Weather Type Reconstruction using Machine Learning Approaches

Pfister, Lucas Martin (2024). Weather Type Reconstruction using Machine Learning Approaches. [Software & Other Digital Items]

	Text (Readme file) README.txt - Additional Metadata Available under License Creative Commons: Attribution (CC-BY). Download (882B)
	Text (CAP9 weather type reconstructions (comma separated value-file)) CAP9_reconstructions_1728-2020.csv Available under License Creative Commons: Attribution (CC-BY). Download (2MB)
	Other (Code for weather type reconstruction (Jupyter notebook)) WTrec_reconstruction.ipynb Available under License Creative Commons: Attribution (CC-BY). Download (66kB)
	Text (Dummy input data for code (comma separated value-file)) WTrec_DummyTrainingData.csv Available under License Creative Commons: Attribution (CC-BY). Download (1MB)
	Archive (Collection of pre-trained Keras neural network-models) NN_models.zip Available under License Creative Commons: Attribution (CC-BY). Download (1MB)

This database contains the code and data used for weather type reconstruction in the paper by Pfister et al. (2024).

Item Type:	Software & Other Digital Items
Division/Institute:	10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
UniBE Contributor:	Pfister, Lucas Martin
Subjects:	500 Science > 550 Earth sciences & geology
Publisher:	Institute of Geography and Oeschger Centre for Climate Change Research, University of Bern, Switzerland
Projects:	[UNSPECIFIED] WeaR: Daily Weather Reconstructions to Study Decadal Climate Swings
Language:	English
Submitter:	Lucas Martin Pfister
Date Deposited:	15 Apr 2024 13:25
Last Modified:	15 Apr 2024 13:25
Uncontrolled Keywords:	Weather type, weather reconstruction, machine learning, CAP9, historical climatology
BORIS DOI:	10.48350/195666
URI:	https://boris.unibe.ch/id/eprint/195666

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