NOAA National Severe Storms Laboratory

output

20122025

most citedUsing Machine Learning to Calibrate Storm-Scale Probabilistic Guidance of Severe Weather Hazards in the Warn-on-Forecast System

67 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

C. Homeyer2 profiles2 · h 32
Corey K. Potvin2 · h 5
C. Potvin2 · h 21
Montgomery L. Flora2 · h 11
A. Ebtehaj1 · h 20
A. McGovern1 · h 31
Amy McGovern1 · h 3
A. Protat1 · h 46
Brice E Coffer1 · h 12
B. Saavedra1 · h 9
Charlie Becker1 · h 6
Christopher D. Wirz1 · h 15

collaborating institutions

University of OklahomaUS8 papers
Cooperative Institute for Mesoscale Meteorological StudiesUS4 papers
Colorado State UniversityUS3 papers
Cooperative Institute for Research in the AtmosphereUS3 papers
University of Colorado BoulderUS3 papers
NSF National Center for Atmospheric ResearchUS2 papers
Academia SinicaTW1 paper
Albany State UniversityUS1 paper
Bureau of MeteorologyAU1 paper
Cooperative Institute for Research in Environmental SciencesUS1 paper
Desert Research InstituteUS1 paper
Herzberg Institute of AstrophysicsCA1 paper

Showing 2020 · physics.ao-phShow all

1 paper · 2 filters

physics.ao-ph2020★ 67 cited

Using Machine Learning to Calibrate Storm-Scale Probabilistic Guidance of Severe Weather Hazards in the Warn-on-Forecast System

Montgomery Flora, Corey K. Potvin, Patrick S. Skinner +2

A primary goal of the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast (WoF) project is to provide rapidly updating probabilistic guidance to human forecaste…