2022
DOI: 10.1016/j.atmosres.2021.105920
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Evaluation of ALADIN NWP model forecasts by IR10.8 μm and WV06.2 μm brightness temperatures measured by the geostationary satellite Meteosat Second Generation

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Cited by 5 publications
(2 citation statements)
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“…This channel is instrumental in deriving Cloud Motion Vectors (CMVs) [22] by tracking cloud feature movements between consecutive images, which are correlated to wind speed and direction at cloud layer altitudes. Unlike visible bands, the IR 10.8 μm band enables continuous observation both during the day and night, essential for ongoing wind speed forecasting, and is also less impacted by atmospheric scattering and absorption, ensuring stable and consistent measurements beneficial for computer vision techniques [21,22]. Figure 1 shows an example of two satellite images from the database with 2 h difference.…”
Section: Datamentioning
confidence: 99%
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“…This channel is instrumental in deriving Cloud Motion Vectors (CMVs) [22] by tracking cloud feature movements between consecutive images, which are correlated to wind speed and direction at cloud layer altitudes. Unlike visible bands, the IR 10.8 μm band enables continuous observation both during the day and night, essential for ongoing wind speed forecasting, and is also less impacted by atmospheric scattering and absorption, ensuring stable and consistent measurements beneficial for computer vision techniques [21,22]. Figure 1 shows an example of two satellite images from the database with 2 h difference.…”
Section: Datamentioning
confidence: 99%
“…The satellite imagery was collected from the '0-degree service', a key mission of Meteosat Second Generation, which furnishes High Rate SEVIRI image data across 12 spectral bands from 01-01-2022 at 00:00 UTC until 31-12-2022 at 23:30 UTC at 30-min intervals, leading to 17,520 images. The SEVIRI instrument facilitates a thorough image scan of the Earth at 15-minute intervals, presenting a high-frequency data acquisition, fundamental in tracking the evolution of cloud structures and patterns in near-real-time, which opens opportunity cloud tracking and, successively, short-term wind speed and direction forecasting [21].…”
Section: Datamentioning
confidence: 99%