paper
2021
Observations & remote sensing
New model or method
Classical ML (trees, GP, linear, kernels)NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)University of Oklahoma (AI2ES) Journal
2021-07-01
047
Jul 2021
Shruti Ashok Upadhyaya, Pierre‐Emmanuel Kirstetter, Robert J. Kuligowski et al.
Quarterly Journal of the Royal Meteorological Society
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC), University of Oklahoma (AI2ES)
A machine-learning classifier on GOES-16 ABI channels with NWP inputs identifies precipitation occurrence with 97% accuracy and convective types at 76%.
Classifying precipitation from GEO satellite observations: Prognostic model
In one sentence. A machine-learning classifier on GOES-16 ABI channels with NWP inputs identifies precipitation occurrence with 97% accuracy and convective types at 76%.
Labels
- Topic
- Observations & remote sensing
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- Satellite, Radar, NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1002/qj.4134 OpenAlex:W4213315021
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.