WARNING APPLICATIONS RESEARCH

image of a flooded house

Aggregate hailstone approximately six inches in diameter. The Warning Applications group works on systems that help forecasters detect, monitor and predict the occurrence of severe weather.

 

Related links:

Past Warning Applications (SWAT) Group Projects

Mesocyclone Detection Algorithm (MDA)

Statistics show that storms with mesocyclones (very strong circulations within a thunderstorm) produce severe weather approximately 95% of the time, and tornadoes approximately 20% of the time. The Mesocyclone Detection Algorithm (MDA) detects these strong circulations in thunderstorms and forecasts their movements for up to 30 minutes. The algorithm also analyzes the mesocyclone and produces information about the strength of rotation, depth, and diameter. All of these parameters are useful to meteorologists as they try to determine whether or not to issue severe thunderstorm or tornado warnings.

Read more about the Mesocyclone Detection Algorithm

Tornado Detection Algorithm (TDA)

Tornadic winds are the strongest produced by nature. The Tornado Detection Algorithm (TDA) examines Doppler radar velocity data to detect signatures that indicate a tornado or signal its development.

Read more about the Tornado Detection Algorithm

Radar Severe Weather Case Studies

Experimental algorithms and displays developed at NSSL were used in the analysis of a number of classic, as well as unique, severe storm case studies from a radar and warning perspective.

View the Case Studies

Hail Detection Algorithm (HDA)

Hail greater than 3/4 inch diameter is considered severe by the NWS. Doppler radar data are examined in real-time by the NSSL-developed Hai lDetection Algorithm (HDA) to determine the probability that the storm is producing hail >3/4 inch diameter. It also estimates the maximum hailstone size associated with a storm.

Damaging Downburst Prediction Algorithm (DDPA)

The Damaging Downburst Prediction Algorithm (DDPA) is designed to short-term predict and detect the divergent outflow patterns often associated with downbursts. The DDPA uses radar-detectable precursors that have been found to occur 10-15 minutes before a downburst. Some known precursors are: convergence above the cloud base within a storm, a descending reflectivity core, and in some cases, rotation above the cloud base. The output from the algorithm indicates either a prediction or detection of a downburst event and an estimate of its strength.

Read more about the Damaging Downburst Prediction and Detection Algorithm Offsite link warning

Storm Cell Identification and Tracking Algorithm (SCIT)

Knowing the present location of thunderstorms and their movement is crucial to the NWS meteorologist. The Storm Cell Identification and Tracking algorithm (SCIT) identifies the location of storms, tracks them over time, and forecasts their movements for the next 30 minutes. The SCIT algorithm also analyzes the identified storm cells and provides the meteorologist with information in the form of a table about the cell's potential to produce severe weather.