Reception and Processing of Meteosat-12 FCI and LI Data Using Open-Source Solutions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F25%3AN0000031" target="_blank" >RIV/00020699:_____/25:N0000031 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Reception and Processing of Meteosat-12 FCI and LI Data Using Open-Source Solutions

Popis výsledku v původním jazyce

The next-generation Meteosat Third Generation (MTG) satellites introduce advanced capabilities with the Flexible Combined Imager (FCI) and Lightning Imager (LI), but also significantly increase processing demands due to higher spatial and temporal resolution and larger data volumes. This poster presents an efficient workflow developed at the Czech Hydrometeorological Institute (CHMI) for receiving, processing, and distributing these data using open-source solutions. Our system leverages Pytroll for data processing, Proxmox and modern workflow automation tools for cluster management, and Ceph for scalable and highly available storage. To ensure robustness against outages and maintain product availability, we employ automated failover mechanisms. Data distribution is handled via EUMETCast (Satellite and Terrestrial), supporting both operational and research applications. We discuss key challenges, performance optimizations, and integration strategies that enhance accessibility and efficiency for MTG data users. Additionally, user-friendly tools such as JupyterHub with integrated Ceph storage facilitate data analysis.

Název v anglickém jazyce

Reception and Processing of Meteosat-12 FCI and LI Data Using Open-Source Solutions

Popis výsledku anglicky

The next-generation Meteosat Third Generation (MTG) satellites introduce advanced capabilities with the Flexible Combined Imager (FCI) and Lightning Imager (LI), but also significantly increase processing demands due to higher spatial and temporal resolution and larger data volumes. This poster presents an efficient workflow developed at the Czech Hydrometeorological Institute (CHMI) for receiving, processing, and distributing these data using open-source solutions. Our system leverages Pytroll for data processing, Proxmox and modern workflow automation tools for cluster management, and Ceph for scalable and highly available storage. To ensure robustness against outages and maintain product availability, we employ automated failover mechanisms. Data distribution is handled via EUMETCast (Satellite and Terrestrial), supporting both operational and research applications. We discuss key challenges, performance optimizations, and integration strategies that enhance accessibility and efficiency for MTG data users. Additionally, user-friendly tools such as JupyterHub with integrated Ceph storage facilitate data analysis.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů