Articles | Volume 7, issue 3
https://doi.org/10.5194/amt-7-823-2014
https://doi.org/10.5194/amt-7-823-2014
Research article
 | 
31 Mar 2014
Research article |  | 31 Mar 2014

Determination of circumsolar radiation from Meteosat Second Generation

B. Reinhardt, R. Buras, L. Bugliaro, S. Wilbert, and B. Mayer

Related authors

Machine learning for improvement of upper tropospheric relative humidity in ERA5 weather model data
Ziming Wang, Luca Bugliaro, Klaus Gierens, Michaela I. Hegglin, Susanne Rohs, Andreas Petzold, Stefan Kaufmann, and Christiane Voigt
EGUsphere, https://doi.org/10.5194/egusphere-2024-2012,https://doi.org/10.5194/egusphere-2024-2012, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Bayesian cloud-top phase determination for Meteosat Second Generation
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024,https://doi.org/10.5194/amt-17-4015-2024, 2024
Short summary
Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations
Ziming Wang, Husi Letu, Huazhe Shang, and Luca Bugliaro
Atmos. Chem. Phys., 24, 7559–7574, https://doi.org/10.5194/acp-24-7559-2024,https://doi.org/10.5194/acp-24-7559-2024, 2024
Short summary
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024,https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Development of a HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
EGUsphere, https://doi.org/10.5194/egusphere-2024-167,https://doi.org/10.5194/egusphere-2024-167, 2024
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024,https://doi.org/10.5194/amt-17-4183-2024, 2024
Short summary
Bayesian cloud-top phase determination for Meteosat Second Generation
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024,https://doi.org/10.5194/amt-17-4015-2024, 2024
Short summary
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024,https://doi.org/10.5194/amt-17-3863-2024, 2024
Short summary
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024,https://doi.org/10.5194/amt-17-3679-2024, 2024
Short summary
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024,https://doi.org/10.5194/amt-17-3583-2024, 2024
Short summary

Cited articles

Baum, B., Heymsfield, A., Yang, P., and Bedka, S.: Bulk scattering models for the remote sensing of ice clouds, Part 1: Microphysical data and models, J. Appl. Meteorol., 44, 1885–1895, 2005a.
Baum, B., Yang, P., Heymsfield, A., Platnick, S., King, M. D., Hu, Y. X., and Bedka, S.: Bulk scattering models for the remote sensing of ice clouds, Part 2: Narrowband models, J. Appl. Meteorol., 44, 1896–1911, 2005b.
Baum, B. A., Yang, P., Heymsfield, A. J., Schmitt, C. G., Xie, Y., Bansemer, A., Hu, Y.-X., and Zhang, Z.: Improvements in shortwave bulk scattering and absorption models for the remote sensing of ice clouds, J. Appl. Meteorol. Climatol., 50, 1037–1056, https://doi.org/10.1175/2010JAMC2608.1, 2011.
Bugliaro, L., Zinner, T., Keil, C., Mayer, B., Hollmann, R., Reuter, M., and Thomas, W.: Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI, Atmos. Chem. Phys., 11, 5603–5624, https://doi.org/10.5194/acp-11-5603-2011, 2011.
Bugliaro, L., Mannstein, H., and Kox, S.: Ice cloud properties from space, in: Atmospheric Physics, edited by: Schumann, U., 417–432, Springer-Verlag Berlin Heidelberg, 2012.
Download