Interpretable Deep Learning for Spatial Analysis of Severe Hailstorms: Storm and Analysis Data
d898000
| DOI: 10.5065/6CJA-B154
Abstract:
This repository contains the simulation and analysis data for the paper "Interpretable Deep Learning for Spatial Analysis of Severe Hailstorms." This dataset contains simulated storms extracted from the NCAR Convection-Allowing Ensemble, saved as 96 km by 96 km storm patches containing extensive information about each storm. The dataset also contains saved machine learning and deep learning models used to analyze the storm data along with diagnostic files containing verification and variable importance scores.
Temporal Range:
2016-05-03 00:00:00 to 2016-06-04 12:00:00
Variables:
| Cloud Base Height | Cloud Top Height | Upper Level Winds |
Data Types:
Grid
Data Contributors:
UCAR/NCAR/CISL/TDD
Technology Development Division, Computational and Information Systems Laboratory, National Center for Atmospheric Research, University Corporation for Atmospheric Research
Total Volume:
42.68 GB
(Entire dataset)
Volume details by dataset product
Volume details by dataset product
NCAR_Ensemble_Storm_Patches: 29.83 GB
Spatial_Storm_Results_20171220: 12.85 GB
Data Formats:
HDF5
Metadata Record:
Data License:
This work is licensed under a Creative Commons Attribution 4.0 International License.
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