Exploitation of Multiple Model Layers within LEXIS Weather and Climate Pilot: An HPC-Based Approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F22%3A10251905" target="_blank" >RIV/61989100:27740/22:10251905 - isvavai.cz</a>
Result on the web
<a href="https://www.taylorfrancis.com/chapters/edit/10.1201/9781003176664-8/exploitation-multiple-model-layers-within-lexis-weather-climate-pilot-paola-mazzoglio-emanuele-danovaro-laurent-ganne-andrea-parodi-stephan-hachinger-antonella-galizia-antonio-parodi-jan-martinovič" target="_blank" >https://www.taylorfrancis.com/chapters/edit/10.1201/9781003176664-8/exploitation-multiple-model-layers-within-lexis-weather-climate-pilot-paola-mazzoglio-emanuele-danovaro-laurent-ganne-andrea-parodi-stephan-hachinger-antonella-galizia-antonio-parodi-jan-martinovič</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1201/9781003176664-8" target="_blank" >10.1201/9781003176664-8</a>
Alternative languages
Result language
angličtina
Original language name
Exploitation of Multiple Model Layers within LEXIS Weather and Climate Pilot: An HPC-Based Approach
Original language description
The LEXIS (Large-scale EXecution for Industry & Society) Weather and Climate Pilot is developing a system for the prediction of water-related phenomena and their associated socioeconomic impacts. The system is based on multiple models chained together, as global weather models, high-resolution regional weather models, domain-specific application models (hydrological and forest fire risk forecasts), and impact models providing information (such as air quality and rainfall intensity) for key decisions and policymakers. This chapter describes the key aspect of this pilot in terms of serving model output data and products with cloud and high-performance data analytics environments, on top of a Weather Climate Data API, as well as the porting of models on the LEXIS infrastructure via different virtualization strategies (as virtual machine and dockers). (C) 2022 selection and editorial matter, Olivier Terzo and Jan Martinovic; individual chapters, the contributors.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
HPC, Big Data, and AI Convergence Towards Exascale: Challenge and Vision
ISBN
978-1-03-200984-1
Number of pages of the result
17
Pages from-to
147-163
Number of pages of the book
163
Publisher name
CRC Press
Place of publication
Boca Raton
UT code for WoS chapter
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