This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276.
G1.03
G1.03 Missing evaluation criteria for assessing existing observing capabilities
Gap detailed description
No effort has been made to define and broadly agree amongst global stakeholders the measurement and network characteristics underlying a system of systems approach to Earth Observation. As a result this potentially inhibits realisation of the full benefits of an explicitly system of systems architecture (trickle down, calibration, characterisation etc.). It also places the burden of appropriate use of data squarely on the user, which is an unrealistic expectation in the majority of cases. Different domain areas use specific, but overlapping naming conventions, but often mean very different things. The unwary user is faced with an unenviable task as a result, and this yields sub-optimal and / or incorrect usage of available observational records in many cases.
Activities within GAIA-CLIM related to this gap
Task 1.1 created a guidance to support the designation of non-satellite observational capabilities into a structured system of systems observing architecture, also included under D1.3. This report proposed a specific system of systems approach to observing system design and arose potential approaches to their assessment. Task 1.2 is in the process of undertaking an assessment for a subset of the atmospheric domain that may plausibly contribute to the VO with a deliverable due in M18 (Sept 2016).
Gap remedy(s)
Remedy
Specific remedy proposed
Adoption of the GAIA-CLIM approach or of similar approaches established by globally responsible entities, such as the Global Climate Observing System (GCOS) or WMO Integrated Global Observing System (WIGOS) and / or in subsequent relevant scientific projects. GAIA-CLIM has developed D1.3 which provides a potential framework to initiate discussions. But this is the limit of how far GAIA-CLIM alone can proceed on this gap. WIGOS or GCOS are likely the appropriate bodies to get broader buy-in and enhanced coordination amongst global stakeholders. The adoption of such an approach is currently articulated in the draft version of the third GCOS Implementation Plan. GAIA-CLIM shall also write-up a version of D1.3 for peer-review to gain greater exposure and buy-in (submission foreseen Q4 2016).
Measurable outcome of success
Successful implementation of the system of systems approach and maturity assessment shall be achieved through adoption by WIGOS and /or GCOS (likely modified). Promoting its use to instigate a system of systems approach across atmospheric, oceanic and terrestrial domains and that approach yields demonstrable scientific, technological and financial benefits. In the interim, uptake in other projects would be a demonstrable outcome. INTAROS shall utilize the approach for the Arctic and across terrestrial, oceanic and atmospheric domain areas.
Achievable outcomes
Technological / organizational viability: Medium.
Technologically this is entirely feasible. However, there is a relative lack of buy-in to the concept outside of GAIA-CLIM that is required to be overcome. Although some actors see it as potentially useful, it is not seen as sufficiently relevant within e.g. WIGOS at this time.
Indicative cost estimate: low (<1 million)
Relevance
The adoption of the tiered approach and assessment of maturity within that framework would help to ensure better use of observations across application areas as detailed in D1.3.
Timebound
Currently, potentially to be included as an action for GCOS to consider in their next Implementation Plan spanning 2016-2021. Any adoption as part of WIGOS would next be possible at CG18 in 2019.
Gap risks to non-resolution
Identified future risk / impact |
Probability of occurrence if gap not remedied |
Downstream impacts on ability to deliver high quality services to science / industry / society |
Continued use of inappropriate data in applications |
High |
Impact depends upon the specific role of the data. Examples such as the Ozone hole or tropospheric temperatures suggest potentially large issues. |
Continued within and across domain confusion in naming conventions and data quality assessments |
High |
Confusion to end-users on what different data streams constitute. |
Inefficiencies in network design arising from imperfect knowledge of capabilities |
High |
Economically wasteful use of resources, synergies between observing capabilities not realised leading to degraded assessments of observational change |