DEVELOPMENT OF COMMON NOWCASTING TOOLS IN CENTRAL EUROPEan NATIONAL WEATHER SERVICES

DEVELOPMENT OF DEVELOPMENT OF COMMON NOWCASTING TOOLS IN COMMON NOWCASTING TOOLS IN

CENTRAL EUROPEan CENTRAL EUROPEan NATIONAL WEATHER SERVICESNATIONAL WEATHER SERVICES

V. Zwatz-Meise and A. Jann et. al. V. Zwatz-Meise and A. Jann et. al. 1 , N. Strelec-Mahovi, N. Strelec-Mahovićć and D. Drvar and D. Drvar 2 , , A. Horvath et. al. A. Horvath et. al. 3 , M. Jurasek and J. Kanak et. al. , M. Jurasek and J. Kanak et. al. 4, A. Poredoš et. al. , A. Poredoš et. al. 5

presentors: presentors: [email protected]@gov.si

[email protected]@cirus.dhz.hr

1 Zentralanstalt fur Meteorogie und Geodynamik, Austria (ZAMG)1 Zentralanstalt fur Meteorogie und Geodynamik, Austria (ZAMG)2 Meteorological and Hydrological Service of Croatia (MHS)2 Meteorological and Hydrological Service of Croatia (MHS)3 Hungarian Meteorological Service (HMS)3 Hungarian Meteorological Service (HMS)4 Slovak Hydrometeorological Institute (SHMI)4 Slovak Hydrometeorological Institute (SHMI)5 Environmental Agency of the Republic of Slovenia (EARS) 5 Environmental Agency of the Republic of Slovenia (EARS)

INTRODUCTION - BACKGROUND OF COMMON PROJECTS

PROJECTS

2002-2004 Remote sensing based nowcasting techniques (satellite, radar):

– Convective Cell Detection – Displacement Vectors – Forecast Images

Validation and comparison of methods Conceptual models of convective cell life cycle Training Operationalization of methods

2004-2006 Adaptation to MSG

– Nowcasting methods (above) to MSG– Comparison of some methods with NWCSAF– Fog and low clouds detection module

Integrated high resolution precipitation analysis

RESULTS

ContentContent

missing nowc.tools at the beginning of the projectsmissing nowc.tools at the beginning of the projects– AustriaAustria

all radar-based nowcasting modulesall radar-based nowcasting modules

– Slovenia and SlovakiaSlovenia and Slovakia all satellite-based nowcasting modulesall satellite-based nowcasting modules

– CroatiaCroatia all remote-sensing all remote-sensing nowcasting nowcasting modulesmodules

– HungaryHungary some satellite-based Nowcasting modulessome satellite-based Nowcasting modules

joining limited resourcesjoining limited resourcesof central european NWS of central european NWS (Austria, Croatia, Hungary, Slovakia, Slovenia) (Austria, Croatia, Hungary, Slovakia, Slovenia)

– sharing know-howsharing know-how– establishing common software depositoryestablishing common software depository

exchanging software modules exchanging software modules modules then locally adapted & tuned modules then locally adapted & tuned

Introduction - background of common projectsIntroduction - background of common projects

2002-20042002-2004 ("CEI Nowcasting System")("CEI Nowcasting System") CEI = Central European InititativeCEI = Central European Inititative

– remote sensing, pattern recognition, extrapolationremote sensing, pattern recognition, extrapolation

2004-20062004-2006 ("CONEX II")("CONEX II")

COoperation COoperation andand Networking for Networking for EXcellenceEXcellence

– adaptation to MSG, NWC-SAF, fog & low clouds, prec.analysisadaptation to MSG, NWC-SAF, fog & low clouds, prec.analysis

resources of partner institutes resources of partner institutes ++

additionally funded by the additionally funded by the Austrian Federal Ministry for Education, Science and Culture.Austrian Federal Ministry for Education, Science and Culture.

