multi-model short-range ensemble forecasting at spanish met institute

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