Inner convective system cloud-top wind estimation using multichannel infrared satellite images

• Published in: International journal of remote sensing Vol. 35; no. 2; pp. 651 - 670
• Main Authors: Negri, R.G., Machado, L.A.T., Borde, R.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 17.01.2014
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Teledetection and vegetation maps; United Kingdom; Europe; Western Europe; models; processes; Estimation; Prediction; thermodynamics; Convective cloud; Satellite observation; Extract; Information; Knowledge; Modeling; System; convection; Weather; Temperature difference; dynamics; depth; brightness temperature; winds; techniques; Structure; Link; climate change; high resolution
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2013.871391

Knowledge of deep convective system cloud processes and dynamic structures is a key feature in climate change and nowcasting. However, the horizontal inner structures at the cloud tops of deep convective systems are not well understood due to lack of measurements and the complex processes linked to dynamics and thermodynamics. This study describes a new technique to extract inner cloud-top dynamics using brightness temperature differences. This new information could help clarify ring and U or V shape structures in deep convection and be potentially useful in nowcasting applications. Indeed, the use of high-resolution numerical weather prediction (NWP) models, which now include explicit microphysical processes, requires data assimilation at very high resolution as well. A standard atmospheric motion vector tracking algorithm was applied to a pair of images composed of combinations of Spinning Enhanced Visible and Infra-red Imager (SEVIRI) channels. Several ranges of channel differences were used in the tracking process, such intervals being expected to correspond to specific cloud-top microphysics structures. Various consistent flows of motion vectors with different speeds and/or directions were extracted at the same location depending on the channel difference intervals used. These differences in speed/direction can illustrate local wind shear situations, or correspond to expansion or dissipation of cloud regions that contain high concentrations of specific kinds of ice crystals or droplets. The results from this technique were compared to models and ancillary data to advance our discussion and inter-comparisons. Also, the technique proposed here was evaluated using SEVIRI images simulated by the radiative transfer model RTTOV with input data from the UK Met Office Unified Model. A future application of the new data is exemplified by showing the relationship between wind divergence calculated from the new atmospheric motion vector and convective cloud top intensification.