Marc Bouvet

Measure and exploitation of multisensor and multiwavelength synergy for remote sensing: 2. Application to the retrieval of atmospheric temperature and water vapor from MetOp

[1] In the companion paper, classical information content (IC) analysis was used to measure the potential synergy between the microwave (MW) and infrared (IR) observations from Atmospheric Microwave Sounding Unit-A, Microwave Humidity Sounder, and Improved Atmospheric Sounding in the Infrared instruments, used to retrieve the atmospheric profiles of temperature and water vapor over ocean, under clear-sky conditions. Some limitations of IC were pointed out that questioned the reliability of this technique for synergy characterization. The goal of this second paper is to develop a methodology to measure realistic potential synergies and to construct retrieval methods able to exploit them. Three retrieval methods are considered: the k nearest neighbors, the linear regression, and the neural networks (NN). These statistical retrieval schemes are tested on an application involving IR and MW synergy. Only clear-sky, near-nadir radiances over ocean are considered. The IR/MW synergy is expected to be stronger in cloudy cases, but it will be shown that it can also be observed in clear situations. The inversion algorithms are calibrated and tested with simulated observations, without any loss of generality, using similar theoretical assumption (same radiative transfer model, observational noise, and a priori information) in order to truly compare the IC and the direct statistical retrieval approaches. Multivariate and nonlinear methods such as the NN approach show that there is a strong potential for synergy. Synergy measurement tools such as the method proposed in this study should be considered in the future for the definition of new missions: The instrument characteristics should be determined not independently, sensor by sensor, but taking into account all the instruments together as a whole observing system.

Improvement of broadband radiance to flux conversion by using the synergy between active and passive remote sensing instruments

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.

In-Orbit Radiometric Calibration and Stability Monitoring of the PROBA-V Instrument

Since its launch in May 2013, the in-orbit radiometric performance of PROBA-V has been continuously monitored. Due to the absence of on-board calibration devices, in-flight performance monitoring and calibration relies fully on vicarious calibration methods. In this paper, the multiple vicarious calibration techniques used to verify radiometric accuracy and to perform calibration parameter updates are discussed. Details are given of the radiometric calibration activities during both the commissioning and operational phase. The stability of the instrument in terms of overall radiometry and dark current is analyzed. Results of an independent comparison against MERIS and SPOT VEGETATION-2 are presented. Finally, an outlook is provided of the on-going activities aimed at improving both data consistency over time and within-scene uniformity.

Results from the radiometric validation of Sentinel-3 optical sensors using natural targets.

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 Envisats 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.