© CNMCA Cap. Davide MELFI Italian Air Force Meteorological Service CNMCA An Italian tool for...

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Cap. Davide MELFIItalian Air Force Meteorological ServiceCNMCA

An Italian tool for convection: NEFODINA

Session 4 ofConvection Week 2011, 6-9 June 2011

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OUTLINE

• The model: NEFODINA

• Features - Case studies

• Summary and Outlook


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Classification

Classes DurationLinear Dim. (Km/pixels)

Area (Km2/pixels)

Single Cell 30-50 min. 5-10 / 1-2 20-80 / 1-3

Multicell ThunderstormSquall line

2-6 hours 20-30 / 3-5 310-700 / 8-20

Supercell 1-6 hours 20-30 / 3-5 310-700 / 8-20

Mesoscale convective system

6-12 hours 350-500 / 60-80100.000-200.000/

2800 - 5500


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Software scheme10.8 m (IR) – time t

6.2 m (WV1) – time t


10.8 m (IR) – time t-1

CONVECTIVE OBJECTS (COs) DETECTION AND TRAKING MODEL

NEFODINA

DYNAMIC ANALYSIS

STATIC ANALYSIS(Tmin, Tmed, Tmod, Area, shape, slope, etc..)

Detection in the IR image of all possible COs using a varying threshold method

Calibration

Filter application to sharpen cloud edges

ASCII OUTPUT WITH STORY OF COs

First detection

LIFE PHASE EVALUATION

Already detected

GRAPHIC OUTPUT

PARENTAL RELATIONSHIPCOs Discrimination on the base

of IR features by comparison with previous slot

CROSS ANALYSISCOs Discrimination on the base

of IR, WV1, WV2 features


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Detection of Cloudy ClusterVARIABLE THRESHOLD ALGORITHM

200 K° < TB < 236 K°


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10.8 m (IR) – time t-1


NEFODINA

DYNAMIC ANALYSIS

STATIC ANALYSIS


Calibration



First detection


Already detected

GRAPHIC OUTPUT






Slope index Ellipticity Cloud Top Area Minimum Temperature Modal Temperature Main Temperature

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10.8 m (IR) – time t-1


NEFODINA

DYNAMIC ANALYSIS



Calibration



First detection


Already detected

GRAPHIC OUTPUT






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Parental Relationship

Cross correlation between the COs detected at time t and the COs detected at time (t-1) evaluated minimizing a weighted distance function d on the position of the centre of gravity d1, minimum temperature d2 and modal temperature d3

23

22

21 dddd


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10.8 m (IR) – time t-1


NEFODINA

DYNAMIC ANALYSIS



Calibration



First detection


Already detected

GRAPHIC OUTPUT






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Cross Analysis

7 JULY 2005 - 17:30

WV1 (6.2 m) WV2 (7.3 m)IR (10.8 m)

We classified as convective the object with the same features in the IR and WV channels


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Cold Objects

Some objects near the limit of the troposphere and therefore near the thermal inversion, showed a top more crushed and cold so they weren’t identified like convective from the algorithm because discarded for the

low value of the slope index

DETECTION ERROR SOLVED:

Nefodina, in spite of the optimal demonstrated performances, is constantly monitored


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Case study: 7 May 2005

Cold Objects


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10.8 m (IR) – time t-1


NEFODINA

DYNAMIC ANALYSIS



Calibration



First detection


Already detected

GRAPHIC OUTPUT






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Life Cicle of a Convective Cell

The Mesoscale Convective Systems (MCSs) are often correlated with heavy

rainfall, thunderstorms and hail showers, frequently causing significant damage

The most intensive weather activities occur during the growing phase


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Development/Dissolving phase


Studies on the minimum temperature, area and slope index of objects detected in IR window channel and WV channels of METEOSAT6 has pointed out that the dissolving phase of the CO starts really only when the cloud top descent is simultaneous to a WV decrease.

