Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data ; volume:14 ; number:4 ; year:2021 ; pages:2699-2716 ; extent:18
Atmospheric measurement techniques ; 14, Heft 4 (2021), 2699-2716 (gesamt 18)

Creator: Lee, Yoonjin
Kummerow, Christian D.
Ebert-Uphoff, Imme

DOI: 10.5194/amt-14-2699-2021

URN: urn:nbn:de:101:1-2021041505282896478902

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:53 AM CEST

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Lee, Yoonjin
Kummerow, Christian D.
Ebert-Uphoff, Imme

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Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data

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Other Objects (12)

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Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager

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Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager

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Detection of deterministic and probabilistic convection initiation using Himawari-8 Advanced Himawari Imager data

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