multi-model short-range ensemble forecasting at spanish met institute j. a. garcía-moya, a....
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Multi-model Short-Range Ensemble Forecasting at
Spanish Met Institute
J. A. García-Moya, A. Callado, P. Escriba, C. Santos, D. Santos, J. Simarro
NWP – Spanish Met Service AEMET
10th COSMO General MeetingCracovia – September 2008
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SREPS at AEMET
Multi-model Multi-boundaries.72 hours forecast two times a day.Characteristics:
5 limited area models.4 boundary and initial conditions
Resolution: 0.25º, 40 levels.20 member ensemble every 12 hours.Time-lagged Super-Ensemble of 40 members every 12 hours.
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Multi-model
Hirlam (http://hirlam.org).
HRM from DWD (German Weather Service).
MM5 (http://box.mmm.ucar.edu/mm5/).
UM from UKMO (UK Weather Service).
COSMO from COSMO consortium
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Multi-Boundaries
Different global deterministic models:ECMWFUM from UKMO (UK Weather Service)
GFS from NCEP
GME from DWD (German Weather Service)
CMC from Canadian Weather Service
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COSMO area
is the same as HRM
area
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TasksImplementation of LAM models
HIRLAM, HRM, MM5, UM, COSMO each with 5 global models
Pre-process get global data and prepare for each LAM
Post-process probabilistic products, BMA intranet web server
Verification
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TasksCOSMO implementation
Crayx1 machine 5 global models
Vertical interpolation tool interfacing LAM and global models example: GFS isobaric to hybrid levels int2lm tool can be used
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Meteorological Framework
Main Weather Forecast issues are related with Short-Range forecast of extreme events.Convective precipitation is the most dangerous weather event in Spain.Several cases of more than 200 mm/few hours occurs every year.Verification exercises are focused in precipitation using dense gauge network
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Monitoring in real time
Intranet web serverDeterministic outputs
Maps for each member
Probability maps 6h accumulated precipitation 10 m wind speed 24 h 2 m temperature trend
Ensemble mean and spread mapsEPSgrams
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Monitoring
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Whole Area
Zoom over Spain
Deterministic product
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How will be tomorrow compared
with today?
Probabilistic product
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Spread at key
mesoscale areas
Ensemble mean and spread
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Bias&RMSE Z500Implementation error for this member
Despite the error the
Ensemble Mean has very good verification!
Good performance of
COSMO members
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Probabilistic Verification
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Verification exercise24h accumulated precipitation
forecast 06UTC-06UTC against observed 07UTC-07UTCChecked in HH+030 and HH+054
90 days (Apr1 to Jun30 2006).Different rain gauge networks as references:
AEMET precipitation network (pnw)MeteoFrance, DWD, UKMOJoint pnw (many countries)
Verification methodInterpolation to observation points
Verification softwareECMWF Metview + Local developments
Performance scoresECMWF recommendations
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Joint
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Reliability & Sharpness
Good reliability according tothresholds (base rate)forecast length
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Resolution
Good resolutionROC AreasBSSs
Good RV curves0
1
0.5
1
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A Multi-model-Multi-boundaries Short Range Ensemble Prediction System (MMSREPS) has been develop at the INM-Spain.We show here a 3 months verification, 24 hour of accumulated precipitation, dense net of gauge observations.Verification shows quite good results
Conclusions
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References
(2001) Hou D., Kalnay E., & Droegemeier, K.K.: Objective Verification of the SAMEX’98 Ensemble Forecasts. M.W.R., 129, 73-91.(1999) Buizza R., Miller, M., & Palmer, T.N.: Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc., 125, 2887-2908.(1997) Toth Z., & Kalnay E.: Ensemble Forecasting at NCEP and the breeding method. M.W.R., 125, 3297-3319.(1997) Palmer T.N., Barkmeier J., Buizza R., & Petroliagis T.: The ECMWF Ensmble Prediction System. Meteorol. Appl., 4, 301-304.(2004) Palmer, T.N., et al.: Development of a European multi-model ensemble system for seasonal to inter-annual prediction (DEMETER). B.A.M.S., 85, 853-872.(2005) Arribas A., Robertson K.B., & Mylne, K.R.: Test of Poor Man’s Ensemble Prediction System. M.W.R., 133, 1825-1839
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AcknowledgementsEugenia Kalnay (Univ. Of Maryland)Ken Mylne, Jorge Bornemann (MetOffice)Detlev Majewski, Michael Gertz (DWD)Metview Team, Martin Leutbecher (ECMWF)Chiara Marsigli, Ulrich Schättler (COSMO)Olivier Talagrand (LMD)We also like to thank many Met. Services for making their climate network precipitation observations available to us for verification (some of them not yet included): Arpa-Sim-Bolonia (Italy), DWD (Germany), EARS (Slovenia), HNMS (Greece), HMS (Hungary), KNMI (Netherlands), Lombardia (Italy), Météo-France (France), NIMH (Bulgaria), NMAP (Romania), SHMU (Slovakia), UKMO (UK), ZAMG (Austria), Cerdeña (Italy), Marche (Italy), Trento (Italy), Venezia (Italy), FMI (Finland), IMP (Portugal)
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Thank you for your attention