HIGHLANDER – High performance computing to support smart land services

/
Cosa facciamo
/
/
HIGHLANDER – High performance computing to support smart land services

Through the use of High Performance Computing, HIGHLANDER will make it possible to process data and generating climate forecasts and projections to reduce the risks associated with climate change, for a more intelligent and sustainable management of natural resources and the territory.

General Aims

Seeing climate change as a new opportunity is the challenge that HIGHLANDER project has taken on and want to address. HIGHLANDER strives for a smarter management of lands, studying new sectors enabled by emerging technologies interested in reducing risks on human health, forests, agriculture and livestock production. Through the use of High Performance Computing, HIGHLANDER project aims at reducing risks associated with climate change by processing data and obtaining accurate climate forecasts and projections, achieving the goal of having a smarter and sustainable management of natural resources and of the territory.

Highlander Project: a video teaser

CMCC role

CMCC is leader of WP4 on “Simulating the environment: from Numerical Models to Machine Learning Data Integration” to produce downscaling of reanalysis and of climate projections, and will contribute on the different work packages related to Open Data Policy, Downstream application and pre-Operational Services (DApOS) and on HPC and cloud services, besides participating to Dissemination and Communication Activities.

Activities

Thanks to data processing, HIGHLANDER will be fully exploiting new technologies to generate, manage, host and distribute organised sets of data, integrating with already existing geospatial and non-geospatial datasets.

HIGHLANDER will design and implement a continuously updated last generation multi-thematic framework of highly detailed and harmonised data, indicators and tools ranging from remote and in-situ monitoring, to analytical tools and numerical models, up to machine learning algorithms.

The data processing activity will ensure new and already existing datasets accessible to multiple users, HPC-based tools and services, and the long-term functionality of the created services thanks to the involvement of real users during the project. Facilitating the mainstream of information itself into decisions, strategies and plans on different interacting scales and sectors.

Expected results

HIGHLANDER project will be able to develop new cutting-edge applications and services for:

  • a smarter management of agriculture – irrigation schedules, fertilizer inputs, water cycle and sustainability of competing uses (hydropower, domestic, agricultural, ecological) – supporting planning and decision-making when considering territorial resources and systems owing to short-term forecasts and medium-term climate projections, including extreme events and related climate risks;
  • ensuring animal welfare, proper environmental management of natural parks, and forest fire predictions and controls, integrating climate data, satellite observations and Internet of Things (IoT).

 

Partner

CINECA

ART-ER Attractiveness Research Territory

DEDAGROUP Public Services S.r.l.

Agenzia Regionale per la Protezione Ambientale del Piemonte

Agenzia Regionale per la Prevenzione, l’Ambiente e l’Energia dell’Emilia-Romagna (Arpae Emilia-Romagna)

Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici

Università degli Studi della Tuscia

Fondazione Edmund Mach

Confederazione italiana agricoltori provincia di Torino C.I.A.

European Centre for Medium-Range Weather Forecasts

 

Start typing and press Enter to search

Shopping Cart