combining high-resolution numerical weather predictions ... fileeidgenössisches departement des...
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Eidgenössisches Departement des Innern EDI
Bundesamt für Meteorologie und Klimatologie MeteoSchweiz
Combining high-resolution
numerical weather predictions
with human expertise for
localized weather forecasts
Daniel Cattani, Lionel Moret and Dominique Stussi
Federal Office of Meteorology and Climatology MeteoSwiss
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To be the best one must have
- Reactivity
- Consistency
- High resolution
- Quality
- Many wx parameters
- Top scientific level
3 EMS 4–8 September 2017 | Dublin, Ireland MeteoSwiss
Data4WEB’s goal and underlying
principle
Goal: feed MeteoSwiss website with high resolution temporal
and spatial data.
Underlying Principle : man-machine mix to get the best of
the two worlds:
• Model’s high resolution
• Forecaster’s reactivity and local expertise.
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Modified or DMO
gridded forecast
Gridded analyses
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Reactivity
• Rapid update cycle 30 min. Most recent model runs but also last
forecaster’s modification.
• Automatic measurement integration through INCA (nowcasting
system).
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Consistency
Production of coherent forecasts
• Forecasts supervised by a single person
• Single point forecast source
• Consistency with present weather and active warnings
• Coherence with mobilephone app animations : based one the
same source
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High resolution
Spatial and temporal pattern from high resolution models
reproduced
Downscaling of forecaster supervision with IFS (9 km), COSMO-E
(2km) and COMSO-1 (1km).
Adjusting high-resolution NWP ensemble prediction (COSMO-E) with
regionally and temporally aggregated estimate by forecaster (prototype
Adjusting high-resolution NWP (COSMO-E median) with regionally aggregated estimate by
forecaster
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Quality
Full verification (models, forecasters, final products)
- Allows process improvement
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Many parameters
Mosted desired parameter is the pictogram. But a high demand
exists for addional parameters.
data4WEB ensure consistency between parameters;
• Pictograms, temperature and dispersion, precipitation and dispersion
• Wind, precipitation probability, wind and temperature in free atmosphere,
sunshine, confidence index, stratus’ top, and soon road surface forecast
COSMO-1 COSMO-E (median) IFS-ENS (median)
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High scientific level
data4WEB system built on high level science
• Measurement integration through INCA (2D-analyse and
shortterm forecasts), CombiPrecip (2D-analyse combining
raingauge and radar measurement)
• High resolution models; COSMO-NExT, ECMWF Hres
• Ensemble forecast COSMO-e, and ECMWF ENS
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Perspectives
• Build a complete framework for the verification
• Improve the TS localisation
• New probabilistic approach for precipitations, and winds
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• That’s all
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- Champs de modèles utilisés
- Puis pour chaque point d’intérêt, interpolation spatiale
Principe ‘data4web’ Précipitations