ProjectsProjects

Nowcasting of satellite / radar images Nowcasting of satellite / radar images (SatRad)(SatRad)

Validation & comparison of methodsValidation & comparison of methods Conceptual models of convective cell life cycle (CM of CC)Conceptual models of convective cell life cycle (CM of CC) TrainingTraining Operationalization of methodsOperationalization of methods

Projects /Projects / 2002-20042002-2004 / modules/ modules

Nowcasting of satellite / radar images Nowcasting of satellite / radar images (SatRad)(SatRad)– automatic Convective Cell Detection (CCD)automatic Convective Cell Detection (CCD)

CC CC (Convective Cell)(Convective Cell) FCC FCC (Find Convective Cell)(Find Convective Cell) TITAN TITAN ((TTs s Identification, Tracking, Analysis and NowcastingIdentification, Tracking, Analysis and Nowcasting))



automatic Convective Cell Detection (sat ^ radar)automatic Convective Cell Detection (sat ^ radar)– CC CC ("Convective Cell" method)("Convective Cell" method)

– Typical patterns : Typical patterns : CC reach high levels CC reach high levels local IR T min; local IR T min; CC have a circular or oval shape; diameter varies during the CC have a circular or oval shape; diameter varies during the life cycle.life cycle.

Detection procedure: Detection procedure: find the local minimum; investigate find the local minimum; investigate pixels on 4 concentric circles; a sufficiently large pixels on 4 concentric circles; a sufficiently large difference (center vs. surroundings)difference (center vs. surroundings)

Projects /Projects / 2002-20042002-2004 / modules / SatRad / CCD/ modules / SatRad / CCD

– FCC FCC ("Find CC" method)("Find CC" method) Detection procedureDetection procedure: : Detection of nodal pointsDetection of nodal points; ; Transfer Transfer

of nodal pointof nodal points s into cells/gravity centersinto cells/gravity centers; ; CellsCells’ distance ’ distance and cells’ size tests; Outputand cells’ size tests; Output – – Cells’coordinatesCells’coordinates

– TITAN method TITAN method (newly coded following parts of Dixon and Wiener, 1993)(newly coded following parts of Dixon and Wiener, 1993)

Detection procedureDetection procedure: : data evaluated & adapted to ellipses = "cells"data evaluated & adapted to ellipses = "cells"

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– Displacement Vectors (DV)Displacement Vectors (DV) AMV AMV (Atmospheric Motion Vectors) (Atmospheric Motion Vectors) RMV RMV (Radar Motion Vectors) (Radar Motion Vectors) TRACK TRACK (tracking)(tracking) TITANTITAN



Nowcasting of satellite imagesNowcasting of satellite images– AMV (Atmospheric Motion Vectors)AMV (Atmospheric Motion Vectors)

two succesive imagestwo succesive images

standard cross-correlation technique for rectangular targetsstandard cross-correlation technique for rectangular targets– backward tracking of featuresbackward tracking of features

Projects /Projects / 2002-20042002-2004 / modules / SatRad / DV / AMV/ modules / SatRad / DV / AMV

Time t + T (10 min,...)Time t

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Nowcasting of radar imagesNowcasting of radar images– RMV (Radar Motion Vectors)RMV (Radar Motion Vectors)

two succesive images --> vectors two succesive images --> vectors (cross--correlation method TREC)(cross--correlation method TREC)– average vector of entire image --> blank areasaverage vector of entire image --> blank areas

COTREC algorithm COTREC algorithm (variational techn. & shallow continuity equat.)(variational techn. & shallow continuity equat.)– smoothing of vectors ("COntinuity of TREC vectors")smoothing of vectors ("COntinuity of TREC vectors")

Projects /Projects / 2002-20042002-2004 / modules / SatRad / DV / RMV/ modules / SatRad / DV / RMV

An example of RMV field obtained by TREC method (left), smoothed field using COTREC method (right).

