8th European Conference on Severe Storms
Wiener-Neustadt, Austria, 14-18th September 2015
Relationship between human observations of thunderstorms and
PERUN lightning detection network in Poland
Mateusz Taszarek12, Bartosz Czernecki1, Leszek Kolendowicz1, Jerzy Konarski3
1
- Department of Climatology, Institute of Physical Geography and Environmental Planning,
Adam Mickiewicz University, Dzięgielowa 27, 61-680 Poznań, Poland
2
- Skywarn Poland
3
- Institute of Meteorology and Water Management, National Research Institute,
Podleśna 61, 01-673 Warszawa, Poland
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
According to the WMO definition (1953), thunderstorm
can be reported when thunder is heard by the observer.
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
According to the WMO definition (1953), thunderstorm
can be reported when thunder is heard by the observer.
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
According to the WMO definition (1953), thunderstorm
can be reported when thunder is heard by the observer.
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
According to the WMO definition (1953), thunderstorm
can be reported when thunder is heard by the observer.
- Fleagle (1949) pointed that thunder is rarely heard more than 25 km off the
meteorological station
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
According to the WMO definition (1953), thunderstorm
can be reported when thunder is heard by the observer.
- Fleagle (1949) pointed that thunder is rarely heard more than 25 km off the
meteorological station
- Reap and Orville (1990) found that the most reliable value for the daytime is 17 km
while 26 km for the nighttime
Aim of the study
Main aim was to estimate the average distance in which human
detects thunderstorm within the meteorological station.
According to the WMO definition (1953), thunderstorm
can be reported when thunder is heard by the observer.
- Fleagle (1949) pointed that thunder is rarely heard more than 25 km off the
meteorological station
- Reap and Orville (1990) found that the most reliable value for the daytime is 17 km
while 26 km for the nighttime
- Enno (2014) pointed that the radius of 14.7 km was found to be the most appropriate
for meteorological stations.
Database (2002-2013)
Human observations
of thunderstorms
(SYNOP daily summaries)
44 stations
12 419 SYNOP reports with observed thunderstorm
(1 417 days with thunderstorm)
NOAA National Climatic Data Center (NCDC) daily summaries
Database (2002-2013)
Human observations
of thunderstorms
(SYNOP daily summaries)
Instrumental lightning
detection data
(PERUN network)
44 stations
9 sensors
12 419 SYNOP reports with observed thunderstorm
(1 417 days with thunderstorm)
NOAA National Climatic Data Center (NCDC) daily summaries
4 952 203 cloud-to-ground flashes
(2 082 days with thunderstorm)
Institute of Meteorology and Water Management (IMGW)
Database (2002-2013)
Human observations
of thunderstorms
(SYNOP daily summaries)
Instrumental lightning
detection data
(PERUN network)
44 stations
9 sensors
12 419 SYNOP reports with observed thunderstorm
(1 417 days with thunderstorm)
NOAA National Climatic Data Center (NCDC) daily summaries
4 952 203 cloud-to-ground flashes
(2 082 days with thunderstorm)
Institute of Meteorology and Water Management (IMGW)
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
29th July 2013
Wrocław station
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
29th July 2013
Wrocław station
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
29th July 2013
Wrocław station
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
29th July 2013
Wrocław station
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
29th July 2013
Wrocław station
Thunderstorm reported with
CG lighning flash 17 km
away from the observer
17 km
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
10th June 20
Łeba station
23 km
Thunderstorm reported with
CG lighning flash 23 km
away from the observer
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
17th June 2012
Poznań station
Thunderstorm reported with
CG lighning flash 7 km
away from the observer
7 km
Methodology
The main conception was to compare:
- days in which thunderstorm was reported over particular station (SYNOP),
- CG lightning flashes detected by PERUN in those days.
29th July 2013
Wrocław station
TS method
We base on using 2×2 contingency tables (Wilks, 2006) in order to compute
Threat Score (TS) index (also known as Critical Success Index).
TS method
We base on using 2×2 contingency tables (Wilks, 2006) in order to compute
Threat Score (TS) index (also known as Critical Success Index).
Table 1. Number of thunderstorm cases derived from the
Warszawa station within the use of SYNOP and PERUN data
derived from the 18 km radius (2002-2013).
TS method
We base on using 2×2 contingency tables (Wilks, 2006) in order to compute
Threat Score (TS) index (also known as Critical Success Index).
Table 1. Number of thunderstorm cases derived from the
Warszawa station within the use of SYNOP and PERUN data
derived from the 18 km radius (2002-2013).
TS method
We base on using 2×2 contingency tables (Wilks, 2006) in order to compute
Threat Score (TS) index (also known as Critical Success Index).
Table 1. Number of thunderstorm cases derived from the
Warszawa station within the use of SYNOP and PERUN data
derived from the 18 km radius (2002-2013).
We repeat this process for each radius from 10 to 25 km with the step of 0.5 km
TS method
We base on using 2×2 contingency tables (Wilks, 2006) in order to compute
Threat Score (TS) index (also known as Critical Success Index).
Figure 1. TS curve computed as a
relationship between thunderstorm
days derived from SYNOP reports
and PERUN lightning detection data
for Warszawa meteorological station
(2002-2013).
We repeat this process for each radius from 10 to 25 km with the step of 0.5 km
TS method
We base on using 2×2 contingency tables (Wilks, 2006) in order to compute
Threat Score (TS) index (also known as Critical Success Index).
Figure 1. TS curve computed as a
relationship between thunderstorm
days derived from SYNOP reports
and PERUN lightning detection data
for Warszawa meteorological station
(2002-2013).
