This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276.
G6.01 Dispersed governance of high-quality measurement assets leading to gaps and redundancies in capabilities and methodological distinctions
Submitted by Anna Mikalsen on 12 June, 2017 - 15:27
Gap abstract:
Current governance of high-quality measurement programs is highly fractured. Numerous networks exist at national, regional, and global levels that have been set up and funded under a variety of governance models. This fractured management of observational capabilities can lead to, amongst others: redundancies, spatiotemporal gaps, varied data policies and formats, varied data processing choices, and fractured provision of data. The gap thus contributes to various other more specific gaps identified in the gaps-assessment process undertaken within GAIA-CLIM.
Part I Gap description
Primary gap type:
- Governance (missing documentation, cooperation etc.)
Secondary gap type:
- Spatiotemporal coverage
- Vertical domain and/or vertical resolution
- Knowledge of uncertainty budget and calibration
ECVs impacted:
- Temperature,Water vapour, Ozone, Aerosols, Carbon Dioxide, Methane
User category/Application area impacted:
- Operational services and service development (meteorological services, environmental services, Copernicus Climate Change Service (C3S) and Atmospheric Monitoring Service (CAMS), operational data assimilation development, etc.)
- International (collaborative) frameworks and bodies (space agencies, EU institutions, WMO programmes/frameworks etc.)
Non-satellite instrument techniques involved:
- Independent of instrument technique
The G6.01 gap is an effect multiplier on many of the gaps identified in the GAID. As such, its resolution would facilitate resolution of numerous other gaps. Solely a handful of important dependencies are noted here.
The gap identified in G6.02 arises as a result of G6.01. One of the key benefits of resolution of G6.01 would be the potential to rationalise dispersed observational assets.
The resolution to G6.03 will be simpler if a more unified governance of non-satellite measurement networks is achieved and the data is provided from these networks in a more unified manner.
The data policy landscape is a direct result of the fractured governance of observational assets identified in the current gap. Resolving the current gap would aid steps to address the issues detailed in G5.01.
Detailed description:
Non-satellite data sources identified as “reference” and “baseline” quality within GAIA-CLIM have greatly dispersed governance structures. There are numerous national, regional, and global networks, which aim to measure GAIA-CLIM target ECVs to a high standard. This dispersed governance leads to decisions, which, although sensible on an individual network basis, are sub-optimal on a more holistic basis.
This fractured governance both results from but also augments a diversity in historical and present-day funding support, authority, and observational program priorities. Inevitable deleterious results accrue from a fractured governance and support mechanism, which include:
- Geographical dispersal of capabilities
- Unintended and undesirable competition between otherwise synergistic activities
- Different networks take different approaches to data acquisition (measurement practices), data processing and serving, which reduces both accessibility to and comparability of the resulting data.
As such, many of the remaining gaps identified within the GAIA-CLIM GAID are symptoms of the effects of G6.01 remaining unaddressed (see prior section). Although the gap has been identified and articulated here solely for GAIA-CLIM target ECVs, it is symptomatic of broader issues that pervade the governance of all but perhaps for a small handful of non-satellite observational assets and programs. The norm is for multiple parties to be interested in measuring given ECVs and other variables. These parties inevitably undertake a diverse range of approaches, which reduces their comparability and interoperability.
Validation aspects addressed:
- Radiance (Level 1 product)
- Time series and trends
- Representativity (spatial, temporal)
- Calibration (relative, absolute)
Gap status after GAIA-CLIM:
- After GAIA-CLIM this gap remains unaddressed
Part II Benefits to resolution and risks to non-resolution
| Identified benefit | User category/Application area benefitted | Probability of benefit being realised | Impacts |
|---|---|---|---|
More unified voice for non-satellite data management |
|
| Improved ability to engage in strategy planning. Improved responsiveness in a unified fashion to identified user and stakeholder needs. |
Rationalisation of observational assets |
|
| Closer to optimal co-location of high-quality instrumentation leading to better characterisation of atmospheric properties. |
Consistency of data provision |
|
| More consistent provision of data (reduction in variety of portals and / or formats) leading to better ability to utilise the data. |
More efficient use of resources |
|
| Greater value to funders |
| Identified risk | User category/Application area at risk | Probability of risk being realised | Impacts |
|---|---|---|---|
Reduction in funding opportunities for high-quality measurements owing to fractured and competing demands. |
|
| Reduced value of observations. |
Continued fractured governance leading to sub-optimal management and development of high-quality measurement networks. |
|
| Reduced utility of observational data assets through fractured decision-making. |
Part III Gap remedies
Gap remedies:
Remedy 1: Undertake short-term cross-network governance improvements
Primary gap remedy type:
Governance
Proposed remedy description:
Strengthen existing efforts to ensure meaningful collaboration between potentially synergistic or complementary networks. This could be achieved via several means. Improved cross-governance group representation could be implemented between networks that have similar aims / remits which may start to enforce a degree of collaboration and cross-fertilisation of best practices. A more formal approach, which may be relevant in certain cases, is a more formal network memoranda of understanding. On a more practical and working level, synergies can be realised through involvement in joint research and infrastructure activities such as EU Research Infrastructures, Horizon 2020, and Copernicus grants and service contracts or similar activities outside of Europe. Networks should be actively encouraged to participate in such funding opportunities. Funders should explicitly advertise such opportunities and consider targeted research funding opportunities that aim to build synergies between observational networks.
Relevance:
The remedy would lead to improved cross collaboration and understanding between networks of potential synergies and serve to improve the visibility of activities between synergistic groups.
Measurable outcome of success:
Demonstrable increase in collaboration between networks through joint projects, publications describing joint research outcomes, and participation in network meetings
Expected viability for the outcome of success:
- High
Scale of work:
- Programmatic multi-year, multi-institution activity
Time bound to remedy:
- Less than 3 years
Indicative cost estimate (investment):
- Low cost (< 1 million)
Indicative cost estimate (exploitation):
- Yes
Potential actors:
- EU H2020 funding
- Copernicus funding
- National funding agencies
- WMO
- ESA, EUMETSAT or other space agency
Remedy 2: Longer-term rationalisation of observational network governance
Primary gap remedy type:
Governance
Proposed remedy description:
Take steps to assess and as necessary rationalise the number of networks involved in taking high-quality measurements by merging, where possible, leading to more unified governance and planning for these measurement programs, both regionally and globally. To undertake this robustly requires an analysis of the current observational capabilities and governance structure, which should take account of funding, geopolitical remit, and other relevant factors. This may include in-depth survey interviews and other means to fully understand the role, support-model, and uses of each network. Then a rationalisation plan would need to be produced, circulated, and gain broad buy-in amongst the affected networks and associated global oversight bodies. Mergers should only proceed on a no-regrets basis and should not be enforced, if funding support or other essential support would be weakened as a result of the decision. Merged entities must be scientifically more robust, complete, and sustainable as a result of any merger.
Relevance:
The remedy would make it easier for funding and research communities to interact with the high-quality measurement networks.
Measurable outcome of success:
Reduction in complexity of the “ecosystem” of observing networks through time while retaining and enhancing observational capabilities.
Expected viability for the outcome of success:
- Medium
Scale of work:
- Programmatic multi-year, multi-institution activity
Time bound to remedy:
- More than 10 years
Indicative cost estimate (investment):
- Medium cost (< 5 million)
Indicative cost estimate (exploitation):
- No
Potential actors:
- EU H2020 funding
- Copernicus funding
- National funding agencies
- National Meteorological Services
- WMO
- ESA, EUMETSAT or other space agency