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ProjectsProjects 2002-20042002-2004 / modules / SatRad / DV / TRACK/ modules / SatRad / DV / TRACK

Nowcasting of radar ^ sat imagesNowcasting of radar ^ sat images– TRACK TRACK

inputinput == cells’coordinates (from FCC cells’coordinates (from FCC module) and time sequence of imagesmodule) and time sequence of images

cells’parrents detectioncells’parrents detection cells’trajectory constructioncells’trajectory construction cells’trajectory time extrapolation cells’trajectory time extrapolation

T(+2)T(+1)T(0)T(-1)T(-2)T(-3)T(-n)

…

Input data:- Time sequence of images:

Tracking of cells’ centers in time sequence of images Time extrapolation of cell centers

Location ofcell centers

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Nowcasting of radar imagesNowcasting of radar images– TTITANITAN coded following coded following Dixon and Wiener, 1993Dixon and Wiener, 1993

method for radar tracking and echo forecastmethod for radar tracking and echo forecast– cell detection at t0 and t1

normalized eigenvectors, centroid position, parameters like area of the storm, etc.

– cell pairing (parents --> no merging, splitting !)

– cell forecast extrapolation of DVs and trends of ellipses' extrapolation of DVs and trends of ellipses'

parametersparameters validation on case studies

– "diagnostic" mode OK for e.g. climatology of convective objects

– poor forecasts --> "prognostic" mode abandoned

ProjectsProjects 2002-20042002-2004 / modules / SatRad / DV / TITAN/ modules / SatRad / DV / TITAN

new

10' TITANcast (above) missed cells in an actual radar image (below)



– Displacement Vectors (DV)Displacement Vectors (DV) AMV AMV (Atmospheric Motion Vectors) (Atmospheric Motion Vectors) RMV RMV (Radar Motion Vectors) (Radar Motion Vectors) TRACK TRACK (tracking)(tracking) TITANTITAN

– Forecast Images (FI)Forecast Images (FI) FCI FCI (based on AMV)(based on AMV) dBcast dBcast (based on RMV)(based on RMV) TITANTITAN



Nowcasting of sat ^ radar imagesNowcasting of sat ^ radar images– FCI (ForeCast Image)FCI (ForeCast Image)

WhatWhat– computes forecast images from computes forecast images from DVDV field and the second involved image field and the second involved image– for any kind of imagery for any kind of imagery – under the assumption of a motion field remaining unchanged with timeunder the assumption of a motion field remaining unchanged with time

HowHow– Computes for each pixel the trajectoryComputes for each pixel the trajectory– repeatedly applying the displacement given in the repeatedly applying the displacement given in the DDV fileV file

hence, forecasts for lead times = multiples of the hence, forecasts for lead times = multiples of the DDV intervalV interval– considerable smoothing of the trajectory field at every time stepconsiderable smoothing of the trajectory field at every time step– ddetermination of pixel values of the forecast image:etermination of pixel values of the forecast image:

weighted mean of all pixels which are forecast to overlapweighted mean of all pixels which are forecast to overlap– ffilling of gaps with averages of adjacent pixel valuesilling of gaps with averages of adjacent pixel values

Projects /Projects / 2002-20042002-2004 / modules / SatRad / FI / FCI/ modules / SatRad / FI / FCI

Actual sat image and corresponding AMV field (left) forecast sat images (right).

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Nowcasting of radar imagesNowcasting of radar images– dBcastdBcast ( (fforeoreccast ast radar iradar image)mage)

WhatWhat– computes forecast images from computes forecast images from RRMV field and the second involved imageMV field and the second involved image

– for any kind of imagery for any kind of imagery

– under the assumption of a motion field remaining unchanged with timeunder the assumption of a motion field remaining unchanged with time HowHow

– extrapolated echo patterns <-- backward-time integration of trajectoriesextrapolated echo patterns <-- backward-time integration of trajectories

– ... similar to FCI (see above) ...... similar to FCI (see above) ...

