Probabilistic forecasts of (severe) thunderstorms for the purpose of

issuing a weather alarm

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

KNMI

IUGG 2007

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

IUGG 2007

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

IUGG 2007

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)

IUGG 2007

MOS system for (severe) thunderstorms

Ensemble of advectedradar data (0 to +6 h)

(Ensemble of advected)

lightning data (0 to +6 h)

Probability of thunderstorms (0 to +6 h/ +6 to +12 h)

In developing the LR model you need a 3/2-year long data archive

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

NWP model forecasts (0 to

+12 h)

Logistic regression (LR) model

Example of logistic regression equation

using only the first predictor (region M-MS; period: 15-21 UTC)

)....exp(1

1

110 ppXaXaaP

(event) :regression Logistic

Pro

bab

ility

of

thu

nd

ers

torm

s

Fraction of ensemble with no. of flashes ≥ 4 [SAFIR 1440 +0620]

binary predictandlogistic curve

IUGG 2007

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.

IUGG 2007

Predictand definitions

Predictand for thunderstorms: Probability of > 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 > 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).

IUGG 2007

Case 10 June 2007 (15-21 UTC; +6 to +12 h)

09 UTC run (based on H 1006 and EC 0912)

‘Clim.’ prob. of thunderstorms: 5-19 % ‘Clim.’ cond. prob. of severe thunderstorms (≥ 200 discharges/5 min.): 5 % (abs. prob.: < 1 %)

Probability of thunderstorms

Cond. prob. of severe thunderstorms(≥ 50 discharges/ 5 min.) (≥ 200 discharges/

5 min.)

Maximum 5-min. lightning intensity

IUGG 2007

Verification results 2006 (Probability of > 1 discharge)

Bri

er

skill

sco

re

(%)

0 to +6 h +6 to +12 h

Bri

er

skill

sco

re (

%)

Time (UTC) Time (UTC)

Bri

er

skill

sco

re

(%)

IUGG 2007

Reliability diagrams (’05-’06;15-21 UTC; 0 to +6h)

Ob

serv

ed

fr

eq

uen

cy

Forecast probability

Ob

serv

ed

fr

eq

uen

cy

Forecast probability

≥ 50 discharges/ 5 min. ≥ 100 discharges/ 5 min.

IUGG 2007

Conclusions and outlook

Probabilistic forecasts for thunderstorms (> 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.