The paper “High performance computing to support land, climate, and user-oriented services: The HIGHLANDER Data Portal” was recently published on Meteorological Applications. 

Highlander project strove for a smarter management of lands, studying new sectors enabled by emerging technologies interested in reducing risks on human health, agriculture, and livestock production. Using High-Performance Computing, Highlander project aimed at reducing risks associated with climate change by processing data and obtaining accurate climate forecasts, achieving the goal of having a more intelligent, sustainable management of natural resources and of the territory. 

Thanks to data processing, Highlander fully exploited new technologies to generate, manage, host and distribute organised sets of data, integrating with already existing geospatial and non-geospatial datasets. Designing and implementing a continuously updated last generation multi-thematic framework of highly detailed and harmonised data, indicators and tools ranging from remote and in-site monitoring, analytical tools and numerical models to machine learning algorithms. 

Co-funded by Connecting European Facility Programme and European Union under the  Grant agreement n° INEA/CEF/ICT/A2018/1815462, the project benefited also from collaborations with various partners, including regional environmental protection agencies (the Agenzia Regionale per la Prevenzione e l’Ambiente of EmiliaRomagna, ARPAE, and the Agenzia Regionale per la Prevenzione e l’Ambiente of Piedmont, ARPAP), the European Centre for Medium-Range Weather Forecasts (ECMWF), the University of Tuscia (UNITUS; in particular, the Department for Innovation in Biological, Agro-food and Forest systems, DIBAF), the Foundation EuroMediterranean Center on Climate Change (CMCC), the Foundation Edmund Mach (FEM), Deda Next (https://, last access: September 29, 2023), and ART-ER Attractiveness Research Territory 

In the paper, members of the team present in detail the results of the projects, the HIGHLANDER Data Portal architecture, features, and data products. 

Read the paper at this link.