## 3 Fiducial Reference Measurements (FRMs)  
### Need for FRMs  
The terminology 'Fiducial Reference Measurement', with its initialism 'FRM', was first elaborated and used in the framework of the Sentinel-3 Validation Team (S3 VT) meeting in 2013 [8]. It was particularly relevant in the context of Copernicus for distinguishing between in situ measurements that are managed by the Copernicus in situ component [9], which are also used for other purposes in their own right and the Cal/Val measurements managed by the Copernicus Space Component that are used for satellite-specific Calibration or Validation purposes. As a result, the term FRM was initially defined as \"the suite of independent tailored and fully characterised measurements that provide the maximum Return On Investment (ROI) for a satellite mission by delivering, to users, the required confidence in data products, in the form of independent validation results and satellite measurement uncertainty estimation, over the entire end-to-end duration of a satellite mission.\" [8].  
Figure 1 illustrates this principle: If we have no FRMs, then we cannot really use the mission for any quantitative purpose as we have no idea how accurate the data products are; if we have many FRMs, this is great scientifically (statistical significance, geographic/condition coverage, robust network, etc.) but incurs additional costs, with a reduced ROI. There is a balance between these two extremes to deliver a satellite mission with a known product quality that is \"fit for purpose\".  
In an attempt to create a more robust validation framework and encourage, where appropriate, teams to specifically tailor their observations to address the needs of satellites, as well as helping funding bodies distinguish and allocate resources, the European Space Agency (ESA) expanded the concept to other applications and technology domains and actively encouraged the creation and utilization of the label 'Fiducial Reference Measurement' in the international arena through bodies such as CEOS. In creating the FRM label and associated criteria (see below), the objective has been to create a distinction and special case of observations that are optimised to meet the needs of the satellite community.  
Note that the use of FRM labels for particular data sets does not imply that observations not classified as FRMs are of inferior quality. The FRM label is used where specific requirements (Section 3.2) are met for a specific satellite measurand/product and, in particular, where datasets are suitable for a defined class of satellite observations.  
These principles subsequently formed the basis for an ongoing series of projects funded by European organisations, European Union (EU), ESA, European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) to explore, establish and evidence FRM quality observations and in many cases, networks of sites, around the globe that adhere to the FRM principles for a wide range of observation and sensor types spanning surface temperature and reflectance, atmospheric composition, sea and ice level height, etc.  
Figure 1: A simple cost/benefit analysis of the FRM concept. The red line indicates the investment profile and cost over time. The cost is high during initial investment to create the infrastructure and capability, then drops for operations. The blue line indicates benefits to the satellite mission (measured as ‘confidence in product performance’) over time. The purple curve indicates a hypothetical optimum cost/benefit curve. FRM: fiducial reference measurement. Note it could be argued that in the longer term, the ROI actually continues to increase as more satellite users benefit.