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Weather-based ML Datasets

Research datakeyboard_double_arrow_right Dataset 11 Jul 2023Publisher:Zenodo

Authors: Flora, Montgomery; Potvin, Corey; McGovern, Amy; Handler, Shawn; Chase, Randy;

doi: 10.5281/zenodo.8136709 , 10.5281/zenodo.8184201 , 10.5281/zenodo.8136708

Weather-based ML Datasets

- Summary
- Subjects
- Metrics

Abstract

Included are three datasets from Handler et al. (2020), Flora et al. (2021), and Chase et al. (2022. 2023). Handler et al. (2020) is a 1-hr HRRR-based nowcasting dataset predicting frozen road surfaces. Flora et al. (2021) is a 0-150 min severe weather dataset derived from the convection-allowing ensemble system known as the Warn-on-Forecast System. Lastly, the Chase et al. dataset is a lower resolution of the Storm EVent ImagRy (SEVIR; Veillette et al. 2020) dataset where the goal is to predict lightning.

Keywords

Severe weather; lightning; road conditions; satellite; convection-allowing; HRRR

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	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.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average