Probabilistic forecasts of severe thunderstorms for the purpose of issuing a weather alarm

1
Probabilistic forecasts of (severe) thunderstorms
for the purpose of issuing a weather alarm

• Maurice Schmeits, Kees Kok, Daan Vogelezang and
  Rudolf van Westrhenen
• KNMI

2
Outline

• Introduction Weather alarm for severe
  thunderstorms
• Method Model output statistics (MOS)
• Data used in MOS system for (severe)
  thunderstorms
• Illustration of statistical method
• Definitions of predictands
• Case (10 June 2007)
• Verification results
• Conclusions and outlook

3
Weather alarm for severe thunderstorms (I)

• Weather alarm if probability of 500
  discharges/5 min./(50x50 km2) 90 in next 12
  hours
• One of the least predictable phenomena
• History (note other criterion) many misses,
  only a few hits and no false alarms
• Goal decrease number of misses and increase
  number of hits, while keeping number of false
  alarms low
• Means new objective probabilistic forecasting
  system

4
Model output statistics (MOS)

• Aim
• Features

To determine a statistical relationship (mostly
via regression) between a predictand (i.e. the
occurrence of a thunderstorm in this case) and
predictors from NWP model forecasts (and possibly
from observations)

• forecasts possible for predictands that are not
  available from direct model output
• (reliable) probabilistic forecasts possible,
  even while using output from a single model run
• separate regression equation for each forecast
  projection (correction of systematic model
  errors)

5
MOS system for (severe) thunderstorms

• 3/2 years of data 1 July 2002 until 1 July 2005
  (warm half years only, i.e. 16 April 15
  October)
• 2/3 part for development and 1/3 part for
  verification
• predictands reprocessed lightning data (Saskia
  Noteboom)
• potential predictor set 1 radar data (0 to 6 h
  only)
• potential predictor set 2 lightning data (0 to
  6 h only)
• potential predictor set 3 17 thunderstorm
  indices, computed from weather model 1
• potential predictor set 4 (derived) DMO
  (forecasts) from model 2
• potential predictor set 5 (co)sine day of the
  year
• regression equations contain at least 2 and at
  most 5 predictors
• severe thunderstorms all 12 regions pooled
• run frequency 8 times per day (every 3 hours)
• forecast projections 0 to 12 h (6-h periods)

6
MOS system for (severe) thunderstorms
Ensemble of advected radar data (0 to 6 h)
(Ensemble of advected) lightning data (0 to 6 h)
NWP model forecasts (0 to 12 h)
Logistic regression (LR) model
Probability of thunderstorms (0 to 6 h/ 6 to
12 h)

• Archive
• 2/3 part for development
• 1/3 part for verification

In developing the LR model you need a 3/2-year
long data archive
7
Example of advection vectors and lightning
data17 July 2004 (1140 UTC)
RV
HV
???
???
???
???
8
Example of logistic regression equation using
only the first predictor (region M-MS period
15-21 UTC)
binary predictand logistic curve
Probability of thunderstorms
Fraction of ensemble with no. of flashes 4
SAFIR 1440 0620
9
Where the are we?

• Introduction Weather alarm for severe
  thunderstorms
• Method Model output statistics (MOS)
• Data used in MOS system for (severe)
  thunderstorms
• Illustration of statistical method
• Definitions of predictands
• Case (10 June 2007)
• Verification results
• Conclusions and outlook

10
Weather alarm for severe thunderstorms (II)

• Weather alarm if probability of 500
  discharges/5 min./(50x50 km2) 90 in next 12
  hours
• 2000-2005 climatology on the basis of this
  criterion only twice a year (between 30 April
  and 15 September)
• Statistical methods are not capable of handling
  such rare events.
• Therefore, other predictand definitions have been
  used.

