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Rationale

The advent of the European Commission's Copernicus Programme marks the start of a new era in Earth Observation for Societal Benefit. The operational capability being implemented for Copernicus will deliver a step-change in the end-to-end chain that begins with observing our environment by satellite-based and in-situ-based instruments, and ends with providing end-user services to decision-makers and the general public.  By bringing the full chain within one programme, Copernicus provides the co-ordinated framework to exploit scientific and technological innovation and to translate these into usable high-quality information tailored to diverse sectors of society.

Hence a critical component of the Copernicus framework is the provision of high-quality observational datasets from satellites. It follows that these need to be calibrated and validated to standards that enable them to be used with confidence for applications across a broad range of sectors. In turn, this requires ancillary datasets from in-situ and other sources that need to be of high-quality and sufficient quantity to robustly characterise sensor performance and radiative transfer modelling to provide confidence in the satellite data. For the purpose of validation, established practice from space agencies and other satellite dataset providers is to make substantial use of satellite-to-satellite intercomparisons combined with in-situ datasets and supplemented by datasets from operational numerical weather prediction and/or reanalyses (which blend observations with model forecasts taking into account the uncertainties in both). Few, if any, of these comparator measures constitute fully traceable estimates. The challenges to rigorous satellite data characterisation are therefore formidable because without traceability in the comparator measures there is ambiguity in any comparison.

The objective of the Consortium is to play a full role in supporting Copernicus by establishing prioritized needs for further observational capacity targeted at providing the required step-change in satellite calibration and validation capability. The principal aim is to lead to a step change of availability of, and ability to utilize, truly reference quality traceable measurements in support of satellite data characterisation. It is only if robust uncertainty estimates are placed on the ground-based and sub-orbital data and used in the analysis that unambiguous interpretation of EO sensor performance can occur. The magnitude of the challenge requires a co-ordinated approach to both establish the strategic approach and define specific campaigns. The Consortium has drawn together leading stakeholders from the relevant communities, who provide the necessary experience to fulfil the objectives.  Specifically, the consortium has been chosen to bring together scientific, technical and leadership expertise in high-quality in-situ and sub-orbital observations, gap analyses, modelling, satellite operations and data assimilation, and in setting the priorities for the EO community at the European and global levels.

Robust EO instrument characterisation is about significantly more than simply where and when a given set of EO and ground-based / sub-orbital measurements is taken. It requires, in addition, quantified uncertainty estimation for the reference measurements and an understanding of additional uncertainties that accrue and increase the apparent discrepancy between measured data sets through mismatches in spatio-temporal sampling, given the complex spatial and temporal variability of the atmosphere, spanning spatial scales from sub-kilometer to synoptic scale and timescales from seconds to decades. It also needs user tools, which include statistical tools and the integrating capabilities afforded by data assimilation systems to enable users to access and work with the data in a ‘virtual observatory’ setting. Mapping of capabilities in a spatio-temporal sense will be undertaken by GAIA-CLIM for several of those atmospheric, land and oceanic ECVs, which are measured by EO instruments. Subsequent measurement mapping and the development of a range of tools will be undertaken with a focus on the atmosphere as a test case, in particular fundamental geophysical (temperature, humidity) and composition (long lived greenhouse gases, ozone and its precursors, aerosols) parameters of importance to environmental monitoring across a broad range of time and space scales. Comparisons and mapping to EO data will be undertaken at both level1b (radiance) and level2/3 (parameter) data levels. There is a particular focus upon the value of high quality reference / benchmark measurement capabilities to long-term sustained high-quality characterisation of space based EO sensor performance to maximise their value for climate applications. Tools and capabilities developed in this project with direct application to atmospheric ECVs defined by GCOS (among which a few are linked as well to e.g. air pollution and air traffic management) will be built in such a way as to be extendable in future to further atmospheric parameters and the terrestrial and oceanic domains.

Scientific objectives

S1.  Define and document a tiered system of systems approach to EO measurements characterisation, based upon measurement properties, in order to categorize ground-based and sub-orbital measurement capabilities.

S2.  Map in geographical space, and in terms of temporal congruence with EO measurements current and known future ground-based and sub-orbital capabilities into the system of systems framework for several of those atmospheric, oceanic and terrestrial GCOS ECVs that are measured from space.

S3.  Provide quantified uncertainty estimates on atmospheric measurements for temperature, water vapour,  carbon dioxide, methane, ozone and precursors (nitrogen dioxide, carbon monoxide, formaldehyde), and aerosols with a focus on provision of reference quality measurement uncertainties that are traceable to recognised measurement standards.

S4.  Understand and quantify the metrology of data comparisons, including additional uncertainties that result from measurement mismatches in both space-time and in terms of the measurement volume and interval, using a suite of multi-dimensional descriptions with explicit physics, statistical methods and data assimilation systems. Some metrology errors are irreducible; others can be reduced by optimisation of the measurement settings.

S5.  Integrate into data assimilation systems (global atmospheric models and reanalysis systems) the ability to utilize reference measurements so as to enable traceable characterisation of EO data.

S6.  Perform a Cal/Val gap analysis based upon geographical coverage, measurement capabilities / characterisation, user needs, technological impediments and opportunities, and national and international measurement strategies and governance. Produce a set of prioritised recommendations arising.

Technological objectives

These technological objectives, taken together, form the basis for a ‘virtual observatory’ that will allow users to undertake data analysis and visualization with the aim of making the use of ground based and sub-orbital reference measurements a routine and integral part of EO instrument characterisation.

T1.  Development of mapping tools to enable visualization of observing capabilities.

T2.  Development of software tools that are extendable to quantify comparison uncertainties associated with space-time differences in sampling and smoothing of atmospheric structures and variability.

T3.  Development of the ability to use reference quality measurements in a data assimilation framework to provide a robust data assimilation tie-points assuring traceability.

T4.  Development and population of match-up database of satellite measurements with reference measurements including measurement uncertainties and comparison uncertainties, and diagnostics from data assimilation systems.

User outreach objectives

O1. To demonstrate to a wide audience (including satellite agencies, industry, and applied scientists) how reference measurements can be used to underpin the calibration and validation of EO data.

O2. Systematic consulting of the satellite and modelling end-user communities.

O3. Stakeholder meetings and canvassing throughout the project lifetime.

O4. Provision of software tools under a creative common licensing system.

O5. Provision of a graphical interface mapping tool of observing capabilities.

O6. Provision of collocation match up database and associated graphical user interface tools for reference quality observations for a number of atmospheric ECVs.

O7. Presentations by consortium partners at international meetings and papers in the peer reviewed literature to promote partnership with the consortium.

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