Projects /Projects / 2002-20042002-2004 / modules / SatRad / FI / / modules / SatRad / FI / dBcastdBcast

Error of dBcast (from bottom to top): stratiform case, frontal convection, organized convection, air--mass

convection

Originating radar image and corresponding AMV field (left), 30' forecast radar image (middle), actual radar

image (right).

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Projects /Projects / 2002-20042002-2004 / modules / validation/ modules / validation & comparison & comparison

nowcast of satellite imagenowcast of satellite image– nowcast: +30,+60,+120 min; period: Sep-Jan 03, number of cases: > 4000nowcast: +30,+60,+120 min; period: Sep-Jan 03, number of cases: > 4000

evaluation method:evaluation method:– MeteoSat "B" MeteoSat "B" image divided into squares; image divided into squares; filled with 0/1 when > thresholdfilled with 0/1 when > threshold– for every square: contingency tablesfor every square: contingency tables

evaluated method: evaluated method: FCI method (using AMV fields);FCI method (using AMV fields); e.g. +120 min:e.g. +120 min:– average / best / worst : average / best / worst : POD % ~POD % ~ 88 / 94 /67 88 / 94 /67; ; FAR FAR %% ~ 11 / 6 / 30 ~ 11 / 6 / 30

nowcast of sat Conv.Cell positionnowcast of sat Conv.Cell position– nowcast: +60 min; period: summer 2003 (nov&dec/2003), number of cases: 44 (600)nowcast: +60 min; period: summer 2003 (nov&dec/2003), number of cases: 44 (600)

evaluation method:evaluation method:– a Central European sector of the sata Central European sector of the sat image divided into squares; image divided into squares;– for every square: contingency tablesfor every square: contingency tables

compared 4 methods: FCC (or CC) + TRACK (or AMV);compared 4 methods: FCC (or CC) + TRACK (or AMV); quite similar resuts: quite similar resuts: – POD ~POD ~ 30% 30%; FAR ~ 65% (allowing app. 30km of CC distances); FAR ~ 65% (allowing app. 30km of CC distances)– POD ~POD ~ 45% 45%; FAR ~ 45% (allowing app. 45km of CC distances); FAR ~ 45% (allowing app. 45km of CC distances)– POD ~POD ~ 65% 65%; FAR ~ 20% (allowing app. 100km of CC distances); FAR ~ 20% (allowing app. 100km of CC distances)

nowcast of radar Conv.Cell positionnowcast of radar Conv.Cell position– nowcast: +30 min; period: summer 2002&2003, number of cases: > 800nowcast: +30 min; period: summer 2002&2003, number of cases: > 800

evaluation method:evaluation method:– RadarRadar image divided into squares; image divided into squares;– for every square: contingency tablesfor every square: contingency tables

evaluated method: evaluated method: FCC + TRACKFCC + TRACK– POD ~POD ~ 37% 37%; FAR ~ 39% (allowing app. 5km of CC distances); FAR ~ 39% (allowing app. 5km of CC distances)– POD ~POD ~ 62% 62%; FAR ~ 20% (allowing app. 15km of CC distances); FAR ~ 20% (allowing app. 15km of CC distances)

Projects /Projects / 2002-20042002-2004 / modules / validation/ modules / validation & comparison 2 & comparison 2

nowcast of precipitation areasnowcast of precipitation areas diagnosed QUALITATIVELY (yes/no)diagnosed QUALITATIVELY (yes/no)

– interpolatiinterpolation on ((weather reportsweather reports, , IR sat IR sat > > threshold, radar) to sat_gridthreshold, radar) to sat_grid then then extrapolated with FCI method extrapolated with FCI method (using AMV fields)(using AMV fields)

– nowcast: +30,+60,+120 min; period: Jan-Sep 03, 3 hourly, nowcast: +30,+60,+120 min; period: Jan-Sep 03, 3 hourly,

– every pixel within Austriaevery pixel within Austria all weather situations/ all pixels : all weather situations/ all pixels : no signal - comparable to persistenceno signal - comparable to persistence "nowcast" situations/ "interesting" pixel = "nowcast" situations/ "interesting" pixel = starts/stops/keeps starts/stops/keeps rainingraining

