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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Claim

Deep learning models for generation of precipitation maps based on NWP Data

Research datakeyboard_double_arrow_right Dataset 24 Oct 2022 English Publisher:Zenodo
Authors: Rojas-Campos, Adrian;

doi: 10.5281/zenodo.7244319 , 10.5281/zenodo.7244318

Deep learning models for generation of precipitation maps based on NWP Data

Abstract

Numpy arrays used in the paper "Deep learning models for generation of precipitation maps based on NWP". trn = training set vld = validation set tst = test set x = COSMO-DE-EPS ensemble statistics y = high definition radar precipitation t = time c = COSMO-DE-EPS precipitation prediction

Related Organizations
Keywords

Precipitation, COSMO, NWP, Deep Learning, Radar,

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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