The new ECMWF seasonal forecast system (system 4)
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1 The new ECMWF seasonal forecast system (system 4) Franco Molteni, Tim Stockdale, Magdalena Balmaseda, Roberto Buizza, Laura Ferranti, Linus Magnusson, Kristian Mogensen, Tim Palmer, Frederic Vitart Met. Application - Met. Oper. - Data services ECMWF, Reading, U.K. Slide 1 Slide 1
2 In 1995 ECMWF started an experimental programme in seasonal forecasting. Successful predictions of the exceptional El Nino event of 1997 encouraged the Council to support the seasonal forecast activity Operational phase started in 2002 with S.F. System 2 EUROSIP multi-model system with MF and UKMO (2005) In 2007 was implemented S.F. System3 Coupled model IFS-OASIS-HOPE, OI ocean d.a. November 2011 System 4 is the new operational S.F. New coupled system: IFS-OASIS-NEMO, 3D-var Slide 2 (NEMOVAR) ocean d.a. Slide 2
3 ECMWF Seasonal Forecasting System Observations Data Assimilation Coupled model Forecast Products Current state of the atmosphere Atmospheric model Coupler Current state of the ocean Ocean Model Slide 3 3
4 ECMWF Seasonal Forecasting System Observations Data Assimilation Current state of the atmosphere 4-D variational d.a. System 4 Initial Con. Gen. of Perturb. Current state of the ocean 3-D v.d.a. (NEMOVAR) Slide 4 4
5 The ECMWF Seasonal fc. system Coupled model Atmospheric model H-TESSEL System 4 IFS 36R4 0.7 deg (T255) 91 levels Initial Conditions for Ens. Forecasts Coupler OASIS-3 Ocean Model NEMO 1/1-0.3 d. lon/lat Slide 5 42 levels
6 ECMWF System 4: main features Operational forecasts - 51-member ensemble from 1 st day of the month - released on the 8 th - 7-month integration Re-forecast set - 30 years, start dates from 1 Jan 1981 to 1 Dec member ensembles, 7-month integrations - 13-month extension from 1 st Feb/May/Aug/Nov Experimental ENSO outlook - 13-month extension from 1 st Feb/May/Aug/Nov - 15-member ensemble Slide 6
7 Bias in S4 re-forecasts: SST (DJF) Start: 1 Nov. 1981/2010 Verify: Dec-Feb System 4 System 3 Slide 7
8 Bias in S4 re-forecasts: MSLP (DJF) Start: 1 Nov. 1981/2010 Verify: Dec-Feb System 4 System 3 Slide 8
9 Bias in S4 re-forecasts: rainfall (JJA) Start: 1 May 1981/2010 Verify: Jun-Aug System 4 System 3 Slide 9
10 NINO 3.4 performance: verifying FMA ( ) System 3 Months 4-6 S4 shows: Marginally higher correlation Better ratio spread/ RMSE Too large amplitudes anomalies System 4 NINO 3.4 Corr Spread/rmse Sd m/sd obs System Slide System
11 Mean square skill score Amplitude Ratio Forecast time (months) Calibration of ENSO SST indices 1.6 NINO3 SST anomaly amplitude ratio Forecast time (months) S4 non calib. S4 calibrated S3 NINO3 SST mean square skill scores MAGICS 6.12 nautilus - net Wed May 11 10:38: start dates from to , various corrections Ensemble sizes are 15 (0001), 11 (0001) and 11 (0001) Fcast S4 Fcast S4 Fcast S3 Persistence Slide Forecast time (months)
12 NiNO3.4 plumes: calibrated vs non calibrated Slide 12 Footer-text Slide 12