– % of correct pixels = app. 70% (30') to 60 % (120') --- 10% better than persistence % of correct pixels = app. 70% (30') to 60 % (120') --- 10% better than persistence "nowcast" situations/ "changing" pixel = "nowcast" situations/ "changing" pixel = starts/stopsstarts/stops rainingraining

– % of correct pixels = app. 30% (30') to 40 % (120')% of correct pixels = app. 30% (30') to 40 % (120')

– precipitation areas (manually selected, automatic counting of pixels)precipitation areas (manually selected, automatic counting of pixels)– % of correct pixels = % of correct pixels = app. 50% (120') for MCS to 70 % (120') for frontsapp. 50% (120') for MCS to 70 % (120') for fronts

Projects /Projects / 2002-20042002-2004 / modules / validation/ modules / validation & comparison 3 & comparison 3

PODs, FARs ... and what now?PODs, FARs ... and what now?– Q: are such methods really useful?Q: are such methods really useful?– A: a A: a useful nowcasting product must:useful nowcasting product must:

lead to better results than persistence : lead to better results than persistence : – some of the above comparisons indeed confirmed that methods (e.g. nowcast of some of the above comparisons indeed confirmed that methods (e.g. nowcast of

convective cells) can be better than persistence up to three times,convective cells) can be better than persistence up to three times, assist at subjective nowcasting : assist at subjective nowcasting :

– some of the investigations among operational forecasters showed that methods are some of the investigations among operational forecasters showed that methods are accepted reasonably well in the subjective operational practice:accepted reasonably well in the subjective operational practice:

example answers to the iexample answers to the investigationnvestigation (G: general fcast, A: airport) (G: general fcast, A: airport)

GG AA TogetherTogether

AMVAMV 44 22 66/1/111

FCIFCI 55 33 88/1/111

VIS+IRVIS+IR 33 22 5/15/111

AMVCCAMVCC 55 11 66/1/111

FCICCFCICC 77 11 8/18/111

The satellite based nowcasting products give better overview of atmospheric evolution

(agreed by 8).

Which products do you use in the operational

process? VeryVery MostlyMostly UsefulUseful SometimesSometimes NotNot

AMVAMV 11 22 55 33

FCIFCI 55 44 22

VIS+IRVIS+IR 55 44 22

AMVCCAMVCC 55 33 33

FCICCFCICC 44 44 33

How useful you find each product?

Q: In which situations are sat. nowcasting products valuable?

A: “nice advection”; frontal zone with intensive Cb; stratiform process (WF better, CF "also good"); time of frontal passage; determination of high/low clouds; tracking of storm cells;




Projects /Projects / 2002-20042002-2004 / modules / / modules / CM of CCCM of CC

Conceptual models of life cycles of convective cells Conceptual models of life cycles of convective cells – using time series of remote sensing datausing time series of remote sensing data

– using LAM models (Aladin - MM5) --> no firm resultsusing LAM models (Aladin - MM5) --> no firm results




Projects /Projects / 2002-20042002-2004 / modules / / modules / trainingtraining

brochure, posters, etc.brochure, posters, etc. Computer Aided Learning (CAL) - Training CDComputer Aided Learning (CAL) - Training CD Joined Joined Training Workshop Training Workshop ((sponsored by EUMETSAT)sponsored by EUMETSAT)

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Projects /Projects / 2002-20042002-2004 / modules / / modules / operationalization operationalization

commonly developed methods --> operational usecommonly developed methods --> operational use– examples of "national" operational visualization examples of "national" operational visualization

of "common" nowcast of "common" nowcast products:products:

new data source - MSG

– adaptation of the developed CEI nowcasting methods to MSG

– comparison of some CEI methods with NWC SAF products

– fog and low clouds detection module

integrated high resolution precipitation analysis

adaptation of NWP output


Adaptation to MSGAdaptation to MSG– AMV, FCIAMV, FCI

– common RGB compositescommon RGB composites detection/dyagnosis of certain featuresdetection/dyagnosis of certain features

– combinations of channels (e.g. combinations of channels (e.g. 139139, , 321321, etc.), etc.)– difference of channels (e.g. 4-9 for fog, etc.)difference of channels (e.g. 4-9 for fog, etc.)

