Operational cloud products from TROPOMI on Sentinel-5 Precursor and prospects for Sentinel-4 on MTG-S

Abstract

Accurate trace gas and aerosol retrieval for satellite missions focused on atmospheric composition requires a precise knowledge of cloud properties in the UV/VIS/NIR spectral region. Such missions dedicated to atmospheric composition and air quality monitoring include the operational GOME-2 instruments on-board MetOp-A/B, the recently launched TROPOMI instrument on Sentinel-5P and the upcoming UVN/Sentinel-4 instruments on MTG-S and the UVNS/Sentinel-5 instruments on EPS-SG. Furthermore, cloud information from UV/VIS/NIR spectrometers, such as S5P, S4, and S5, is complementary to the information retrieved using sensors operating in the thermal IR. In this work we present the operational cloud products from the Sentinel-5 Precursor mission and prospects for Sentinel-4. These operational cloud products are generated using the latest version of the OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) algorithms which have been successfully applied to the operational processing of GOME/ERS-2 and GOME-2 MetOp-A/B data. The ROCINN algorithm retrieves cloud height, cloud optical thickness and cloud albedo from NIR measurements in and around the oxygen A-band (~760nm) taking as input the cloud fraction computed with the OCRA algorithm based on a broad-band UV/VIS color space approach. Two approaches which treat the clouds differently are implemented to the ROCINN algorithm. The first approach called Clouds-as-Reflecting-Boundaries (CRB) assume that the cloud is a reflecting surface whereas the second and more realistic model called Clouds-as-Layers (CAL) represents the cloud as a homogeneous cluster of scattering spherical particles.