National Severe Storm Laboratory's
Warning Decision Support System (WDSS-II)
 
(WFO LSX's Contribution to test and evaluation of WDSS-II Algorithms) (Update 11/2010)


 The Warning Decision Support System (WDSS-II) is a multi-radar / sensor realtime ingest and processing system that can be used to evaluate experimental applications (algorithms) in an operational warning scenario.  This system is also a powerful application development tool.  It is quite easy to add new products and and test / evaluate current applied research concepts into the system. WDSS-II also provides a seamless path from data ingest, data processing and output using standard formats.  This helps improves the pace of science and technology infusion into operational warning systems. 

The WDSS-II system is primary used for applied research, prototype algorithm development, and algorithm evaluation. Here at WFO St. Louis we are not only able to view high-resolution reflectivity, Doppler velocity data, but also a host of algorithms the system provides the warning forecasters. In many of our severe weather events, we have used WDSS-II algorithms to provide vital information to warning forecasters in the decision to warn or not to warn. Some of the algorithms we are testing during recent years and today include: 

1) 0-3 km Azmiuthal Shear Algorithm 
2) Hail Detection
Algorithm (HDA)
3) 


We surveyed the 0-3 km Azmiuthal Shear Algorithm and Multishear Algorithm to investigate the magnitude of Azmiuthal Shear with time. Much of the work was completed on warm and transitional season mesovortices. We experience about 40% QLCS cases over a year in our County Warning Area (CWA). We test this algorithm mainly within the range of 140 km from the WSR-88D during the warm season and 130 km during the transitional season events. Since many of our mesovortices associated with convective lines initially form at low-levels (below 2.5 km), radar sampling and viewing angle issues can become problematic at distant ranges from the WSR-88D.  In many of our warm and transitional season QLCS - bow echo cases from the early to mid 1990s to present the strongest rotation falls within the 0.5 to 2.5 km layer through the mature stage of the mesovortex.  Some of the warm season mesovortices may exceed 2.5 km layer. We will show examples of various case studies below.  In a couple of our High-Precipitation supercell cases we detected the strongest rotation at or just below 3 km, thus we were able to test the 0-3 km azmiuthal shear algorithm for these cases.  We will show examples of both QLCS (with embedded bow echoes) and HP storms. .  
  
Case 1:


(under construction)


                     

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 below 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.

 

DDPDA

Damaging Downburst Prediction and Detection Algorithm

TDA

Tornado Detection Algorithm

MDA

Mesocyclone Detection Algorithm

SAA

Snow Accumulation Algorithm

 

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