Projects /Projects / 2004-20062004-2006 / modules / MSG / AMV, FCI, RGB/ modules / MSG / AMV, FCI, RGB

MSG-1, 5 June 2003, 11:30 UTC, RGB 01-03-09

Example of 120 min forecast out of 15 min interval between two successive IR 10.9 images; grey shades for current image, vectors for AMVs, isolines for some values of nowcast image

Adaptation to MSGAdaptation to MSG

– Conceptual models of convective cellsConceptual models of convective cells

comparison of conv.cell detection algorithms comparison of conv.cell detection algorithms CEI (CC, FCC) CEI (CC, FCC)

vs.vs."Rapidly Developing Thunderstorm" (Nowcasting-SAF)"Rapidly Developing Thunderstorm" (Nowcasting-SAF)

inclusion of MSG channels for cloud phase and life cycleinclusion of MSG channels for cloud phase and life cycle e.g. e.g. 3 (1.6 µm), 4 (3.9 µm), HRVIS3 (1.6 µm), 4 (3.9 µm), HRVIS

– eventually improved "cell detection" algorithmeventually improved "cell detection" algorithm e.g. ch10 - ch9 filter to distinguish e.g. ch10 - ch9 filter to distinguish

non-convective phenomena (such as lee non-convective phenomena (such as lee clouds) clouds)

from actual convection. from actual convection.

Projects /Projects / 2004-20062004-2006 / modules / MSG / CEI vs. NWCSAF/ modules / MSG / CEI vs. NWCSAF

Adaptation to MSG Adaptation to MSG – fog and low cloud detectionfog and low cloud detection

Qualitative analysis of low cloudsQualitative analysis of low clouds– thresholds --> binarized image (yes/no)thresholds --> binarized image (yes/no)

– day- & night-time algorithmday- & night-time algorithm difference (e.g. ch4-ch9)difference (e.g. ch4-ch9) combination (e.g. ch9, ch4, diff.)combination (e.g. ch9, ch4, diff.) dawn/dusk problemsdawn/dusk problems

Projects /Projects / 2004-20062004-2006 / modules / MSG / fog & low clouds/ modules / MSG / fog & low clouds

Example of "fog and low clouds" product. Red areas indicate appearance of this phenomena

(according to the algorithm). Overlayed is MSG IR 10.9 image and ww from SYNOPs.

Area left of the tilted line (purple) illustrates the dawn/dusk sensitivity of the algorithm.

Adaptation to MSG Adaptation to MSG – fog and low cloud detectionfog and low cloud detection

(more info) --> P (more info) --> P 4.304.30: : AA. . WirthWirth, , ZAMGZAMG, , AustriaAustria. Day/night-time low cloud . Day/night-time low cloud

detection using different spectral detection using different spectral bands from meteosat second generationbands from meteosat second generation

Qualitative analysis Qualitative analysis + surface.temperature + surface.temperature --> --> lower fog boundarylower fog boundary

– model model (or (or objective analysis)objective analysis) T T vs. vs. cloud top T (ch 10.8)cloud top T (ch 10.8) in certain range -- > high probability for fog reaching the groundin certain range -- > high probability for fog reaching the ground

Q: ? to use NWCSAF Cloud Type product instead ?Q: ? to use NWCSAF Cloud Type product instead ?– classes „low“ and „very low“classes „low“ and „very low“

– although often confusing low clouds and snow ...although often confusing low clouds and snow ...

– ... it is still developing !... it is still developing !

