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 2003http://wwwt.emc.ncep.noaa.gov/gmb/ens/

Acknowledgements:H.-L. Pan, S. Lord, D. Michaud, and T. Marchok

Contents

Introduction Configuration of NCEP global ensemble

forecast system Recent implementation (May 2003) Performance statistics Next implementation (Oct-Nov. 2003) Ongoing research / Plans

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)

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

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

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

Experimental results (2)

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

--- operational (control)--- I – reduced spread--- J – reduced spread

--- Climate mean forecast

spread

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

Experimental results (4)

Tropical storm track errors

Atlantic, east Pacific and west Pacific regions

Comparing to operational ensemble, ensemble control and GFS

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

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

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)

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)