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Concerning Thunderstorm (Potential) prediction Jan PARFINIEWICZ , Inst. of Meteorology and Water Management,MOLC 01-673 Warszawa, ul. Podleśna 61, Poland

Concerning Thunderstorm ( Potential ) prediction

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Concerning Thunderstorm ( Potential ) prediction. Jan PARFINIEWICZ , Inst. of Meteorology and Water Management,MOLC 01-673 Warszawa, ul. Podleśna 61, Poland. Essential: Self-learning Engine Thunderstorms Quantification End-User oriented Warning System. - PowerPoint PPT Presentation

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Page 1: Concerning Thunderstorm ( Potential )  prediction

Concerning Thunderstorm (Potential) prediction

Jan PARFINIEWICZ , Inst. of Meteorology and Water Management,MOLC

01-673 Warszawa, ul. Podleśna 61, Poland

Page 2: Concerning Thunderstorm ( Potential )  prediction

Essential:

Self-learning EngineThunderstorms Quantification

End-User oriented Warning System

Page 3: Concerning Thunderstorm ( Potential )  prediction

Self-learning Engines:

1) Kalman Filter (KF) 2) Artificial Neural Network

some generalisation to KF:after each signal an automatic renewal of the multi-

regression set of parameters

KF++’s: basic statistics allows on dispersion control (clasical physics)

Page 4: Concerning Thunderstorm ( Potential )  prediction

Thunderstorms Quantificationat 1st: SYNOP WW code => Convection Strength (CS) [0-7]

• CS Clouds ------------------------------------- • 0 No - • 1 light Cu • 2 moderate Cu med.• 3 quite strong Cb cal. • 4 Thunder possib. Cb cap.• 5 Thunder • 6 Hail possibility• 7 Hail -------------------------------------to be done:

• Tornado’s SuCell’s

data WW2CS /! 0 1 2 3 4 5 6 7 8 9 +2,1,1,1,0,0,0,0,0,0, !0 +1,0,0,5,1,2,2,6,7,7, !1 +0,0,0,0,0,4,3,3,0,5, !2 +0,0,0,0,0,0,0,0,0,5, !3 +1,0,0,0,0,0,1,0,0,0, !4 +0,0,0,0,0,0,0,0,0,0, !5 +2,1,1,1,1,1,0,1,0,1, !6 +0,0,0,0,0,0,0,0,0,0, !7 +4,4,3,3,3,3,3,3,3,3, !8 +6,5,5,5,5,6,7,6,5,7/ !9

at 2end:

Page 5: Concerning Thunderstorm ( Potential )  prediction

Tempora mutantur at nos mutamur in illiss

The System has been learning & I was learning together Recognizing SuperCell as a

mobile Power Station [W/m2] - TORNADO generator

scaling strength of Tornado :1 – 5where 1 is Chojnice,PL , episode: 20120714:14.30’-15.30’

[W/m2] ~ [MJ/10’*10km^2]

Page 6: Concerning Thunderstorm ( Potential )  prediction

Chojnice,PL , episode: 20120714:14.30’-15.30

Page 7: Concerning Thunderstorm ( Potential )  prediction

End-User oriented Warning System

End-User = CasualtiesEssential:

EMPATHY to CASUALTIES categories:

1) Presentation system (W. Łazarewicz)2) Precise Warning Message System3) End-User Entity including Verification

Page 8: Concerning Thunderstorm ( Potential )  prediction

Presentation: http://awiacja.imgw.pl1)Observed storms: all moderate severe … time scale time scale

Severe Tornado

Page 9: Concerning Thunderstorm ( Potential )  prediction

Presentation: http://awiacja.imgw.pl categories: 1) Observed storms 2) Possible danger zone Pb+ = 1 3) Storm Potential 4) Strength of convection model option COSMO: 07km/14km

1) Observed storms2) Possible danger zone Pb+ = 1

Page 10: Concerning Thunderstorm ( Potential )  prediction

CONCLUSIONS

Include Tornado’s scaling into prediction

Continue search for potential predictors

Dewelop 3-step Warnig System :12h, 3h, 1/2h