severe weather analysis and forecasting with the integration of

7.05
SEVERE WEATHER ANALYSIS AND FORECASTING WITH THE
INTEGRATION OF LIGHTNING, RADAR AND SATELLITE
INFORMATION IN OPERATIONAL CENTER IN BRAZIL
Cesar Beneti¹* Leonardo Calvetti¹ Marco Jusevicius¹ Augusto Pereira Filho² Rosangela B. Gin³
¹SIMEPAR, Curitiba, PR, Brazil ²USP/IAG, Sao Paulo, SP, Brazil ³UNIFEI, Sao Paulo, SP, Brazil
1. INTRODUCTION
Recent studies of total (intracloud and cloud-toground) lightning observations have shown that
although equatorial Africa stands out as the most
active lightning region on Earth, the most violent and
extreme lightning storms are more concentrated in the
subtropic to the extratropics (Goodman 2003). In
South America, southern parts of Brazil and
northeastern Argentina are regions particularly prone
to severe weather events (strong winds, intense
precipitation, tornadoes, hail, flash flood, lightning), as
Gin et al (1998), Gin and Beneti (2003) and Pinto et al
(1992), among others, have shown. However, up to
now, there is a limited knowledge in relation to the
frequency, type, morphology and intensity of cloud-toground lightning related to these storms, as well as
the environment in which they occur.
The operational suite in weather surveillance and
forecasting offices has changed a lot in the past few
years. Besides conventional meteorological information, remote systems such as satellite, weather
radars, and lightning sensors supply real-time vital
information. The primary tools for detecting thunderstorms are weather radar, lightning detectors and
satellite imagery. Lightning detection systems and
radars are capable of storms surveillance with shorter
time intervals between observations and the
integration with meteorological satellites provides
meteorological surveillance for a larger area in real
time.
Although lightning detection systems allow for the
surveillance of electrically active storms, it is not yet
possible to evaluate spatial and temporal evolution of
the storms quantitatively. With a Doppler weather
radar, hazard storm potential (e.g. flash flood, hail,
strong wind, tornado), precipitation estimation and
forecasting (in conjunction with numerical weather
prediction models) are already possible.
Severe storms with lightning activity affect
constantly Parana State, in the south of Brazil, where
the experience with operational systems integration
for analysis and forecasting of severe weather is
presented. With this work, we expect to have a better
understanding and improvement of our forecasting
abilities related to those storms with strong
precipitation and lightning. The integration of these
systems in an operational environment such as
available at SIMEPAR are the initial steps to achieve
these goals.
This paper presents a description of the
experience with integration of lightning data and other
information
for severe weather monitoring and
forecasting in a meteorological operational center in
the south of Brazil and also analysis of some severe
events registered in the area.
*Corresponding author address:
Cesar Beneti,
SIMEPAR, Caixa Postal 19100, Curitiba, PR, Brazil,
CEP 81590-110. E-mail: [email protected]
2. HYDROMETEOROLOGICAL MONITORING
SYSTEMS AVAILABLE AT SIMEPAR
For the analysis and forecasting of severe storms
occurrence in the south of Brazi, a network of
hydrometeorological observation systems, operated
by SIMEPAR since 1996, is composed of a network of
hydrometeorological automatic stations; a S-band
Doppler weather radar; satellite reception and
processing; lightning detection sensors network,
computer facilities. Figure 1 presents the location of
the hydrometeorological monitoring system described
in this section.
Figure 1 – SIMEPAR Hydrometeorological Monitoring
System in the south of Brazil operated by SIMEPAR.
2.1 Automatic Weather Stations
A network of 35 automatic hydrological stations,
measuring precipitation and river level, and 35
meteorological stations provides hourly observations
of precipitation, pressure, temperature, humidity, wind
direction, velocity and solar net radiation throughout
Parana state, which are operated by SIMEPAR. A
network of automatic raingauge stations from other
companies are also used, with a total of more than
100 points of measurements of hydrometeorological
variables.
Every 3 hours, in general, data from these stations
are transmitted by satellite to SIMEPAR where they
are processed, archived, used for assimilation in
numerical weather prediction model and integrated
with other informations for weather forecasting and
monitoring as well as research applications.
2.2 S-Band Doppler Weather Radar
SIMEPAR operates a weather radar installed in
the central region of Parana with a Doppler coverage
(radius of 200km, with wind and precipitation
measurements) including Curitiba metropolitan area
and central and east parts of Parana State. This is a
S-Band Doppler radar, EEC DWSR-95S model, with a
0.95 antenna beam width, configured to provide high
spatial (4km2 area) and temporal (5 to 10 minutes)
resolution information.
