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Recent changes in the NCEP global ensemble forecast system

Recent changes in the NCEP global ensemble forecast system. Yuejian Zhu, Zoltan Toth, Richard Wobus*, and Lacey Holland* EMC/NCEP *SAIC at NCEP September 19 2003 http://wwwt.emc.ncep.noaa.gov/gmb/ens/ Acknowledgements: H.-L. Pan, S. Lord, D. Michaud, and T. Marchok. Contents.

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Recent changes in the NCEP global ensemble forecast system

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  1. Recent changes in the NCEP global ensemble forecast system Yuejian Zhu, Zoltan Toth, Richard Wobus*, and Lacey Holland* EMC/NCEP *SAIC at NCEP September 19 2003 http://wwwt.emc.ncep.noaa.gov/gmb/ens/ Acknowledgements: H.-L. Pan, S. Lord, D. Michaud, and T. Marchok

  2. Contents • Introduction • Configuration of NCEP global ensemble forecast system • Recent implementation (May 2003) • Performance statistics • Next implementation (Oct-Nov. 2003) • Ongoing research / Plans

  3. Introduction • NCEP global ensemble system operated daily since December 1992. • Initial perturbations are generated by Breeding method (Toth and Kalnay, 1993 1997) • Ensemble size: <10 --> 25 (now)  45 (next month) • Ensemble resolution: T62  T126 (first 180 hours) • Ensemble based products have been generated. • Wide range of users both nationally and internationally • Evaluation (including potential economic value)

  4. NCEP global ensemble current configuration • High resolution Control • 4 cycles (00, 06, 12, 18 UTC) • 3 different resolutions (from high to low) • Ensemble • 2 cycles (00, 12 UTC) • 2 different resolutions • 5 pairs (+/- perturbation) • BGM • Total • 1 low resolution control • 25 global forecasts/day

  5. Recent implementation (April 29 2003) • Motivation: Bring initial perturbation amplitude more in line with actual uncertainty in analysis • Compare fit of first guess to observational data with perturbation amplitude • Additional consideration: NCEP global ensemble does not account for model error • Set initial amplitudes somewhat above level of initial uncertainty (forecast error at 2-3 days matches ensemble pert. amplitudes) • Change: Revise mask used to set perturbation amplitudes: • 10% reduced for NH • 60% reduced for SH • 50% reduced for tropics • Experimental period: • 20020824 – 20020930 (38 days) • Results:1.5% (NH) and 7.6% (SH) RMS error reduction

  6. Experimental results (1) • NH 500hPa height Brier Skill Scores (BSS) and decomposition (resolution and reliability) • No significant impact by reducing spread by 10% • Similar results for PAC, RMS, and other probabilistic scores --- operational (control) --- I – reduced spread --- J – reduced spread

  7. --- Climate mean forecast Experimental results (2) --- operational (control) --- I – reduced spread --- J – reduced spread • Top: SH 500hPa height PAC • There is a significant improvement from short to medium range • Bottom: SH 500hPa height RMS errors • Similar to PAC, reduced spread, decreased RMS errors spread

  8. Experimental results (3) • Top: SH 500hPa height economic values for 10:1 cost-loss ratio • Experiments have higher values for all lead times • Bottom: SH 500hPa height ROC area skill scores (ROCASS) • Experiments improve probabilistic forecast skill

  9. Experimental results (4) • Tropical storm track errors • Atlantic, east Pacific and west Pacific regions • Comparing to operational ensemble, ensemble control and GFS

  10. Current performance (1) • 45-day statistics • Top: NH (20-80N) 500hPa height PAC for GFS, ensemble control and mean, ensemble mean is better than GFS for 4-day and beyond • Bottom: NH 500hPa height RMS for GFS, CTL, ensemble mean and climate, and ensemble spread

  11. Current performance (2) • 45-day statistics • Top: SH (20-80S) 500hPa height PAC for GFS, ensemble control and mean, ensemble mean is better than GFS for 1% for 5-day forecast • Bottom: SH 500hPa height RMS for GFS,CTL, ensemble mean and climate, and ensemble spread

  12. Next implementation • Time: October-November 2003 • Extending T126 model resolution from 84 hours to 180 hours • Increasing ensemble size from 25 to 45 by adding 10 (5 pairs) at 0600UTC and 10 (5 pairs) at 1800UTC • Adding more probabilistic forecast products: PQPF (old, total precipitation), PQRF(rain), PQSF(snow), PQIF(ice pellets) and PQFF(freezing rain)

  13. Ongoing work • Adapt ETKF for rescaling in (place of) breeding method (Wang and Bishop) • Explore new ways to account for model related errors in ensemble forecasting (use different/modified convective schemes, etc) • Bias-correct first and second moments of ensemble Plans • Develop North American Ensemble Forecast System (Joint work with Meteorological Service of Canada, for joint NCEP-MSC ensemble products) • Inter-compare 4 different ensemble-based data assimilation algorithms (collaborative work among 4 groups)

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