output
20122025
most citedUsing Machine Learning to Calibrate Storm-Scale Probabilistic Guidance of Severe Weather Hazards in the Warn-on-Forecast System

67 citations

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5 papers · 1 filter

physics.ao-ph2025★ 2 cited

HRRRCast: a data-driven emulator for regional weather forecasting at convection allowing scales

Daniel Abdi, Isidora Jankov, Paul Madden +5

The High-Resolution Rapid Refresh (HRRR) model is a convection-allowing model used in operational weather forecasting across the contiguous United States (CONUS). To provide a comp…

physics.ao-ph2025

Supercell environments using GridRad-Severe and the HRRR: Addressing discrepancies between prior tornado datasets

Brice Coffer, Matthew Parker, Michael Coniglio +1

Storm-relative helicity (SRH) is an important ingredient in supercell development, as well as mesocyclone intensity, and is linked to tornadogenesis and tornado potential. Derived…

physics.ao-ph2024★ 30 cited

Changes in mesoscale convective system precipitation structures in response to a warming climate

Wenjun Cui, Thomas Galarneau, Kimberly Hoogewind

Mesoscale convective systems (MCSs) are crucial components of the hydrological cycle and often produce flash floods. Given their impact, it is crucial to understand how they will c…

physics.ao-ph2023★ 8 cited

The Effects of Spatial Interpolation on a Novel, Dual-Doppler 3D Wind Retrieval Technique

Jordan P. Brook, Alain Protat, Corey K. Potvin +2

Three-dimensional wind retrievals from ground-based Doppler radars have played an important role in meteorological research and nowcasting over the past four decades. However, in r…

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…