This Fundamental Climate Data Record (FDCR) ensemble product contains both recalibrated AVHRR/3 MetOp-A Radiance/Brightness Temperature data with associated metrologically traceable uncertainties in the FIDUCEO FCDR format. It also contains files containing an Ensemble dataset consisting of perturbations to the associated FIDUCEO FCDR radiances and brightness temperatures. By applying the 10 perturbations to the baseline FCDR radiances and brightness temperatures a user is able to generate 10 sets of new measurements whose variance capture the associated underlying uncertainty distributions contained in the Easy FCDR itself. The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project AVHRR FCDR improves on existing AVHRR level-1B: in the infrared the calibration has been improved with a measurement function approach such that the data is of better quality (noise has been reduced, outliers have been filtered) the metrologically traceable uncertainties have been derived together with their associated effects, cross-channel correlations and long-term correlation structures have now been calculated from the processed data and are being understood and used to improve data quality and consistency. For the Ensemble product the sensors have been calibrated against the Advanced Along-Track Scanning Radiometer (AATSR) sensor with additional corrections to calibration parameters which make the data better able to derive sea surface temperature estimates that are consistent with theInternational Comprehensive Ocean-Atmosphere Data Set (ICOADS) drifting buoy network. Because the Ensemble has been tuned for Sea Surface Temperature retrieval it should only be used over ocean scenes.

The BACI System State Vector datasets cover large regional sites in Europe, West, Eastern and Southern Africa in addition to smaller fast track sites in Denmark, Wytham Forest, Kruger National Park, Hainich, Viterbo, Romania, Slovenia, Ethiopia and Southern/Central/Northern Somalia. The BACI datasets address one of main complications in combining different Earth Observation (EO) data streams is a requirement of common time and space resolution. These data are gap free time series, of EO data across optical (reflectance, albedo), passive microwave (LST) and active microwave (backscatter) domains. This collection contains optimally smoothed and filtered time series of reflectance, albedo and backscatter datasets, starting in 2000 and running to the present, as the core SSV output. Crucially, the SSV data is provided with consistent uncertainties, which is key for use in downstream quantitative modelling and change detection applications, particularly to help attribute and explain detected change. Changes in the Earth’s surface can have very different properties and so can influence very different domains of the electromagnetic spectrum. As a result these datasets are particularly useful for trying to detect changes in ecosystem structure and function, a potentially vital application for satellite monitoring of the Earth system.