11
Predictand definitions
Predictand for thunderstorms Probability of gt 1
lightning discharge in a 6h period (00-06, 03-09,
06-12, 09-15, 12-18, 15-21, 18-00 or 21-03 UTC)
in a 90x80 km2 region. Predictands for severe
thunderstorms Conditional probability of X,
Y or Z discharges/ 5 min. in a 6h period in a
90x80 km2 region with condition gt 1 discharge in
the same 6h period in the same region. Here X 50
(all 6-h periods) Y 100 and Z 200 (12-18,
15-21 and 18-00 UTC).
12
Case 17 July 2004 (12-18 UTC 0 to 6 h)
1150 UTC run (based on SAFIR 171140, H 170600
and EC 161200)
Probability of thunderstorms
Cond. prob. of severe thunderstorms ( 50
discharges/ 5 min.) ( 200 discharges/ 5 min.)
Maximum 5-min. lightning intensity
http//bcp127.knmi.nl/vreedede/bclpgm2_arc/latest
.cgi
Clim. prob. of thunderstorms 6-22 Clim.
cond. prob. of severe thunderstorms ( 200
discharges/5 min.) 4 (abs. prob. lt 1 )
13
Case 25 June 2006 (15-21 UTC 6 to 12 h)
0850 UTC run
Probability of thunderstorms
Cond. prob. of severe thunderstorms ( 50
discharges/ 5 min.) ( 200 discharges/ 5 min.)
Maximum 5-min. lightning intensity
Clim. prob. of thunderstorms 5-19 Clim.
cond. prob. of severe thunderstorms ( 200
discharges/5 min.) 5 (abs. prob. lt 1 )
14
Case 25 June 2006 (15-21 UTC 0 to 6 h)
1450 UTC run (based on H 251200 and EC 241200)
Probability of thunderstorms
Cond. prob. of severe thunderstorms ( 50
discharges/ 5 min.) ( 200 discharges/ 5 min.)
Maximum 5-min. lightning intensity
http//bcp127.knmi.nl/vreedede/bclpgm2_arc/latest
.cgi
Clim. prob. of thunderstorms 5-19 Clim.
cond. prob. of severe thunderstorms ( 200
discharges/5 min.) 5 (abs. prob. lt 1 )
15
Case 8 June 2007 (15-21 UTC 6 to 12 h)
09 UTC run (based on H 0806 and EC 0712)
Probability of thunderstorms
Cond. prob. of severe thunderstorms ( 50
discharges/ 5 min.) ( 200 discharges/ 5 min.)
Maximum 5-min. lightning intensity
Clim. prob. of thunderstorms 5-19 Clim.
cond. prob. of severe thunderstorms ( 200
discharges/5 min.) 5 (abs. prob. lt 1 )
16
Case 8 June 2007 (15-21 UTC 0 to 6 h)
15 UTC run (based on H 0812 and EC 0712)
Cond. prob. of severe thunderstorms ( 50
discharges/ 5 min.) ( 200 discharges/ 5 min.)
Probability of thunderstorms
Maximum 5-min. lightning intensity
Clim. prob. of thunderstorms 5-19 Clim.
cond. prob. of severe thunderstorms ( 200
discharges/5 min.) 5 (abs. prob. lt 1 )
17
Case 10 June 2007 (15-21 UTC 6 to 12 h)
09 UTC run (based on H 1006 and EC 0912)
Probability of thunderstorms
Cond. prob. of severe thunderstorms ( 50
discharges/ 5 min.) ( 200 discharges/ 5 min.)
Maximum 5-min. lightning intensity
Clim. prob. of thunderstorms 5-19 Clim.
cond. prob. of severe thunderstorms ( 200
discharges/5 min.) 5 (abs. prob. lt 1 )
18
Verification results 2006 (Probability of gt 1
discharge)
0 to 6 h
6 to 12 h
Brier skill score ()
Brier skill score ()
Brier skill score ()
Time (UTC)
Time (UTC)
19
Reliability diagrams (05-0612-18 UTC 0 to 6h)
50 discharges/ 5 min.
100 discharges/ 5 min.
Observed frequency
Observed frequency
Forecast probability
Forecast probability
20
Reliability diagrams (05-0615-21 UTC 0 to 6h)
50 discharges/ 5 min.
100 discharges/ 5 min.
Observed frequency
Observed frequency
Forecast probability
Forecast probability
21
Reliability diagrams (05-0618-00 UTC 0 to 6h)
50 discharges/ 5 min.
100 discharges/ 5 min.
Observed frequency
Forecast probability
22
Reliability diagram 1 (05-06) 50 discharges/
5 min. (15-21 UTC 0 to 6h)
Observed frequency
Forecast probability
23
Reliability diagram 2 (05-06) 100
discharges/ 5 min. (15-21 UTC 0 to 6h)
Observed frequency
Forecast probability
24
Reliability diagram 3 (05-06) 50 discharges/
5 min. (00-06 UTC 0 to 6h)
Observed frequency
Forecast probability
25
Reliability diagram 4 (05-06) 50 discharges/
5 min. (06-12 UTC 0 to 6h)
Observed frequency
Forecast probability
26
Conclusions and outlook

• Probabilistic forecasts for thunderstorms (gt 1
  discharge) are skilful with respect to the
  2000-2004 climatology.
• Probabilistic forecasts for severe thunderstorms
  ( 50/ 100 discharges per 5 min.) are
  reasonably skilful with respect to the 2000-2004
  climatology.
• The system has been pre-operational at KNMI since
  Spring of 2006 and will be fully operational
  later this year.
• It is expected that this system will help the
  forecasters to decide whether a weather alarm for
  severe thunderstorms should be issued.

27
Verification results (Cond. prob. of
50/100/200 discharges/ 5 min.)
0 to 6 h
6 to 12 h
Brier skill score ()
Brier skill score ()
Time (UTC)
Time (UTC)
28
Reliability diagram 1 50 discharges/ 5 min.
(12-18 UTC 0 to 6h)
BSS 30 Bias 0.2 N 235
Observed frequency
Forecast probability
29
Reliability diagram 2 100 discharges/ 5 min.
(12-18 UTC 0 to 6h)
BSS 32 Bias 4.7 N 235
Observed frequency
Forecast probability
30
Reliability diagram 3 200 discharges/ 5 min.
(12-18 UTC 0 to 6h)
BSS 62 Bias 1.3 N 235
Observed frequency
Forecast probability
31
Reliability diagram 4 300 discharges/ 5 min.
(12-18 UTC 0 to 6h)
Observed frequency
BSS 38 Bias 0.7 N 235
Forecast probability
32
Reliability diagram 5 400 discharges/ 5 min.
(12-18 UTC 0 to 6h)
Observed frequency
BSS 26 Bias 0.1 N 235
Forecast probability
33
Reliability diagram 6 500 discharges/ 5 min.
(12-18 UTC 0 to 6h)
Observed frequency
BSS 13 Bias 1.0 N 235
Forecast probability