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Global fine resolution mapping of ozone metrics through explainable machine learning

; ; ; ; ; ; ;

In
Abstracts & presentations / EGU General Assembly 2021, Seiten/Artikel-Nr: EGU21-7596, 1 Seite

Konferenz/Event:EGU General Assembly 2021 , online , vEGU21 , 2021-04-19 - 2021-04-30

ImpressumGöttingen : Copernicus Gesellschaft mbH

UmfangEGU21-7596, 1 Seite

Online
DOI: 10.5194/egusphere-egu21-7596

DOI: 10.18154/RWTH-CONV-246944
URL: https://publications.rwth-aachen.de/record/842789/files/842789.pdf
URL: https://egusphere.net/conferences/EGU21/index.html

Einrichtungen

  1. Lehrstuhl für Methoden der Modellbasierten Entwicklung in den Computergestützten Ingenieurwissenschaften (422410)
  2. Aachen Institute for Advanced Study in Computational Engineering Science (080003)


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Dokumenttyp
Abstract/Contribution to a conference proceedings

Format
online

Sprache
English

Interne Identnummern
RWTH-CONV-246944
Datensatz-ID: 842789

Beteiligte Länder
Germany

 GO

Creative Commons Attribution CC BY 4.0 ; OpenAccess
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080003
422410
 Record created 2022-03-14, last modified 2024-10-23
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