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PYTHON ENVIRONMENTS
Python is increasingly popular in a scientific environment thanks to its wide selection of well maintained modules or packages. On mistral we provide several options ranging from quick usage with a set of predefined modules up to highly customized environments for very specific requirements. MISTRAL — USER PORTAL Mistral, the High Performance Computing system for Earth system research (HLRE-3), is DKRZ's first petascale supercomputer.The HPC system has a peak performance of 3.14 PetaFLOPS and consists of approx. 3,300 compute nodes, 100,000 compute cores, 266 WORLD DATA CENTER FOR CLIMATE The World Data System (WDS, see below) is an international effort to set up domain specific data archives as services for the scientific community. The WDC for Climate collects, stores, and disseminates Earth System data with a focus on climate simulation data and climate related data products. WDCC's mission is closely related to that ofDKRZ
CDO EXAMPLES
E.g. extract the variable tas in a time range and compute the field mean (result is a time series): cdo -fldmean -seltimestep,1/12 -selvar,precip infile outfile. Notice: the data will be processed using the operators given from the right to the left! In this example: extract variable tsurf. select timesteps 1 to 12. VISUALIZATION SERVER The results of the modeling calculated on the supercomputer can be directly analyzed on the data visualization nodes. By using a remote 3D rendering technique (VirtualGL / TurboVNC) the system can conveniently be used over the internet. Documentation for using Mistral's vis nodes in the User Portal. Visualization services atDKRZ.
DKRZ CMIP DATA POOL (DKRZ CDP) PARTITIONS AND LIMITS Partitions and Limits. In SLURM multiple nodes can be grouped into partitions which are sets of nodes with associated limits for wall-clock time, job size, etc. These limits are hard limits for the jobs and can not be overruled. The defined partitions can overlap, i.e. one node might be THE MONASH UNIVERSITY SIMPLE CLIMATE MODEL The Monash University Simple Climate Model CMIP6 CITATION 'CMCC CMCC-CM2-VHR4 MODEL OUTPUT PREPARED The model used in climate research named CMCC-CM2-VHR4, released in 2017, includes the components: aerosol: prescribed MACv2-SP, atmos: CAM4 (1/4deg; 1152 x 768 longitude/latitude; 26 levels; top at ~2 hPa), land: CLM4.5 (SP mode), ocean: NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude; 50 DKRZ - PARTNER DER KLIMAFORSCHUNG DKRZ itself does not conduct climate research but is a partner in various scientific projects with the aim of further improving support for climate science. Communication: Climate change and model-based climate projections are time and time again at the center of public attention. On this page, you will find a variety of media andinformation
PYTHON ENVIRONMENTS
Python is increasingly popular in a scientific environment thanks to its wide selection of well maintained modules or packages. On mistral we provide several options ranging from quick usage with a set of predefined modules up to highly customized environments for very specific requirements. MISTRAL — USER PORTAL Mistral, the High Performance Computing system for Earth system research (HLRE-3), is DKRZ's first petascale supercomputer.The HPC system has a peak performance of 3.14 PetaFLOPS and consists of approx. 3,300 compute nodes, 100,000 compute cores, 266 WORLD DATA CENTER FOR CLIMATE The World Data System (WDS, see below) is an international effort to set up domain specific data archives as services for the scientific community. The WDC for Climate collects, stores, and disseminates Earth System data with a focus on climate simulation data and climate related data products. WDCC's mission is closely related to that ofDKRZ
CDO EXAMPLES
E.g. extract the variable tas in a time range and compute the field mean (result is a time series): cdo -fldmean -seltimestep,1/12 -selvar,precip infile outfile. Notice: the data will be processed using the operators given from the right to the left! In this example: extract variable tsurf. select timesteps 1 to 12. VISUALIZATION SERVER The results of the modeling calculated on the supercomputer can be directly analyzed on the data visualization nodes. By using a remote 3D rendering technique (VirtualGL / TurboVNC) the system can conveniently be used over the internet. Documentation for using Mistral's vis nodes in the User Portal. Visualization services atDKRZ.