13 Anomaly correlation Anomaly correlation Rms error (deg C) Rms error (deg C) SST scores: Nino 3.4 and Eq. Atlantic EQATL SST rms errors NINO3.4 SST rms errors 360 start dates from to , various corrections Ensemble sizes/corrections are 15/AS (0001) and 11/BC (0001) 95% confidence interval for 0001, for given set of start dates Fcast S4 Fcast S3 Persistence Ensemble sd Forecast time (months) NINO3.4 SST anomaly correlation wrt NCEP adjusted OIv climatology Forecast time (months) Solid: S4 error S3 error Dashed: S4 spread S3 spread S4 ACC S3 ACC Pers. ACC Forecast time (months) Slide start dates from to , various corrections Ensemble sizes/corrections are 15/AS (0001) and 11/BC (0001) 95% confidence interval for 0001, for given set of start dates Fcast S4 Fcast S3 Persistence Ensemble sd EQATL SST anomaly correlation wrt NCEP adjusted OIv climatology Forecast time (months) MAGICS 6.12 nautilus - net Tue Jul 26 13:52: MAGICS 6.12 nautilus - net Tue Jul 26 13:52:
14 Ens-mean ACC in S4 re-forecasts: 2m T (JJA) Start: 1 May 1981/2010 Verify: Jun-Aug System 4 System 3 Slide 14
15 Reliability: 2m T > upper tercile over Europe, JJA Sys 4 Sys3 Slide 15
16 Ens-mean ACC in S4 re-forecasts: rainfall (JJA) Start: 1 May 1981/2010 Verify: Jun-Aug System 4 System 3 Slide 16
17 Variability of tropical rainfall: EOF comparison EOF 1 S4 shows higher predictive skill for the Western Africa rainfall than S3 GPCP S3 S4 EOF 2 Slide 17
18 Slide 18 Footer-text Slide 18
19 Prediction of tropical cyclone frequency: NW Pacific System 4 vs. ERA-Int. July-Dec Slide 19 System 3 vs. ERA-Int.
20 Cyclone track density new product from S4 and its verification Slide 20 Track density for the July-Dec. period from fc. started on 1 May
21 ENSO skill: comparison with other seasonal fc. systems NINO3.4 Anomaly Correlation 3-month running means Slide 21 From: Barnston et al. 2011: Skill of Real-time Seasonal ENSO Model Predictions during Is Our Capability Increasing? BAMS, accepted
22 Conclusions Seasonal fc. System-4 (S4): IFS-NEMO coupled model, 3-D var. ocean data assimilation (NEMOVAR), higher atmos. spatial resolution than S3, larger ensemble size, extended re-forecast set. Model biases: much reduced extra-tropical biases, too strong trade winds and cold SST bias in the equatorial Pacific. ENSO SST variability is overestimated. SST forecast skill: similar to S3 in the NINO regions (better in NINO3, slightly worse in NINO4), increased in the tropical and sub-trop. Atlantic. Skill for atmospheric variables: spatial averages of ensemble-mean scores are consistently higher than in S3 (NH summer better than winter). Tropical atmospheric variability: more realistic patterns of rainfall variability, better simulation of the interannual and decadal variation in tropical cyclone frequency. Reliability: the enhanced internal variability and better match between Slide 22 spread and error lead to more reliable seasonal forecasts w.r.t. S3 in both tropical and extra-tropical regions.
23 Mean square skill score ENSO skill: comparison with EUROSIP partners NINO3.4 SST mean square skill scores 154 start dates from to , various corrections Ensemble sizes are 15 (0001), 11 (0001), 11 (0001) and 11 (0001) 1 ECMWF S4 ECMWF S3 Météo-France S3 Met Office S Forecast time (months) Slide 31 ECMWF S4 1.6 ECMWF S3 NINO3.4 SST anomaly amplitude ratio
24 NINO 3.4 performance: verifying JJA ( ) 11 m System 3 Months 2-4 NINO 3.4 Corr Spread/rmse Sd m/sd obs System System System 4 Months 5-7 Similar correlation Better ratio spread/ RMSE Ratio of sd (model/ref) indicates that S4 produces Slide 32 anomalies with too large amplitudes 32
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