FIDUCEO will create new climate datasets from Earth Observations with rigorous treatment of uncertainty informed by the discipline of metrology. This responds to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. Our approach is (1) to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and [Thematic] Climate Data Records (CDRs) that are widely applicable and metrologically rigorous and (2) to build new FCDRs and CDRs, making them easily accessible, with complete and traceable estimates of stability and uncertainty. New tools for metrologically rigorous analysis will be created, including tools for stability analysis and ensemble creation. The chosen FCDRs have a length relevant to climate (>20 years) and can support numerous CDRs. Selected CDRs will be generated that illustrate new capabilities (e.g. equi-probable ensembles) as well as the benefits from use of the new FCDRs, such as improved stability and traceable uncertainties. Specifically, we will create: harmonised radiances (FCDRs) for the following sensors: AVHRR, HIRS, AMSU-B/MHS and MVIRI; and geophysical datasets, with uncertainties, for: ensemble sea and lake surface temperature, tropospheric humidity, aerosol optical depth and surface albedo. All data, software tools and methods will be freely and openly accessible and will be disseminated in a variety of forms including e-learning modules. All data will be available in both a common “easy” format (for general users) and community-standard formats. FIDUCEO will liaise explicitly with relevant programmes (Copernicus Climate Change Service, NOAA Climate Data Records programme, SCOPE-CM, re-analysis initiatives etc), and hold with two workshops for dialogue with the user community. By both creating valuable datasets and defining and applying rigorous new metrological methods, FIDUCEO aims for a broad and lasting impact in the field of climate data from space.

There is a recognised need for establishing sound methods for the characterisation of satellite-based Earth Observation (EO) data by surface-based and sub-orbital measurement platforms - spanning Atmosphere, Ocean and Land observations and the entire radiance spectrum. 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 through mismatches in sampling location and time and the distinct measurement footprints to enable a complete mapping of the reference measurements onto EO measurements. 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. 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.