continuously working on the improvement and development on the EDMF (Eddy Diffusivity Mass Flux) parameterization towards bin macrophysics scheme that is at the moment implemented and tested in an LES framework.+We are continuously working on the further development of the EDMF (Eddy Diffusivity Mass Flux) framework for describing transport and clouds in turbulent/convective flows. One ongoing activitiy is the implementation of EDMF as subgrid scheme in LES, using the code as a simple non-hydrostatic circulation model and allowing tests in the convective grey zone (see below). Another is to couple EDMF to a thermal population model, in an attempt to make EDMF aware of convective organization and memory.
  
-**[[greyzone|The convective Grey Zone]]** +**[[greyzone|Convective Grey Zone]]** 
-A big challenge for parameterization development are the increasing resolutions of NWP models, which start to resolve important processes for cloud formation and organization - the so called "Greyzone"Parameterizations have to take the resolution into account and find a consistent way to reduce their own activity+The ever increasing resolution of NWP models is fast becoming a big challenge for existing parameterization schemes in ESMs. The problem is that previously fully parameterized subgrid-scale processes such as convective clouds are now becoming partially resolved. This situation is also known as the "convective grey zone"The way forward is being hotly debated in the community. One option is to skip the grey zone entirely and switch to global LES for weather and climate prediction. Another option is to design smart parameterizations that properly take discretization effects into account. At InScAPE we pursue new ways to make convective parameterizations adaptable to scale. In doing so, we obtain new insights into the spatial structure of convective cloud fields.
  
  
 ==== High Performance Computing (HPC) ==== ==== 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 JURECA and newly 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]]).
start.1632480148.txt.gz · Last modified: 2021/09/24 12:42 by neggers