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Influence of the Madden-Julian Oscillation on the predictability in the extra-tropics

This study examines the influence of Madden-Julian Oscillation (MJO) on weather predictability in midlatitudes and subtropical regions. Using NASA Goddard Laboratory for the Atmospheres GCM, the research investigates the impact of MJO strength, phase, and seasonal variations on forecast skills, particularly in extreme precipitation events. Results indicate higher predictability during active MJO phases, with enhancements observed in different regions. However, some model shortcomings affect the accuracy of predictions, highlighting the need for further refinement in MJO representation.

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Influence of the Madden-Julian Oscillation on the predictability in the extra-tropics

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  1. Influence of the Madden-Julian Oscillation on the predictability in the extra-tropics Charles Jones, Duane E. Waliser, K. M. Lau and William Stern • Motivation: strength and/or accuracy of the MJO representation in numerical weather forecast models have a significant impact on medium-to-extended range midlatitudes weather forecasts (Ferranti et al. 1990; Lau and Chang 1992). • Challenge: previous studies relied on NWP models with unrealistic representation of the MJO (weaker and faster). • What is the overall influence of MJO activity on weather predictability in the midlatitudes and subtropical regions (e.g. Americas)? • How does this influence depend on the MJO strength and phase? • Are seasonal variations in MJO activity important? • Does MJO variability (e.g. strength and phase) influence forecast skills of extreme precipitation events in the Americas?

  2. Approach • NASA Goddard Laboratory for the Atmospheres (GLA) GCM (Kalnay et al. (1983). • GLA model performed very well with respect to MJO representation in AMIP study (Slingo et al. 1996; Sperber et al. (1996). • Ten year control run with climatological SST version of the model. • MJO events selected with extended empirical orthogonal function analysis (EEOF) of 30-90 day rainfall anomalies (32N-32S; 32.5E-92.5W). • Candidate MJO events and Null cases were chosen from the amplitude time series of EEOF modes 1 and 2. • Conducted a set of twin numerical predictability experiments: 75 cases [(4 MJO phases + Null phase) * 15 events]. • Perturbation to initial conditions based on scaled day-to-day root-mean-square from daily averaged values of the model’s four prognostic variables (u,v,T,q). • For each alternative initial condition, model was integrated for 90 days. Waliser et al. 2002: Potential Predictability of the Madden-Julian Oscillation. Bull. Am. Meteor. Soc (in press).

  3. Observed and Model Canonical MJO

  4. Null Mode 1 > 0 Mode 1 < 0 Mode 2 > 0 Mode 2 < 0 • 15 Events Selected • From Each Type • 2 Perturbations • Run for Each Event • Perturbations Added • Were ~ < 5% of • Day-to-Day Variability Example: N.H. Winter - MJO Initial Condition Selection

  5. Composite filtered (30-90 days) rainfall anomalies for the 15 initial conditions selected to represent the four “phases” of the MJO as well as the null cases Except in null case (lower left), the headings indicate the geographic region of the most intense MJO-related rainfall RAINFALL

  6. Control (Verification) I.C. 1 2 3 90 Forecast Anomaly Correlation Coefficient • Subtract daily climatology: Z500, SF200, U850, Rain • ACC is computed for each set of MJO phase and Null cases for lead times  = 1, 30 days • Domains: N.H., S.H. and Tropics (Z500, SF200, U850); Indian/W. Pac., N. America and S. America (Rainfall) Fisher Transform: Test:  = 1, 30 days Standardized Root-Mean-Square Error

  7. Northern Hemisphere 20N – 60N ACC

  8. Northern Hemisphere 20N – 60N

  9. Northern Hemisphere 20N – 60N RMS

  10. Tropical Region 20S – 20N ACC RMS

  11. Southern Hemisphere 60S – 20S ACC

  12. Rainfall

  13. Conclusions • Results from boreal winter predictability experiments (GLA) suggest that predictability is higher during MJO active phases than in quiescent periods. Agreement with NWP predictive studies (Ferranti et al. 1990; Lau and Chang 1992). • Northern Hemisphere (20N – 60N): • Enhanced (suppressed) convection in Indian Ocean (W. Pacific) suggests a gain of 1-3 days in useful skill relative to quiescent MJO. • Tropical Region (20S – 20N): • Slight increase in predictability of U850 when there is enhanced (suppressed) convection in W. Pacific (Indian ocean). • Southern Hemisphere (60S – 20S): • Moderate predictability increase in Z500 and U850 during C.PAC and Indian phases. • Rainfall: no statistically significant differences between active MJO and quiescent periods. • Caveats: model shortcomings in MJO representation. Fixed SST’s. Model contains too little variability over western Indian Ocean and southern maritime continent region.

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