Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Presentation . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Presentation . 2020
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Broadening access to supercomputers for CMIP6 and CORDEX multimodel comparisons

Authors: Moreno de Castro, Maria; Kindermann, Stephan;

Broadening access to supercomputers for CMIP6 and CORDEX multimodel comparisons

Abstract

Presented at EGU2020 - https://doi.org/10.5194/egusphere-egu2020-19121 Presentation of a new service designed to assist the users of model data in running their analyses in world-class supercomputers. The increase of data volumes and model complexities can be challenging for data users with limited access to high performance computers or low network bandwidth. To avoid heavy data transfers, strong memory requirements, and slow sequential processing, the data science community is rapidly moving from classical client-side to new server-side frameworks. Three simple steps enable server-side users to compute in parallel and near the data: (1) discover the data you are interested in, (2) perform your analyses and visualizations in the supercomputer, and (3) download the outcome. A server-side service is especially beneficial for exploiting the high-volume data collections produced in the framework of internationally coordinated model intercomparison projects like CMIP5/6 and CORDEX and disseminated via the Earth System Grid Federation (ESGF) infrastructure. To facilitate the adoption of server-side capabilities by the ESGF users, the infrastructure project of the European Network for Earth System Modelling (IS-ENES3) is now opening its high performance resources and data pools at the CMCC (Italy), JASMIN (UK), IPSL (France), and DKRZ (Germany) supercomputing centers. The data pools allow access to results from several models on the same site and the data and resources are locally maintained by the hosts. Besides, our server-side framework not only speeds the workload but also reduces the errors in file format conversions and standardizations and software dependencies and upgrade. The service is founded by the EU Commission and it is free of charge. Presentation of several use cases showing how easy and flexible it is to use our analysis platforms for multimodel comparisons of CMIP5/6 and CORDEX data.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 7
    download downloads 11
  • 7
    views
    11
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
7
11
Green
Funded by