Satellite-Derived 3D Wind Retrievals: Techniques, Applications and Model Impact
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 249
Special Issue Editors
Interests: polar wind retrieval; satellite-derived atmospheric motion vectors; MODIS data assimilation
Interests: atmospheric motion vectors; satellite wind retrievals; wind lidar mission
Special Issue Information
Dear Colleagues,
For more than two decades, atmospheric motion vectors (AMVs) have been derived by tracking cloud features primarily using visible and infrared (IR) imaging instruments aboard geostationary and polar-orbiting satellites. These 2D AMVs provide wind information at cloud-top, representing a single vertical level at a given geographic location. They are widely used in numerical weather prediction (NWP) models and in operational weather forecasting.
In recent years, the exploration of 3D winds has advanced using hyperspectral IR observations from geostationary and polar-orbiting satellites. Employing radiative transfer models, IR radiances are converted to humidity fields on pressure surfaces, producing trackable features over time. This approach enables the derivation of 3D winds that complement traditional 2D AMVs, as they are retrieved in clear skies and above clouds using methods that incorporate optical flow and deep-learning techniques.
This Special Issue of Atmosphere invites contributions that advance 3D wind derivation, including improvements to existing algorithms, quality control, error characterization, validation and assessments of impact on weather prediction models. Contributions demonstrating innovative meteorological applications of 3D winds are also encouraged, particularly those that enhance understanding of atmospheric dynamics and improve forecasting and nowcasting decision-making.
Dr. David Santek
Dr. Régis Borde
Guest Editors
Manuscript Submission Information
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Keywords
- 3D winds
- atmospheric motion vectors
- deep learning
- optical flow
- hyperspectral ir retrievals
- microwave retrievals
- meteorological applications
- numerical weather prediction impacts
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