The Fluorescence Explorer (FLEX) is one of ESA’s 8th Earth Explorer mission candidates, which has been recently initiated for feasibility (Phase A) study as part of the ESA Living Planet programme. Together with the second candidate mission CarbonSat, these missions will undergo a preliminary concept review and a preliminary requirements review. FLEX has reached a status, where the requirements have been consolidated such that the instrument and satellite concepts could be formulated. The selection of the instrument concepts were derived from detailed trade-offs, which had the aim to meet the instrument requirements while staying in line with the allocated resources for the mission. Although the instrument concepts are not yet fully frozen with respect to all aspects, we will report about the most promising configurations and the expected performance as compared to the scientific requirements.
The recently launched SENTINEL-3 mission measures sea surface topography, sea/land surface temperature, and ocean/land surface colour with high accuracy. The mission provides data continuity with the ENVISAT mission through acquisitions by multiple sensing instruments. Two of them, OLCI (Ocean and Land Colour Imager) and SLSTR (Sea and Land Surface Temperature Radiometer) are optical sensors designed to provide continuity with Envisat's MERIS and AATSR instruments. During the commissioning, in-orbit calibration and validation activities are conducted. Instruments are in-flight calibrated and characterized primarily using on-board devices which include diffusers and black body. Afterward, vicarious calibration methods are used in order to validate the OLCI and SLSTR radiometry for the reflective bands. The calibration can be checked over dedicated natural targets such as Rayleigh scattering, sunglint, desert sites, Antarctica, and tentatively deep convective clouds. Tools have been developed and/or adapted (S3ETRAC, MUSCLE) to extract and process Sentinel-3 data. Based on these matchups, it is possible to provide an accurate checking of many radiometric aspects such as the absolute and interband calibrations, the trending correction, the calibration consistency within the field-of-view, and more generally this will provide an evaluation of the radiometric consistency for various type of targets. Another important aspect will be the checking of cross-calibration between many other instruments such as MERIS and AATSR (bridge between ENVISAT and Sentinel-3), MODIS (bridge to the GSICS radiometric standard), as well as Sentinel-2 (bridge between Sentinel missions). The early results, based on the available OLCI and SLSTR data, will be presented and discussed.
A new permanently instrumented radiometric calibration site for high/medium resolution imaging satellite sensors is currently under development, focussing on the visible and near infra-red parts of the spectrum. The site will become a European contribution to the Committee on Earth Observation Satellites (CEOS) initiative RadCalNet (Radiometric Calibration Network). The exact location of the permanent monitoring instrumentation will be defined following the initial site characterisation. The new ESA/CNES RadCalNet site will have a robust uncertainty budget and its data fully SI traceable through detailed characterisation and calibration by NPL of the instruments and artefacts to be used on the site. This includes a CIMEL sun photometer (the permanent instrumentation) an ASD FieldSpec spectroradiometer, Gonio Radiometric Spectrometer System (GRASS), and reference reflectance standards.
The ESA EarthCARE (Earth Clouds Aerosols and Radiation Explorer) mission includes the BBR (Broad-Band
Radiometer), the instrument responsible to provide measurements of broadband radiances over the along-track
satellite path. The BBR footprint will be geolocated in space and time with the passive sensor, MSI (Multi-Spectral Imager), and the active sensors, ATLID (ATmospheric LIDar) and CPR (Cloud Profiler Radar) onboard the same platform.
The role of the BBR was defined to provide the boundary condition for top of atmosphere flux densities.
Thus, the radiance to flux conversion is the main objective for the BBR retrieval algorithms. This conversion
has been so far carried out by using specific angular distribution models (ADMs). In this process, every radiance
is classified in a unique scene bin of observations characterized by a similar anisotropic behaviour. Each of these
scene bins is defined by a range of values distinguishable by the MSI. But the MSI can only extract vertically
integrated retrievals. Therefore, in multi-layer cloud configurations, scene identification (ID) by means of the
MSI retrievals will not distinguish the 3-D structure of the real scenes. Thus, these scenes will most probably be
wrongly identified. But, since active sensors are present on the same satellite platform, it would be possible to
use their observations to contribute to the BBR scene ID.
This work shows a preliminary simulation approach to demonstrate the advantages of this methodology by
applying it to multi-layer clouds. The clouds have been built with a stochastic cloud generator model, and the
radiative transfer simulations have been carried out with the EarthCARE Simulator, a Monte-Carlo code capable
to reproduce the observations of the different mission instruments taking into account the specific characteristics
of each sensor.