This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276.
G1.04
G1.04 Lack of a comprehensive review of current non-satellite observing capabilities for the study of ECVs in atmospheric, ocean and land domains
Gap detailed description
Non-satellite observations support an increasingly wide range of applications in monitoring and forecasting of the atmosphere, and of the oceans and land surfaces, at different time scales (including near-real-time and delayed mode applications). These activities support an increasing range of services with high socio-economic benefits. User requirements have become more stringent and new requirements have increasingly appeared with respect to these applications (and undoubtedly shall continue to do so). These observation systems provide the products in one or more of real-time, near-real-time and non-real-time (those that provide a mix may apply different processing to different timescale releases with, in general, greater quality assurance for delayed mode products). In order to allow EO providers and users to maximize the value of existing observations and implement a user-friendly mapping facility, a comprehensive review of the current observing capabilities at European and global scale is needed for all the ECVs. This will also facilitate an identification of the existing geographical gaps in the global observing system. While a comprehensive review of space-based missions and needs has been put together within official documents of the international community (e.g. the CEOS Handbook and the “Satellite Supplement” to the 2nd GCOS Implementation Plan), in contrast the mapping of current non-satellite observing capabilities is piecemeal and poorly documented. It is based on the information provided voluntarily by each network or station to some international data portals in an uncoordinated way, often on an ECV by ECV basis. Extensive reviews have been provided by WMO, GEOSS, GCOS, but they are limited to those networks and ECVs relevant for their institutional mission, and often disagree with one another.
Activities within GAIA-CLIM related to this gap
GAIA-CLIM task 1.2 will make considerable efforts to identify possible options to remedy this gap as detailed in the Gap remedy text below. These will be documented in GAIA-CLIM task 1.2, deliverable D1.6: Report on data capabilities by ECV and by system of systems layer for ECVs measurable from space. (CNR; M18)
Gap remedy(s)
Remedy
GAIA-CLIM will make considerable efforts in putting together an extensive review of the existing non-satellite measurement capabilities for several techniques and networks, concentrating on the priority ECVs within the GAIA-CLIM project. Results will be delivered in September 2016 (deliverable D1.6). This assessment will include an assessment of their measurement maturity. Discussion on how to establish over the long -term the service offered under this task in the framework of the C3S program is ongoing. Current C3S call for tender Lot 3 may provide the needed funding support to sustain this activity.
Specific remedy proposed
GAIA-CLIM will make considerable efforts in putting together one of the most extensive reviews of the measurement maturity against assessable measurement properties for existing capabilities and for the measurement of a multitude of ECVs, focussing primarily upon the priority ECVs within the GAIA-CLIM project. Discussion on how to establish over the long-term the service offered under this task including the delivery of different measurement maturity data streams to end-users to enable their easy use and application in the frame C3S program is ongoing. The current C3S call for tender may provide the needed funding support to sustain this activity.
It has been recognized by the consortium that the review would be significantly reinforced by a sustained exchange of rich measurement metadata information resulting from an enhanced coordination amongst global stakeholders, like the WMO Commission on Basic Systems, GCOS, GEOSS, GAW, and the various federated networks reporting to these programs. Such rich metadata exchange under e.g. enhanced WIGOS metadata standards would greatly aid an assessment as to which tier different observing networks may fall within and ensure their appropriate usage. Ambiguity around current practices, instrumentation etc. complicates an assessment for many of the networks that might be assessable under Task 1.2. Currently, this looks quite uncertain and requires further plans and a cost assessment.
Measurable outcome of success
Use of the collected geographical metadata in the ‘Virtual Observatory’, and hence downstream applications. The timeline for the assessment and quantification of these datasets can be quantified in the first two years after the end of the project, to allow the full development of the ‘Virtual Observatory’, which will make these results and metadata available to all the potential GAIA-CLIM users. At that stage, the users level of satisfaction will be quantifiable.
Achievable outcomes
Technological / organizational viability: High
Indicative cost estimate: medium (>1million), bigger investments may depend on the size of the service requested and offered to the end-users
Relevance
The GAIA-CLIM work provides one of the first attempt to remove the fragmentation already experienced in the past creating a metadaset with the discovery metadata for a large number of networks at the global scale.
Timebound
First results will be delivered in September 2016 (deliverable D1.6) and they will be improved over the duration of GAIA-CLIM project. In order to have a long-term impact, this metadata service must be supported and sustained in the frame of C3S or other funding programs.
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 |
Fragmentation of metadata among international bodies and measurements programs. |
High |
Minimize the value of existing observations and the capability of the users to simultaneously use products for a multitude of ECVs and from varying data sources. |