2021
DOI: 10.5194/amt-14-3371-2021
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Evaluation of Visible Infrared Imaging Radiometer Suite (VIIRS) neural network cloud detection against current operational cloud masks

Abstract: Abstract. Cloud properties are critical to our understanding of weather and climate variability, but their estimation from satellite imagers is a nontrivial task. In this work, we aim to improve cloud detection, which is the most fundamental cloud property. We use a neural network applied to Visible Infrared Imaging Radiometer Suite (VIIRS) measurements to determine whether an imager pixel is cloudy or cloud-free. The neural network is trained and evaluated using 4 years (2016–2019) of coincident measurements … Show more

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Cited by 8 publications
(1 citation statement)
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“…Using an ANN, Minnis et al (2016) retrieved thick ice cloud COD at night and Håkansson et al (2018) accurately determined CTP and CTH. Stengel et al (2020), Wang et al (2020), and White et al (2021) use ANNs for cloud detection and phase discrimination. These and other examples demonstrate that ANNs have significant potential for improving the characterization of global cloudiness.…”
Section: Artificial Neural Networkmentioning
confidence: 99%
“…Using an ANN, Minnis et al (2016) retrieved thick ice cloud COD at night and Håkansson et al (2018) accurately determined CTP and CTH. Stengel et al (2020), Wang et al (2020), and White et al (2021) use ANNs for cloud detection and phase discrimination. These and other examples demonstrate that ANNs have significant potential for improving the characterization of global cloudiness.…”
Section: Artificial Neural Networkmentioning
confidence: 99%