A selection of radar products (e.g. rainfall
accumulation, wind profile, nowcasting algorithms)
and also raw volumetric radar data are automatically
transmitted in real-time from the radar site to the
Weather Forecasting Center at SIMEPAR where they
area analyzed by the meteorology staff and integrated
with other observations with applications developed
in-house. Some of these applications are presented in
this paper. In the near future, volume data will also be
incorporated in the data assimilation system for
improvement of numerical weather prediction models.
Radar data is already integrated with raingauge and
satellite information for quantitative precipitation
estimation and forecasting.
16 nodes each running operational numerical weather
prediction models and other research applications,
another high-performance computer running data
base applications, and several workstations and
personal computers for software development,
weather monitoring, and dissemination of products
and services.
In order to visualize model output and other
meteorological observations (satellite, radar, lightning
and station data) an integrated tool was developed
(Zandona et al 2005). Figure 4 presents examples of
model and satellite information available for analysis.
2.3 Meteorological Satellite Information
A system for the reception and processing of realtime high-resolution data from meteorological
satellites provides products and algorithms for several
applications. Among those are fog and fire detection,
precipitation estimation, and vertical profiles of
temperature (TOVS), besides visible, infra-red and
water vapor images which are used in weather
monitoring and forecasting.
2.4 Lightning Detection System
In 1998, SIMEPAR (a meteorological center),
CEMIG and FURNAS (power companies) started a
joint cooperation agreement which created the
Brazilian Lightning Detection Network (BLDN)
covering the south, southeast and center-west of
Brazil handling real time lightning information (Beneti
and Sato 2000) as presented in Figure 2. With this
integration, data from 24 sensors are shared with
three central analyzers (Curitiba-PR, Rio de JaneiroRJ and Belo Horizonte-MG), with an increase in area
coverage, lightning detection efficiency and location
accuracy. Figure 2 presents the location of BLDN
sensors.
Although this network initially started with only
three companies (SIMEPAR, CEMIG and FURNAS),
there are other institutions and power companies
integrating this with the perspective of more 26
sensors by the end of 2005.
The lightning detection system employs a time-ofarrival (TOA) and magnetic-direction-finding (MDF)
technology to detect, locate and measure CG lightning
strokes. A network central analyzer ingests data from
the sensors and run algorithms for lightning detection
and location (Cummins et al 1998). The results
computed by the central analyzer are immediately
made available to the meteorologists at SIMEPAR
Weather Forecasting Center through dedicated
purpose computers and also archived in the system’s
database. For each lightning stroke detected, its
location, time of occurrence, and other characteristics
area available in the system’s database. After
lightning data has been archived, several products are
generated for applications on storm forecasting and
monitoring at SIMEPAR, real-time monitoring of
transmission and distribution systems for Parana
Power Company (COPEL) and other users.
For the dissemination of real-time lightning data,
historical analysis, lightning related severe weather
alerts and integration with radar and satellite
information, applications were developed at SIMEPAR
and presented in Figure 3 (Vasconcellos et al 2003).
2.5 Scientific Visualization and Processing System
Computational facilities at SIMEPAR include two
high-performance parallel processing computers with
Figure 2 – Location of the Brazilian Lightning Detection
Network sensors in 2005.
Figure 3 – Lightning data and power line (above) and
integration with infrared satellite image (below) using
application developed at SIMEPAR for internet
dissemination.
(a)
(a)
(b)
Figure 4 – Examples of numerical model output visualization
(a) sea level pressure and temperature; (b) surface wind and
infrared satellite information.
2.6 Weather Forecast Center Activities
The wealth of meteorological data available for
weather forecasters, the differing characteristics of the
various observing systems, and the ability to integrate
these data into a comprehensive analysis of the
atmospheric state are vital points to be considered in
an operational environment.
A team of meteorologists in a 24/7 shift routine
elaborates medium range forecast for south and
southeast of Brazil, as well as short-range and veryshort-range forecast warnings for several users,
mainly Parana State Civil Defense, power companies,
petrol refineries, civil aviation and others.
