paper
2025
Benchmarks, datasets & evaluation
Nowcasting Evaluation or intercomparison of existing models
0–6 hColorado State University (incl. CIRA)NOAA (incl. GFDL, PSL, GSL, NCEP/EMC) Journal
2025-08-06
051
Aug 2025
Stephanie M. Ortland, Michael J. Pavolonis
Artificial Intelligence for the Earth Systems
Colorado State University (incl. CIRA), NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)
Object-based tracking of ThunderCast thunderstorm nowcasts finds 69.4% of 17,054 tracks are true positives, and most of those lack lightning.
Benchmarks, datasets & evaluation
An Object-Based Evaluation of Output from a Deep Learning Model for Thunderstorm Nowcasting
In one sentence. Object-based tracking of ThunderCast thunderstorm nowcasts finds 69.4% of 17,054 tracks are true positives, and most of those lack lightning.
Labels
- Topic
- Benchmarks, datasets & evaluation, Nowcasting
- Type
- Evaluation or intercomparison of existing models
- Time scale
- 0–6 h
- Domain
- Regional
- Data
- Satellite, Radar
- Status
- Research
- Identifiers
- DOI:10.1175/aies-d-24-0071.1 OpenAlex:W4413019616
- Added
- 2026-10-22
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