The best observational performance
at the distance of 19 km
We repeat this process for each radius from 10 to 25 km with the step of 0.5 km
Delta method
Involves comparing for particular station the total number of thunderstorm
days basing on SYNOP reports with the number of thunderstorm days
derived from the lightning data.
Delta method
Involves comparing for particular station the total number of thunderstorm
days basing on SYNOP reports with the number of thunderstorm days
derived from the lightning data.
Table 2. Number of thunderstorm days derived from the
Warszawa station within the use of SYNOP and PERUN data
derived from the 18 km radius (2002-2013).
Delta method
Involves comparing for particular station the total number of thunderstorm
days basing on SYNOP reports with the number of thunderstorm days
derived from the lightning data.
Table 2. Number of thunderstorm days derived from the
Warszawa station within the use of SYNOP and PERUN data
derived from the 18 km radius (2002-2013).
Delta method
Involves comparing for particular station the total number of thunderstorm
days basing on SYNOP reports with the number of thunderstorm days
derived from the lightning data.
Table 2. Number of thunderstorm days derived from the
Warszawa station within the use of SYNOP and PERUN data
derived from the 18 km radius (2002-2013).
We repeat this process for each radius from 10 to 25 km with the step of 0.5 km
Delta method
Involves comparing for particular station the total number of thunderstorm
days basing on SYNOP reports with the number of thunderstorm days
derived from the lightning data.
Figure 2. Delta curve computed as a
relationship between thunderstorm
days derived from SYNOP reports
and PERUN lightning detection data
for Warszawa meteorological station
(2002-2013).
We repeat this process for each radius from 10 to 25 km with the step of 0.5 km
Delta method
Involves comparing for particular station the total number of thunderstorm
days basing on SYNOP reports with the number of thunderstorm days
derived from the lightning data.
Figure 2. Delta curve computed as a
relationship between thunderstorm
days derived from SYNOP reports
and PERUN lightning detection data
for Warszawa meteorological station
(2002-2013).
The best observational performance
at the distance of 19.5 km
We repeat this process for each radius from 10 to 25 km with the step of 0.5 km
Results
For each meteorological station (44), we compute TS and Delta indexes for each radius
from 10 to 25 km with 0.5 km step.
Results
For each meteorological station (44), we compute TS and Delta indexes for each radius
from 10 to 25 km with 0.5 km step.
Results
For each meteorological station (44), we compute TS and Delta indexes for each radius
from 10 to 25 km with 0.5 km step.
Results
For each meteorological station (44), we compute TS and Delta indexes for each radius
from 10 to 25 km with 0.5 km step.
Avg. number of thunderstorm days (2002-2013)
SYNOP data
Lightning data
Avg. number of thunderstorm days (2002-2013)
SYNOP data
Lightning data
Avg. number of thunderstorm days (2002-2013)
SYNOP data
14 km
12 km
24 km
21 km
13 km
Lightning data
Summary
- This study is the first one that provides such an analysis with the use of such a large
database (12 years, 12 419 SYNOP reports, 4 952 203 cloud-to-ground flashes ).
Summary
- This study is the first one that provides such an analysis with the use of such a large
database (12 years, 12 419 SYNOP reports, 4 952 203 cloud-to-ground flashes ).
- Mean observational threshold range vary from 16.9 km (Delta method) to 18.2 km
(TS method). Although the used methods strongly differ from each other, they
provide reasonably similar values.
Summary
- This study is the first one that provides such an analysis with the use of such a large
database (12 years, 12 419 SYNOP reports, 4 952 203 cloud-to-ground flashes ).
- Mean observational threshold range vary from 16.9 km (Delta method) to 18.2 km
(TS method). Although the used methods strongly differ from each other, they
provide reasonably similar values.
- We believe that an average of these two methods giving us the final value of 17.5 km
may be the most reliable estimate that expresses how thunderstorms are perceived
by human.
Summary
- This study is the first one that provides such an analysis with the use of such a large
database (12 years, 12 419 SYNOP reports, 4 952 203 cloud-to-ground flashes ).
- Mean observational threshold range vary from 16.9 km (Delta method) to 18.2 km
(TS method). Although the used methods strongly differ from each other, they
provide reasonably similar values.
- We believe that an average of these two methods giving us the final value of 17.5 km
may be the most reliable estimate that expresses how thunderstorms are perceived
by human.
- Values over particular stations varies from 12 to 24 km(stations have different
localization characteristics, thunderstorms are reported by different meteorological
Observers).
Summary
- This study is the first one that provides such an analysis with the use of such a large
database (12 years, 12 419 SYNOP reports, 4 952 203 cloud-to-ground flashes ).
- Mean observational threshold range vary from 16.9 km (Delta method) to 18.2 km
(TS method). Although the used methods strongly differ from each other, they
provide reasonably similar values.
- We believe that an average of these two methods giving us the final value of 17.5 km
may be the most reliable estimate that expresses how thunderstorms are perceived
by human.
- Values over particular stations varies from 12 to 24 km(stations have different
localization characteristics, thunderstorms are reported by different meteorological
Observers).
- Obtained threshold value (17.5 km) can be applied in the studies that aim to compute
lightning characteristics in the way how they would be perceived by human,
particularly thunderstorm days.
Summary
Czernecki, B., M. Taszarek, L. Kolendowicz, J.
Konarski, 2015: Relationship between human
observations of thunderstorms and PERUN
lightning detection network in Poland. Atm. Res.
In press, 10.1016/j.atmosres.2015.08.003.