-56-54

-52-50

-48-46

-44-42

-40

1 3 5 7 9 11 13 15 17 19 21 23 25

time (10 minutes)

BT

(C

)

7.001 111 WVWVIR TTT

7.001 111 WVWVIR TTT

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GRIB FILE

Model Fields

New Output




10.8 m (IR) – time t-1


NEFODINA

DYNAMIC ANALYSIS



Calibration



First detection


Already detected

GRAPHIC OUTPUT






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10.8 m (IR) – time t-1


NEFODINA

DYNAMIC ANALYSIS



Calibration



First detection


Already detected

GRAPHIC OUTPUT






© CNMCA An Italian tool for convection: NEFODINA

Output


OutputWith red shades are

indicated the cloud top

of the detected

convective cell

forecasted in growing

phase

With pink shades are

indicated the cloud top

of the detected

convective cell

forecasted in

decreasing phase.

The dark red and dark

pink colors are used to

indicate the most

intensive convective

regions.

Blue shades are used to show the cloud to which we are interested.

Dark blue is used for lowest cloud and light blue/yellow for highest

clouds.

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Output

num

ero

iden

tific

ativ

o de

lla c

ella

AA

MM

GG

G

ora

min

uti

riga

colo

nna

Tm

in K

(IR

)

Tm

ed K

(IR

)

Tm

od K

(IR

)

Tm

in K

WV

6.2

Tm

ed K

WV

6.2

Are

a (I

R)

slop

e in

dex

(IR

)

27 5 2 15 12 30 243 346 219,9 227,8 227,4 222,4 221,9 2 3,627 5 2 15 12 15 241 346 221,2 227,2 225 223 223 2 2,427 5 2 15 12 0 241 352 221,2 226,7 223,8 223,3 222,7 2 327 5 2 15 11 45 242 353 219,9 226,6 222,5 222,4 221,8 2 3,627 5 2 15 11 30 244 354 218,5 226,8 222,5 221,9 220,8 2 2,927 5 2 15 11 15 244 355 219,9 226,6 222,5 222,3 221,5 2 3,627 5 2 15 11 0 247 353 219,9 226,9 223,8 222,2 221,5 2 4,227 5 2 15 10 45 248 354 218,5 227,5 226,2 221,5 221,1 2 2,527 5 2 15 10 30 248 354 219,9 228,4 227,4 222,5 221,4 2 2,627 5 2 15 10 15 248 354 219,9 228,9 230,8 222,7 221,9 2 3,227 5 2 15 10 0 247 354 221,2 229,2 231,9 223,4 223,2 2 427 5 2 15 9 45 246 355 222,5 229,9 227,4 224,1 223,7 2 3,127 5 2 15 9 30 245 355 222,5 230,6 233 224,1 223,9 2 2,927 5 2 15 9 15 246 357 223,8 231,3 230,8 224,5 224,1 2 4,327 5 2 15 9 0 247 358 225 231,6 234 225,1 224,5 2 3,427 5 2 15 8 45 248 360 226,2 231,1 231,9 225,7 225,7 2 1,727 5 2 15 8 30 251 362 227,4 232,8 234 226 226,6 2 1,1

-999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -99928 5 2 15 12 30 240 149 225 230,7 233 225,5 224,4 2 4

-999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -99930 5 2 15 12 30 277 139 219,9 228,2 222,5 223 222,3 2 4,1

-999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -99932 5 2 15 12 30 265 512 228,5 232,2 230,8 0 0 2 5,832 5 2 15 12 15 266 508 227,4 232,8 233 225,9 227,1 2 3,432 5 2 15 12 0 266 502 228,5 232,3 230,8 225,8 227,5 2 4,2

Ascii file with the storyAscii file with the story


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Case study: 2 July 2009

SINGLE CELLSCase study: 03 Agoust 2009

MULTICELL

Case study: 23 September 2009

SUPERCELL



Verification Against Lightning Data

Correlation = 84%

Case study: 2 July 2009


NEFODINAEvery area capability:Maritime operations

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Conclusions

• NEFODINA has been developed to detect and forecast the severe convective systems present on the scene and all the convective cells inside these systems.

• This is an important support for forecasters of the IAFMS, who test every day the performance and the reliability of this product, to diagnose the convective activity, evaluate its severity and its potential development.

• Early warning with second derivative

• Convection and Lightning

• The last three days of data on ftp.meteoam.it (contact point [email protected])


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