NORCE Norwegian Research Centre AS (NO)
Despite considerable research progress in understanding the polar region over the last decades, many gaps remain in observational capabilities and scientific knowledge. These gaps limit present ability to understand and interpret on-going processes, prediction capabilities and forecasting in the Arctic region, thereby hampering evidence-based decision-making. Addressing these gaps represents a key priority in order to establish a solid scientific basis for understanding earth science processes in the Polar Regions.
The Cryosphere Virtual Lab aims at supporting the cryosphere scientific community to address those gaps promoting an Open Science approach, where sharing of data (e.g., EO satellite, in-situ, airborne, ancillary, high level products), knowledge, tools and results is at the center of the science process.
Since more than 20 years, “Earth Observation” (EO) satellites developed or operated by ESA and other satellite operators are providing a wealth of data. The Sentinel missions, along with the Copernicus Contributing Missions, Earth Explorers and many other missions provide routine monitoring of our environment at the global scale, thereby delivering an unprecedented amount of data. This expanding operational capability of global monitoring from space, combined with data from long-term EO archive (e.g. ERS, Envisat, Landsat etc.), in-situ networks and models provide scientists with unprecedented insight into how our oceans, atmosphere, land and ice operate and interact as part of an interconnected Earth System.
While the availability of the growing volume of environmental data from space represents a unique opportunity for science, general R&D, and applications, it also poses a major challenge to achieve its full potential in terms of efficiently accessing and combining the different datasets (EO data, airborne, in-situ…) and sharing scientific knowledge, tools and results in order to speed up the scientific process. Firstly, because the emergence of large volumes of data raises new issues in terms of discovery, access, exploitation, and visualization, with implications on how scientists do “data-intensive” Earth Science. Secondly, because the inherent growing diversity and complexity of data and users, whereby different communities – having different needs, methods, languages and protocols – need to cooperate and share knowledge to make sense of a wealth of data of different nature (e.g. EO, in-situ, model), structure, format and error budgets and speed up the scientific development process.
Responding to these technological and community challenges requires the development of new ways of working, capitalizing on Information and Communication Technology (ICT) developments to facilitate the exploitation, analysis, sharing, mining and visualization of massive EO data sets and high-level products within Europe and beyond following an Open Science approach. Evolution in information technology provide new opportunities to provide more significant support to EO data exploitation within the Open Science paradigm. In this context, new ITC developments and the concept of Virtual laboratories make scientific networking, on-line collaboration, sharing of data, tools and knowledge among scientific communities not only possible, but also mainstream.
The Cryosphere Virtual Laboratory (CVL) will become a community open science tool, where EO satellite data and derived products can be accessed, visualised, processed, shared and validated. In order to achieve this objective, the CVL shall provide access and facilitate sharing of relevant space and non-space data (aerial, UAV, coastal radar, in-situ etc.). Following an Open Science approach, the CVL shall mainly be designed to support scientist to access and share EO data, high-level products, in-situ data, and open source code (algorithms, models) to carry out scientific studies and projects, sharing results, knowledge and resources. The Cryosphere Virtual Laboratory will form part of an ecosystem of thematic laboratories capitalizing on ICT technologies to maximize the scientific exploitation of EO satellite data from past and future missions.
Geoscientific Model Development (2022)