Tornado Warning Decisions Using Phased Array Radar Data

Weather and Forecasting: Early Online Release

Tornado Warning Decisions Using Phased Array Radar Data

Authors:  Pamela Heinselman, Daphne LaDue, Darrel M. Kingfield, and Robert Hoffman

The 2012 Phased Array Radar Innovative Sensing Experiment identified how rapidly scanned full-volumetric data captured known mesoscale processes and impacted tornado-warning lead time. Twelve forecasters from nine National Weather Service forecast offices used this rapid-scan phased array radar (PAR) data to issue tornado warnings on two low-end tornadic and two nontornadic supercell cases. Verification of the tornadic cases revealed that forecasters’ use of PAR data provided a median tornado-warning lead time (TLT) of 20 min.  Precursors that triggered forecasters’ decisions to warn occurred within one or two typical WSR-88D scans, indicating PAR’s temporal sampling better matches the time-scale at which these precursors evolve.

Share this:

Multiple-Radar Multiple Sensor system developed at NSSL goes into NWS operations

Screen Shot 2014-10-16 at 9.13.23 AMWeather forecasters rely on an incredibly large amount of information when they make forecasts and issue warnings. A new system, activated by NOAA’s National Weather Service last week, quickly harnesses the tremendous amount of weather data from multiple sources, intelligently integrates the information, and provides a detailed picture of the current weather.

The Multiple Radar Multiple Sensor (MRMS) system combines data streams from multiple radars, satellites, surface observations, upper air observations, lightning reports, rain gauges and numerical weather prediction models to produce a suite of decision-support products every two minutes. Because it provides better depictions of high-impact weather events such as heavy rain, snow, hail, tornadoes, and other threats, forecasters can quickly diagnose severe weather and issue more accurate and earlier forecasts and warnings.

“MRMS uses a holistic approach to merging multiple data sources, allowing forecasters to better analyze data and potentially make better predictions,” said Ken Howard, a research meteorologist at NOAA’s National Severe Storms Laboratory who helped design MRMS. “It was developed in collaboration with NOAA’s National Weather Service hydrologists and forecasters who tested experimental versions and provided valuable input and feedback.”

Researchers at NOAA’s National Severe Storms Laboratory designed the MRMS system to improve decision making within NOAA and other agencies – marking another NOAA research to operations success. Implementation of the system into NWS operations was funded in part by the Disaster Relief Appropriations Act of 2013.

MRMS will improve the ability of forecasters to issue public warnings and advisories for severe weather such as tornadoes, hail and flash floods, and will help improve forecasts for safety of air traffic.

NSSL’s experimental version of the MRMS system has been available at various National Weather Service offices, but now that it is becoming operational, NOAA researchers plan to continue their collaboration with NOAA partners such as developers, trainers and forecasters to collect best practices and case studies. The system is designed so that new techniques and products can be added, increasing its capabilities.

“The nationally consistent products available from the MRMS are another important step toward NOAA’s goal of building a Weather Ready Nation by providing better analyses and forecasts to a wide range of decision makers,” said Louis Uccellini, Ph.D., director of NOAA’s National Weather Service. “This is another tool to help ensure communities are better prepared and more resilient in the face of high-impact weather events.”

MRMS data are also an input into the newly operational High-Resolution Rapid Refresh weather model, which will improve the quality of forecasts and warnings for severe weather events.

NOAA researchers developed the MRMS system in cooperation with The University of Oklahoma’s Cooperative Institute for Mesoscale Meteorological Studies.

Share this: