Filters

2021 - 20232

More filters

2022 - 20242
Reset filters

Settings

Author: Bley, Sebastian × Subject: SEVIRI ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples
    (Katlenburg-Lindau : European Geosciences Union, 2021) Deneke, Hartwig; Barrientos-Velasco, Carola; Bley, Sebastian; Hünerbein, Anja; Lenk, Stephan; Macke, Andreas; Meirink, Jan Fokke; Schroedter-Homscheidt, Marion; Senf, Fabian; Wang, Ping; Werner, Frank; Witthuhn, Jonas
    The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1ĝ€¯km2 compared to the standard 3×3ĝ€¯km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6ĝ€¯μm, 0.8ĝ€¯μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6ĝ€¯μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6ĝ€¯μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.
  • Thumbnail Image
    Item
    Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
    (Katlenburg-Lindau : Copernicus, 2023) Hünerbein, Anja; Bley, Sebastian; Horn, Stefan; Deneke, Hartwig; Walther, Andi
    The EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol-cloud-radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150km swath and a pixel sampling at 500m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.