symposium-2 - ecmwf · symposium-2 features extensive use of numerical analyses and forecasts,...
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Symposium-2
Towards an optimal combination of numerical prediction and human interpretation
Frédéric Atger, Météo-France
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Modern weather forecasting
Allow/favour forecaster
interpretation
Offer a wide variety of end
products
Get the best of numerical
prediction
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Modern weather forecasting
NWP feeds weather database
Industrialized production
Forecasters interact with
database
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Symposium
(from συµπόσιον ~ party, feast)
� SYstème Météorologique de Prévision, Orienté Services, Intéressant des Usagers Multiples (~ user oriented weather forecasting system for various applications)
� Since 1995 Météo-France regional forecasters (100++) update a database several times a day
� NWP output + post-processed data (MOS, KF) used for initialisation
� Wide range of automatically produced end forecasts
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Symposium
100 km Point wise representation
Variable resolution depends on local climate
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Symposium Products
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Symposium Products
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Symposium Products
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Symposium limitations
� NWP feeding is not exhaustive, nor systematic ("NWP on demand")
� Limited range of products– Some parameters/lead times not available– Forecasts mostly deterministic
� Central forecasting office provides NWP guidance only, no database feeding → lack of consistency
� Pointwise representation makes forecaster supervision a time consuming, boring task
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Symposium-2 features
� Extensive use of numerical analyses and forecasts, including ensemble products, post-processed data, nowcasts, etc
� Automatic elaboration of a wide spectrum of forecast end products, including probabilistic forecasts for all time ranges
� Central forecasting office feeds database, regional offices modify and validate
� Weather parameters are represented under different forms in order to facilitate forecasters interaction with the data base
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Representation of weather parameters
� Point values– Observation style → MOS/KF feeding– Perfect when local effects are essential (eg temperature - not clouds)– Easy to modify… a small number of point values
� Gridded fields– Model style → DMO feeding– Perfect when HR models perform well (eg wind - not precip, fog, etc)– Easy to modify… when space variability is low
� Weather objects– Forecaster style → Forecaster drawing… or NWP post-processing– Perfect for weather (cloud cover, precipitations, visibility)– Easy to modify… with appropriate tools, at the appropriate scale
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100 km
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Identification et suivi d’objets AROME
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Symposium-2 data base
� Point values (eg temperature), gridded fields (eg wind) and weather objects (cloud cover, precipitations, visibility)
� All probabilistic– Probabilities of occurrence (eg thunderstorm)– Quantiles of the pdf (Q10 to Q90, Q1 and Q99 when required)
� From yesterday to medium range– Forecast range: as long as interpretation makes sense– Direct feeding with observations, numerical analyses (satellite, radar,
lightning), nowcasts (radar extrapolation)
� Time step 1h or more, flexible� France and around
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Symposium
Regional Symposium
NWP
End products
Data for production
Prob fcsts
Central
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Symposium-2
RegionalSymposium
NWP
End products
Data for production
Central
Symposium
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Symposium-2 challenges
� Forecasters interact with probabilistic database– Realistic?
� Forecasters in charge of contiguous domains share weather objects (and fields)– Consistency?
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Interaction with probabilistic database
� Quantiles + probabilities → millions of data� Most modifications in deterministic mode (Q50), eg temperature,
cloud cover, etc� Probabilistic component modified through shortcuts leading to
predefined quantiles– Weather description (eg "spare showers")– Intervals (eg "1-3 mm/hour")– Specific probabilities (eg "prob T<0")
� When required, possibility to interact with full pdf (quantiles) and full range of probabilities
� Examples:– Contour of weather objects– Precipitation amount
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Weather objects – initial contouring
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Weather objects – cellular representation
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Modification of rain amount
� Deterministic style: 1mm, max 5mm locally� Probabilistic translation : Q50 = 1mm, Q90 = 5mm� System modifies pdf accordingly:
– Q20 = 0.2mm– Q80 = 3mm– Q99 = 11mm
� Other possibilities:– Forecaster modifies an interval
eg Q20-Q80 = 0-2mm– Forecaster modify Q99 only
0
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2,7 4
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Sharing objects
� Real weather objects (fronts, fog areas, convective cells) move through domain boundaries
� Forecasters in charge of contiguous domains must cooperate, otherwise weather objects will not exist in the database
� Similar feature with fields� Updating rules help cooperation:
– Forecasters have to publish (= make known) any modification they plan to introduce in the database in order to inform their neighbours
– Assumption: when aware of inconsistencies forecasters naturally try to come to an agreement
– Convergence is faster under time constraint… increasing efficiency and reactivity
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Time
Reg. 1
Reg. 2
Reg. 3
…
Reg. n
Cooperation
Production
Forecaster validations
System validation
Central office updates database
Publications
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Cooperation experiment – central level
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Cooperation experiment – regional level
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Future
� Increase reactivity by frequent updating� Take advantage of very high frequency, very high resolution NWP� Make pdf reflect relative performance of NWP vs forecasters
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ensemble
climate
Time
pdf pdf pdf pdf pdf pdf
ensemble
HR model
HR model
HR model
forecaster
HR model
forecaster
forecaster obs
Continuous probabilistic updating
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Symposium-3 ?
Regional
NWPCentral