In parallel, driven in part by the critical needs of climate change, there has been a significant move towards a more coordinated and comprehensive assessment and reporting of the quality, biases and residual uncertainty in the observations made by different satellite sensors. This is illustrated by examples of infrastructure and methods on the CEOS calvalportal [1], most notably that of the Radiometric Calibration Network (RadCalNet) [2]. More recently, this need has been enhanced with the emergence of new commercial satellite operators ensuring that users have a transparent and fair means to judge the adequacy of data products to meet their needs. All of these developments have led to the endorsement by The Group on Earth Observations (GEO) of a CEOS Working Group Cal/Val (WGCV) and World Meteorological Organization (WMO) Global Space-based Inter-Calibration System (GSICS)-led community initiative to create a Quality Assurance Framework for Earth Observation (QA4 EO) [3]. QA4 EO provides a set of principles and associated guidance including specifically tailored tools [4] to encourage the provision of internationally consistent quality indicators on their delivered data. QA4 EO guidelines state that _it is critical that data and derived products are easily accessible in an open manner and have an associated indicator of quality traceable to reference standards (preferably SI) so users can assess suitability for their applications i.e., 'fitness for purpose'_. The QA4 EO principles, and means to establish and demonstrate them, were tailored from those in common usage across many commercial and scientific sectors, ultimately derived from the best practices of the international metrology community. The latter is charged by intergovernmental treaties with ensuring international consistency and long-term reliability of measurements to support trade and legislation, through the international system of units (SI) [5]. The robustness of the SI and its dissemination over century-long timescales is underpinned by adherence to clear principles:  
Unequivocal, documented, consensus definition of'references' and the _mises-en-pratique_[6] to realise them. Documented evidence of the degree of traceability (residual bias) and associated uncertainty of a measurement relative to the'reference' through:  
* regular, openly reported comparison with independent peers (where there is no independent representative measurement with lower uncertainties), or
* comparison (validation/calibration) against an independent representative measurement of the same measurement with similar or lower uncertainties than that being evidenced. * detailed comprehensive assessment of uncertainty of the measurement and its traceability to the reference that is peer reviewed alongside comparison results. One key element of QA4 EO relates to post-launch Cal/Val of satellite-delivered data through an independently derived data set that can be correlated to that of the satellite observation. Of course, for this process to be robust, the independent data set itself must also be fully characterised in a manner consistent with QA4 EO principles: i.e., that it has documented evidence of its level of consistency with a suitable reference (nominal 'truth') within an associated uncertainty. The uncertainty associated with the comparison process itself, which almost always involves a transformation of the'reference' measurand to be comparable/representative of that observed by the satellite, must also be characterised and be sufficiently small. In practice, the'reference' should be community agreed and ideally tied to SI. The need to evidence these core principles as a differentiator is the basis for creating the label Fiducial Reference Measurement (FRM). In this paper, we provide some background as to the critical need for such a tailored set of validation data (FRM) (Section 2). This is followed in Sections 3.1 and 3.2 by a potted history of the creation of the core criteria that must be fulfilled to achieve the FRM label.