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Studying the Influence of Climate Changes on European Ozone Levels

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Zahari Zlatev
  • Ivan Dimov, Bulgarian Academy of Sciences
  • ,
  • István Faragó, Budapest University of Technology and Economics, MTA-ELTE
  • ,
  • Krassimir Georgiev, Bulgarian Academy of Sciences
  • ,
  • Ágnes Havasi, Eotvos Lorand University, MTA-ELTE

The large-scale air pollution model UNI-DEM (the Unified Danish Eulerian Model) was used together with several carefully selected climatic scenarios. It was necessary to run the model over a long time-interval (sixteen consecutive years) and to use fine resolution on a very large space domain. This caused great difficulties because it was necessary to (a) perform many runs with different input parameters, (b) use huge input files containing the needed meteorological and emission data, (c) resolve many problems related to the computational difficulties, (d) develop and apply carefully prepared parallel codes, (e) exploit efficiently the cache memories of the available computers and (f) store in a proper way huge output files for visualization and animation. It will be described how these difficult tasks have been resolved and many results related to some potentially harmful ozone levels will be presented.

Original languageEnglish
Title of host publicationLarge-Scale Scientific Computing
EditorsIvan Lirkov, Svetozar Margenov
PublisherSpringer
Publication year2020
Pages391-399
ISBN (print)9783030410315
DOIs
Publication statusPublished - 2020
Event12th International Conference on Large-Scale Scientific Computing, LSSC 2019 - Sozopol, Bulgaria
Duration: 10 Jun 201914 Jun 2019

Conference

Conference12th International Conference on Large-Scale Scientific Computing, LSSC 2019
LandBulgaria
BySozopol
Periode10/06/201914/06/2019
SeriesLecture Notes in Computer Science
Volume11958
ISSN0302-9743

    Research areas

  • AOT40, Climate changes, High-speed computers, Large-scale air pollution models, Non-linear PDEs, Parallel codes

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ID: 190885394