Articles | Volume 21, issue 16
https://doi.org/10.5194/acp-21-12273-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-12273-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Understanding the model representation of clouds based on visible and infrared satellite observations
Stefan Geiss
CORRESPONDING AUTHOR
Hans Ertel Centre for Weather Research, Ludwig-Maximilians-Universität, Munich, Germany
Leonhard Scheck
Hans Ertel Centre for Weather Research, Ludwig-Maximilians-Universität, Munich, Germany
Deutscher Wetterdienst, Offenbach, Germany
Alberto de Lozar
Deutscher Wetterdienst, Offenbach, Germany
Martin Weissmann
Institut für Meteorologie und Geophysik, Universität Wien, Vienna, Austria
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Cited
13 citations as recorded by crossref.
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- Progress, challenges, and future steps in data assimilation for convection‐permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021 G. Hu et al. 10.1002/asl.1130
- Evaluating Latent-Heat-Nudging Schemes and Radar forward Operator Settings for a Convective Summer Period over Germany Using the ICON-KENDA System Y. Zeng et al. 10.3390/rs14215295
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- A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images F. Baur et al. 10.5194/amt-16-5305-2023
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- Impact of tropical convective conditions on solar irradiance forecasting based on cloud motion vectors A. Roy et al. 10.1088/1748-9326/ac94e6
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12 citations as recorded by crossref.
- Evaluating the Impact of Planetary Boundary Layer, Land Surface Model, and Microphysics Parameterization Schemes on Simulated GOES-16 Water Vapor Brightness Temperatures S. Griffin & J. Otkin 10.3390/atmos13030366
- Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation M. Shams Eddin & J. Gall 10.5194/gmd-17-2987-2024
- Exploring the characteristics of Fengyun-4A Advanced Geostationary Radiation Imager (AGRI) visible reflectance using the China Meteorological Administration Mesoscale (CMA-MESO) forecasts and its implications for data assimilation Y. Zhou et al. 10.5194/amt-17-6659-2024
- Progress, challenges, and future steps in data assimilation for convection‐permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021 G. Hu et al. 10.1002/asl.1130
- Evaluating Latent-Heat-Nudging Schemes and Radar forward Operator Settings for a Convective Summer Period over Germany Using the ICON-KENDA System Y. Zeng et al. 10.3390/rs14215295
- Sensitivity of cloud-phase distribution to cloud microphysics and thermodynamics in simulated deep convective clouds and SEVIRI retrievals C. Han et al. 10.5194/acp-23-14077-2023
- Inspecting the sensitivity of radiation schemes for numerical modelling of cloudburst events in the North West Himalayan region S. Biswas & C. Singh 10.1007/s40808-025-02494-w
- Correcting Forecast Time Biases in CMA-MESO Using Himawari-9 and Time-Shift Method X. Song et al. 10.3390/rs17040617
- Aerosol–cloud–radiation interaction during Saharan dust episodes: the dusty cirrus puzzle A. Seifert et al. 10.5194/acp-23-6409-2023
- A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images F. Baur et al. 10.5194/amt-16-5305-2023
- Partial analysis increments as diagnostic for LETKF data assimilation systems T. Diefenbach et al. 10.1002/qj.4419
- Impact of tropical convective conditions on solar irradiance forecasting based on cloud motion vectors A. Roy et al. 10.1088/1748-9326/ac94e6
1 citations as recorded by crossref.
Latest update: 30 Jun 2025
Short summary
This study demonstrates the benefits of using both visible and infrared satellite channels to evaluate clouds in numerical weather prediction models. Combining these highly resolved observations provides significantly more and complementary information than using only infrared observations. The visible observations are particularly sensitive to subgrid water clouds, which are not well constrained by other observations.
This study demonstrates the benefits of using both visible and infrared satellite channels to...
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