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O3as: an online ozone trend analysis service within EOSC-synergy

Kerzenmacher, Tobias ORCID iD icon; Kozlov, Valentin ORCID iD icon; Esteban Sanchis, Borja ORCID iD icon; Cayoglu, Ugur; Hardt, Marcus ORCID iD icon; Braesicke, Peter

Abstract (englisch):

O3as is a service within the framework of the European Open Science Cloud-Synergy (EOSC-Synergy) project supporting scientists working on the Chemistry-Climate Model Initiative (CCMI, http://blogs.reading.ac.uk/ccmi/ccmi-phase-two/) for the quadrennial global assessment of ozone depletion (https://www.esrl.noaa.gov/csl/assessments/ozone/2018/). The next assessment will be due in 2022. The recent ozone assessment report consists of six chapters and five appendices with about 25 people actively working on each chapter and a multitude of people working in support of the preparation of the document. O3as shall provide an invaluable service to extract ozone trends from large data volumes created by climate projection models producing figures of stratospheric ozone trends in publication quality, in a coherent way. A web application shall be provided where a user configures their requests to perform simple analyse. This request is passed to the O3as service via an O3as REST API call. There, the O3as service processes the request, where the reduced data set is accessed via WebDAV and OIDC. In order to produce a reduced data set, regular tasks are run on an HPC to copy primary data and perform data preparation (e.g. ... mehr


Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Scientific Computing Center (SCC)
Universität Karlsruhe (TH) – Zentrale Einrichtungen (Zentrale Einrichtungen)
Publikationstyp Vortrag
Publikationsdatum 22.01.2021
Sprache Englisch
Identifikator KITopen-ID: 1000140947
HGF-Programm 46.21.02 (POF IV, LK 01) Cross-Domain ATMLs and Research Groups
Weitere HGF-Programme 12.11.27 (POF IV, LK 01) Stratosph. impacts on regional climate with link to ocean
Veranstaltung 5th Data Science Symposium (2021), Online, 22.01.2021
Projektinformation EOSC-synergy (EU, H2020, 857647)
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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