DKRZ CMIP DATA POOL (DKRZ CDP) PARTITIONS AND LIMITS Partitions and Limits. In SLURM multiple nodes can be grouped into partitions which are sets of nodes with associated limits for wall-clock time, job size, etc. These limits are hard limits for the jobs and can not be overruled. The defined partitions can overlap, i.e. one node might be THE MONASH UNIVERSITY SIMPLE CLIMATE MODEL The Monash University Simple Climate Model CMIP6 CITATION 'CMCC CMCC-CM2-VHR4 MODEL OUTPUT PREPARED The model used in climate research named CMCC-CM2-VHR4, released in 2017, includes the components: aerosol: prescribed MACv2-SP, atmos: CAM4 (1/4deg; 1152 x 768 longitude/latitude; 26 levels; top at ~2 hPa), land: CLM4.5 (SP mode), ocean: NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude; 50 THE MODEL — ENGLISH The Earth system model MPI-ESM is based on the following model components: ECHAM6 (atmosphere), MPIOM (ocean physics), JSBACH (terrestrial biosphere) and HAMOCC (ocean’s biogeochemistry).HLRE-3 MISTRAL
The first phase of Mistral, the high performance computing system for Earth system research (HLRE-3), consists of computer components by Atos/Bull, a disk storage system by Xyratex/Seagate and high performance network switches by Mellanox. These components are distributed over 79 racks weighing up to or even more than a ton, which are connected by bundles of fiber fabric.HAPPI — ENGLISH
The international HAPPI (Half a degree Additional Heating, Prognosis and Projected Impacts) initiative is the response of climate scientists to the announcement of the 1.5°C special report (SR1.5) of the IPCC (Intergovernmental Panel on Climate Change).OCEAN — ENGLISH
High Resolution ICON Ocean Simulation. The ICON model consists of an atmospheric and an ocean component. These are the first results of a high resolution experiment using the ICON ocean component, with a horizontal resolution of 20km and a time interval of 15 minutes.GITLAB.DKRZ.DE
Prerequisites. GitLab access is available for all DKRZ users. In order to use the GitLab resource, project administrators need to activate the "Gitlab" permission per user on luv.dkrz.de before a user can login to gitlab.dkrz.de with his/her LDAP password.. Once activated, each user is allowed to create up to 5 git projects/repositories -please contact
INTERACTIVE PROGRAMMING COURSE FOR DKRZ The research group "Scientific computing" at DKRZ has been supporting the university lectures about efficient programming for several years. Within the scope of Hamburg Open Online University the project “Interactive C-programming course” was initiated. HPSS — USER PORTAL Kerberos is the preferred way to use pftp in a job script.. Simplified packing and file transfer via packems. The process of packing & archiving of multiple data files to HPSS and their retrieval is simplified by the packages "packems". DKRZ NCL EXAMPLE USE MARKERS TO PLOT DATA ON GRID DKRZ NCL example use markers to plot data on grid. This example shows how to create a raster filled contour plot which is used to create a second plot using markers instead of raster filled contour. The colors are retrieved from the raster filled contour plot and the size is given by another variable, here quality factor, for each grid cell. PYTHON MATPLOTLIB EXAMPLE XY-PLOT The scripts creates an xy-plot using different colors and dash pattern. Software requirements: Python 3. Numpy. matplotlib. Run the xy-plot example script: python matplotlib_xy_plot.py. Script matplotlib_xy_plot.py: """ DKRZ matplotlib script: matplotlib_xy_plot.py - line attributes - legend - title - x-labels, y-labels 25.06.15 meier-fleischer THE MONASH UNIVERSITY SIMPLE CLIMATE MODEL The Monash University Simple Climate Model*
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DKRZ - PARTNER DER KLIMAFORSCHUNG HÖCHSTE RECHENLEISTUNG. AUSGEREIFTES DATENMANAGEMENT. KOMPETENTER SERVICE. ------------------------- Über uns: Das Deutsche Klimarechenzentrum ist eine nationale Serviceeinrichtung und ein wichtiger Partner der Klimaforschung. Unsere Hochleistungsrechner, Datenspeicher und Dienste bilden die zentrale Forschungsinfrastruktur für die simulationsbasierte Klimawissenschaft in Deutschland. ------------------------- Hochleistungsrechner: Klimasimulationen erfordern Supercomputer und Datenspeichersysteme der höchsten Leistungsklasse. Die Systeme des DKRZ sind optimal auf die datenintensiven Anforderungen der Klimawissenschaften zugeschnitten und gehören weltweit zu den leistungsstärksten für die Wissenschaft eingesetzten Rechnern. ------------------------- Dienste: Das DKRZ-Fachpersonal unterstützt Klimawissenschaftler bei der optimalen Nutzung der Systeme und bietet eine Reihe von Diensten rund um Klimamodelle, Klimasimulationen und Klimadaten an: von der Unterstützung der Ausführung von Klimasimulationen, der Parallelisierung und Optimierung der Modelle über Management, Speicherung und Publikation der Daten bis hin zu Analyse und Visualisierung der Daten. ------------------------- Projekte und Partner: Internationale Spitzenforschung erfordert eine gute Vernetzung und starke Partner. Lernen Sie diese kennen und erfahren Sie, welche wissenschaftlichen Fragestellungen mit Unterstützung des DKRZ bearbeitet werden. Das DKRZ betreibt selbst keine Klimaforschung, ist aber in vielen Forschungsprojekten vertreten mit dem Ziel, die Klimawissenschaften noch besser zu unterstützen. ------------------------- Kommunikation: Insbesondere der Klimawandel und Zukunftsprojektionen mit Klimamodellen stehen immer wieder stark im Fokus der Öffentlichkeit. Bei uns finden Sie vielfältige Medien und Informationen rund um das DKRZ, aber auch darüber, was Klimawissenschaftler mit Hilfe des DKRZ und seiner Hochleistungsrechner erforschen.Artikelaktionen
11.05.2020
Neues YouTube-Video zum Projekt DYAMOND++ online01.05.2020
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S4F-Podcast: Im Gespräch mit Michael Böttinger07.04.2020
Datenkollektionen für die Klimaforschung am DKRZ verfügbar26.03.2020
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Architect and Developer for python based data handling (all genders)11.05.2020
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