LEXIS Weather and Climate Large-Scale Pilot

Parodi, Antonio; Danovaro, Emanuele; Hawkes, James; Quintino, Tiago; Lagasio, Martina; Delogu, Fabio; D’Andrea, Mirko; Parodi, A. Ferretto; Sardo, Biagio Massimo; Ajmar, Andrea; Mazzoglio, Paola; Brocheton, Fabien; Ganne, Laurent; García‐Hernández, Rubén; Hachinger, Stephan; Hayek, Mohamad; Terzo, Olivier; Křenek, Jan; Martinovič, Jan

doi:10.1007/978-3-030-50454-0_25

Cited by 7 publications

(3 citation statements)

References 13 publications

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“…We can find several EU funded projects targeting the convergence between HPC and DA. The LEXIS project [54,55,56] tackles the description and automation of computational workflows (e.g., simulations with subsequent data analysis steps) providing easy access to federated computing and data systems.…”

Section: Other Related Projectsmentioning

confidence: 99%

Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence

Ejarque

Badía

Albertin

et al. 2022

Future Generation Computer Systems

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Section: Other Related Projectsmentioning

confidence: 99%

Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence

Ejarque

Badía

Albertin

et al. 2022

Future Generation Computer Systems

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“…В некоторых направлениях успели сложиться свои традиции и популярные наборы программных инструментов, в то время как другие начинали формироваться в последние несколько лет. Однако, в большинстве случаев справедливы следующие общие проблемы [7,8,9,10,11…”

Section: актуальные задачиunclassified

Requirements and architecture design for cloud PaaS orchestrator

Lazarev¹,

Borisenko²

2022

Proceedings of ISP RAS

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Cloud technologies provide abilities for simple and reliable scaling of resources, due to which they have become widespread. The task of managing distributed services in a cloud environment is especially relevant today. Special programs are used for that purpose named “orchestrators” which implement the functions of lifecycle management for applications. However, the existing solutions have many limitations and are not applicable in the general case. Also there is no single standard or protocol for interaction with such tools which requires adaptation of programs for each particular case. The main objectives of this paper are to identify the requirements for a platform-level cloud computing (PaaS) orchestrator, as well as to propose flexible architecture patterns for such tools.

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“…The Weather and Climate pilot of the LEXIS (Large-scale EXecution for Industry & Society) H2020 project aims at developing workflows based on weather-related models to improve existing hydro-meteorological applications for severe rainfall, flash-flood, wildland forest fires, and air quality predictions [1,2]. This pilot is taking advantage of cloud solutions and large-scale geographically distributed High-Performance Computing (HPC) resources displaced in several European countries to run experiments that require the processing of a large amount of data on a dedicated platform.…”

Section: Introductionmentioning

confidence: 99%

Detecting Extreme Rainfall Events Using the WRF-ERDS Workflow: The 15 July 2020 Palermo Case Study

Mazzoglio

Parodi

2022

Water

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In this work, we describe the integration of Weather and Research Forecasting (WRF) forecasts produced by CIMA Research Foundation within ITHACA Extreme Rainfall Detection System (ERDS) to increase the forecasting skills of the overall early warning system. The entire workflow is applied to the heavy rainfall event that affected the city of Palermo on 15 July 2020, causing urban flooding due to an exceptional rainfall amount of more than 130 mm recorded in about 2.5 h. This rainfall event was not properly forecasted by meteorological models operational at the time of the event, thus not allowing to issue an adequate alert over that area. The results highlight that the improvement in the quantitative precipitation scenario forecast skills, supported by the adoption of the H2020 LEXIS computing facilities and by the assimilation of in situ observations, allowed the ERDS system to improve the prediction of the peak rainfall depths, thus paving the way to the potential issuing of an alert over the Palermo area.

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LEXIS Weather and Climate Large-Scale Pilot

Cited by 7 publications

References 13 publications

Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence

Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence

Requirements and architecture design for cloud PaaS orchestrator

Detecting Extreme Rainfall Events Using the WRF-ERDS Workflow: The 15 July 2020 Palermo Case Study

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