The proposed developments should be modular and scalable, and proposals should provide a proof-of-concept or a prototype that can be easily adapted by at least one of the Copernicus Services and / or an observing network or similar delivering critical in situ data to Copernicus.
Address these areas of R&I:
-Facilitation of efficient and methodologically sound reuse of in situ data collected during field experiments for validation of Copernicus data and information services.
-Innovative observation strategies and concepts to improve the observational capacity in selected data sparse areas.
-Synergy of complementary types of surface observations.
-Application of machine learning technologies for quality control and real-time meteorological and hydrological in situ observations.
– Optimal use of early observations. Evaluation and assessment of past observing methods and environmental factors, and on error analysis, quality control and bias adjustment of the in situ historical record;
– Better use of Copernicus relevant observations and auxiliary data collected during R&I projects not easily recoverable and reusable for validation purposes in an operational context;
– Enhanced availability and quality of in situ data critical for the production and validation of Copernicus products and data services;
– Appropriate consideration of Copernicus Services’ cross-cutting challenges and R&I priorities.