In order to disseminate all the information and
forecasts available in real time or as needed, we have
developed some applications for the Operational
Weather Forecast Center at SIMEPAR. An interactive
system allows the forecaster to inherit a forecast
database from the previous shift in which he/she can
update or modify the bulletins. Using a database
environment containing various weather elements
previously identified and selected, the forecaster no
longer needs to type in text for routinely scheduled
forecast products (Figure 5a). A quality control system
is used to constantly evaluate forecasting skills,
specially for the very-short-range forecasts, due to the
necessity to qualify the severe weather alerts within
the users needs. All warnings and contacts are
registered in this database for evaluation, monitoring
and distribution through the internet, as in Figure 5b.
(b)
Figure 5 – Database interactive system for weather
forecasting bulletin dissemination and evaluation. (a)
Medium range forecast bulletin environment; (b)
Nowcasting and very-short-range environment.
3 SEVERE STORM EVENTS
Four severe mesoscale convective systems were
chosen for this study: two storm events with large
amount of hail, strong wind and flash flood in Curitiba
metropolitan area, a pre-frontal squall line with strong
wind and intensive precipitation along its displacement
throughout Parana state, and another supercell storm
which affected the west of Parana with severe
damage for power transmission lines. For these
events, data from SIMEPAR hydrometeo-rological
observation systems, described in the previous
section, will be presented and discussed.
3.1 Supercell Event on 06 July 2003
A pre-frontal environment in the previous day and
the fast passage of the cold front during 06 July 2003
generated conditions for severe weather occurrence
in Parana State. This storm caused severe damage in
the Curitiba Metropolitan Area (henceforth CMA).
Several car accidents in highways with one death,
more than 60 thousand people in the area had power
cuts for more than 6 hours. Large amount of hail in
less than 30 minutes fell in Curitiba. With the hail
event, flooding followed. For about 3 hours before it
reach CMA, meteorologists at SIMEPAR were
monitoring this storm, sending alerts and reports to
Civil Defense and power companies, regarding its
strength and possible damages.
Figure 6 presents lightning information from
1600UTC to 2100UTC. A total of 1776 strokes, with
96% negative polarity, were selected to be related to
this storm event. From lightning information, storm
movement, from west to east, was evaluated to be
about 50km/h. Wind observations from the automatic
weather stations network recorded wind gust in
excess of 60km/h.
Air temperature drop around 7ºC in Curitiba when
the storm reach its boundary. Raingauge network
recorded values of more than 30mm in one hour (not
shown here).
Radar observations from this event showed a
stationary behavior during most of the storm life cycle,
with a tilt in the direction of movement related to
atmosphere steering level. Echo top (15dBZ
threshold) above 10km was observed most of the
time. Reflectivity vertical cross sections (not shown
here) identified hail around 1900 and 2000UTC
reaching surface. Variations of cloud top and vertical
reflectivity structure were observed, however, after
hail occurrence (around 1930UTC).
A comparison of storm relative vertically integrated
liquid (VILMAX) and lightning rate activity is shown in
Figure 7. High VILMAX values are an indication of hail
in the storm, which was confirmed later in the day.
During this storm life cycle two peaks for VILMAX
were observed. However, only 5 minutes prior to this
increase in VILMAX, an increase in lightning activity
was observed.
Surface equivalent potential temperature obtained
from the meteorological network indicated that the
storm path was along the area of strong gradient
region with an increase in lightning activity in its peak,
as observed in other studies (Smith et al. 2000,
Gilmore and Wicker 2002, Carey and Buffalo 2005,
among others).
The strong relation between electrical activity,
storm updrafts and cloud ice water content implies
that an increase in electrical activity should follow
severe weather, such as hail and strong wind gust, as
observed in this storm. Although not shown, vertical
reflectivity profile showed that this storm was very
efficient in producing and maintaining itself during its
displacement in Parana state.
3.2 Squall Line Event on 09 December 2003
Although hail was not observed during this squall
line event of 09 December 2003, it has interesting
electrical characteristics and related weather. In
Figure 9, a satellite image with lightning information
related to a frontal system in the south of Brazil,
around Parana region is presented. High lightning
activity was observed around the continental cold front
border, as one should expect. Since its relative broad
area of activity and strong indication of severity,
meteorologists were able to evaluate its mean velocity
displacement and warn the area, basically the whole
Parana State, with possible strong winds, hail, power
interruption, as it was later confirmed.
