67 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of OklahomaUS7 papers
- NOAA National Severe Storms LaboratoryUS4 papers
- North Carolina State UniversityUS3 papers
- Colorado State UniversityUS2 papers
- Cooperative Institute for Research in the AtmosphereUS2 papers
- NOAA Storm Prediction Center2 papers
- Pennsylvania State UniversityUS2 papers
- University of Colorado BoulderUS2 papers
- Albany State UniversityUS1 paper
- Augsburg UniversityUS1 paper
- Cooperative Institute for Research in Environmental SciencesUS1 paper
- Florida State UniversityUS1 paper
9 papers
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…
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…
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications
John S. Schreck, David John Gagne, Charlie Becker +13
Robust quantification of predictive uncertainty is critical for understanding factors that drive weather and climate outcomes. Ensembles provide predictive uncertainty estimates an…
A Machine Learning Tutorial for Operational Meteorology, Part II: Neural Networks and Deep Learning
Randy J. Chase, David R. Harrison, Gary Lackmann +1
Over the past decade the use of machine learning in meteorology has grown rapidly. Specifically neural networks and deep learning have been used at an unprecedented rate. In order…
Supercell low-level mesocyclones: Origins of inflow and vorticity
Brice Coffer, Matthew Parker, John Peters +1
The development of low-level mesocyclones in supercell thunderstorms has often been explained via the development of storm-generated streamwise vorticity along a baroclinic gradien…
A Machine Learning Tutorial for Operational Meteorology, Part I: Traditional Machine Learning
Randy J. Chase, David R. Harrison, Amanda Burke +2
Recently, the use of machine learning in meteorology has increased greatly. While many machine learning methods are not new, university classes on machine learning are largely unav…
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…
Possible Implications of Self-Similarity for Tornadogenesis and Maintenance
Pavel Bělík, Brittany Dahl, Douglas Dokken +3
Self-similarity in tornadic and some non-tornadic supercell flows is studied and power laws relating various quantities in such flows are demonstrated. Magnitudes of the exponents…
Determining Key Model Parameters of Rapidly Intensifying Hurricane Guillermo(1997) using the Ensemble Kalman Filter
Humberto C. Godinez, Jon M. Reisner, Alexandre O. Fierro +2
In this work we determine key model parameters for rapidly intensifying Hurricane Guillermo (1997) using the Ensemble Kalman Filter (EnKF). The approach is to utilize the EnKF as a…