67 citations
- 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
4 papers · 1 filter
Machine Learning Estimation of Maximum Vertical Velocity from Radar
Randy J. Chase, Amy McGovern, Cameron Homeyer +2
The quantification of storm updrafts remains unavailable for operational forecasting despite their inherent importance to convection and its associated severe weather hazards. Updr…
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…
On the dual advantage of placing observations through forward sensitivity analysis
Shady E Ahmed, Omer San, Sivaramakrishnan Lakshmivarahan +1
The four-dimensional variational data assimilation methodology for assimilating noisy observations into a deterministic model has been the workhorse of forecasting centers for over…
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…