Radar observations, Figure 10, showed a leading
line trailing stratiform mesoscale convective system
with cloud echo top height (15dBZ threshold) well
above 8km throughout its life cycle. Reflectivity above
45dBZ was observed in the convective region of the
squall line during its movement along Parana region,
with more than 8 hours of observation. This situation
is indicative of severe weather, as observe: gust wind
above 50km/h with some peaks above 80km/h,
precipitation rate of more than 30mm/h, strong
lightning activity (Figure 11). Civil Defense reports
throughout the state were issued with more than 5
thousand families with some destruction in their
homes (mostly rooftops).
One interesting observation of this severe storm
event was the polarity reversion during part of the
storm life cycle, as presented in Figure 12. Lightning
activity was mostly concentrated on the convective
region of the squall line, with a total of 14321 CG
lightning strokes detected with the SIMEPAR LPATS.
For this event, 64% of the total lightning observation
was positive and 46% was negative CG strokes,
although future analysis will be necessary to confirm
and identify the main storms related with
predominantly positive polarity cloud-to-ground
lightning.
Figure 6 – Lightning information from 1600 to 2100UTC,
for 06 July2003. This supercell storm reached Curitiba
around 1900UTC.
Figure 7 – Temporal evolution of VILMAX and stroke rate
for 06 July 2003 storm. Vertical arrow indicates the time of
hail storm observation in Curitiba.
Figure 8 – Surface equivalent potential temperature and
lightning strokes for 06 July 2003, indicating storm path.
Figure 9 – IR satellite and lightning information integrated
for the squall line of 09 December 2003.
gradient of reflectivity, with values of 45dBZ and
above throughout its displacement in Curitiba
Metropolitan Area (CMA). Figure 14 presents a low
elevation (0.7deg) PPI for this storm shortly after its
passage in Curitiba. During a time of its development
there was indication of a hook echo in this storm as
shown in this example. Reflectivity profiles indicated
values above 45dBZ up to 5km during the most
intense hours.
Due to its lightning activity and radar
characteristics, the forecasters were able to identify
this storm with 2 hours before it reached CMA,
sending out warnings to Civil Defense and Parana
Power Company.
Strong lightning activity followed this storm during
nearly 5 hours, with more than 1500 strokes with 96%
of negative polarity as in Figures 15 and 16. The
stroke rate and polarity were similar to the observed in
the storm described in section 3.1 of this paper.
Storm relative vertically integrated liquid
(VILMAX), obtained from volumetric radar observations indicate the presence of hail in the storm,
which was later confirmed when it moved along
Curitiba area, causing great impact in the city, with
flooding in main roads, trees falling, powerline
disruptions and rooftops blown away. Again,
tornadoes were not observed in this case.
Figure 10 - Radar reflectivity vertical cross-section of
squall line event on 09 December 2003, 0051UTC.
Figure 11 – Lightning information integrated from 2200 to
0600UTC during passage of squall line on 09 December
2003.
Figure 13 – Infrared satellite and lightning information at
2045UTC, 21April 2005 event.
Figure 12 – Temporal evolution of CG stroke rate for the
squall line event on 09 December 2003.
3.3 Supercell Event on 21 April 2005
Initially embedded in an environment with postfrontal (Figure 13) high humidity and large thermal
instability, this storm presented a strong convective
Figure 14 – Reflectivity data from SIMEPAR S-Band
Doppler weather Radar and lightning location for 21 April
2005, 2134UTC.
Surface observations from meteorological stations
network, indicated wind gust in excess of 70km/h, and
temperature drop around 7C in one hour.
Accumulated precipitation in those stations indicated
around 30mm/h, comparable to radar observations.
Similar to previous events, the predominant area
of lightning occurrence was in the most intense
gradient of surface equivalent potential temperature,
as presented in Figure 17. This feature should be
looked more carefully in the future, specially
compared to cloud base height, instability and
lightning activity, as well.
Figure 15 – Lightning information from 1800 to 2200UTC,
for 21 April2005. This supercell storm passed near
Curitiba around 2100UTC.
line which connects one of the most important hydroelectrical power plants in Brazil, Itaipu plant, and the
metropolitan areas of Sao Paulo and Rio de Janeiro.
When this storm reached the transmission line, nine
towers fell down, usually built to support gust winds in
excess of 200km/h. In this case, as the storm did not
move near meteorological surface stations, wind gust
was not registered.
Synoptic conditions indicated an environment with
instability, moist and warm for this time of the year,
after the passage of a cold front through the area, as
indicated in the infrared image and radiosonde for
Iguassu Falls, Figures 18 and 19, respectively.
