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"The concept of meteorological triggers - staying ahead of (severe) weather developments" by Marcel Molendijk

The concept of meteorological triggers - staying ahead of ...€¦ · This presentation z The forecaster’s domain z overview z challenges for the forecaster (changing the data into

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Page 1: The concept of meteorological triggers - staying ahead of ...€¦ · This presentation z The forecaster’s domain z overview z challenges for the forecaster (changing the data into

"The concept of meteorological triggers- staying ahead of (severe) weather

developments"

by Marcel Molendijk

Page 2: The concept of meteorological triggers - staying ahead of ...€¦ · This presentation z The forecaster’s domain z overview z challenges for the forecaster (changing the data into

This presentationThe forecaster’s domain

overview challenges for the forecaster (changing the data into information)(future) changes in this domain

The concept of meteorological triggers (“wake-up calls”)the general concept (supporting the forecaster)example: trigger dashboard

The storm surge of last Friday (not really part of this presentation…)

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ECMWF (2)

HIRLAM (4)

UKMO (4)

VIMOLA (24)

SATTELITE obs (96

)

RADAR obs (288)

ground and upper air observations (24hrs/day)

The forecaster’s domain (simplified) at KNMI

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find relevant data, convert into information and communicate, on time.

Loads of observations: ground obs., upper air, RADAR, satellite (MSG), ..Many models: ECMWF, HIRLAM, RACMO, UKMO, VIMOLA

DMO and postprocessed data (statistical, downscaling)Product constraints: consistency, timely production, accuracy, ..

Forecaster’s challenge

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(IT) developments: more data (e.g. MSG) more frequent (model) updatesimproved modelsmore new products (improved models, more data available)

Increased automatic productionMore products can be produced automatically without loss of meteorological qualityHow to keep the forecaster alert? (“Less to do is lessaware”)

(future) changes in the forecaster’s domain

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The haystack of meteorological data will continue to grow…

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Looking for relevant data; the needle?All information useful for the forecaster to do his work right(on time, accurate, correct information..)

most of the time this data is (by far) less then the amountof data brought to the forecaster

monitoring observations and models account for 50% of the forecaster’s working time

production of alerts and warnings is prone to human errorstight working schedule makes elaborations on interesting

weather developments difficult

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Helping the forecaster to find the needleAutomatic determination of (severe) weather events by“trigger” generation modules:

combining product (warning) threshold and area definitionwith observations (ground, upper air, satellite, RADAR, etc.), forecasts and many more (e.g. comparing model-model, model-obs.)

Triggers are brought to central forecaster’s dashboardWhat, when and where is presented in short; furtherbackground information is provided by linked Intranet pages

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The concept of triggers

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thresholdvalue

Valid period parameter

urladditionalinformation

detailed info

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remove triggers (trigger generation time)

remove triggers (valid period)

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Filtering triggers (filtering filters…)

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Geographical presentation of triggers

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Trigger in detailKNMI Weather-alarm

amount of precipitation> 75 mm / 24 hours or >100 mm / 72 hoursAny area of 50x50 km or coherent structure of 50 km

5 min RADAR data calibrated with ground observations

Trigger generating module produces trigger if thresholds are met

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RADAR+ spatial distr- amount

ground obs.- spatial distr+ amount

trigger module+ spatial distr+ amount

Combining with warningdefinition (area, treshold)

trigger dashboard

detailed info(intranet)

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Trigger for the number of lightning strikes observed (>500/5 min 50x50 km)

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Actual status and further developmentsTriggers implemented:

Observations: amount of precipitation, snow, lightning, windspeedForecasts: EPS-based information on (a.o.) windspeed, gusts, amount of precipitation, snow, visibility.

Further developments:Extension of type (stormsurge) and number of triggers & triggergeneration modules(model vs. products, model vs. obs, model1 vs model2, monitoring production-schedule, etc.)Iterating process with forecasters (risk in large number of triggers..)

Other developments (NinJo, Google-Maps, etc.)Connection with production tools (“first guess products”)

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Source: University of Oklahoma

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Storm surge09-11-2007

..closed for the first time ever..

Pictures: www.nos.nl

..although that wasn’t really necessary..

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Storm surge support at KNMIEPS winds in North sea coupled to

WOMOD (statistical model)WAQUA (dynamic wind surge model)

Extra surge shiftClose cooperation with Dutch Storm Surge Warning Service

Triggers not yet implemented

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Area’s and tidal barriers of the DutchStorm Surge Warning Service

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Visit of our government minister (not planned)..

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367 cm (and an impressed government minister!)

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Special thanks to my colleaguesNico MaatRobert MureauHans de Vries

http://www.knmi.nl/~jwdv/WAQUA/EPS