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Earth System Data Exploration Andere Formen:ESDE

CoordinatorSchultz, Martin
Grant period2017-07-01 -
Funding bodyForschungszentrum Jülich GmbH
IdentifierG:(DE-Juel-1)ESDE

Note: EN: The ESDE group explores the use of state-of-the-art deep learning methods for analysing and forecasting atmospheric data with a focus on air quality and weather and a dedication to open data and open science. Our ability to analyse air quality, weather and climate data is fundamentally important to save lives, for example during extreme weather events, to protect nature and biodiversity and to create and preserve economic value through science-based decision making on mitigation and protection measures. Modern machine learning can play an important role to complement or even substitute traditional simulation models and to extract more information from the huge amount of environmental monitoring data that has become available in recent years. We see the handling, processing and distribution of such data with modern high-performance computing technology abiding to open, federated and FAIR principles as a necessary requirement for building sustainable tools for the analysis of the environment, but also as an interesting research topic in itself.
 

Recent Publications

All known publications ...
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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;
BERT Bi-modal self-supervised learning for crop classification using Sentinel-2 and Planetscope
Frontiers in remote sensing 6, 1555887 () [10.3389/frsen.2025.1555887] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings/Contribution to a book  ;  ;  ;  ;  ;
Applying AtmoRep for Diverse Weather Applications
NIC Symposium 2025 Proceedings
The 12th John von Neumann Institute for Computing (NIC) Symposium, JülichJülich, Germany, 6 Mar 2025 - 7 Mar 20252025-03-062025-03-07 52, 301- 311 () [10.34734/FZJ-2025-02398] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Poster (After Call)  ;  ;  ;  ;  ;
Easier Access to ESM Data: Implementation at Jülich Supercomputing Centre
EGU General Assembly, EGU25, ViennaVienna, Austria, 28 Apr 2025 - 2 May 20252025-04-282025-05-02 [10.5194/egusphere-egu25-19091] OpenAccess  Download fulltext Files  Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;  ;  ;
Mantik: A Workflow Platform for the Development of Artificial Intelligence on High-Performance Computing Infrastructures
The journal of open source software 9(98), 6136 () [10.21105/joss.06136] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Poster (After Call)  ;  ;  ;
Downscaling with the foundation model AtmoRep
European Geosciences Union General Assembly 2024, EGU 2024, ViennaVienna, Austria, 14 Apr 2024 - 19 Apr 20242024-04-142024-04-19 [10.5194/egusphere-egu24-18331] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Poster (Other)  ;  ;  ;  ;  ;  ;
A Benchmark Dataset for Meteorological Downscaling
International Conference on Learning Representations, ICLR 2024, ViennaVienna, Austria, 7 May 2024 - 11 May 20242024-05-072024-05-11 [10.34734/FZJ-2024-07390] OpenAccess  Download fulltext Files  Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Talk (non-conference) (Plenary/Keynote)  ;  ;  ;
AtmoRep - Towards a Foundation Model for the Atmosphere
Artificial Intelligence for Weather and Climate Autumn School 2024, AIWCAS 2024, TrentoTrento, Italy, 28 Oct 2024 - 31 Oct 20242024-10-282024-10-31  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Conference Presentation (Other)  ;  ;  ;  ;  ;  ;
DownscaleBench: A benchmark dataset for statisticaldownscaling of meteorological fields
Workshop on Large-Scale Deep Learning for the Earth System, LSDL4ES 2024, BonnBonn, Germany, 29 Aug 2024 - 30 Aug 20242024-08-292024-08-30 [10.34734/FZJ-2024-07387] OpenAccess  Download fulltext Files  Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings  ;  ;  ;  ;  ;  ;
A Benchmark Dataset for Meteorological Downscaling
International Conference on Learning Representations, ICLR 2024, ViennaVienna, Austria, 7 May 2024 - 11 May 20242024-05-072024-05-11 N/A () [10.34734/FZJ-2024-07378] OpenAccess  Download fulltext Files  Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;
Exascale Computing and Data Handling: Challenges and Opportunities for Weather and Climate Prediction
Bulletin of the American Meteorological Society 105(12), E2385–E2404 () [10.1175/BAMS-D-23-0220.1]  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

All known publications ...
Download: BibTeX | EndNote XML,  Text | RIS | 

 Datensatz erzeugt am 2022-06-07, letzte Änderung am 2022-06-07
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