Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

Weather forecasts are inherently uncertain. Therefore, for many applications forecasts are
only considered valuable if an uncertainty estimate can be assigned to them. Currently, the …

Abstract The Multi-Radar Multi-Sensor (MRMS) system, which was developed at the
National Severe Storms Laboratory and the University of Oklahoma, was made operational …

For radar aeroecology studies, the identification of the type of scatterer is critically important.
Here, we used a random forest (RF) algorithm to develop a variety of scatterer classification …

Object-Based Verification of a Prototype Warn-on-Forecast System in: Weather and Forecasting
Volume 33 Issue 5 (2018) Jump to Content Jump to Main Navigation Logo Logo Logo Logo …

Berkowitz, DS, JA Schultz, S. Vasiloff, KL Elmore, CD Payne, and JB Boettcher, 2013: Status
of dual pol QPE in the WSR-88D network. Preprints, 27th Conf. on Hydrology, Austin, TX …

The upgrade of the national network of next‐generation weather surveillance radars
(NEXRAD) in the United States to dual polarizations has been completed, providing three …

Abstract The National Oceanic and Atmospheric Administration's (NOAA) Big Data
Partnership (BDP) was established in April 2015 through cooperative research agreements …

Artificial intelligence (AI) and machine learning (ML) have become important tools for
environmental scientists and engineers, both in research and in applications. Although …

A Physically Based Precipitation–Nonprecipitation Radar Echo Classifier Using Polarimetric
and Environmental Data in a Real-Time National System in: Weather and Forecasting Volume …