ANALYSIS AND NOWCASTING (SCAN)
National Weather Service, NOAA
Silver Spring, Maryland
Sudhir K. Goel
M. Thomas Filiaggi
General Sciences Corporation
Michael E. Churma
Research and Data Systems Corporation
Silver Spring, Maryland
National Severe Storms Laboratory
Environmental Research Laboratories, NOAA
The System for Convection Analysis and
Nowcasting (SCAN; Smith et al. 1998a) is an integrated suite of multi-sensor applications which detects,
analyzes and monitors convection, and generates
short-term probabilistic forecast and warning guidance
for severe weather and flash floods automatically within
the National Weather Service's (NWS's) Advanced
Weather Interactive Processing System (AWIPS). The
goals of SCAN are:
1. To provide forecasters with accurate, timely, and consistent severe weather and flash flood guidance.
Corresponding author address: Dr. Stephan B. Smith, TDL/NWS, SSMC2, 1325 East-West Highway, Silver Spring, MD 20910.
2. To develop "smart" computer displays, menus, and
graphical user interfaces that optimize the utility of
the AWIPS Display 2 Dimensional (D2D; Biere 1998)
and are compatible with the warning decision process.
3. To develop multi-sensor databases to support the
verification of thunderstorm, severe weather, and
flash flood forecasts/warnings.
4. To supplement forecaster event monitoring with
multi-sensor, automated event monitoring.
5. To accelerate the rate of technology transfer from
research to operations.
Operational implementation of SCAN will result
in longer lead times on warned events, fewer missed
events, increased forecaster situational awareness,
reduced forecaster fatigue during warning situations,
rapid improvement in implemented techniques, and a
well-defined focus for applied research.
This paper describes the functionality of the first two operational versions of SCAN (1.0 and 2.0), as well as plans for future enhancements. Additional information on SCAN development for AWIPS and other SCAN-related items is available from the SCAN homepage at www.nws.noaa.gov/tdl/scan/scan2.html.
2. SCAN 1.0
SCAN is being implemented in AWIPS
incrementally. Each new version contains new and/or
improved functionality. The first version (1.0; delivered
to the field starting in November 1998 as part of
AWIPS 4.1) represents the foundation for subsequent
versions. Accordingly, two candidate applications were
chosen based on their varied use of modernized NWS
data sets and on their applicability to the severe
thunderstorm and flash flood warning problems.
The first application, the AWIPS thunderstorm
product (Churma and Smith 1998) uses radar and
cloud-to-ground (CG) lightning data to automatically
detect the presence of thunderstorms near specific
sites. The second is a 1-hr radar-based quantitative
precipitation forecast algorithm (Kitzmiller and Churma
1999) pertinent to flash flood forecasting.
Another new AWIPS functionality introduced in
SCAN 1.0 is the radar cell pop-up (dialog) box. This
application allows the user to query a radar-detected
storm cell by simply clicking near the cell as displayed
on the D2D screen. The click launches a pop-up
window that displays basic and derived cell attributes
including cell ID, cell motion, maximum reflectivity,
maximum vertical integrated liquid (VIL), probability of
large hail, probability of severe weather, probability of
heavy precipitation, and CG lightning frequency.
Similarly, a thunderstorm detection pop-up can be
launched by clicking on any site displayed in the D2D
that is being monitored for thunderstorms. This box
displays the thunderstorm site decision (yes or no) and
the data inputs used in calculating it (radar and lightning, radar only, or lightning only). A graphical user
interface allows forecasters to modify the SCAN storm
cell depictable and thus provides a basic cell ranking
and sorting capability to the D2D. Additional details
about SCAN 1.0 can be found in the AWIPS 4.1 D2D
User's Guide (Kucera and Osborn 1998).
3. SCAN 2.0
The National Severe Storms Laboratory (NSSL)
has for several years developed algorithms that examine
integrated meteorological data to identify severe weather
phenomenon. In support of these applications, NSSL
has also designed and implemented new concepts for
displaying warning relevant information for efficient and
rapid access. The combined (algorithms and display)
system, called the Warning Decision Support System
(WDSS; Eilts et al. 1999), has been tested operationally
with great success at selected NWS offices across the
Figure 1 shows the first operational version of the
WDSS radar cell table as it will appear in the AWIPS
D2D, as a part of SCAN 2.0. Since AWIPS does not
receive base radar data (WDSS does receive base
data), only the output of algorithms which have been
implemented in the operational NEXRAD Radar Product
Generator (and are thus available in radar product form)
are included. Along with the basic cell table, cell attribute trends and trend sets, rate of change alarms, as well
as mesocyclone and tornado vortex signature tables are
also being implemented. In addition, the user will be
able to rank and sort the radar-detected cells by most of
the displayed cell attributes as well as by the standard
NSSL ranking algorithm, which is based on cell severity.
The SCAN County Warning Area (CWA) Threat Index (SCTI) for severe weather and flash floods is another important component of SCAN 2.0. The SCTI will automatically, determine the level of severe weather and flash flood threat for a given CWA.
4. FUTURE ENHANCEMENTS
The National Center for Atmospheric Research
has developed and refined an integrated system designed to produce automated guidance on the detection,
tracking and short period (0-60 min) forecasting of
thunderstorms. Operational implementation of this
Thunderstorm Autonowcast System will provide a very
important prognostic component to SCAN which will
result in longer lead times on warned events.
A very significant improvement in the flash flood detection/forecasting capability of SCAN will be achieved by implementation of the Areal Mean Basin Estimated Rainfall (AMBER) algorithm (Jendrowski and Davis 1998) which maps high resolution radar precipitation rates onto high resolution (<10 sq. km) stream basins. Further enhancement of SCAN flash flood detection/forecasting capability will come from the implementation of the GOES satellite-based rainfall estimation algorithm developed by Vincente and Scofield (1998).
Automated GOES satellite-based thunderstorm
anvil tracking (Zaras and Rabin 1998) is another
application that will bring to bear the remotely-sensed
data sources of the modernized NWS on the diagnosis
of severe convective storms.
Some of above applications have already been operationally tested as part of the SCAN Field Test (Smith et al. 1998b; Johnson et al. 1999; and Roberts et al. 1999)
The authors would like to thank Dave Glass,
J.T. Johnson, Ken Sperow, Bill Carrigg, Don Mugnai,
Dave Kitzmiller, and Tom Graziano for assistance in
the SCAN effort.
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_____, J. T. Johnson, R. D. Roberts, S. M. Zubrick, and
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Figure 1: SCAN 2.0 (WDSS) radar cell table (top) with single cell attribute trend window (bottom). Cell attributes shown from left to right are cell ID, azimuth, range, tornado vortex signature, mesocyclone, probability of severe hail, probability of hail, hail size, maximum vertically integrated liquid, maximum reflectivity, height of maximum reflectivity, cell direction, cell speed, probability of large hail, probability of severe weather, percentage of positive CG lightning flashes, and CG lightning rate. Trend window is for height of maximum reflectivity for cell "C8" and was launched by clicking on that entry in the main table.