Figure 20 presents radar and lightning information
by the time the storm reaches the power transmission
line. Although the radar is about 340km distant, with
beam width of 0.95deg and beam elevation around
6km, reflectivities above 50dBZ were registered,
indicating the severity of a supercell structure with a
high reflectivity core, and consequently strong vertical
circulation, possible hail and wind gusts, as later
observed. A hook echo was also observed during
some period of observation.
During this day the meteorologists expected some
storms to occur in the region due to the indication
from numerical models and atmospheric conditions in
the area, but all indications for such a severe event
were only possible when signature from satellite IR
image and lightning activity were integrated. When the
radar image showed strong reflectivity in such a
distance from the antenna, they were also confirming
the warnings issued to Civil Defense in the area
during that day.
Figure 16 – Temporal evolution of VILMAX and lightning
stroke rate for 21 April 2005 event.
Figure 18 – Infrared satellite and lightning information at
2045UTC, 14 June 2005 event.
Figure 17 – Storm path (lightning strokes) and surface
equivalent potential temperature for 21 April 2005.
3.4 Supercell Event on 14 June 2005
This event occurred during the night, affecting
towns mostly along an important power transmission
Figure 19 – Iguassu Falls radiosonde profiles before
(14June 1200UTC) and after (15June 0000UTC) the
supercell event of 14 June 2005.
Figure 22 also presents the temporal evolution of
lightning stroke rate and polarity for this event,
indicating some periods of predominantly positive
polarity. Since the data utilized in this work is obtained
simply from the real-time processing, some
investigation will be done in the future to confirm this
polarity distribution, as the storm occurred in the
boundary of the lightning detection network.
When comparing the surface distribution of
equivalent potential temperature and lightning
occurrence as in Figure 23, once again it is observed
that the storm moved along an area of strong
gradient, indicating this feature as a possible area of
severe weather occurrence.
Figure 20 – PPI at 0.1deg elevation reflectivity data from
the weather radar and lightning location for 14 June
2005, 2220UTC. Indication of power transmission lines in
red.
Figure 21 – Storm path with cloud-to-ground lightning
strokes for 14 June 2005, from 1900 to 0200UTC.
Figure 22 – Storm path with cloud-to-ground lightning
strokes for 14 June 2005, from 1900 to 0200UTC.
Lightning activity was observed throughout more
than 7 hours of this storm life cycle. Although other
small convective systems were observed around this
supercell storm, it was possible to isolate the lightning
strokes related to this storm and analyze it in
comparison to lightning stroke rate and polarity during
its life cycle as presented in Figures 21 and 22,
respectively, during all the time of observations.
Figure 23 – Storm path with cloud-to-ground lightning
strokes and surface equivalent potential temperature
variation for 14 June 2005, from 1900 to 0200UTC.
4 CONCLUSIONS
In the last few years, a collection of severe
weather events such as tornadoes, supercells, squall
lines and even a hurricane-like storm took place in the
southern parts of Brazil which have caused several
damage to the population and properties.
Those severe storms affect constantly Parana
State, in the south of Brazil, where the experience
with operational systems integration for analysis and
forecasting in conjunction with professional knowledge
and timely dissemination of warnings has helped the
population, government, Civil Defense and industries
to minimize the damage they generally provoke with
terrible economic and social impacts.
This paper describes the experience of lightning
data analysis and severe weather monitoring and
forecasting in a meteorological operational center
located in a region particularly prone to hazardous
weather. With a strong interest in research and
development of applications for severe weather
analysis and forecasting and for the operative use of
lightning information, we have developed not only
tools for the integration of lightning, radar, satellite,
numerical models and automatic weather stations for
nowcasting purposes,
but also applications for
management and distribution of lightning information
for several operative end users, such as analysis and
correlation of lightning strikes with power supply
faults. The result of these developments are routinely
used during nowcasting activities, specially related to
preventing damages and injuries, and also disruptions
in the power system of Parana companies.
This paper also presents preliminary results of the
analysis of electrical and hydrometeorological
characteristics of severe storms, specially with hail
and intense precipitation. The set of storms presented
here have no indication of tornadoes. However, other
cases will be investigated in the future to analyze
more carefully these severe weather events. Although
predominantly negative CG mesoscale convective
systems are common, positive CG storms such as the
leading line trailing stratiform squall line and a
supercell storm presented here are related to strong
severe weather events, and will be studied further.
With this work, we expect to have a better
understanding and improvement of our forecasting
abilities related to those storms with strong
precipitation and lighting. The integration of
observation systems in an operational environment
such as described in this paper are the initial steps to
achieve these goals.
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