Dataset Details
HRRR ML Storm Mode Analyses
Storms extracted from the HRRR and associated modes predicted by machine learning. The dataset consists of storms extracted from the operational HRRR runs with the Hagelslag package. Multiple storm mode machine learning models are applied to the storms to predict the mode (supercell, QLCS, or disorganized). The data are available in an AWS cloud bucket to support interactive visualization and analysis but could be used for other applications.
Data Type
Numerical model output
Dataset Size
445.3 GB and growing
File Type
csv, netCDF, geojson
Time Range (YYYY-MM-DD)
2022-04-03 to present
Geographic Scope
Continental U.S.
Spatial Resolution
3 km grid spacing
Time Resolution
Hourly
Grid Size
Continental U.S.
Input Data Source
High Resolution Rapid Refresh (HRRR)
Application / Use Case
Surface and subsurface ocean conditions, marine weather, marine fisheries, particle tracking, etc.
Zambon, J. B., R. He, and J. C. Warner (2014) Investigation of Hurricane Ivan using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Model, Ocean Dynamics, 64(11), 1535-1554, doi: 10.1007/s10236-014-0777-7
Dataset and/or GitHub URL
Dataset: storm-mode.s3.us-west-2.amazonaws.com/index.html, Github: github.com/NCAR/HWT_mode, Visualization: ncar.github.io/modeview
Point of Contact
David John Gagne (dgagne [at] ucar [dot] edu)