National Severe Storm Laboratory's
Warning Decision Support System (WDSS)

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What is WDSS? WDSS consist of several enhanced or new WSR-88D severe weather detection and prediction algorithms as well as innovative display capabilities that provides information to warning meteorologist to support decision making during time of severe / hazardous weather. Forecasters have the capability to survey 'high resolution' reflectivity / Doppler velocity data (0.25 km data at ranges
up to 125 n miles (230 km) as well as evaluate the
performance of NSSL's latest severe weather
detection and prediction algorithms.

Staff members at WFO St. Louis Missouri are
actively involved in testing several of NSSL's
severe weather detection and predicition algorithms.

 

                                                                                                                                                            

WFO St. Louis Missouri is one of
several sites across the United States in
testing these algorithms in 'real time'
severe weather and winter weather
events. The map on the right shows
past and current NWS offices (in red)
and future sites (in green) involved in
the testing of the algorithms.

Much of our testing focuses on four
primary algorithms:
1) Mesocyclone Detection Algorithm
2) Tornado Detection Algorithm (TDA)
3) Damaging Downburst Prediction
and Detection Algorithm (DDPDA)
These 3 algorithms are part of the
Severe Storms Analysis Program
(SSAP). The fourth algorithm we
are currently testing is the
'Snow Accumulation Algorithm' (SAA).
We are working on 'Optimizing' these algorithms for the St. Louis and Mid-Mississipp Valley Region.  

WDSS is comprised of three main hardware systems:
- Real-time Ingest and Data Dissemination System (RIDDS)
- Radar Utilities for Doppler Data Streams (RUDDS)
- Severe Storm Analysis Program (SSAP)
- Radar and Algorithm Display System (RADS)

- Severe Storm Analysis Program (SSAP) consists of:
1) An enhanced Mesocyclone Detection Algorithm (MDA) which includes a vertically-integrated strength index (MSI), Neural Network-derived probability functions, and a mesocyclone tracking function.
2) An enhanced Tornado Detection Algorithm (TDA) and a tornado tracking function.
3) Build 9.0 Hail Detection Algorithm (HDA) with probability products and near storm environment thermodynamic data input.
4) Build 9.0 Storm Cell Identification and Tracking (SCIT) algorithm.
5) A new Damaging Downburst Prediction and Detection Algorithm (DDPDA) to predict and detect severe downburst winds at the surface. The Mid-Altitude Radial Convergence (MARC) velocity signature developed here at WFO St. Louis is part of DDPDA.

 

Recent studies we have participated in & and preliminary results.

 

 

 

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