Projects /Projects / 2004-20062004-2006 / modules / MSG / fog & low clouds 2/ modules / MSG / fog & low clouds 2

Integrated high-resolution precipitation analysisIntegrated high-resolution precipitation analysis

– Quantitative analysis of precipitationQuantitative analysis of precipitation Production of (national) integrated prec.fields Production of (national) integrated prec.fields

– from surface observations, radar data, NWC-SAF productsfrom surface observations, radar data, NWC-SAF products

Synthesis of the (national) prec.fields --> supranationalSynthesis of the (national) prec.fields --> supranational– exchanging national productsexchanging national products

– with common softwarewith common software

– Semiquantitative analysis Semiquantitative analysis where the quantitative analyses are missing where the quantitative analyses are missing

--> beyond the common --> beyond the common regionregion

– including e.g. foreign countries / sea / mountainsincluding e.g. foreign countries / sea / mountains

intensity in e.g. 3 categories (light/medium/strong) intensity in e.g. 3 categories (light/medium/strong) – from an available combination of NWC-SAF products/radar from an available combination of NWC-SAF products/radar

data/conventional precipitation measurementsdata/conventional precipitation measurements

Projects /Projects / 2004-20062004-2006 / modules / MSG / Precip. analysis/ modules / MSG / Precip. analysis

Adaptation of NWP outputAdaptation of NWP output

– in : in : llocal observations, remote sensing data, high resolution topographyocal observations, remote sensing data, high resolution topography

– between: objective analysis, adaptation of DMO, assimilation of local data, ...between: objective analysis, adaptation of DMO, assimilation of local data, ...

– out: out: analysis & nowcasting fieldsanalysis & nowcasting fields ; frequent update ...; frequent update ...

operational national examples:operational national examples:– MEANDER (H)MEANDER (H)

((more info) --> O 6more info) --> O 6..14: 14: AA. Horvath. Horvath

NNowcasting system of the hungarian meteorological serviceowcasting system of the hungarian meteorological service

– INCA (A)INCA (A)

((more info) --> O 2more info) --> O 2..13: T. Haiden13: T. Haiden

Prediction of convective cell initiation in mountainous terrain Prediction of convective cell initiation in mountainous terrain using a high-resolution analysis systemusing a high-resolution analysis system

– exchange of know-how, collaboration, ...., --> common orientationexchange of know-how, collaboration, ...., --> common orientation remote-sensing remote-sensing & NWP & NWP & operational nowcasting & operational nowcasting

specialists specialists

Projects /Projects / 2004-20062004-2006 / modules / MSG / NWP/ modules / MSG / NWP

nothing revolutionary ...nothing revolutionary ...– way of work -- common for projectsway of work -- common for projects– scientifically -- well-known, relatively simple methodsscientifically -- well-known, relatively simple methods– ... ...

... but noteworthy anyway... but noteworthy anyway– operationally:operationally:

improved or even first operational nowc.applications improved or even first operational nowc.applications in partner NWServicesin partner NWServices

resources were "optimized":resources were "optimized":– used for adaptation and local tuning used for adaptation and local tuning

instead instead for re-coding of algorithmsfor re-coding of algorithms "... spirit of international collaboration is enhanced ...""... spirit of international collaboration is enhanced ..."

– operational exchange of nowc.data became more possibleoperational exchange of nowc.data became more possible

– and so, as such:and so, as such: " ... an example of possible fruitful cross-border meteo-collaboration ..." " ... an example of possible fruitful cross-border meteo-collaboration ..."

:-):-)

ResultsResults

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Brown symbols: cells failing the VIS test

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Demonstration of the FCC detection process

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AMVs + CCs zoom 29 August 2003

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AMVs + ccs zoom 29 August 2003/ 17:00

IR nowc + ccs zoom 29 August 2003 /17:00 + 0030




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Radar 05 October 2003 09:20




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Radar 05 October 2003 09.50 + 10 Min




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Documents

DEVELOPMENT OF COMMON NOWCASTING TOOLS IN CENTRAL EUROPEan NATIONAL WEATHER SERVICES