- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
Comparing storm resolving models and climates via unsupervised machine learning ; volume:13 ; number:1 ; day:15 ; month:12 ; year:2023 ; pages:1-15 ; date:12.2023
Scientific reports ; 13, Heft 1 (15.12.2023), 1-15, 12.2023
- Creator
-
Mooers, Griffin
Pritchard, Mike
Beucler, Tom
Srivastava, Prakhar
Mangipudi, Harshini
Peng, Liran
Gentine, Pierre
Mandt, Stephan
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-023-49455-w
- URN
-
urn:nbn:de:101:1-2024030107452962762059
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:55 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Mooers, Griffin
- Pritchard, Mike
- Beucler, Tom
- Srivastava, Prakhar
- Mangipudi, Harshini
- Peng, Liran
- Gentine, Pierre
- Mandt, Stephan
- SpringerLink (Online service)
Other Objects (12)
Author Correction: Comparing storm resolving models and climates via unsupervised machine learning
Climates
Comparing weak- and unsupervised methods for resonant anomaly detection
Comparing forests across climates and biomes : qualitative assessments, reference forests and regional intercomparisons
Impact of Precipitation Mass Sinks on Midlatitude Storms over a Wide Range of Climates
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Storm identification for high-energy wave climates as a tool to improve long-term analysis
Organizational Climates and Age
Evaluation of Supercell Storm Triggering Factors Based on a Cloud Resolving Model Simulation
Resolving power
Impact of precipitation mass sinks on midlatitude storms in idealized simulations across a wide range of climates
Author Correction: Comparing storm resolving models and climates via unsupervised machine learning
Climates
Comparing weak- and unsupervised methods for resonant anomaly detection
Comparing forests across climates and biomes : qualitative assessments, reference forests and regional intercomparisons
Impact of Precipitation Mass Sinks on Midlatitude Storms over a Wide Range of Climates
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Storm identification for high-energy wave climates as a tool to improve long-term analysis
Organizational Climates and Age
Evaluation of Supercell Storm Triggering Factors Based on a Cloud Resolving Model Simulation
Resolving power
Impact of precipitation mass sinks on midlatitude storms in idealized simulations across a wide range of climates
Author Correction: Comparing storm resolving models and climates via unsupervised machine learning
Climates
Comparing weak- and unsupervised methods for resonant anomaly detection
Comparing forests across climates and biomes : qualitative assessments, reference forests and regional intercomparisons
Impact of Precipitation Mass Sinks on Midlatitude Storms over a Wide Range of Climates
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Storm identification for high-energy wave climates as a tool to improve long-term analysis
Organizational Climates and Age
Evaluation of Supercell Storm Triggering Factors Based on a Cloud Resolving Model Simulation
Resolving power